Fork the pycirk repo on GitHub.
-Clone your fork locally:
+Fork the pycirk repo on GitHub.
Clone your fork locally:
$ git clone git@github.com:your_name_here/pycirk.git
Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
+Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
$ mkvirtualenv pycirk
$ cd pycirk/
$ python setup.py develop
Create a branch for local development:
+Create a branch for local development:
$ git checkout -b name-of-your-bugfix-or-feature
Now you can make your changes locally.
When you’re done making changes, check that your changes pass flake8 and the +
When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:
$ flake8 pycirk tests
$ python setup.py test or py.test
@@ -111,28 +109,27 @@ Get Started!Commit your changes and push your branch to GitHub:
+Commit your changes and push your branch to GitHub:
$ git add .
$ git commit -m "Your detailed description of your changes."
$ git push origin name-of-your-bugfix-or-feature
Submit a pull request through the GitHub website.
-Submit a pull request through the GitHub website.
Pull Request Guidelines¶
Before you submit a pull request, check that it meets these guidelines:
-
-
- The pull request should include tests. -
- If the pull request adds functionality, the docs should be updated. Put +
The pull request should include tests.
+If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the -feature to the list in README.rst.
-- The pull request should work for Python 2.7, 3.4, 3.5 and 3.6, and for PyPy. Check +feature to the list in README.rst. +
The pull request should work for Python 2.7, 3.4, 3.5 and 3.6, and for PyPy. Check https://travis-ci.org/FDonati/pycirk/pull_requests -and make sure that the tests pass for all supported Python versions.
+and make sure that the tests pass for all supported Python versions.
Related Topics
Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/_build/html/genindex.html b/docs/_build/html/genindex.html index dc18352..35c6135 100644 --- a/docs/_build/html/genindex.html +++ b/docs/_build/html/genindex.html @@ -1,12 +1,10 @@ - + - - +A
R
- relabel_to_save() (pycirk.labels.Labels method)
- retrieve_specified_data() (in module pycirk.results) + +
- rsd_engine() (in module pycirk.results)
- RY() (pycirk.fundamental_operations.Operations.IOT method) @@ -424,13 +423,11 @@
Related Topics
Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 diff --git a/docs/_build/html/history.html b/docs/_build/html/history.html index b71fdf6..f7ce3aa 100644 --- a/docs/_build/html/history.html +++ b/docs/_build/html/history.html @@ -1,11 +1,9 @@ - + - - +History
0.1.0 (2018-05-11)¶
-- First release on PyPI.
+First release on PyPI.
@@ -82,13 +81,11 @@ Related Topics
@@ -109,7 +106,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/index.html b/docs/_build/html/index.html
index ac2daec..89d5b5b 100644
--- a/docs/_build/html/index.html
+++ b/docs/_build/html/index.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Welcome to pycirk’s documentation! — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -78,9 +77,9 @@ Welcome to pycirk’s documentation!
Indices and tables¶
@@ -121,13 +120,11 @@ Related Topics
@@ -148,7 +145,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/installation.html b/docs/_build/html/installation.html
index 2adaad5..34cd9b0 100644
--- a/docs/_build/html/installation.html
+++ b/docs/_build/html/installation.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Installation — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -105,13 +104,11 @@ Related Topics
@@ -132,7 +129,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/modules.html b/docs/_build/html/modules.html
index 085ec6d..decafbe 100644
--- a/docs/_build/html/modules.html
+++ b/docs/_build/html/modules.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -99,13 +98,11 @@ Related Topics
@@ -126,7 +123,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/objects.inv b/docs/_build/html/objects.inv
index abfd61f..80b3251 100644
Binary files a/docs/_build/html/objects.inv and b/docs/_build/html/objects.inv differ
diff --git a/docs/_build/html/py-modindex.html b/docs/_build/html/py-modindex.html
index 8f8668a..ca4e296 100644
--- a/docs/_build/html/py-modindex.html
+++ b/docs/_build/html/py-modindex.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Python Module Index — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -149,13 +148,11 @@ Related Topics
@@ -176,7 +173,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/pycirk.html b/docs/_build/html/pycirk.html
index f403053..1b33f9e 100644
--- a/docs/_build/html/pycirk.html
+++ b/docs/_build/html/pycirk.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk package — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -50,7 +49,7 @@ Submodules
-
-class
pycirk.fundamental_operations.Operations[source]¶
+class pycirk.fundamental_operations.Operations[source]¶
Bases: object
Contains all basic operations to transform SUTs into IOTs and verify them
It contains two subclasses defining two different trasformation methods
@@ -58,58 +57,58 @@
Submodules
-
-class
IOT[source]¶
+class IOT[source]¶
Bases: object
General IOT operations subclass
some methods repeat from other subclasses
but it’s good to have them divided for clarity
-
-
bY(inv_diag_yj)[source]¶
+bY(inv_diag_yj)[source]¶
Calculates intensities of extensions in final demand
Method for transformation matrix of bY
(e.g. final demand emissions)
@@ -117,13 +116,13 @@ Submodules
-
-
x(Y)[source]¶
+x(Y)[source]¶
total product output s the sum of Si and y
@@ -132,46 +131,46 @@ Submodules
-
-class
PxP_ITA_MSC[source]¶
+class PxP_ITA_MSC[source]¶
Bases: object
Model with Market Share Coef.
Prod x Prod Industry Technology assumption
-
-
S(inv_diag_g)[source]¶
+S(inv_diag_g)[source]¶
Intermediate coefficients
Input requirements
Z = U * inv(diag(g))
@@ -179,7 +178,7 @@ Submodules
-
-
Z(D, diag_q)[source]¶
+Z(D, diag_q)[source]¶
Intermediates
Z = inter_coef * D * diag(q)
@@ -188,19 +187,19 @@ Submodules
-
-class
PxP_ITA_TC[source]¶
+class PxP_ITA_TC[source]¶
Bases: object
Model with Transformation Coefficients
ProdxProd Industry Technology assumption
-
-
L(T, inv_diag_q)[source]¶
+L(T, inv_diag_q)[source]¶
Input coefficients intermediates
A = U * T * inv[diag (q)]
Multiplier matrix
@@ -209,20 +208,20 @@
Submodules
-
-
R(diag_q)[source]¶
+R(diag_q)[source]¶
Calculates absolute extensions
@@ -231,12 +230,12 @@ Submodules
-
-
calculate_characterized()[source]¶
+calculate_characterized()[source]¶
-
-
delta_Y(Yalt)[source]¶
+delta_Y(Yalt)[source]¶
method to calculate difference in Y
Y = final demand baseline
Yalt = final demand scenario
@@ -244,7 +243,7 @@ Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
Submodules
-
-class
pycirk.labels.Labels[source]¶
+class pycirk.labels.Labels[source]¶
Bases: object
-
-
apply_labels(matrix, labels, axis=0)[source]¶
+apply_labels(matrix, labels, axis=0)[source]¶
Applies labels to a dataframe
axis = 0 => Index
axis = 1 => columns
@@ -285,20 +284,20 @@ Submodules
-
-
calc_no_of_something(labels)[source]¶
+calc_no_of_something(labels)[source]¶
A general method to calculate the number of unique entries contained
in a series
-
-
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
+get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
Calculates all unique entries (labels) contained in a dataframe and
puts them together with their units and total count of unique entries
It returns an object… which is munched, not a pretty solution but it
@@ -307,43 +306,43 @@
Submodules
-
-
identify_labels(M_name)[source]¶
+identify_labels(M_name)[source]¶
A method to understand what type of labels are being handled depending
on the name of the matrix in dataframe type that is being passed
-
-
list_of_something(labels)[source]¶
+list_of_something(labels)[source]¶
A general method to return a list of unique entries contained in a series
-
-
relabel(M, column_labels, index_labels)[source]¶
+relabel(M, column_labels, index_labels)[source]¶
Processes apply_labels and apply _names together
-
-
relabel_to_save(data, trans_method, labels_directory)[source]¶
+relabel_to_save(data, trans_method, labels_directory)[source]¶
This function makes sure that everything is labeled in IOT tables
trans_method = 0 is prod x prod , 1 is ind x ind
-
-
save_labels(data, directory)[source]¶
+save_labels(data, directory)[source]¶
saves the labels of the database in the labels directory
@@ -359,7 +358,7 @@ Submodules
-
-
pycirk.make_scenarios.basic_add(a, at)[source]¶
+pycirk.make_scenarios.basic_add(a, at)[source]¶
Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@ Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
-
-
-
+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}})
\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
First release on PyPI.
Indices and tables¶
@@ -121,13 +120,11 @@Related Topics
@@ -148,7 +145,7 @@Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/_build/html/installation.html b/docs/_build/html/installation.html index 2adaad5..34cd9b0 100644 --- a/docs/_build/html/installation.html +++ b/docs/_build/html/installation.html @@ -1,11 +1,9 @@ - + - - +Related Topics
@@ -132,7 +129,7 @@Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/_build/html/modules.html b/docs/_build/html/modules.html index 085ec6d..decafbe 100644 --- a/docs/_build/html/modules.html +++ b/docs/_build/html/modules.html @@ -1,11 +1,9 @@ - + - - +Related Topics
@@ -126,7 +123,7 @@Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/_build/html/objects.inv b/docs/_build/html/objects.inv index abfd61f..80b3251 100644 Binary files a/docs/_build/html/objects.inv and b/docs/_build/html/objects.inv differ diff --git a/docs/_build/html/py-modindex.html b/docs/_build/html/py-modindex.html index 8f8668a..ca4e296 100644 --- a/docs/_build/html/py-modindex.html +++ b/docs/_build/html/py-modindex.html @@ -1,11 +1,9 @@ - + - - +Related Topics
@@ -176,7 +173,7 @@Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 diff --git a/docs/_build/html/pycirk.html b/docs/_build/html/pycirk.html index f403053..1b33f9e 100644 --- a/docs/_build/html/pycirk.html +++ b/docs/_build/html/pycirk.html @@ -1,11 +1,9 @@ - + - - +Submodules
-
-class
pycirk.fundamental_operations.Operations[source]¶
+class pycirk.fundamental_operations.Operations[source]¶
Bases: object
Contains all basic operations to transform SUTs into IOTs and verify them
It contains two subclasses defining two different trasformation methods
@@ -58,58 +57,58 @@
Submodules
-
-class
IOT[source]¶
+class IOT[source]¶
Bases: object
General IOT operations subclass
some methods repeat from other subclasses
but it’s good to have them divided for clarity
-
-
bY(inv_diag_yj)[source]¶
+bY(inv_diag_yj)[source]¶
Calculates intensities of extensions in final demand
Method for transformation matrix of bY
(e.g. final demand emissions)
@@ -117,13 +116,13 @@ Submodules
-
-
x(Y)[source]¶
+x(Y)[source]¶
total product output s the sum of Si and y
@@ -132,46 +131,46 @@ Submodules
-
-class
PxP_ITA_MSC[source]¶
+class PxP_ITA_MSC[source]¶
Bases: object
Model with Market Share Coef.
Prod x Prod Industry Technology assumption
-
-
S(inv_diag_g)[source]¶
+S(inv_diag_g)[source]¶
Intermediate coefficients
Input requirements
Z = U * inv(diag(g))
@@ -179,7 +178,7 @@ Submodules
-
-
Z(D, diag_q)[source]¶
+Z(D, diag_q)[source]¶
Intermediates
Z = inter_coef * D * diag(q)
@@ -188,19 +187,19 @@ Submodules
-
-class
PxP_ITA_TC[source]¶
+class PxP_ITA_TC[source]¶
Bases: object
Model with Transformation Coefficients
ProdxProd Industry Technology assumption
-
-
L(T, inv_diag_q)[source]¶
+L(T, inv_diag_q)[source]¶
Input coefficients intermediates
A = U * T * inv[diag (q)]
Multiplier matrix
@@ -209,20 +208,20 @@
Submodules
-
-
R(diag_q)[source]¶
+R(diag_q)[source]¶
Calculates absolute extensions
@@ -231,12 +230,12 @@ Submodules
-
-
calculate_characterized()[source]¶
+calculate_characterized()[source]¶
-
-
delta_Y(Yalt)[source]¶
+delta_Y(Yalt)[source]¶
method to calculate difference in Y
Y = final demand baseline
Yalt = final demand scenario
@@ -244,7 +243,7 @@ Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
Submodules
-
-class
pycirk.labels.Labels[source]¶
+class pycirk.labels.Labels[source]¶
Bases: object
-
-
apply_labels(matrix, labels, axis=0)[source]¶
+apply_labels(matrix, labels, axis=0)[source]¶
Applies labels to a dataframe
axis = 0 => Index
axis = 1 => columns
@@ -285,20 +284,20 @@ Submodules
-
-
calc_no_of_something(labels)[source]¶
+calc_no_of_something(labels)[source]¶
A general method to calculate the number of unique entries contained
in a series
-
-
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
+get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
Calculates all unique entries (labels) contained in a dataframe and
puts them together with their units and total count of unique entries
It returns an object… which is munched, not a pretty solution but it
@@ -307,43 +306,43 @@
Submodules
-
-
identify_labels(M_name)[source]¶
+identify_labels(M_name)[source]¶
A method to understand what type of labels are being handled depending
on the name of the matrix in dataframe type that is being passed
-
-
list_of_something(labels)[source]¶
+list_of_something(labels)[source]¶
A general method to return a list of unique entries contained in a series
-
-
relabel(M, column_labels, index_labels)[source]¶
+relabel(M, column_labels, index_labels)[source]¶
Processes apply_labels and apply _names together
-
-
relabel_to_save(data, trans_method, labels_directory)[source]¶
+relabel_to_save(data, trans_method, labels_directory)[source]¶
This function makes sure that everything is labeled in IOT tables
trans_method = 0 is prod x prod , 1 is ind x ind
-
-
save_labels(data, directory)[source]¶
+save_labels(data, directory)[source]¶
saves the labels of the database in the labels directory
@@ -359,7 +358,7 @@ Submodules
-
-
pycirk.make_scenarios.basic_add(a, at)[source]¶
+pycirk.make_scenarios.basic_add(a, at)[source]¶
Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@ Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
-
-
-
+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["authors","contributing","history","index","installation","modules","pycirk","readme","usage"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.cpp":1,"sphinx.domains.javascript":1,"sphinx.domains.math":2,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,"sphinx.ext.viewcode":1,sphinx:55},filenames:["authors.rst","contributing.rst","history.rst","index.rst","installation.rst","modules.rst","pycirk.rst","readme.rst","usage.rst"],objects:{"":{pycirk:[6,0,0,"-"]},"pycirk.fundamental_operations":{Operations:[6,1,1,""]},"pycirk.fundamental_operations.Operations":{IOT:[6,1,1,""],PxP_ITA_MSC:[6,1,1,""],PxP_ITA_TC:[6,1,1,""],calculate_characterized:[6,2,1,""],delta_Y:[6,2,1,""],delta_x:[6,2,1,""],inv:[6,2,1,""],verifyIOT:[6,2,1,""]},"pycirk.fundamental_operations.Operations.IOT":{A:[6,2,1,""],B:[6,2,1,""],IOT:[6,2,1,""],L:[6,2,1,""],R:[6,2,1,""],RY:[6,2,1,""],Z:[6,2,1,""],bY:[6,2,1,""],x:[6,2,1,""],x_IAy:[6,2,1,""]},"pycirk.fundamental_operations.Operations.PxP_ITA_MSC":{A:[6,2,1,""],B:[6,2,1,""],D:[6,2,1,""],L:[6,2,1,""],R:[6,2,1,""],S:[6,2,1,""],Z:[6,2,1,""]},"pycirk.fundamental_operations.Operations.PxP_ITA_TC":{B:[6,2,1,""],L:[6,2,1,""],R:[6,2,1,""],T:[6,2,1,""],Z:[6,2,1,""]},"pycirk.labels":{Labels:[6,1,1,""]},"pycirk.labels.Labels":{apply_labels:[6,2,1,""],calc_no_of_something:[6,2,1,""],get_labels:[6,2,1,""],get_unique_labels:[6,2,1,""],identify_labels:[6,2,1,""],list_of_something:[6,2,1,""],load_labels:[6,2,1,""],organize_unique_labels:[6,2,1,""],relabel:[6,2,1,""],relabel_to_save:[6,2,1,""],save_labels:[6,2,1,""]},"pycirk.make_scenarios":{basic_add:[6,3,1,""],basic_mult:[6,3,1,""],counterfactual:[6,3,1,""],counterfactual_engine:[6,3,1,""],make_counterfactuals:[6,3,1,""],make_new:[6,3,1,""],substitution:[6,3,1,""]},"pycirk.make_secondary_flows":{allocate_sec_mat:[6,3,1,""],make_secondary:[6,3,1,""]},"pycirk.organize_io":{organizer:[6,3,1,""]},"pycirk.positions":{make_coord_array:[6,3,1,""],make_coord_array_for_make_sec:[6,3,1,""],single_position:[6,3,1,""]},"pycirk.pycirk":{Launch:[6,1,1,""]},"pycirk.pycirk.Launch":{all_results:[6,2,1,""],delete_previous_IO_builds:[6,2,1,""],save_results:[6,2,1,""],scenario_results:[6,2,1,""]},"pycirk.pycirk_settings":{Settings:[6,1,1,""]},"pycirk.pycirk_settings.Settings":{assign_labels_to_class:[6,2,1,""],check_dataset_location:[6,2,1,""],check_expand_directory:[6,2,1,""],create_output_folder:[6,2,1,""],create_scenario_file:[6,2,1,""],load_dataset:[6,2,1,""],load_results_params:[6,2,1,""],number_scenarios:[6,2,1,""],project_specs:[6,2,1,""],scenario_file:[6,2,1,""],set_IO_scenario:[6,2,1,""],set_SUTs:[6,2,1,""],set_save_directory:[6,2,1,""],transform_to_io:[6,2,1,""]},"pycirk.results":{iter_thru_for_results:[6,3,1,""],retrieve_specified_data:[6,3,1,""]},"pycirk.save_utils":{add_date_to_gen_specs:[6,3,1,""],save_outputs:[6,3,1,""]},"pycirk.transformation_methods":{Transform:[6,1,1,""]},"pycirk.transformation_methods.Transform":{IOTpxpSTA_MSCm:[6,2,1,""],IOTpxpSTA_TCm:[6,2,1,""]},pycirk:{cli:[6,0,0,"-"],fundamental_operations:[6,0,0,"-"],labels:[6,0,0,"-"],make_scenarios:[6,0,0,"-"],make_secondary_flows:[6,0,0,"-"],organize_io:[6,0,0,"-"],positions:[6,0,0,"-"],pycirk:[6,0,0,"-"],pycirk_settings:[6,0,0,"-"],results:[6,0,0,"-"],save_utils:[6,0,0,"-"],transformation_methods:[6,0,0,"-"]}},objnames:{"0":["py","module","Python 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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}})
\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
pycirk.fundamental_operations.Operations[source]¶Bases: object
Contains all basic operations to transform SUTs into IOTs and verify them It contains two subclasses defining two different trasformation methods @@ -58,58 +57,58 @@
Submodules
-
-class
IOT[source]¶
+class IOT[source]¶
Bases: object
General IOT operations subclass
some methods repeat from other subclasses
but it’s good to have them divided for clarity
-
-
bY(inv_diag_yj)[source]¶
+bY(inv_diag_yj)[source]¶
Calculates intensities of extensions in final demand
Method for transformation matrix of bY
(e.g. final demand emissions)
@@ -117,13 +116,13 @@ Submodules
-
-
x(Y)[source]¶
+x(Y)[source]¶
total product output s the sum of Si and y
@@ -132,46 +131,46 @@ Submodules
-
-class
PxP_ITA_MSC[source]¶
+class PxP_ITA_MSC[source]¶
Bases: object
Model with Market Share Coef.
Prod x Prod Industry Technology assumption
-
-
S(inv_diag_g)[source]¶
+S(inv_diag_g)[source]¶
Intermediate coefficients
Input requirements
Z = U * inv(diag(g))
@@ -179,7 +178,7 @@ Submodules
-
-
Z(D, diag_q)[source]¶
+Z(D, diag_q)[source]¶
Intermediates
Z = inter_coef * D * diag(q)
@@ -188,19 +187,19 @@ Submodules
-
-class
PxP_ITA_TC[source]¶
+class PxP_ITA_TC[source]¶
Bases: object
Model with Transformation Coefficients
ProdxProd Industry Technology assumption
-
-
L(T, inv_diag_q)[source]¶
+L(T, inv_diag_q)[source]¶
Input coefficients intermediates
A = U * T * inv[diag (q)]
Multiplier matrix
@@ -209,20 +208,20 @@
Submodules
-
-
R(diag_q)[source]¶
+R(diag_q)[source]¶
Calculates absolute extensions
@@ -231,12 +230,12 @@ Submodules
-
-
calculate_characterized()[source]¶
+calculate_characterized()[source]¶
-
-
delta_Y(Yalt)[source]¶
+delta_Y(Yalt)[source]¶
method to calculate difference in Y
Y = final demand baseline
Yalt = final demand scenario
@@ -244,7 +243,7 @@ Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
Submodules
-
-class
pycirk.labels.Labels[source]¶
+class pycirk.labels.Labels[source]¶
Bases: object
-
-
apply_labels(matrix, labels, axis=0)[source]¶
+apply_labels(matrix, labels, axis=0)[source]¶
Applies labels to a dataframe
axis = 0 => Index
axis = 1 => columns
@@ -285,20 +284,20 @@ Submodules
-
-
calc_no_of_something(labels)[source]¶
+calc_no_of_something(labels)[source]¶
A general method to calculate the number of unique entries contained
in a series
-
-
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
+get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
Calculates all unique entries (labels) contained in a dataframe and
puts them together with their units and total count of unique entries
It returns an object… which is munched, not a pretty solution but it
@@ -307,43 +306,43 @@
Submodules
-
-
identify_labels(M_name)[source]¶
+identify_labels(M_name)[source]¶
A method to understand what type of labels are being handled depending
on the name of the matrix in dataframe type that is being passed
-
-
list_of_something(labels)[source]¶
+list_of_something(labels)[source]¶
A general method to return a list of unique entries contained in a series
-
-
relabel(M, column_labels, index_labels)[source]¶
+relabel(M, column_labels, index_labels)[source]¶
Processes apply_labels and apply _names together
-
-
relabel_to_save(data, trans_method, labels_directory)[source]¶
+relabel_to_save(data, trans_method, labels_directory)[source]¶
This function makes sure that everything is labeled in IOT tables
trans_method = 0 is prod x prod , 1 is ind x ind
-
-
save_labels(data, directory)[source]¶
+save_labels(data, directory)[source]¶
saves the labels of the database in the labels directory
@@ -359,7 +358,7 @@ Submodules
-
-
pycirk.make_scenarios.basic_add(a, at)[source]¶
+pycirk.make_scenarios.basic_add(a, at)[source]¶
Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@ Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
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+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}})
\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
IOT[source]¶Bases: object
General IOT operations subclass some methods repeat from other subclasses but it’s good to have them divided for clarity
-
-
bY(inv_diag_yj)[source]¶
+ Calculates intensities of extensions in final demand Method for transformation matrix of bY (e.g. final demand emissions)
@@ -117,13 +116,13 @@Submodules
- -
+x(Y)[source]¶x(Y)[source]¶total product output s the sum of Si and y
- -
bY(inv_diag_yj)[source]¶
Submodules
-
-class
PxP_ITA_MSC[source]¶
+class PxP_ITA_MSC[source]¶
Bases: object
Model with Market Share Coef.
Prod x Prod Industry Technology assumption
-
-
S(inv_diag_g)[source]¶
+S(inv_diag_g)[source]¶
Intermediate coefficients
Input requirements
Z = U * inv(diag(g))
@@ -179,7 +178,7 @@ Submodules
-
-
Z(D, diag_q)[source]¶
+Z(D, diag_q)[source]¶
Intermediates
Z = inter_coef * D * diag(q)
@@ -188,19 +187,19 @@ Submodules
-
-class
PxP_ITA_TC[source]¶
+class PxP_ITA_TC[source]¶
Bases: object
Model with Transformation Coefficients
ProdxProd Industry Technology assumption
-
-
L(T, inv_diag_q)[source]¶
+L(T, inv_diag_q)[source]¶
Input coefficients intermediates
A = U * T * inv[diag (q)]
Multiplier matrix
@@ -209,20 +208,20 @@
Submodules
-
-
R(diag_q)[source]¶
+R(diag_q)[source]¶
Calculates absolute extensions
@@ -231,12 +230,12 @@ Submodules
-
-
calculate_characterized()[source]¶
+calculate_characterized()[source]¶
-
-
delta_Y(Yalt)[source]¶
+delta_Y(Yalt)[source]¶
method to calculate difference in Y
Y = final demand baseline
Yalt = final demand scenario
@@ -244,7 +243,7 @@ Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
Submodules
-
-class
pycirk.labels.Labels[source]¶
+class pycirk.labels.Labels[source]¶
Bases: object
-
-
apply_labels(matrix, labels, axis=0)[source]¶
+apply_labels(matrix, labels, axis=0)[source]¶
Applies labels to a dataframe
axis = 0 => Index
axis = 1 => columns
@@ -285,20 +284,20 @@ Submodules
-
-
calc_no_of_something(labels)[source]¶
+calc_no_of_something(labels)[source]¶
A general method to calculate the number of unique entries contained
in a series
-
-
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
+get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
Calculates all unique entries (labels) contained in a dataframe and
puts them together with their units and total count of unique entries
It returns an object… which is munched, not a pretty solution but it
@@ -307,43 +306,43 @@
Submodules
-
-
identify_labels(M_name)[source]¶
+identify_labels(M_name)[source]¶
A method to understand what type of labels are being handled depending
on the name of the matrix in dataframe type that is being passed
-
-
list_of_something(labels)[source]¶
+list_of_something(labels)[source]¶
A general method to return a list of unique entries contained in a series
-
-
relabel(M, column_labels, index_labels)[source]¶
+relabel(M, column_labels, index_labels)[source]¶
Processes apply_labels and apply _names together
-
-
relabel_to_save(data, trans_method, labels_directory)[source]¶
+relabel_to_save(data, trans_method, labels_directory)[source]¶
This function makes sure that everything is labeled in IOT tables
trans_method = 0 is prod x prod , 1 is ind x ind
-
-
save_labels(data, directory)[source]¶
+save_labels(data, directory)[source]¶
saves the labels of the database in the labels directory
@@ -359,7 +358,7 @@ Submodules
-
-
pycirk.make_scenarios.basic_add(a, at)[source]¶
+pycirk.make_scenarios.basic_add(a, at)[source]¶
Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@ Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
-
-
-
+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}})
\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
PxP_ITA_MSC[source]¶Bases: object
Model with Market Share Coef. Prod x Prod Industry Technology assumption
-
-
S(inv_diag_g)[source]¶
+ Intermediate coefficients Input requirements Z = U * inv(diag(g))
@@ -179,7 +178,7 @@Submodules
- -
+Z(D, diag_q)[source]¶Z(D, diag_q)[source]¶Intermediates Z = inter_coef * D * diag(q)
- -
S(inv_diag_g)[source]¶
Submodules
-
-class
PxP_ITA_TC[source]¶
+class PxP_ITA_TC[source]¶
Bases: object
Model with Transformation Coefficients
ProdxProd Industry Technology assumption
-
-
L(T, inv_diag_q)[source]¶
+L(T, inv_diag_q)[source]¶
Input coefficients intermediates
A = U * T * inv[diag (q)]
Multiplier matrix
@@ -209,20 +208,20 @@
Submodules
-
-
R(diag_q)[source]¶
+R(diag_q)[source]¶
Calculates absolute extensions
@@ -231,12 +230,12 @@ Submodules
-
-
calculate_characterized()[source]¶
+calculate_characterized()[source]¶
-
-
delta_Y(Yalt)[source]¶
+delta_Y(Yalt)[source]¶
method to calculate difference in Y
Y = final demand baseline
Yalt = final demand scenario
@@ -244,7 +243,7 @@ Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
Submodules
-
-class
pycirk.labels.Labels[source]¶
+class pycirk.labels.Labels[source]¶
Bases: object
-
-
apply_labels(matrix, labels, axis=0)[source]¶
+apply_labels(matrix, labels, axis=0)[source]¶
Applies labels to a dataframe
axis = 0 => Index
axis = 1 => columns
@@ -285,20 +284,20 @@ Submodules
-
-
calc_no_of_something(labels)[source]¶
+calc_no_of_something(labels)[source]¶
A general method to calculate the number of unique entries contained
in a series
-
-
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
+get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
Calculates all unique entries (labels) contained in a dataframe and
puts them together with their units and total count of unique entries
It returns an object… which is munched, not a pretty solution but it
@@ -307,43 +306,43 @@
Submodules
-
-
identify_labels(M_name)[source]¶
+identify_labels(M_name)[source]¶
A method to understand what type of labels are being handled depending
on the name of the matrix in dataframe type that is being passed
-
-
list_of_something(labels)[source]¶
+list_of_something(labels)[source]¶
A general method to return a list of unique entries contained in a series
-
-
relabel(M, column_labels, index_labels)[source]¶
+relabel(M, column_labels, index_labels)[source]¶
Processes apply_labels and apply _names together
-
-
relabel_to_save(data, trans_method, labels_directory)[source]¶
+relabel_to_save(data, trans_method, labels_directory)[source]¶
This function makes sure that everything is labeled in IOT tables
trans_method = 0 is prod x prod , 1 is ind x ind
-
-
save_labels(data, directory)[source]¶
+save_labels(data, directory)[source]¶
saves the labels of the database in the labels directory
@@ -359,7 +358,7 @@ Submodules
-
-
pycirk.make_scenarios.basic_add(a, at)[source]¶
+pycirk.make_scenarios.basic_add(a, at)[source]¶
Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@ Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
-
-
-
+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}})
\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
PxP_ITA_TC[source]¶Bases: object
Model with Transformation Coefficients ProdxProd Industry Technology assumption
-
-
L(T, inv_diag_q)[source]¶
+ Input coefficients intermediates A = U * T * inv[diag (q)]
Multiplier matrix @@ -209,20 +208,20 @@
Submodules
- -
+R(diag_q)[source]¶R(diag_q)[source]¶Calculates absolute extensions
- -
L(T, inv_diag_q)[source]¶
Submodules
-
-
calculate_characterized()[source]¶
+calculate_characterized()[source]¶
-
-
delta_Y(Yalt)[source]¶
+delta_Y(Yalt)[source]¶
method to calculate difference in Y
Y = final demand baseline
Yalt = final demand scenario
@@ -244,7 +243,7 @@ Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
calculate_characterized()[source]¶delta_Y(Yalt)[source]¶delta_Y(Yalt)[source]¶
method to calculate difference in Y Y = final demand baseline Yalt = final demand scenario
@@ -244,7 +243,7 @@Submodules
-
-
delta_x(Lalt, y)[source]¶
+delta_x(Lalt, y)[source]¶
method to calculate difference in q
L = Leontief of baseline
Lalt = Leontief of scenario
@@ -252,13 +251,13 @@ Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
delta_x(Lalt, y)[source]¶method to calculate difference in q L = Leontief of baseline Lalt = Leontief of scenario
@@ -252,13 +251,13 @@Submodules
-
-
inv()[source]¶
+inv()[source]¶
Returns inverse by dividing by 1 and eliminating inf and nan values
inv()[source]¶Returns inverse by dividing by 1 and eliminating inf and nan values
pycirk.labels.Labels[source]¶pycirk.labels.Labels[source]¶
Bases: object
-
-
apply_labels(matrix, labels, axis=0)[source]¶
+ Applies labels to a dataframe axis = 0 => Index axis = 1 => columns
@@ -285,20 +284,20 @@Submodules
- -
+calc_no_of_something(labels)[source]¶calc_no_of_something(labels)[source]¶A general method to calculate the number of unique entries contained in a series
- -
apply_labels(matrix, labels, axis=0)[source]¶
-
-
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
+ Calculates all unique entries (labels) contained in a dataframe and puts them together with their units and total count of unique entries
It returns an object… which is munched, not a pretty solution but it @@ -307,43 +306,43 @@
Submodules
- -
+identify_labels(M_name)[source]¶identify_labels(M_name)[source]¶A method to understand what type of labels are being handled depending on the name of the matrix in dataframe type that is being passed
- -
get_unique_labels(dataframe_of_labels, for_units=True)[source]¶
-
-
list_of_something(labels)[source]¶
+ A general method to return a list of unique entries contained in a series
list_of_something(labels)[source]¶
-
-
relabel(M, column_labels, index_labels)[source]¶
+ Processes apply_labels and apply _names together
relabel(M, column_labels, index_labels)[source]¶
-
-
relabel_to_save(data, trans_method, labels_directory)[source]¶
+ This function makes sure that everything is labeled in IOT tables
trans_method = 0 is prod x prod , 1 is ind x ind
relabel_to_save(data, trans_method, labels_directory)[source]¶
-
-
save_labels(data, directory)[source]¶
+ saves the labels of the database in the labels directory
save_labels(data, directory)[source]¶
Submodules
-
-
pycirk.make_scenarios.basic_add(a, at)[source]¶
+pycirk.make_scenarios.basic_add(a, at)[source]¶
Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@ Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
-
-
-
+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}})
\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
pycirk.make_scenarios.basic_add(a, at)[source]¶Adds values together
a : numpy.array
at : numpy array
@@ -367,39 +366,39 @@Submodules
-
-
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
+pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶
Policy intervention
It may be a primary intervention or an acillary action.
-
-- a: numpy.array
-- a supply chain or a point in it subject to a change
-- kt: float
-- technical coefficient (max achievable technically)
-- kp: float
-- penetration coefficient (level of market penet. of the policy)
-- ide: int
-- identification number of the intervention in case of missing information
+
+- a: numpy.array
a supply chain or a point in it subject to a change
+- kt: float
technical coefficient (max achievable technically)
+- kp: float
penetration coefficient (level of market penet. of the policy)
+- ide: int
identification number of the intervention in case of missing information
+
A a numpy.array of the same order/shape of a
-
-
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
+pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a
specific matrix
-
-- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
+
+- scen_file: str
directory of the file in which the scenarios are specified
+- scen_noint
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
matrix affected by the policies
+- M_namestr
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+
A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@ Submodules
-
-
pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶
This function allows for the proccessing of the specified interventions
onto a selected matrix. It calls various functions to modify the values
in a specified matrix.
-
-- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied
-(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to
-specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another
-according to specifications in scenarios.xlsx
+
+- Mnumpy.array
matrix of reference
+- inter_sets: dict
contains all specfication concerning the changes to be applied
+(intervention sets)
+- subsbool
If True it will call the subsitution function according to
+specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another
+according to specifications in scenarios.xlsx
+
i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@ Submodules
-
-
pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶
Calculate all the counterfactual IO matrices
-
-- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
+
+- dataobj
An object containing all necessary matrices of the IO system
+- scen_noint
the identification number of the scenario to reference in scen_file
+- scen_filestr
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+
An object contaning a mofified IO system
-
-
pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶
Organizes the data concerning the changes and calls the functions
to modified matrices based on specied scenarios
-
-- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
+
+- filterd_changes: pandas.DataFrame
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
matrix on which to implement the changes
+- M_namestr
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+
g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@ Submodules
-
-
pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶
Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that
@@ -481,14 +480,14 @@
Submodules
-- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes
-(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
+
+- dnumpy.array
transaction with which we are substituting
+- snumpy.array
original transaction that was subject to changes
+(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+
A numpy.array of modified d
@@ -505,7 +504,7 @@ Submodules
-
-
pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶
This function allows to move the primary material output from the
secondary material industries to the secondary material output.
This allows for the presence of secondary materials in the IOT
@@ -516,7 +515,7 @@
Submodules
-
-
pycirk.make_secondary_flows.make_secondary(data)[source]¶
+pycirk.make_secondary_flows.make_secondary(data)[source]¶
This allows to allign secondary flow in such a way that they then
appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@ Submodules
-
-
pycirk.organize_io.organizer(data)[source]¶
+pycirk.organize_io.organizer(data)[source]¶
@@ -570,53 +569,53 @@ Submodules
-
-
pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the specification of the
users.
-
-- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix
+
+- cat_coordint, numpy.array, bool
the numerical coordinate of a specific category belonging to a matrix
in the IO or SUT system. If None is passed then it will return an
-array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system.
+array of all coordinates in range no_categories.
+
+- reg_coordint, numpy.array, bool
the numerical coordinate of a specific region in the IO or SUT system.
If None is passed then it will return an array of all coordinates in
-range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries.
+
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point specified by the user
-
-
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
+pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location
of secondary materials and processing categories
-
-- coordinates : int, numpy.array
-- the numerical coordinate of secondary categories belonging to the SUT system
-- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+
+- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+- no_countriesint
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
A numpy.array referring to each coordinate point
-
-
pycirk.positions.single_position(item, labels)[source]¶
+pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position
of the specified values
-
-- item : str
-- The label the user is looking for
-- labels : obj
-- An object cointaining a set of labels
-(as specified in the labels.py module)
+
+- itemstr
The label the user is looking for
+- labelsobj
An object cointaining a set of labels
+(as specified in the labels.py module)
+
An numpy.array containing the coordinate of a specific label
or None in case of there is no specified label
@@ -632,62 +631,59 @@ Submodules
-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
Bases: object
Pycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis.
From here, you can launch all the analysis specifications listed under
scenarios.xlsx
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
-- scenario_results : int
-Allows to calculate the results for a given specified scenario
-0 = baseline data
-- all_results :
-- Retrieves all results for all specified scenarios and baseline
-- save_results : int and bool
-- save all specified analytical results from all scenario and baseline
+
+- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+- all_results :
Retrieves all results for all specified scenarios and baseline
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+
-
-- analysis.xlsx : excel file
-- to be found under the default folder on the specified directory
-it allows to specify the parameters for your scenario and analysis
-- IO tables : pkl
-- IO tables of the specified scenarios, these are located in the output
-folder in the save directory
-- results : DataFrame
-- results gathered from the processed scenarios and baseline
+
+- analysis.xlsxexcel file
to be found under the default folder on the specified directory
+it allows to specify the parameters for your scenario and analysis
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output
+folder in the save directory
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+
-
-
all_results()[source]¶
+all_results()[source]¶
Process all scenarios and collects their results together with
Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@ Submodules
-
-
delete_previous_IO_builds()[source]¶
+delete_previous_IO_builds()[source]¶
Call this method if you want to elinate all previous
IO databases created by pycirk. SUTs database is not affected.
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+save_results(scen_no=None, output_dataset=False)[source]¶
Saves all results in excel format for info and results or in
pickle format for the dataset
-
-- scen_no: int
-0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in
-pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in
+pd.DataFrames
+
Default values will save all results from the all_results method
and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified
in which case it would save also a data.pkl file
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same
-output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the
-results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
-This is only possible if outputting single scenario (scen_no != None)
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same
+output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the
+results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+This is only possible if outputting single scenario (scen_no != None)
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+scenario_results(scen_no, output_dataset=False)[source]¶
Run to output results of a specified scenario
-
-- scen_no: int
-- 0 = baseline
-1-n = specified scenarios
-- output_datase: bool
-- If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
+- scen_no: int
0 = baseline
+1-n = specified scenarios
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+
specified results in DataFrame form or a dictionary containing results
and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@ Submodules
-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
Bases: object
This class allows for to specify the settings for pycirk.
-
-- method : int
-SUTs to IO transformation methods
+
+- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
- make_secondary : bool
-modifies SUT so that secondary technologies which process scrap
+
- make_secondarybool
modifies SUT so that secondary technologies which process scrap
materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+- save_directorystr
directory in which you want to work and save your results
- save_directory : str
-- directory in which you want to work and save your results
aggregation : int, bool
0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-- file : bool, str
-- allows you to specify where the dataset is placed. None will use the
-default location within the installed package
-- test : bool
-- if set to true it will run the test settings under under pycirk//tests
+
+- filebool, str
allows you to specify where the dataset is placed. None will use the
+default location within the installed package
+- testbool
if set to true it will run the test settings under under pycirk//tests
+
-
--
-
assign_labels_to_class()[source]¶
-Assigns all labels to their respective attributes in the Labels class
-These are used througout the program to find coordinates and
-label results
-
-
-
-
check_dataset_location()[source]¶
+check_dataset_location()[source]¶
It identifies where the baseline dataset is located and whether it is
present in the directory. If an IO database was already created in the
past then it will just return it’s location and type instead of
@@ -808,74 +793,74 @@
Submodules
-
-
check_expand_directory(directory)[source]¶
+check_expand_directory(directory)[source]¶
Checking that we are using the right directory for the right OS
-
-
create_output_folder()[source]¶
+create_output_folder()[source]¶
It creates an output folder where to save analytical results
This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+create_scenario_file()[source]¶
It creates a new scenario file by copying the original from
pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+project_specs(test=False)[source]¶
General specifications for the project, they are also used to mark
the output files
-
-
scenario_file()[source]¶
+scenario_file()[source]¶
It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+set_IO_scenario(data, scen_no)[source]¶
Class the functions to modify the IO database according to your
scenario specifications
-
-
set_save_directory()[source]¶
+set_save_directory()[source]¶
It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+transform_to_io()[source]¶
Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent
then it will launch the function to modify the database
@@ -899,20 +884,25 @@ Submodules
-
-
pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶
It uses your analytical specification on scenarios.xlxl
to return a dataframe of the desired results
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
Separate, collect and rename results for base and scenarios according
to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table
spec_row = row in the scenarios sheet specifying settings
+
+
pycirk.save_utils module¶
@@ -923,34 +913,34 @@ Submodules
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
It saves results into a previously specified directory
-
-- results : pandas.DataFrame
-- a dataframe containing only selected results
-- directory : str
-- the general location specified for your scenarios.xlsx file
-- specs : dict
-- a dictionary containing general info about the project (e.g. author, institution, etc)
-- scen_no : int or None
-- an integer specifying the scenario number or enter None to save all results
-- data : dict of pd.DataFrames
-- a completely new dataset to be pickled. Default value is None otherwise
-pass the dataset
+
+- resultspandas.DataFrame
a dataframe containing only selected results
+- directorystr
the general location specified for your scenarios.xlsx file
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise
+pass the dataset
+
-
-- scenarios.xlsx : excel file
-- scenario settings excel file used for the analysis in the same output directory with the results
-- info_and_results.xlsx : excel file
-- excel file containing general info about project plus the results from the analysis
-- data.pkl : pickle file
-- new modified IO dataset in pickle format
+
+- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+- data.pklpickle file
new modified IO dataset in pickle format
+
@@ -964,19 +954,19 @@ Submodules
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class pycirk.transformation_methods.Transform(SUTs)[source]¶
Bases: object
Transforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+IOTpxpSTA_MSCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Market share coef method
-
-
IOTpxpSTA_TCm()[source]¶
+IOTpxpSTA_TCm()[source]¶
IOT prod x prod Single tech Industry-technology assumption
Technical coef method
@@ -1033,13 +1023,11 @@ Related Topics
@@ -1060,7 +1048,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html
index 81bdb33..b55d322 100644
--- a/docs/_build/html/readme.html
+++ b/docs/_build/html/readme.html
@@ -1,11 +1,9 @@
-
+
-
-
+
pycirk — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -40,25 +39,31 @@ pycirk
-Documentation: https://cmlplatform.github.io/pycirk/
+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html
10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+
Once you have a copy of the source, you can install it with:
-$ python setup.py install
+$ python setup.py install
+
1.3 Data¶
@@ -73,36 +78,41 @@ 2. Usage
2.1. Import package¶
-import pycirk
+import pycirk
+
2.2. Initialize¶
-my_work = pycirk.Launch(method, directory, aggregation)
+my_work = pycirk.Launch(method, directory, aggregation)
+
2.3. set your scenarios and analysis¶
-- Open scenarios.xls in the directory that was specified
-- From there you can specify interventions and parameters for the analysis
-- save and continue to the following steps
+Open scenarios.xls in the directory that was specified
From there you can specify interventions and parameters for the analysis
save and continue to the following steps
2.4. Run scenarios¶
Run one specific scenario
-my_work.scenario_results(scen_no, output_dataset)
-(0 = baseline)
+my_work.scenario_results(scen_no, output_dataset)
+(0 = baseline)
+
Run all scenarios
-my_work.all_results()
+my_work.all_results()
+
2.5. save scenarios¶
Save your results
-my_work.save_results()
+my_work.save_results()
+
2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@ 2.5. save scenarios
+
-
-
-Command
-Variables
+
+Command
Variables
-tm, –transf_method TEXT
-0 = PXP ITA_TC; 1 = PXP ITA_MSC
+-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT
-if left black it will be default
+-dr, –directory TEXT
if left black it will be default
-ag, –aggregation
-1 = bi-regional (EU-ROW)
-0 = None (49 regions)
+-ag, –aggregation
1 = bi-regional (EU-ROW)
+0 = None (49 regions)
-sc, –scenario TEXT
-all, 1, 2,… accepted - 0=baseline
+-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT
-False=no, True=yes
+-s, –save TEXT
False=no, True=yes
-od, –output_dataset
-False=no, True=yes
+-od, –output_dataset
False=no, True=yes
–help
-Show this message and exit.
+–help
Show this message and exit.
2.6.2. Command example
-pycirk -tm 0 -dr “” -sc “1” -s True -od False
+pycirk -tm 0 -dr “” -sc “1” -s True -od False
+
3. Features¶
Examples of policies that can be modelled through the software:
-- sharing
-- recycling
-- life extension
-- rebound effects
-- substituion
-- market and value added changes
-- efficiency
+sharing
recycling
life extension
rebound effects
substituion
market and value added changes
efficiency
The tables in which it is possible to apply changes:
-- total requirement matrix (A)
-- intermediate transactions (Z)
-- final demand (Y)
-- primary inputs (W)
-- emission intermediate extentions (E)
-- material intermediate extensions (M)
-- resource intermediate extensions (R)
-- emission final demand extension (EY)
-- material final demand extension (MY)
-- resource final demand extensions (RY)
-- primary inputs coefficients (w)
-- emission intermediate extentions coefficients (e)
-- material intermediate extensions coefficients (m)
-- resource intermediate extensions coefficients (r)
-- emission final demand extension coefficients (eY)
-- material final demand extension coefficients (mY)
-- resource final demand extensions coefficients (rY)
+total requirement matrix (A)
intermediate transactions (Z)
final demand (Y)
primary inputs (W)
emission intermediate extentions (E)
material intermediate extensions (M)
resource intermediate extensions (R)
emission final demand extension (EY)
material final demand extension (MY)
resource final demand extensions (RY)
primary inputs coefficients (w)
emission intermediate extentions coefficients (e)
material intermediate extensions coefficients (m)
resource intermediate extensions coefficients (r)
emission final demand extension coefficients (eY)
material final demand extension coefficients (mY)
resource final demand extensions coefficients (rY)
It is possible to specify:
-- region of the intervention
-- whether the intervention affects domestic, import transactions or both
+region of the intervention
whether the intervention affects domestic, import transactions or both
@@ -194,36 +205,36 @@ 4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-- matrix = specifies in which matrix of IOT the changes are applied
-- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
-- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
-- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
-- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
-- ka = absolute values for addition
-- kp = penetration coefficient (level of market penetration of the policy); unit = %
-- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
-- substitution = tells the software whether it needs to substitute values among specified categories
-- sk = which intervention should be substituted
-- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
+matrix = specifies in which matrix of IOT the changes are applied
change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
ka = absolute values for addition
kp = penetration coefficient (level of market penetration of the policy); unit = %
copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
substitution = tells the software whether it needs to substitute values among specified categories
sk = which intervention should be substituted
swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
These can be set for:
-- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
-- final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
-- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
-- emissions extensions e.g. E_CO2_c (CO2 - combustion)
-- material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
-- resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
+product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
emissions extensions e.g. E_CO2_c (CO2 - combustion)
material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-- product categories
-- primary input categories
-- emissions extensions
-- material extensions
-- resource extensions
-- region of interest
-- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
+product categories
primary input categories
emissions extensions
material extensions
resource extensions
region of interest
impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
@@ -281,13 +292,11 @@ Related Topics
@@ -308,7 +317,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html
index f3aeacb..99a5cee 100644
--- a/docs/_build/html/search.html
+++ b/docs/_build/html/search.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Search — pycirk 1.5.0 documentation
@@ -14,14 +12,11 @@
+
-
-
-
+
@@ -55,7 +50,7 @@ Search
containing fewer words won't appear in the result list.
@@ -114,7 +109,7 @@ Related Topics
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js
index ebf188b..a048e1c 100644
--- a/docs/_build/html/searchindex.js
+++ b/docs/_build/html/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html
index b27e54d..3342033 100644
--- a/docs/_build/html/usage.html
+++ b/docs/_build/html/usage.html
@@ -1,11 +1,9 @@
-
+
-
-
+
Usage — pycirk 1.5.0 documentation
@@ -13,6 +11,7 @@
+
@@ -79,13 +78,11 @@ Related Topics
@@ -106,7 +103,7 @@ Quick search
©2019, Franco Donati.
|
- Powered by Sphinx 1.8.2
+ Powered by Sphinx 2.2.0
& Alabaster 0.7.12
|
diff --git a/docs/pycirk.rst b/docs/pycirk.rst
index 3262eb4..4258a86 100644
--- a/docs/pycirk.rst
+++ b/docs/pycirk.rst
@@ -8,103 +8,103 @@ pycirk.cli module
-----------------
.. automodule:: pycirk.cli
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.fundamental\_operations module
-------------------------------------
.. automodule:: pycirk.fundamental_operations
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.labels module
--------------------
.. automodule:: pycirk.labels
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_scenarios module
-----------------------------
.. automodule:: pycirk.make_scenarios
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.make\_secondary\_flows module
------------------------------------
.. automodule:: pycirk.make_secondary_flows
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.organize\_io module
--------------------------
.. automodule:: pycirk.organize_io
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.positions module
-----------------------
.. automodule:: pycirk.positions
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk module
--------------------
.. automodule:: pycirk.pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.pycirk\_settings module
------------------------------
.. automodule:: pycirk.pycirk_settings
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.results module
---------------------
.. automodule:: pycirk.results
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.save\_utils module
-------------------------
.. automodule:: pycirk.save_utils
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
pycirk.transformation\_methods module
-------------------------------------
.. automodule:: pycirk.transformation_methods
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
Module contents
---------------
.. automodule:: pycirk
- :members:
- :undoc-members:
- :show-inheritance:
+ :members:
+ :undoc-members:
+ :show-inheritance:
diff --git a/pycirk/__init__.py b/pycirk/__init__.py
index 7c98474..ce62d6d 100644
--- a/pycirk/__init__.py
+++ b/pycirk/__init__.py
@@ -4,6 +4,6 @@
__author__ = """Franco Donati"""
__email__ = 'f.donati@cml.leidenuniv.nl'
-__version__ = '1.5.0'
+__version__ = '1.5.5'
from pycirk.pycirk import Launch
\ No newline at end of file
diff --git a/setup.cfg b/setup.cfg
index ba2f433..d7e8652 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
[bumpversion]
-current_version = 1.5.0
+current_version = 1.5.5
commit = True
tag = True
pycirk.make_scenarios.basic_mult(ide, a, kt, kp)[source]¶Policy intervention
It may be a primary intervention or an acillary action.
--
-
- a: numpy.array -
- a supply chain or a point in it subject to a change -
- kt: float -
- technical coefficient (max achievable technically) -
- kp: float -
- penetration coefficient (level of market penet. of the policy) -
- ide: int -
- identification number of the intervention in case of missing information +
- a: numpy.array
a supply chain or a point in it subject to a change
+
+- kt: float
technical coefficient (max achievable technically)
+
+- kp: float
penetration coefficient (level of market penet. of the policy)
+
+- ide: int
identification number of the intervention in case of missing information
+
-
+
A a numpy.array of the same order/shape of a
pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶pycirk.make_scenarios.counterfactual(scen_file, scen_no, M, M_name, labels)[source]¶
Separates changes by matrix subject to intervention and apply them on a specific matrix
-@@ -570,53 +569,53 @@-
- scen_file: str
-- directory of the file in which the scenarios are specified
-- scen_no : int
-- specific scenario e.g “1” or “scenario_1”
-- M : numpy.array
-- matrix affected by the policies
-- M_name : str
-- matrix name as diplayed under sheet_name[“matrix”]
-- labels : obj
-- matrix labels
++
- scen_file: str
- +
directory of the file in which the scenarios are specified
+- scen_noint
- +
specific scenario e.g “1” or “scenario_1”
+- Mnumpy.array
- +
matrix affected by the policies
+- M_namestr
- +
matrix name as diplayed under sheet_name[“matrix”]
+- labelsobj
matrix labels
+A numpy array modified according to the specified changes in the scenario file
@@ -407,22 +406,22 @@Submodules
- -
+pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶pycirk.make_scenarios.counterfactual_engine(M, inter_sets, subs=False, copy=False)[source]¶This function allows for the proccessing of the specified interventions onto a selected matrix. It calls various functions to modify the values in a specified matrix.
--
- M : numpy.array
-- matrix of reference
-- inter_sets: dict
-- contains all specfication concerning the changes to be applied -(intervention sets)
-- subs : bool
-- If True it will call the subsitution function according to -specifications in scenarios.xlsx
-- copy : bool
-- if True it will copy value from one part of the matrix to another -according to specifications in scenarios.xlsx
++
- Mnumpy.array
- +
matrix of reference
+- inter_sets: dict
- +
contains all specfication concerning the changes to be applied +(intervention sets)
+- subsbool
- +
If True it will call the subsitution function according to +specifications in scenarios.xlsx
+- copybool
if True it will copy value from one part of the matrix to another +according to specifications in scenarios.xlsx
+i : index coordinate
g : column coordinate
@@ -436,35 +435,35 @@Submodules
- -
+pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶pycirk.make_scenarios.make_counterfactuals(data, scen_no, scen_file, labels)[source]¶Calculate all the counterfactual IO matrices
--
- data : obj
-- An object containing all necessary matrices of the IO system
-- scen_no : int
-- the identification number of the scenario to reference in scen_file
-- scen_file : str
-- the directory where the scenarios.xlsx file is store
-- labels : obj
-- an object containing all labels for the IO matrices
++
- dataobj
- +
An object containing all necessary matrices of the IO system
+- scen_noint
- +
the identification number of the scenario to reference in scen_file
+- scen_filestr
- +
the directory where the scenarios.xlsx file is store
+- labelsobj
an object containing all labels for the IO matrices
+An object contaning a mofified IO system
- -
+pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶pycirk.make_scenarios.make_new(filtered_changes, M, M_name, labels)[source]¶Organizes the data concerning the changes and calls the functions to modified matrices based on specied scenarios
--
@@ -505,7 +504,7 @@- filterd_changes: pandas.DataFrame
-- A table filtered by matrix name containing all changes to be applied
-- M : numpy.array
-- matrix on which to implement the changes
-- M_name : str
-- nomenclature referring to the matrix to be changed
-- labels: obj
-- object containing all matrix labels
++
- filterd_changes: pandas.DataFrame
- +
A table filtered by matrix name containing all changes to be applied
+- Mnumpy.array
- +
matrix on which to implement the changes
+- M_namestr
- +
nomenclature referring to the matrix to be changed
+- labels: obj
object containing all matrix labels
+g is any column in the matrix
i is any row row in the matrix
@@ -473,7 +472,7 @@Submodules
- -
+pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶pycirk.make_scenarios.substitution(d, s, fx_kp)[source]¶Moves the value from one or multiple cells (in the same row or column)
Substitution: Material subsitution or certain types of rebound effects
If the size of the array of the original value is different from that @@ -481,14 +480,14 @@
Submodules -
- d : numpy.array
-- transaction with which we are substituting
-- s : numpy.array
-- original transaction that was subject to changes -(the transactions from which the value is coming from)
-- fx_kp : float
-- relative size of c that is added on the transaction to expand d
++
- dnumpy.array
- +
transaction with which we are substituting
+- snumpy.array
- +
original transaction that was subject to changes +(the transactions from which the value is coming from)
+- fx_kpfloat
relative size of c that is added on the transaction to expand d
+A numpy.array of modified d
Submodules
- -
+pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶pycirk.make_secondary_flows.allocate_sec_mat(V, U, Y, prod_or, ind_or)[source]¶This function allows to move the primary material output from the secondary material industries to the secondary material output. This allows for the presence of secondary materials in the IOT @@ -516,7 +515,7 @@
Submodules
- -
+pycirk.make_secondary_flows.make_secondary(data)[source]¶pycirk.make_secondary_flows.make_secondary(data)[source]¶This allows to allign secondary flow in such a way that they then appear in the IOT
Primary Products’ positions
@@ -557,7 +556,7 @@Submodules
- -
+pycirk.organize_io.organizer(data)[source]¶pycirk.organize_io.organizer(data)[source]¶Submodules
- -
+pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶pycirk.positions.make_coord_array(cat_coord, reg_coord, no_countries, no_categories)[source]¶It creates an an array of coordinates based on the specification of the users.
--
- cat_coord : int, numpy.array, bool
-- the numerical coordinate of a specific category belonging to a matrix +
++
- cat_coordint, numpy.array, bool
- -
the numerical coordinate of a specific category belonging to a matrix in the IO or SUT system. If None is passed then it will return an -array of all coordinates in range no_categories.
- reg_coord : int, numpy.array, bool
-- the numerical coordinate of a specific region in the IO or SUT system. +array of all coordinates in range no_categories. +
+- reg_coordint, numpy.array, bool
- -
the numerical coordinate of a specific region in the IO or SUT system. If None is passed then it will return an array of all coordinates in -range no_countries.
- no_countries : int
-- the total number of countries or regions in the dataset
-- no_categories : int
-- the total number of categories referring one axis in the chosen matrix
+range no_countries. +- no_countriesint
- +
the total number of countries or regions in the dataset
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+A numpy.array referring to each coordinate point specified by the user
pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶pycirk.positions.make_coord_array_for_make_sec(coordinates, no_countries, no_categories)[source]¶
It creates an an array of coordinates based on the total location of secondary materials and processing categories
--
-
- coordinates : int, numpy.array -
- the numerical coordinate of secondary categories belonging to the SUT system -
- no_countries : int -
- the total number of countries or regions in the dataset -
- no_categories : int -
- the total number of categories referring one axis in the chosen matrix +
- coordinatesint, numpy.array
the numerical coordinate of secondary categories belonging to the SUT system
+
+- no_countriesint
the total number of countries or regions in the dataset
+
+- no_categoriesint
the total number of categories referring one axis in the chosen matrix
+
-
+
A numpy.array referring to each coordinate point
pycirk.positions.single_position(item, labels)[source]¶pycirk.positions.single_position(item, labels)[source]¶
Takes a dataframe of the multiindex and identifies the position of the specified values
--
-
- item : str -
- The label the user is looking for -
- labels : obj -
- An object cointaining a set of labels -(as specified in the labels.py module) +
- itemstr
The label the user is looking for
+
+- labelsobj
An object cointaining a set of labels +(as specified in the labels.py module)
+-
-class
pycirk.pycirk.Launch(method=0, make_secondary=False, save_directory=None, aggregation=1, file=None, test=False)[source]¶
+class Bases:
objectPycirk’s main class and methods
Initialize the pycirk programme to make EEIO scenarios and analysis. From here, you can launch all the analysis specifications listed under scenarios.xlsx
--
-
- method : int -
SUTs to IO transformation methods
+-
+
- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
-- make_secondary : bool -
modifies SUT so that secondary technologies which process scrap +
- make_secondarybool
modifies SUT so that secondary technologies which process scrap materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+
+- save_directorystr
directory in which you want to work and save your results
-- save_directory : str -
- directory in which you want to work and save your results
aggregation : int, bool
-0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-
- file : bool, str -
- allows you to specify where the dataset is placed. None will use the -default location within the installed package -
- test : bool -
- if set to true it will run the test settings under under pycirk//tests +
- filebool, str
allows you to specify where the dataset is placed. None will use the +default location within the installed package
+
+- testbool
if set to true it will run the test settings under under pycirk//tests
+- scenario_results : int -
Allows to calculate the results for a given specified scenario
-0 = baseline data
-
-- all_results : -
- Retrieves all results for all specified scenarios and baseline -
- save_results : int and bool -
- save all specified analytical results from all scenario and baseline +
- scenario_resultsint
Allows to calculate the results for a given specified scenario
+0 = baseline data
+
+- all_results :
Retrieves all results for all specified scenarios and baseline
+
+- save_resultsint and bool
save all specified analytical results from all scenario and baseline
+- analysis.xlsx : excel file -
- to be found under the default folder on the specified directory -it allows to specify the parameters for your scenario and analysis -
- IO tables : pkl -
- IO tables of the specified scenarios, these are located in the output -folder in the save directory -
- results : DataFrame -
- results gathered from the processed scenarios and baseline +
- analysis.xlsxexcel file
to be found under the default folder on the specified directory +it allows to specify the parameters for your scenario and analysis
+
+- IO tablespkl
IO tables of the specified scenarios, these are located in the output +folder in the save directory
+
+- resultsDataFrame
results gathered from the processed scenarios and baseline
+-
-
all_results()[source]¶
+ Process all scenarios and collects their results together with Baseline analysis results
It outputs a pandas.DataFrame with all results
@@ -695,52 +691,51 @@Submodules
- -
+delete_previous_IO_builds()[source]¶delete_previous_IO_builds()[source]¶Call this method if you want to elinate all previous IO databases created by pycirk. SUTs database is not affected.
- -
-
-
save_results(scen_no=None, output_dataset=False)[source]¶
+ Saves all results in excel format for info and results or in pickle format for the dataset
--
-
- scen_no: int -
0 = baseline
-1-n = specified scenarios
-
-- output_datase: bool -
- If true it will output a dictionary containing all IOT tables in -pd.DataFrames +
- scen_no: int
0 = baseline
+1-n = specified scenarios
+
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in +pd.DataFrames
+- scenarios.xlsx : excel file -
- scenario settings excel file used for the analysis in the same -output directory with the results -
- info_and_results.xlsx : excel file -
- excel file containing general info about project plus the -results from the analysis -
- data.pkl : pickle file -
- new modified IO dataset in pickle format -This is only possible if outputting single scenario (scen_no != None) +
- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same +output directory with the results
+
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the +results from the analysis
+
+- data.pklpickle file
new modified IO dataset in pickle format +This is only possible if outputting single scenario (scen_no != None)
+
-
+
Default values will save all results from the all_results method and they will output only scenario.xlsx and info_and_results.xlsx
Output_dataset is only possible when scen_no is specified in which case it would save also a data.pkl file
--
-
-
+
-
-
scenario_results(scen_no, output_dataset=False)[source]¶
+ Run to output results of a specified scenario
--
-
- scen_no: int -
- 0 = baseline -1-n = specified scenarios -
- output_datase: bool -
- If true it will output a dictionary containing all IOT tables in pd.DataFrames +
- scen_no: int
0 = baseline +1-n = specified scenarios
+
+- output_datase: bool
If true it will output a dictionary containing all IOT tables in pd.DataFrames
+-
-class
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
+class Bases:
objectThis class allows for to specify the settings for pycirk.
--
-
- method : int -
SUTs to IO transformation methods
+-
+
- methodint
SUTs to IO transformation methods
0 = Prod X Prod Ind-Tech Assumption Technical Coeff method
-1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
+1 = Prod X Prod Ind-Tech Assumption Market Share Coeff method
-- make_secondary : bool -
modifies SUT so that secondary technologies which process scrap +
- make_secondarybool
modifies SUT so that secondary technologies which process scrap materials into primary materials are also available in the IO tables
False = Don’t modify
-True = Modify
+True = Modify
+
+- save_directorystr
directory in which you want to work and save your results
-- save_directory : str -
- directory in which you want to work and save your results
aggregation : int, bool
-0 = None (multi-regional 49 regions)
1 = bi-regional (EU- ROW)
-
-
- file : bool, str -
- allows you to specify where the dataset is placed. None will use the -default location within the installed package -
- test : bool -
- if set to true it will run the test settings under under pycirk//tests +
- filebool, str
allows you to specify where the dataset is placed. None will use the +default location within the installed package
+
+- testbool
if set to true it will run the test settings under under pycirk//tests
+-
-
assign_labels_to_class()[source]¶
- Assigns all labels to their respective attributes in the Labels class -These are used througout the program to find coordinates and -label results
--
-
check_dataset_location()[source]¶
+ It identifies where the baseline dataset is located and whether it is present in the directory. If an IO database was already created in the past then it will just return it’s location and type instead of @@ -808,74 +793,74 @@
Submodules
- -
+check_expand_directory(directory)[source]¶check_expand_directory(directory)[source]¶Checking that we are using the right directory for the right OS
- -
-
-
create_output_folder()[source]¶
+ It creates an output folder where to save analytical results This is placed in the user’s working directory
-
-
create_scenario_file()[source]¶
+ It creates a new scenario file by copying the original from pycirk directory to the new working directory specified by the user
-
-
project_specs(test=False)[source]¶
+ General specifications for the project, they are also used to mark the output files
-
-
scenario_file()[source]¶
+ It returns where the working scenarios.xlsx file is located
-
-
set_IO_scenario(data, scen_no)[source]¶
+ Class the functions to modify the IO database according to your scenario specifications
-
-
set_save_directory()[source]¶
+ It specifies where the scenario file for input is located
-
-
transform_to_io()[source]¶
+ Transforms the SUT dataset into an IO system
If the user specified to make secondary material processing apparent then it will launch the function to modify the database
@@ -899,20 +884,25 @@Submodules
- -
+pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶pycirk.results.iter_thru_for_results(data, analysis_specs, scen_no, labels)[source]¶It uses your analytical specification on scenarios.xlxl to return a dataframe of the desired results
- -
-
-
pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶
+ Separate, collect and rename results for base and scenarios according to specifications under th sheet “analysis” in scenarios.xls
data = any IOT table spec_row = row in the scenarios sheet specifying settings
-
-
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶
+ Adds timemark to general specifications e.g. authors, institution etc
-
-
pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶
+ It saves results into a previously specified directory
--
-
- results : pandas.DataFrame -
- a dataframe containing only selected results -
- directory : str -
- the general location specified for your scenarios.xlsx file -
- specs : dict -
- a dictionary containing general info about the project (e.g. author, institution, etc) -
- scen_no : int or None -
- an integer specifying the scenario number or enter None to save all results -
- data : dict of pd.DataFrames -
- a completely new dataset to be pickled. Default value is None otherwise -pass the dataset +
- resultspandas.DataFrame
a dataframe containing only selected results
+
+- directorystr
the general location specified for your scenarios.xlsx file
+
+- specsdict
a dictionary containing general info about the project (e.g. author, institution, etc)
+
+- scen_noint or None
an integer specifying the scenario number or enter None to save all results
+
+- datadict of pd.DataFrames
a completely new dataset to be pickled. Default value is None otherwise +pass the dataset
+- scenarios.xlsx : excel file -
- scenario settings excel file used for the analysis in the same output directory with the results -
- info_and_results.xlsx : excel file -
- excel file containing general info about project plus the results from the analysis -
- data.pkl : pickle file -
- new modified IO dataset in pickle format +
- scenarios.xlsxexcel file
scenario settings excel file used for the analysis in the same output directory with the results
+
+- info_and_results.xlsxexcel file
excel file containing general info about project plus the results from the analysis
+
+- data.pklpickle file
new modified IO dataset in pickle format
+
-
+
-
-
-
+
-
-class
pycirk.transformation_methods.Transform(SUTs)[source]¶
+class Bases:
objectTransforms SUTs to IOT an calcualate extensions
-
-
IOTpxpSTA_MSCm()[source]¶
+ IOT prod x prod Single tech Industry-technology assumption Market share coef method
IOTpxpSTA_MSCm()[source]¶-
-
IOTpxpSTA_TCm()[source]¶
+ IOT prod x prod Single tech Industry-technology assumption Technical coef method
IOTpxpSTA_TCm()[source]¶Related Topics
-
-
- Open scenarios.xls in the directory that was specified -
- From there you can specify interventions and parameters for the analysis -
- save and continue to the following steps +
Open scenarios.xls in the directory that was specified
+From there you can specify interventions and parameters for the analysis
+save and continue to the following steps
- sharing -
- recycling -
- life extension -
- rebound effects -
- substituion -
- market and value added changes -
- efficiency +
sharing
+recycling
+life extension
+rebound effects
+substituion
+market and value added changes
+efficiency
- total requirement matrix (A) -
- intermediate transactions (Z) -
- final demand (Y) -
- primary inputs (W) -
- emission intermediate extentions (E) -
- material intermediate extensions (M) -
- resource intermediate extensions (R) -
- emission final demand extension (EY) -
- material final demand extension (MY) -
- resource final demand extensions (RY) -
- primary inputs coefficients (w) -
- emission intermediate extentions coefficients (e) -
- material intermediate extensions coefficients (m) -
- resource intermediate extensions coefficients (r) -
- emission final demand extension coefficients (eY) -
- material final demand extension coefficients (mY) -
- resource final demand extensions coefficients (rY) +
total requirement matrix (A)
+intermediate transactions (Z)
+final demand (Y)
+primary inputs (W)
+emission intermediate extentions (E)
+material intermediate extensions (M)
+resource intermediate extensions (R)
+emission final demand extension (EY)
+material final demand extension (MY)
+resource final demand extensions (RY)
+primary inputs coefficients (w)
+emission intermediate extentions coefficients (e)
+material intermediate extensions coefficients (m)
+resource intermediate extensions coefficients (r)
+emission final demand extension coefficients (eY)
+material final demand extension coefficients (mY)
+resource final demand extensions coefficients (rY)
- region of the intervention -
- whether the intervention affects domestic, import transactions or both +
region of the intervention
+whether the intervention affects domestic, import transactions or both
- matrix = specifies in which matrix of IOT the changes are applied -
- change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level -
- reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column) -
- cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column) -
- kt = technical coefficient (max achievable technically); a negative value means reduction; unit = % -
- ka = absolute values for addition -
- kp = penetration coefficient (level of market penetration of the policy); unit = % -
- copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation) -
- substitution = tells the software whether it needs to substitute values among specified categories -
- sk = which intervention should be substituted -
- swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = % +
matrix = specifies in which matrix of IOT the changes are applied
+change_type = Primary and ancillary are only used to specify the type of intervention from a conceptual level
+reg_o or reg_d = Regional coordinates (o=origin or row, d=destination or column)
+cat_o or cat_d = category (e.g. products or extensions ) coordinates (o=origin or row, d=destination or column)
+kt = technical coefficient (max achievable technically); a negative value means reduction; unit = %
+ka = absolute values for addition
+kp = penetration coefficient (level of market penetration of the policy); unit = %
+copy = allows you to copy a specific transation to a different point in the matrices (useful for proxy creation)
+substitution = tells the software whether it needs to substitute values among specified categories
+sk = which intervention should be substituted
+swk = Substitution weighing factor (how much of the original transaction should be substituted); allows to simulate difference in prices and physical properties between categories; unit = %
- product category e.g. C_STEL (basic iron), C_PULP (pulp), etc. -
- final demand category e.g. F_HOUS (households), F_GOVE (government), etc. -
- primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc. -
- emissions extensions e.g. E_CO2_c (CO2 - combustion) -
- material extensions e.g. NI.02 (Nature Inputs: Coking Coal) -
- resource extension e.g. L_1.1 (Land use - Arable Land - Rice) +
product category e.g. C_STEL (basic iron), C_PULP (pulp), etc.
+final demand category e.g. F_HOUS (households), F_GOVE (government), etc.
+primary input category e.g. E_HRHS (employment highly skilled), T_TLSA (taxes less subsidies), etc.
+emissions extensions e.g. E_CO2_c (CO2 - combustion)
+material extensions e.g. NI.02 (Nature Inputs: Coking Coal)
+resource extension e.g. L_1.1 (Land use - Arable Land - Rice)
- product categories -
- primary input categories -
- emissions extensions -
- material extensions -
- resource extensions -
- region of interest -
- impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list +
product categories
+primary input categories
+emissions extensions
+material extensions
+resource extensions
+region of interest
+impact categories # Please see the data_validation_list sheet in the scenarios.xls file for the comprehensive list
-
+
-
-
check_dataset_location()[source]¶create_output_folder()[source]¶create_scenario_file()[source]¶project_specs(test=False)[source]¶scenario_file()[source]¶set_IO_scenario(data, scen_no)[source]¶set_save_directory()[source]¶transform_to_io()[source]¶pycirk.results.retrieve_specified_data(data, spec_row, labels)[source]¶@@ -1060,7 +1048,7 @@pycirk.save_utils module¶
@@ -923,34 +913,34 @@Submodules
pycirk.save_utils.add_date_to_gen_specs(specs)[source]¶pycirk.save_utils.save_outputs(results, directory, specs, scen_no, data=None)[source]¶Submodules
pycirk.transformation_methods.Transform(SUTs)[source]¶Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/_build/html/readme.html b/docs/_build/html/readme.html index 81bdb33..b55d322 100644 --- a/docs/_build/html/readme.html +++ b/docs/_build/html/readme.html @@ -1,11 +1,9 @@ - + - - +pycirk — pycirk 1.5.0 documentation @@ -13,6 +11,7 @@ + @@ -40,25 +39,31 @@pycirk
-Documentation: https://cmlplatform.github.io/pycirk/+Documentation: https://pycirk.readthedocs.io/en/latest/readme.html10.5281/zenodo.1492957
+To cite the use of the software in your research please use the following publication:
+“Modeling the circular economy in environmentally extended input-output tables: Methods, software and case study”
+https://doi.org/10.1016/j.resconrec.2019.104508
1. Installation¶
1.2. From source¶
Clone repository:
-
+$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git$ git clone https://fdonati@bitbucket.org/CML-IE/pycirk.git
+Once you have a copy of the source, you can install it with:
-
+$ python setup.py install$ python setup.py install
+1.3 Data¶
@@ -73,36 +78,41 @@2. Usage
2.1. Import package¶
-
+import pycirkimport pycirk
+2.2. Initialize¶
-
+my_work = pycirk.Launch(method, directory, aggregation)my_work = pycirk.Launch(method, directory, aggregation)
+2.3. set your scenarios and analysis¶
-
-
2.4. Run scenarios¶
Run one specific scenario
-
+my_work.scenario_results(scen_no, output_dataset) -(0 = baseline)my_work.scenario_results(scen_no, output_dataset) +(0 = baseline)
+Run all scenarios
-
+my_work.all_results()my_work.all_results()
+2.5. save scenarios¶
Save your results
-
+my_work.save_results()my_work.save_results()
+2.6. Use from command line
2.6.1. pycirk –help
Usage: pycirk [OPTIONS]
@@ -110,82 +120,83 @@2.5. save scenarios +
- - -- + + Command -Variables + +Command
Variables
-tm, –transf_method TEXT -0 = PXP ITA_TC; 1 = PXP ITA_MSC +-tm, –transf_method TEXT
0 = PXP ITA_TC; 1 = PXP ITA_MSC
-dr, –directory TEXT -if left black it will be default +-dr, –directory TEXT
if left black it will be default
-ag, –aggregation -1 = bi-regional (EU-ROW) -0 = None (49 regions) +-ag, –aggregation
1 = bi-regional (EU-ROW) +0 = None (49 regions)
-sc, –scenario TEXT -all, 1, 2,… accepted - 0=baseline +-sc, –scenario TEXT
all, 1, 2,… accepted - 0=baseline
-s, –save TEXT -False=no, True=yes +-s, –save TEXT
False=no, True=yes
-od, –output_dataset -False=no, True=yes +-od, –output_dataset
False=no, True=yes
–help -Show this message and exit. +–help
Show this message and exit.
2.6.2. Command example
-
+pycirk -tm 0 -dr “” -sc “1” -s True -od Falsepycirk -tm 0 -dr “” -sc “1” -s True -od False
+3. Features¶
Examples of policies that can be modelled through the software:
-
-
The tables in which it is possible to apply changes:
-
-
It is possible to specify:
-
-
@@ -194,36 +205,36 @@@@ -281,13 +292,11 @@4. Important modules¶
From this .xls file it is possible to set different types of interventions and the analysis to perform:
-
-
These can be set for:
-
-
Furthemore, from the analysis sheet you can set the following variables to be compared in the analysis:
-
-
Related Topics
@@ -308,7 +317,7 @@Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/_build/html/search.html b/docs/_build/html/search.html index f3aeacb..99a5cee 100644 --- a/docs/_build/html/search.html +++ b/docs/_build/html/search.html @@ -1,11 +1,9 @@ - + - - +Search — pycirk 1.5.0 documentation @@ -14,14 +12,11 @@ + - - - + @@ -55,7 +50,7 @@Search
containing fewer words won't appear in the result list.Related Topics
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js index ebf188b..a048e1c 100644 --- a/docs/_build/html/searchindex.js +++ b/docs/_build/html/searchindex.js @@ -1 +1 @@ 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to pycirk\u2019s documentation!","Installation","pycirk","pycirk package","pycirk","Usage"],titleterms:{"import":7,analysi:7,bug:1,cli:6,content:6,contribut:1,contributor:0,credit:[0,7],data:7,deploi:1,develop:0,document:[1,3],featur:[1,7],feedback:1,fix:1,from:[4,7],fundamental_oper:6,get:1,guidelin:1,histori:2,implement:1,indic:3,initi:7,instal:[4,7],label:6,lead:0,make_scenario:6,make_secondary_flow:6,modul:[6,7],organize_io:6,packag:[6,7],posit:6,pull:1,pycirk:[3,5,6,7],pycirk_set:6,releas:[4,7],report:1,request:1,result:6,run:7,save:7,save_util:6,scenario:7,set:7,sourc:[4,7],stabl:[4,7],start:1,submit:1,submodul:6,tabl:3,tip:1,transformation_method:6,type:1,usag:[7,8],welcom:3,write:1,xls:7,your:7}}) \ No newline at end of file diff --git a/docs/_build/html/usage.html b/docs/_build/html/usage.html index b27e54d..3342033 100644 --- a/docs/_build/html/usage.html +++ b/docs/_build/html/usage.html @@ -1,11 +1,9 @@ - + - - +Usage — pycirk 1.5.0 documentation @@ -13,6 +11,7 @@ + @@ -79,13 +78,11 @@Related Topics
@@ -106,7 +103,7 @@Quick search
©2019, Franco Donati. | - Powered by Sphinx 1.8.2 + Powered by Sphinx 2.2.0 & Alabaster 0.7.12 | diff --git a/docs/pycirk.rst b/docs/pycirk.rst index 3262eb4..4258a86 100644 --- a/docs/pycirk.rst +++ b/docs/pycirk.rst @@ -8,103 +8,103 @@ pycirk.cli module ----------------- .. automodule:: pycirk.cli - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.fundamental\_operations module ------------------------------------- .. automodule:: pycirk.fundamental_operations - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.labels module -------------------- .. automodule:: pycirk.labels - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.make\_scenarios module ----------------------------- .. automodule:: pycirk.make_scenarios - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.make\_secondary\_flows module ------------------------------------ .. automodule:: pycirk.make_secondary_flows - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.organize\_io module -------------------------- .. automodule:: pycirk.organize_io - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.positions module ----------------------- .. automodule:: pycirk.positions - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.pycirk module -------------------- .. automodule:: pycirk.pycirk - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.pycirk\_settings module ------------------------------ .. automodule:: pycirk.pycirk_settings - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.results module --------------------- .. automodule:: pycirk.results - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.save\_utils module ------------------------- .. automodule:: pycirk.save_utils - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: pycirk.transformation\_methods module ------------------------------------- .. automodule:: pycirk.transformation_methods - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: Module contents --------------- .. automodule:: pycirk - :members: - :undoc-members: - :show-inheritance: + :members: + :undoc-members: + :show-inheritance: diff --git a/pycirk/__init__.py b/pycirk/__init__.py index 7c98474..ce62d6d 100644 --- a/pycirk/__init__.py +++ b/pycirk/__init__.py @@ -4,6 +4,6 @@ __author__ = """Franco Donati""" __email__ = 'f.donati@cml.leidenuniv.nl' -__version__ = '1.5.0' +__version__ = '1.5.5' from pycirk.pycirk import Launch \ No newline at end of file diff --git a/setup.cfg b/setup.cfg index ba2f433..d7e8652 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.5.0 +current_version = 1.5.5 commit = True tag = True
-
+
specified results in DataFrame form or a dictionary containing results and a dictionary of dataframes containing IO matrices
@@ -758,47 +753,37 @@Submodules
pycirk.pycirk_settings.Settings(method=0, make_secondary=False, save_directory='', aggregation=1, file=None, test=False)[source]¶
-
+
-
-
-
+
-
-
-
+
all_results()[source]¶save_results(scen_no=None, output_dataset=False)[source]¶scenario_results(scen_no, output_dataset=False)[source]¶
-
+
An numpy.array containing the coordinate of a specific label or None in case of there is no specified label
@@ -632,62 +631,59 @@