Initial commit

Author: Arya Farahi

LICENSE

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+The MIT License (MIT)
+
+Copyright (c) 2019 Arya Farahi
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.

data/TNG300_Halos.csv

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+from kllr import *
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+import sys
+
+print(sys.path)
+
+df = pd.read_csv('./data/TNG300_Halos.csv')
+print(df.columns)
+x = np.array(df.M200)
+y = np.array(df.MGas)
+
+
+
+# data, ax = Plot_Fit(df, 'M200', 'MGas', show_data=True, cutoff=13.5, ax=None) ## PASSED
+# data, ax = Plot_Fit_Split(df, 'M200', 'MGas', 'z_form', split_bins = [0.0, 0.2, 0.3, 0.6]) ## PASSED
+# data, ax = Plot_Fit_Params(df, 'M200', 'MGas') ## PASSED
+# data, ax = Plot_Fit_Params_Split(df, 'M200', 'MGas', 'z_form', split_bins = [0.0, 0.2, 0.3, 0.6])
+# data, ax = Plot_Correlation(df, 'M200', 'MGas', 'MStar') ## PASSED
+# data, ax = Plot_Correlation_Split(df, 'M200', 'MGas', 'MStar', 'z_form', split_bins = [0.0, 0.2, 0.3, 0.6]) ##PASSED
+# data, ax = Plot_Covariance(df, 'M200', 'MGas', 'MStar', GaussianWidth=0.2)
+# data, ax = Plot_Covariance_Split(df, 'M200', 'MGas', 'MStar', 'z_form', split_bins = [0.0, 0.2, 0.3, 0.6]) ## PASSED
+# ax = Plot_Correlation_Matrix(df, 'M200', ['MGas', 'MGas_T', 'sigma_DM_3D']) ## PASSED
+# ax = Plot_Correlation_Matrix_Split(df, 'M200', ['MGas', 'MGas_T', 'sigma_DM_3D'], 'z_form', split_bins=[0.0, 0.2, 0.3, 0.6]) ## PASSED
+# ax = Plot_Covariance_Matrix(df, 'M200', ['MGas', 'MStar', 'sigma_DM_3D']) ## PASSED
+# ax = Plot_Covariance_Matrix_Split(df, 'M200', ['MGas', 'MStar', 'MStar_BCG100'], 'z_form', split_bins=[0.0, 0.2, 0.3, 0.6]) ## PASSED
+# data, ax = Plot_Residual(df, 'M200', 'MGas') ## PASSED
+data, ax = Plot_Residual_Split(df, 'M200', 'MGas', 'z_form', split_bins = [0.0, 0.2, 0.3, 0.6])
+
+plt.show()

example.py

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+from .regression_model import kllr_model
+from .regression_plotting import Plot_Fit, Plot_Fit_Split, Plot_Fit_Params, Plot_Fit_Params_Split,\
+                Plot_Correlation, Plot_Correlation_Split, Plot_Covariance, Plot_Covariance_Split,\
+                Plot_Correlation_Matrix, Plot_Correlation_Matrix_Split, Plot_Covariance_Matrix,\
+                Plot_Covariance_Matrix_Split, Plot_Residual, Plot_Residual_Split