Tools for examining the Rubin Observatory scheduler and progress

COPYRIGHT

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+Copyright 2022 Fermi Research Alliance, LLC.

README.md

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 # schedview
-Tools for monitoring the Rubin Observatory scheduler and related LSST survey progress and strategy data.
+Tools for visualizing Rubin Observatory scheduler behaviour and LSST survey status
+
+## Development state
+
+The current code is in a early stage of development. The architecture will
+be documented by [RTN-037](https://rtn-037.lsst.io/), currently little more than
+an outline.
+
+## Applications
+
+There are presently two different applications in this project:
+
+- `metric_maps`, a tool for visualizing metric output of MAF that takes the form
+of a sky map.
+- `sched_maps`, a tool for examing some elements of the state of objects used by
+the scheduler, particularly those that take the form of a sky map, although some
+indications of other elements are also present.
+
+The project contains example data for each. At present, to use the example data,
+different versions of dependencies are required, so the installation instructions
+are slightly different in each case. (The reason for this is that the pickles
+containing the sample objects to be viewed with `sched_maps` were created with
+an old version of `rubin_sim`, and this older version needs to be installed for
+these to be loaded.)
+
+## Installation
+
+First, get the code by cloning the github project:
+
+    $ git clone [email protected]:ehneilsen/schedview.git
+
+Go to the development directory, and download and decompress a data file used
+by the automated tests. 
+
+    $ cd schedview
+    $ wget -O schedview/data/bsc5.dat.gz http://tdc-www.harvard.edu/catalogs/bsc5.dat.gz
+    $ gunzip schedview/data/bsc5.dat.gz
+
+Create a `conda` environment with the appropriate dependencies, and activate it.
+If you are running the `metric_maps` application, use the `conda` environment
+file that includes a recent version of `survey_sim`:
+
+    $ # ONLY IF RUNNING metric_maps
+    $ conda env create -f environment.yaml
+    $ conda activate schedview
+
+If you are running `sched_maps`, get the one with the older version:
+
+    $ # ONLY IF RUNNING sched_maps
+    $ conda env create -f environment_080a2.yaml
+    $ conda activate schedview080a2
+
+Install the (development) `schedview` in your new environment:
+
+    $ pip install -e .
+
+Run the tests:
+
+    $ pytest
+
+## Running `metric_maps`
+
+Activate the environment, and start the `bokeh` app. If `SCHEDVIEW_DIR` is the
+directory into which you cloned the `schedview` github repository, then:
+
+    $ conda activate schedview
+    $ bokeh serve ${SCHEDVIEW_DIR}/schedview/app/metric_maps.py
+
+The app will then give you the URL at which you can find the app. The data
+displayed with the above instructions will be the sample metric map in the
+project itself.
+
+If you want to use a different data file, you can set the `METRIC_FNAME`
+to its path before running the `bokeh` app. This is only a very short term
+solution, and will be replaced soon.
+
+## Running `sched_maps`
+
+Activate the environment, and start the `bokeh` app. If `SCHEDVIEW_DIR` is the
+directory into which you cloned the `schedview` github repository, then:
+
+    $ conda activate schedview080a2
+    $ bokeh serve ${SCHEDVIEW_DIR}/schedview/app/sched_maps.py
+
+The app will then give you the URL at which you can find the app.

environment.yaml

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+name: schedview
+channels:
+ - conda-forge
+dependencies:
+ - rubin-sim
+ - bokeh
+ - pytest-flake8
+ - pytest-black
+ - selenium
+ - firefox
+ - geckodriver
+ - build

pyproject.toml

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+[build-system]
+requires = [ "setuptools", "setuptools_scm" ]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "schedview"
+description = "Tools for visualization of Rubin Observatory's scheduler status, strategy and progress on LSST."
+classifiers = [ 
+    "Intended Audience :: Science/Research",
+    "Operating System :: OS Independent",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Topic :: Scientific/Engineering :: Astronomy",
+ ]
+dynamic = [ "version" ]
+
+[tool.setuptools.dynamic]
+version = { attr = "setuptools_scm.get_version" }
+
+[tool.setuptools.packages.find]
+where = [ "" ]
+
+[tool.setuptools_scm]
+write_to = "schedview/version.py"
+write_to_template = """
+# Generated by setuptools_scm
+__all__ = ["__version__"]
+__version__ = "{version}"
+"""
+
+[tool.pytest.ini_options]
+addopts = "--flake8 --black --ignore-glob=*/version.py"
+flake8-ignore = ["E133", "E203", "E226", "E228", "N802", "N803", "N806", "N812", "N813", "N815", "N816", "W503", "**/*/__init__.py ALL", "**/*/version.py ALL"]
+flake8-max-line-length = 110
+flake8-max-doc-length = 79
+testpaths = "."

schedview/__init__.py

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+from .sphere import *

schedview/app/metric_maps.py

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+import bokeh.plotting
+
+from rubin_sim import maf
+
+from schedview.plot.SphereMap import ArmillarySphere, Planisphere, MollweideMap
+from schedview.collect.stars import load_bright_stars
+from schedview.collect import get_metric_path
+
+
+def make_metric_figure(metric_values_fname=None, nside=8, mag_limit_slider=True):
+    """Create a figure showing multiple projections of a set of a MAF metric.
+
+    Parameters
+    ----------
+    metric_values_fname : `str`, optional
+        Name of file from which to load metric values, as saved by MAF
+        in a saved metric bundle. If it is None, the look for the
+        file name in the ``METRIC_FNAME`` environment varable. By default None
+    nside : `int`, optional
+        Healpix nside to use for display, by default 8
+    mag_limit_slider : `bool`, optional
+        Show the mag limit slider for stars?, by default True
+
+    Returns
+    -------
+    fig : `bokeh.models.layouts.LayoutDOM`
+        A bokeh figure that can be displayed in a notebook (e.g. with
+        ``bokeh.io.show``) or used to create a bokeh app.
+
+    Notes
+    -----
+    If ``mag_limit_slider`` is ``True``, it creates a magnitude limit
+    slider for the stars. This is implemented as a python callback, and
+    so is only operational in full bokeh app, not standalone output.
+    """
+
+    if metric_values_fname is None:
+        metric_values_fname = get_metric_path()
+
+    healpy_values = maf.MetricBundle.load(metric_values_fname).metricValues
+
+    star_data = load_bright_stars().loc[:, ["name", "ra", "decl", "Vmag"]]
+    star_data["glyph_size"] = 15 - (15.0 / 3.5) * star_data["Vmag"]
+    star_data.query("glyph_size>0", inplace=True)
+
+    arm = ArmillarySphere()
+    hp_ds, cmap, _ = arm.add_healpix(healpy_values, nside=nside)
+    hz = arm.add_horizon()
+    zd70 = arm.add_horizon(zd=70, line_kwargs={"color": "red", "line_width": 2})
+    star_ds = arm.add_stars(
+        star_data, mag_limit_slider=mag_limit_slider, star_kwargs={"color": "black"}
+    )
+    arm.decorate()
+
+    pla = Planisphere()
+    pla.add_healpix(hp_ds, cmap=cmap, nside=nside)
+    pla.add_horizon(data_source=hz)
+    pla.add_horizon(
+        zd=60, data_source=zd70, line_kwargs={"color": "red", "line_width": 2}
+    )
+    pla.add_stars(
+        star_data,
+        data_source=star_ds,
+        mag_limit_slider=False,
+        star_kwargs={"color": "black"},
+    )
+    pla.decorate()
+
+    mol_plot = bokeh.plotting.figure(plot_width=512, plot_height=256, match_aspect=True)
+    mol = MollweideMap(plot=mol_plot)
+    mol.add_healpix(hp_ds, cmap=cmap, nside=nside)
+    mol.add_horizon(data_source=hz)
+    mol.add_horizon(
+        zd=70, data_source=zd70, line_kwargs={"color": "red", "line_width": 2}
+    )
+    mol.add_stars(
+        star_data,
+        data_source=star_ds,
+        mag_limit_slider=False,
+        star_kwargs={"color": "black"},
+    )
+    mol.decorate()
+
+    figure = bokeh.layouts.row(
+        bokeh.layouts.column(mol.plot, *arm.sliders.values()), arm.plot, pla.plot
+    )
+
+    return figure
+
+
+def add_metric_app(doc):
+    """Add a metric figure to a bokeh document
+
+    Parameters
+    ----------
+    doc : `bokeh.document.document.Document`
+        The bokeh document to which to add the figure.
+    """
+    figure = make_metric_figure()
+    doc.add_root(figure)
+
+
+if __name__.startswith("bokeh_app_"):
+    doc = bokeh.plotting.curdoc()
+    add_metric_app(doc)