Coverage for python/lsst/analysis/tools/actions/plot/skyPlot.py: 11%
164 statements
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« prev ^ index » next coverage.py v6.5.0, created at 2023-01-20 09:04 +0000
1# This file is part of analysis_tools.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
22from __future__ import annotations
24from typing import Mapping, Optional
26import matplotlib.patheffects as pathEffects
27import matplotlib.pyplot as plt
28import numpy as np
29from lsst.pex.config import Field, ListField
30from matplotlib.figure import Figure
31from matplotlib.patches import Rectangle
33from ...interfaces import KeyedData, KeyedDataSchema, PlotAction, Scalar, Vector
34from ...statistics import nansigmaMad
35from .plotUtils import addPlotInfo, mkColormap, plotProjectionWithBinning, sortAllArrays
37# from .plotUtils import generateSummaryStats, parsePlotInfo
40class SkyPlot(PlotAction):
42 xAxisLabel = Field[str](doc="Label to use for the x axis.", optional=False)
43 yAxisLabel = Field[str](doc="Label to use for the y axis.", optional=False)
44 zAxisLabel = Field[str](doc="Label to use for the z axis.", optional=False)
46 plotOutlines = Field[bool](
47 doc="Plot the outlines of the ccds/patches?",
48 default=True,
49 )
51 plotTypes = ListField[str](
52 doc="Selection of types of objects to plot. Can take any combination of"
53 " stars, galaxies, unknown, mag, any.",
54 optional=False,
55 # itemCheck=_validatePlotTypes,
56 )
58 plotName = Field[str](doc="The name for the plot.", optional=False)
60 fixAroundZero = Field[bool](
61 doc="Fix the colorbar to be symmetric around zero.",
62 default=False,
63 )
65 def getInputSchema(self, **kwargs) -> KeyedDataSchema:
66 base = []
67 if "stars" in self.plotTypes: # type: ignore
68 base.append(("xStars", Vector))
69 base.append(("yStars", Vector))
70 base.append(("zStars", Vector))
71 base.append(("starStatMask", Vector))
72 if "galaxies" in self.plotTypes: # type: ignore
73 base.append(("xGalaxies", Vector))
74 base.append(("yGalaxies", Vector))
75 base.append(("zGalaxies", Vector))
76 base.append(("galaxyStatMask", Vector))
77 if "unknown" in self.plotTypes: # type: ignore
78 base.append(("xUnknowns", Vector))
79 base.append(("yUnknowns", Vector))
80 base.append(("zUnknowns", Vector))
81 base.append(("unknownStatMask", Vector))
82 if "any" in self.plotTypes: # type: ignore
83 base.append(("x", Vector))
84 base.append(("y", Vector))
85 base.append(("z", Vector))
86 base.append(("statMask", Vector))
88 return base
90 def __call__(self, data: KeyedData, **kwargs) -> Mapping[str, Figure] | Figure:
91 self._validateInput(data, **kwargs)
92 return self.makePlot(data, **kwargs)
93 # table is a dict that needs: x, y, run, skymap, filter, tract,
95 def _validateInput(self, data: KeyedData, **kwargs) -> None:
96 """NOTE currently can only check that something is not a Scalar, not
97 check that the data is consistent with Vector
98 """
99 needed = self.getInputSchema(**kwargs)
100 if remainder := {key.format(**kwargs) for key, _ in needed} - {
101 key.format(**kwargs) for key in data.keys()
102 }:
103 raise ValueError(f"Task needs keys {remainder} but they were not found in input")
104 for name, typ in needed:
105 isScalar = issubclass((colType := type(data[name.format(**kwargs)])), Scalar)
106 if isScalar and typ != Scalar:
107 raise ValueError(f"Data keyed by {name} has type {colType} but action requires type {typ}")
109 def statsAndText(self, arr, mask=None):
110 """Calculate some stats from an array and return them
111 and some text.
112 """
113 numPoints = len(arr)
114 if mask is not None:
115 arr = arr[mask]
116 med = np.nanmedian(arr)
117 sigMad = nansigmaMad(arr)
119 statsText = (
120 "Median: {:0.2f}\n".format(med)
121 + r"$\sigma_{MAD}$: "
122 + "{:0.2f}\n".format(sigMad)
123 + r"n$_{points}$: "
124 + "{}".format(numPoints)
125 )
127 return med, sigMad, statsText
129 def makePlot(
130 self,
131 data: KeyedData,
132 plotInfo: Optional[Mapping[str, str]] = None,
133 sumStats: Optional[Mapping] = None,
134 **kwargs,
135 ) -> Figure:
136 """Prep the catalogue and then make a skyPlot of the given column.
138 Parameters
139 ----------
140 catPlot : `pandas.core.frame.DataFrame`
141 The catalog to plot the points from.
142 dataId :
143 `lsst.daf.butler.core.dimensions._coordinate._ExpandedTupleDataCoordinate`
144 The dimensions that the plot is being made from.
145 runName : `str`
146 The name of the collection that the plot is written out to.
147 skymap : `lsst.skymap`
148 The skymap used to define the patch boundaries.
149 tableName : `str`
150 The type of table used to make the plot.
152 Returns
153 -------
154 `pipeBase.Struct` containing:
155 skyPlot : `matplotlib.figure.Figure`
156 The resulting figure.
158 Notes
159 -----
160 The catalogue is first narrowed down using the selectors specified in
161 `self.config.selectorActions`.
162 If the column names are 'Functor' then the functors specified in
163 `self.config.axisFunctors` are used to calculate the required values.
164 After this the following functions are run:
166 `parsePlotInfo` which uses the dataId, runName and tableName to add
167 useful information to the plot.
169 `generateSummaryStats` which parses the skymap to give the corners of
170 the patches for later plotting and calculates some basic statistics
171 in each patch for the column in self.config.axisActions['zAction'].
173 `SkyPlot` which makes the plot of the sky distribution of
174 `self.config.axisActions['zAction']`.
176 Makes a generic plot showing the value at given points on the sky.
178 Parameters
179 ----------
180 catPlot : `pandas.core.frame.DataFrame`
181 The catalog to plot the points from.
182 plotInfo : `dict`
183 A dictionary of information about the data being plotted with keys:
184 ``"run"``
185 The output run for the plots (`str`).
186 ``"skymap"``
187 The type of skymap used for the data (`str`).
188 ``"filter"``
189 The filter used for this data (`str`).
190 ``"tract"``
191 The tract that the data comes from (`str`).
192 sumStats : `dict`
193 A dictionary where the patchIds are the keys which store the R.A.
194 and dec of the corners of the patch.
196 Returns
197 -------
198 fig : `matplotlib.figure.Figure`
199 The resulting figure.
201 Notes
202 -----
203 Uses the config options `self.config.xColName` and
204 `self.config.yColName` to plot points color coded by
205 `self.config.axisActions['zAction']`.
206 The points plotted are those selected by the selectors specified in
207 `self.config.selectorActions`.
208 """
209 fig = plt.figure(dpi=300)
210 ax = fig.add_subplot(111)
212 if sumStats is None:
213 sumStats = {}
215 if plotInfo is None:
216 plotInfo = {}
218 # Make divergent colormaps for stars, galaxes and all the points
219 blueGreen = mkColormap(["midnightblue", "lightcyan", "darkgreen"])
220 redPurple = mkColormap(["indigo", "lemonchiffon", "firebrick"])
221 orangeBlue = mkColormap(["darkOrange", "thistle", "midnightblue"])
223 xCol = self.xAxisLabel
224 yCol = self.yAxisLabel
225 zCol = self.zAxisLabel # noqa: F841
227 toPlotList = []
228 # For galaxies
229 if "galaxies" in self.plotTypes:
230 sortedArrs = sortAllArrays(
231 [data["zGalaxies"], data["xGalaxies"], data["yGalaxies"], data["galaxyStatMask"]]
232 )
233 [colorValsGalaxies, xsGalaxies, ysGalaxies, statGalaxies] = sortedArrs
234 statGalMed, statGalMad, galStatsText = self.statsAndText(colorValsGalaxies, mask=statGalaxies)
235 # Add statistics
236 bbox = dict(facecolor="lemonchiffon", alpha=0.5, edgecolor="none")
237 # Check if plotting stars and galaxies, if so move the
238 # text box so that both can be seen. Needs to be
239 # > 2 becuase not being plotted points are assigned 0
240 if len(self.plotTypes) > 2:
241 boxLoc = 0.63
242 else:
243 boxLoc = 0.8
244 ax.text(boxLoc, 0.91, galStatsText, transform=fig.transFigure, fontsize=8, bbox=bbox)
245 toPlotList.append((xsGalaxies, ysGalaxies, colorValsGalaxies, redPurple, "Galaxies"))
247 # For stars
248 if "stars" in self.plotTypes:
249 sortedArrs = sortAllArrays([data["zStars"], data["xStars"], data["yStars"], data["starStatMask"]])
250 [colorValsStars, xsStars, ysStars, statStars] = sortedArrs
251 statStarMed, statStarMad, starStatsText = self.statsAndText(colorValsStars, mask=statStars)
252 # Add statistics
253 bbox = dict(facecolor="paleturquoise", alpha=0.5, edgecolor="none")
254 ax.text(0.8, 0.91, starStatsText, transform=fig.transFigure, fontsize=8, bbox=bbox)
255 toPlotList.append((xsStars, ysStars, colorValsStars, blueGreen, "Stars"))
257 # For unknowns
258 if "unknown" in self.plotTypes:
259 sortedArrs = sortAllArrays(
260 [data["zUnknowns"], data["xUnknowns"], data["yUnknowns"], data["unknownStatMask"]]
261 )
262 [colorValsUnknowns, xsUnknowns, ysUnknowns, statUnknowns] = sortedArrs
263 statUnknownMed, statUnknownMad, unknownStatsText = self.statsAndText(
264 colorValsUnknowns, mask=statUnknowns
265 )
266 bbox = dict(facecolor="green", alpha=0.2, edgecolor="none")
267 ax.text(0.8, 0.91, unknownStatsText, transform=fig.transFigure, fontsize=8, bbox=bbox)
268 toPlotList.append((xsUnknowns, ysUnknowns, colorValsUnknowns, "viridis", "Unknown"))
270 if "any" in self.plotTypes:
271 sortedArrs = sortAllArrays([data["z"], data["x"], data["y"], data["statMask"]])
272 [colorValsAny, xs, ys, statAny] = sortedArrs
273 statAnyMed, statAnyMad, anyStatsText = self.statsAndText(colorValsAny, mask=statAny)
274 bbox = dict(facecolor="purple", alpha=0.2, edgecolor="none")
275 ax.text(0.8, 0.91, anyStatsText, transform=fig.transFigure, fontsize=8, bbox=bbox)
276 toPlotList.append((xs, ys, colorValsAny, orangeBlue, "All"))
278 # Corner plot of patches showing summary stat in each
279 if self.plotOutlines:
280 patches = []
281 for dataId in sumStats.keys():
282 (corners, _) = sumStats[dataId]
283 ra = corners[0][0].asDegrees()
284 dec = corners[0][1].asDegrees()
285 xy = (ra, dec)
286 width = corners[2][0].asDegrees() - ra
287 height = corners[2][1].asDegrees() - dec
288 patches.append(Rectangle(xy, width, height, alpha=0.3))
289 ras = [ra.asDegrees() for (ra, dec) in corners]
290 decs = [dec.asDegrees() for (ra, dec) in corners]
291 ax.plot(ras + [ras[0]], decs + [decs[0]], "k", lw=0.5)
292 cenX = ra + width / 2
293 cenY = dec + height / 2
294 if dataId == "tract":
295 minRa = np.min(ras)
296 minDec = np.min(decs)
297 maxRa = np.max(ras)
298 maxDec = np.max(decs)
299 if dataId != "tract":
300 ax.annotate(
301 dataId,
302 (cenX, cenY),
303 color="k",
304 fontsize=5,
305 ha="center",
306 va="center",
307 path_effects=[pathEffects.withStroke(linewidth=2, foreground="w")],
308 )
310 for (i, (xs, ys, colorVals, cmap, label)) in enumerate(toPlotList):
311 if not self.plotOutlines or "tract" not in sumStats.keys():
312 minRa = np.min(xs)
313 maxRa = np.max(xs)
314 minDec = np.min(ys)
315 maxDec = np.max(ys)
316 # Avoid identical end points which causes problems in binning
317 if minRa == maxRa:
318 maxRa += 1e-5 # There is no reason to pick this number in particular
319 if minDec == maxDec:
320 maxDec += 1e-5 # There is no reason to pick this number in particular
322 plotOut = plotProjectionWithBinning(
323 ax,
324 xs,
325 ys,
326 colorVals,
327 cmap,
328 minRa,
329 maxRa,
330 minDec,
331 maxDec,
332 fixAroundZero=self.fixAroundZero,
333 isSorted=True,
334 )
335 cax = fig.add_axes([0.87 + i * 0.04, 0.11, 0.04, 0.77])
336 plt.colorbar(plotOut, cax=cax, extend="both")
337 colorBarLabel = "{}: {}".format(self.zAxisLabel, label)
338 text = cax.text(
339 0.5,
340 0.5,
341 colorBarLabel,
342 color="k",
343 rotation="vertical",
344 transform=cax.transAxes,
345 ha="center",
346 va="center",
347 fontsize=10,
348 )
349 text.set_path_effects([pathEffects.Stroke(linewidth=3, foreground="w"), pathEffects.Normal()])
350 cax.tick_params(labelsize=7)
352 if i == 0 and len(toPlotList) > 1:
353 cax.yaxis.set_ticks_position("left")
355 ax.set_xlabel(xCol)
356 ax.set_ylabel(yCol)
357 ax.tick_params(axis="x", labelrotation=25)
358 ax.tick_params(labelsize=7)
360 ax.set_aspect("equal")
361 plt.draw()
363 # Find some useful axis limits
364 lenXs = [len(xs) for (xs, _, _, _, _) in toPlotList]
365 if lenXs != [] and np.max(lenXs) > 1000:
366 padRa = (maxRa - minRa) / 10
367 padDec = (maxDec - minDec) / 10
368 ax.set_xlim(maxRa + padRa, minRa - padRa)
369 ax.set_ylim(minDec - padDec, maxDec + padDec)
370 else:
371 ax.invert_xaxis()
373 # Add useful information to the plot
374 plt.subplots_adjust(wspace=0.0, hspace=0.0, right=0.85)
375 fig = plt.gcf()
376 fig = addPlotInfo(fig, plotInfo)
378 return fig