Source code for lsst.sims.maf.plots.neoDistancePlotter

from builtins import zip
import numpy as np
import copy
import matplotlib.pyplot as plt
from .plotHandler import BasePlotter
from matplotlib.patches import Ellipse

__all__ = ['NeoDistancePlotter']


[docs]class NeoDistancePlotter(BasePlotter): """ Special plotter to calculate and plot the maximum distance an H=22 NEO could be observable to, in any particular particular opsim observation. """ def __init__(self, step=.01, eclipMax=10., eclipMin=-10.): """ eclipMin/Max: only plot observations within X degrees of the ecliptic plane step: Step size to use for radial bins. Default is 0.01 AU. """ self.plotType = 'neoxyPlotter' self.objectPlotter = True self.defaultPlotDict = {'title': None, 'xlabel': 'X (AU)', 'ylabel': 'Y (AU)', 'xMin': -1.5, 'xMax': 1.5, 'yMin': -.25, 'yMax': 2.5, 'units': 'Count'} self.filter2color = {'u': 'purple', 'g': 'blue', 'r': 'green', 'i': 'cyan', 'z': 'orange', 'y': 'red'} self.filterColName = 'filter' self.step = step self.eclipMax = np.radians(eclipMax) self.eclipMin = np.radians(eclipMin)
[docs] def __call__(self, metricValue, slicer, userPlotDict, fignum=None): """ Parameters ---------- metricValue : numpy.ma.MaskedArray Metric values calculated by lsst.sims.maf.metrics.PassMetric slicer : lsst.sims.maf.slicers.UniSlicer userPlotDict: dict Dictionary of plot parameters set by user (overrides default values). fignum : int Matplotlib figure number to use (default = None, starts new figure). Returns ------- int Matplotlib figure number used to create the plot. """ fig = plt.figure(fignum) ax = fig.add_subplot(111) inPlane = np.where((metricValue[0]['eclipLat'] >= self.eclipMin) & (metricValue[0]['eclipLat'] <= self.eclipMax)) plotDict = {} plotDict.update(self.defaultPlotDict) plotDict.update(userPlotDict) planetProps = {'Earth': 1., 'Venus': 0.72, 'Mars': 1.52, 'Mercury': 0.39} planets = [] for prop in planetProps: planets.append(Ellipse((0, 0), planetProps[prop] * 2, planetProps[prop] * 2, fill=False)) for planet in planets: ax.add_artist(planet) # Let's make a 2-d histogram in polar coords, then convert and display in cartisian rStep = self.step Rvec = np.arange(0, plotDict['xMax'] + rStep, rStep) thetaStep = np.radians(3.5) thetavec = np.arange(0, 2 * np.pi + thetaStep, thetaStep) - np.pi # array to hold histogram values H = np.zeros((thetavec.size, Rvec.size), dtype=float) Rgrid, thetagrid = np.meshgrid(Rvec, thetavec) xgrid = Rgrid * np.cos(thetagrid) ygrid = Rgrid * np.sin(thetagrid) for dist, x, y in zip(metricValue[0]['MaxGeoDist'][inPlane], metricValue[0]['NEOHelioX'][inPlane], metricValue[0]['NEOHelioY'][inPlane]): theta = np.arctan2(y - 1., x) diff = np.abs(thetavec - theta) thetaToUse = thetavec[np.where(diff == diff.min())] # This is a slow where-clause, should be possible to speed it up using # np.searchsorted+clever slicing or hist2d to build up the map. good = np.where((thetagrid == thetaToUse) & (Rgrid <= dist)) H[good] += 1 # Set the under value to white myCmap = copy.copy(plt.cm.get_cmap('jet')) myCmap.set_under('w') blah = ax.pcolormesh(xgrid, ygrid + 1, H, cmap=myCmap, vmin=.001, shading='auto') cb = plt.colorbar(blah, ax=ax) cb.set_label(plotDict['units']) ax.set_xlabel(plotDict['xlabel']) ax.set_ylabel(plotDict['ylabel']) ax.set_title(plotDict['title']) ax.set_ylim([plotDict['yMin'], plotDict['yMax']]) ax.set_xlim([plotDict['xMin'], plotDict['xMax']]) ax.plot([0], [1], marker='o', color='b') ax.plot([0], [0], marker='o', color='y') return fig.number