/usr/lib/python3/dist-packages/pymoc/util/plot.py is in python3-pymoc 0.4.2-1.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 | # Copyright (C) 2013-2014 Science and Technology Facilities Council.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import healpy
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.pyplot as plt
import numpy as np
def plot_moc(moc, order=None, antialias=0, filename=None,
projection='cart', color='blue', title='', coord_sys='C',
graticule=True, **kwargs):
"""Plot a MOC using Healpy.
This generates a plot of the MOC at the specified order, or the MOC's
current order if this is not specified. The MOC is flattened at an order
of `order + antialias` to generate intermediate color levels.
:param order: HEALPix order at which to generate the plot.
:param antialias: number of additional HEALPix orders to use for
intermediate color levels. (There can be `4 ** antialias` levels.)
:param filename: file in which to save plot. If not specified then
the plot is shown with `plt.show()`.
:param projection: map projection to be used --- can be shortened to
4 characters. One of:
* `'cart[esian]'` (uses `healpy.visufunc.cartview`)
* `'moll[weide]'` (uses `healpy.visufunc.mollview`)
* `'gnom[onic]'` (uses `healpy.visufunc.gnomview`)
:param color: color scheme.
One of:
* `'blue'`
* `'green'`
* `'red'`
* `'black'`
:param title: title of the plot.
:param coord_sys: Healpy coordinate system code for the desired plot
coordinates. One of:
* `'C'` --- Celestial (equatorial)
* `'G'` --- Galactic
* `'E'` --- Ecliptic
:param graticule: whether or not to draw a graticule.
:param \*\*kwargs: passed to the selected Healpy plotting function.
"""
# Process arguments.
plotargs = {'xsize': 3200, 'cbar': False, 'notext': True}
if order is None:
order = moc.order
if projection.startswith('cart'):
plotter = healpy.visufunc.cartview
elif projection.startswith('moll'):
plotter = healpy.visufunc.mollview
elif projection.startswith('gnom'):
plotter = healpy.visufunc.gnomview
else:
raise ValueError('Unknown projection: {0}'.format(projection))
if color == 'blue':
plotargs['cmap'] = LinearSegmentedColormap.from_list(
'white-blue', ['#FFFFFF', '#0000AA'])
elif color == 'green':
plotargs['cmap'] = LinearSegmentedColormap.from_list(
'white-green', ['#FFFFFF', '#008800'])
elif color == 'red':
plotargs['cmap'] = LinearSegmentedColormap.from_list(
'white-red', ['#FFFFFF', '#FF0000'])
elif color == 'black':
plotargs['cmap'] = LinearSegmentedColormap.from_list(
'white-black', ['#FFFFFF', '#000000'])
else:
raise ValueError('Unknown color: {0}'.format(color))
if coord_sys == 'C':
pass
elif coord_sys == 'G':
plotargs['coord'] = ('C', 'G')
elif coord_sys == 'E':
plotargs['coord'] = ('C', 'E')
else:
raise ValueError('Unknown coordinate system: {0}'.format(coord_sys))
# Any other arguments are passed the Healpy plotter directly.
plotargs.update(kwargs)
# Create a Numpy array which is zero for points outside the MOC and one
# for points inside the MOC.
map = np.zeros(12 * 4 ** order)
antialias_shift = 2 * antialias
for cell in moc.flattened(order + antialias):
map[cell >> antialias_shift] += 1.0
# Plot the Numpy array using Healpy.
plotter(map, nest=True, title=title, **plotargs)
if graticule:
healpy.visufunc.graticule()
if filename is not None:
plt.savefig(filename)
else:
plt.show()
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