def test_direct_init(self):
s = DistanceToLonLat(R=6378.273)
coord_meta = {}
coord_meta['type'] = ('longitude', 'latitude')
coord_meta['wrap'] = (360., None)
coord_meta['unit'] = (u.deg, u.deg)
coord_meta['name'] = 'lon', 'lat'
fig = plt.figure(figsize=(4, 4))
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], transform=s, coord_meta=coord_meta)
fig.add_axes(ax)
ax.coords['lon'].grid(color='red', linestyle='solid', alpha=0.3)
ax.coords['lat'].grid(color='blue', linestyle='solid', alpha=0.3)
ax.coords['lon'].set_ticklabel(size=7, exclude_overlapping=True)
ax.coords['lat'].set_ticklabel(size=7, exclude_overlapping=True)
ax.coords['lon'].set_ticklabel_position('brtl')
ax.coords['lat'].set_ticklabel_position('brtl')
ax.coords['lon'].set_ticks(spacing=10. * u.deg)
ax.coords['lat'].set_ticks(spacing=10. * u.deg)
ax.set_xlim(-400., 500.)
ax.set_ylim(-300., 400.)
return fig
def test_ticks_labels(self):
fig = plt.figure(figsize=(6, 6))
ax = WCSAxes(fig, [0.1, 0.1, 0.7, 0.7], wcs=None)
fig.add_axes(ax)
ax.set_xlim(-0.5, 2)
ax.set_ylim(-0.5, 2)
ax.coords[0].set_ticks(size=10, color='blue', alpha=0.2, width=1)
ax.coords[1].set_ticks(size=20, color='red', alpha=0.9, width=1)
ax.coords[0].set_ticks_position('all')
ax.coords[1].set_ticks_position('all')
ax.coords[0].set_axislabel('X-axis', size=20)
ax.coords[1].set_axislabel('Y-axis', color='green', size=25,
weight='regular', style='normal',
family='cmtt10')
ax.coords[0].set_axislabel_position('t')
ax.coords[1].set_axislabel_position('r')
ax.coords[0].set_ticklabel(color='purple', size=15, alpha=1,
weight='light', style='normal',
family='cmss10')
ax.coords[1].set_ticklabel(color='black', size=18, alpha=0.9,
weight='bold', family='cmr10')
ax.coords[0].set_ticklabel_position('all')
ax.coords[1].set_ticklabel_position('r')
return fig
def time_basic_plot():
fig = Figure()
canvas = FigureCanvas(fig)
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], wcs=MSX_WCS)
fig.add_axes(ax)
ax.set_xlim(-0.5, 148.5)
ax.set_ylim(-0.5, 148.5)
canvas.draw()
def test_copy_frame_properties_change_wcs(self):
# When WCS is changed, a new frame is created, so we need to make sure
# that the color and linewidth are transferred over
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8])
fig.add_axes(ax)
ax.coords.frame.set_linewidth(5)
ax.coords.frame.set_color('purple')
ax.reset_wcs()
assert ax.coords.frame.get_linewidth() == 5
assert ax.coords.frame.get_color() == 'purple'
def time_contourf_with_transform():
fig = Figure()
canvas = FigureCanvas(fig)
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], wcs=MSX_WCS)
fig.add_axes(ax)
ax.contourf(DATA, transform=ax.get_transform(TWOMASS_WCS))
# The limits are to make sure the contours are in the middle of the result
ax.set_xlim(32.5, 150.5)
ax.set_ylim(-64.5, 64.5)
canvas.draw()
def time_basic_plot_with_grid_and_overlay():
fig = Figure()
canvas = FigureCanvas(fig)
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], wcs=MSX_WCS)
fig.add_axes(ax)
ax.grid(color='red', alpha=0.5, linestyle='solid')
ax.set_xlim(-0.5, 148.5)
ax.set_ylim(-0.5, 148.5)
overlay = ax.get_coords_overlay('fk5')
overlay.grid(color='purple', ls='dotted')
canvas.draw()
def time_basic_plot_with_grid():
fig = Figure()
canvas = FigureCanvas(fig)
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], wcs=MSX_WCS)
fig.add_axes(ax)
ax.grid(color='red', alpha=0.5, linestyle='solid')
ax.set_xlim(-0.5, 148.5)
ax.set_ylim(-0.5, 148.5)
canvas.draw()
def test_coords_overlay_auto_coord_meta(self):
fig = plt.figure(figsize=(4, 4))
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], wcs=WCS(self.msx_header))
fig.add_axes(ax)
ax.grid(color='red', alpha=0.5, linestyle='solid')
overlay = ax.get_coords_overlay('fk5') # automatically sets coord_meta
overlay.grid(color='black', alpha=0.5, linestyle='solid')
overlay['ra'].set_ticks(color='black')
overlay['dec'].set_ticks(color='black')
ax.set_xlim(-0.5, 148.5)
ax.set_ylim(-0.5, 148.5)
return fig
def test_coords_overlay(self):
# Set up a simple WCS that maps pixels to non-projected distances
wcs = WCS(naxis=2)
wcs.wcs.ctype = ['x', 'y']
wcs.wcs.cunit = ['km', 'km']
wcs.wcs.crpix = [614.5, 856.5]
wcs.wcs.cdelt = [6.25, 6.25]
wcs.wcs.crval = [0., 0.]
fig = plt.figure(figsize=(4, 4))
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7], wcs=wcs)
fig.add_axes(ax)
s = DistanceToLonLat(R=6378.273)
ax.coords['x'].set_ticklabel_position('')
ax.coords['y'].set_ticklabel_position('')
coord_meta = {}
coord_meta['type'] = ('longitude', 'latitude')
coord_meta['wrap'] = (360., None)
coord_meta['unit'] = (u.deg, u.deg)
coord_meta['name'] = 'lon', 'lat'
overlay = ax.get_coords_overlay(s, coord_meta=coord_meta)
overlay.grid(color='red')
overlay['lon'].grid(color='red', linestyle='solid', alpha=0.3)
overlay['lat'].grid(color='blue', linestyle='solid', alpha=0.3)
overlay['lon'].set_ticklabel(size=7, exclude_overlapping=True)
overlay['lat'].set_ticklabel(size=7, exclude_overlapping=True)
overlay['lon'].set_ticklabel_position('brtl')
overlay['lat'].set_ticklabel_position('brtl')
overlay['lon'].set_ticks(spacing=10. * u.deg)
overlay['lat'].set_ticks(spacing=10. * u.deg)
ax.set_xlim(-0.5, 1215.5)
ax.set_ylim(-0.5, 1791.5)
return fig
def test_custom_frame(self):
wcs = WCS(self.msx_header)
fig = plt.figure(figsize=(4, 4))
ax = WCSAxes(fig, [0.15, 0.15, 0.7, 0.7],
wcs=wcs,
frame_class=HexagonalFrame)
fig.add_axes(ax)
ax.coords.grid(color='white')
im = ax.imshow(np.ones((149, 149)), vmin=0., vmax=2.,
origin='lower', cmap=plt.cm.gist_heat)
minpad = {}
minpad['a'] = minpad['d'] = 1
minpad['b'] = minpad['c'] = minpad['e'] = minpad['f'] = 2.75
ax.coords['glon'].set_axislabel("Longitude", minpad=minpad)
ax.coords['glon'].set_axislabel_position('ad')
ax.coords['glat'].set_axislabel("Latitude", minpad=minpad)
ax.coords['glat'].set_axislabel_position('bcef')
ax.coords['glon'].set_ticklabel_position('ad')
ax.coords['glat'].set_ticklabel_position('bcef')
# Set limits so that no labels overlap
ax.set_xlim(5.5, 100.5)
ax.set_ylim(5.5, 110.5)
# Clip the image to the frame
im.set_clip_path(ax.coords.frame.patch)
return fig
def test_rcparams(self):
# Test custom rcParams
with rc_context({
'axes.labelcolor': 'purple',
'axes.labelsize': 14,
'axes.labelweight': 'bold',
'axes.linewidth': 3,
'axes.facecolor': '0.5',
'axes.edgecolor': 'green',
'xtick.color': 'red',
'xtick.labelsize': 8,
'xtick.direction': 'in',
'xtick.minor.visible': True,
'xtick.minor.size': 5,
'xtick.major.size': 20,
'xtick.major.width': 3,
'xtick.major.pad': 10,
'grid.color': 'blue',
'grid.linestyle': ':',
'grid.linewidth': 1,
'grid.alpha': 0.5}):
fig = plt.figure(figsize=(6, 6))
ax = WCSAxes(fig, [0.15, 0.1, 0.7, 0.7], wcs=None)
fig.add_axes(ax)
ax.set_xlim(-0.5, 2)
ax.set_ylim(-0.5, 2)
ax.grid()
ax.set_xlabel('X label')
ax.set_ylabel('Y label')
ax.coords[0].set_ticklabel(exclude_overlapping=True)
ax.coords[1].set_ticklabel(exclude_overlapping=True)
return fig
import matplotlib.cm as cm
from photutils import find_peaks
from astropy import wcs
from astropy.nddata import Cutout2D
from astropy import units as u
filename = './rcutout.fits'
image = fits.open(filename)
try:
from astropy.wcs import WCS
from astropy.visualization.wcsaxes import WCSAxes
wcs = WCS(image[0].header)
fig = plt.figure()
ax = WCSAxes(fig, [.1,.1,.8,.8], wcs=wcs)
fig.add_axes(ax)
except ImportError:
ax = plt.subplot(111)
ax.imshow(image[0].data, cmap=cm.gray, vmin=0, vmax=0.00038, origin='lower')
region_name = './satpeaks4.reg'
r = pyregion.open(region_name).as_imagecoord(header=image[0].header)
from pyregion.mpl_helper import properties_func_default
def fixed_color(shape, saved_attrs):
attr_list, attr_dict = saved_attrs
attr_dict["color"] = "red"
kwargs = properties_func_default(shape, (attr_list,attr_dict))
def plot_image_rs_full(map_in,
xrange=[-1.4, 1.4],
yrange=[-1.4, 1.4],
log_min=0.5,
log_max=3.5,
cmap_name=None,
outfile=None,
dpi=100,
save_interactive=False):
"""
Quick method to plot a map by specifying the x and y range in SOLAR coordinates.
- Unlike plot_image_rs, here the image fills the entire frame, with no outside annotations
like axes labels or colorbars
- xrange and yrange are two elements lists or tuples that specify the solar coords in Rs
- e.g. xrange=[-1.3, -1.3], yrange=[-1.3, 1.3]
- if a output file is specified, it will switch to a non-interactive backend and save the file
without showing the plot (unless save_interactive=True).
- cmap_name (optional) is a string that specifies a sunpy or matplotlib colormap
ToDo:
- put white annotations in the corners that describe the image (time, inst, clon, b0)
- overplot some solar grid lines (e.g. the lat=0 line and/or various clons)
"""
# I don't want to modify the input map at all --> copy the map object just in case
map = copy.deepcopy(map_in)
# info from the map
rs_obs = map.rsun_obs
# get the coordinate positions of the x and y ranges
x0 = xrange[0] * rs_obs.value * u.arcsec
x1 = xrange[1] * rs_obs.value * u.arcsec
y0 = yrange[0] * rs_obs.value * u.arcsec
y1 = yrange[1] * rs_obs.value * u.arcsec
bot_left = SkyCoord(x0, y0, frame=map.coordinate_frame)
top_right = SkyCoord(x1, y1, frame=map.coordinate_frame)
# experiment with different styles of plotting the x and y window
# using "limits" lets you plot outside of the image window, which can be important
# for aligning images.
plot_method = 'limits'
if plot_method == 'submap':
map = map.submap(bot_left, top_right)
# setup the optional colormap
if cmap_name is not None:
cmap = plt.get_cmap(cmap_name)
map.plot_settings['cmap'] = cmap
# Set the map plot min/max
pmin = 10.0**(log_min)
pmax = 10.0**(log_max)
map.plot_settings['norm'] = colors.LogNorm(pmin, pmax)
# Change the colormap so undefined values don't show up white
map.plot_settings['cmap'].set_bad(color='black')
# if saving a file, don't use the interactive backend
if outfile is not None and not save_interactive:
matplotlib.use(mpl_backend_non_interactive)
# setup the figure
fig = plt.figure(figsize=(9, 9))
# Manually specify the axis (vs. getting through map.plot) this way you have more control
axis = WCSAxes(fig, [0.0, 0.0, 1.0, 1.0], wcs=map.wcs)
fig.add_axes(
axis) # note that the axes have to be explicitly added to the figure
# plot the image
map.plot(axes=axis)
# example for adjusting the tick spacing (see astropy examples for WCSAxes)
custom_ticks = True
if custom_ticks:
spacing = map.rsun_obs
axis.coords[0].set_ticks(spacing=spacing)
axis.coords[1].set_ticks(spacing=spacing)
# if plot is NOT a submap, compute the pixel positions and change the matplotlib limits
if plot_method == 'limits':
pp_bot_left = map.world_to_pixel(bot_left)
pp_top_right = map.world_to_pixel(top_right)
axis.set_xlim(left=pp_bot_left.x.value, right=pp_top_right.x.value)
axis.set_ylim(bottom=pp_bot_left.y.value, top=pp_top_right.y.value)
# save the plot (optional)
if outfile is not None:
print("Saving image plot to: " + outfile)
fig.savefig(outfile, dpi=dpi)
# revert to the default MPL backend
if not save_interactive:
plt.close()
matplotlib.use(mpl_backend_default)
else:
plt.show()
else:
plt.show()
def plot(LSM, fileName=None, labelBy=None):
"""
Shows a simple plot of the sky model.
The circles in the plot are scaled with flux. If the sky model is grouped
into patches, sources are colored by patch and the patch positions are
indicated with stars.
Parameters
----------
LSM : SkyModel object
Input sky model
fileName : str, optional
If given, the plot is saved to a file instead of displayed
labelBy : str, optional
One of 'source' or 'patch': label points using source names ('source') or
patch names ('patch')
Examples:
---------
Plot and display to the screen::
>>> LSM = lsmtool.load('sky.model')
>>> plot(LSM)
Plot and save to a PDF file::
>>> plot(LSM, 'sky_plot.pdf')
"""
try:
import os
if 'DISPLAY' not in os.environ:
import matplotlib
if matplotlib.get_backend() is not 'Agg':
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
except Exception as e:
raise ImportError('PyPlot could not be imported. Plotting is not '
'available: {0}'.format(e.message))
try:
try:
from astropy.visualization.wcsaxes import WCSAxes
hasWCSaxes = True
except:
from wcsaxes import WCSAxes
hasWCSaxes = True
except:
hasWCSaxes = False
import numpy as np
from ..operations_lib import radec2xy, makeWCS
global midRA, midDec, ymin, xmin
if len(LSM) == 0:
log.error('Sky model is empty.')
return
fig = plt.figure(1, figsize=(7.66, 7))
plt.clf()
x, y, midRA, midDec = LSM._getXY()
if hasWCSaxes:
wcs = makeWCS(midRA, midDec)
ax = WCSAxes(fig, [0.16, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
else:
ax = plt.gca()
if LSM.hasPatches:
nsrc = len(LSM.getPatchNames())
else:
nsrc = len(LSM)
sm = plt.cm.ScalarMappable(cmap=plt.cm.Set3,
norm=plt.Normalize(vmin=0, vmax=nsrc))
sm._A = []
# Set symbol sizes by flux, making sure no symbol is smaller than 50 or
# larger than 1000
s = []
fluxes = LSM.getColValues('I')
if len(fluxes[fluxes > 0.0]) == 0:
minflux = 0.0
else:
minflux = np.min(fluxes[fluxes > 0.0])
for flux in LSM.getColValues('I'):
if flux > 0.0:
s.append(min(1000.0,
(1.0 + 2.0 * np.log10(flux / minflux)) * 50.0))
else:
s.append(50.0)
# Color sources by patch if grouped
c = [0] * len(LSM)
cp = []
if LSM.hasPatches:
for p, patchName in enumerate(LSM.getPatchNames()):
indices = LSM.getRowIndex(patchName)
cp.append(sm.to_rgba(p))
for ind in indices:
c[ind] = sm.to_rgba(p)
else:
c = [sm.to_rgba(0)] * nsrc
# Plot sources
if hasWCSaxes:
RA = LSM.getColValues('Ra')
Dec = LSM.getColValues('Dec')
ax.set_xlim(np.min(x) - 20, np.max(x) + 20)
ax.set_ylim(np.min(y) - 20, np.max(y) + 20)
plt.scatter(x, y, s=s, c=c)
if LSM.hasPatches:
RAp, Decp = LSM.getPatchPositions(asArray=True)
goodInd = np.where((RAp != 0.0) & (Decp != 0.0))
if len(goodInd[0]) < len(RAp):
log.info('Some patch positions are unset. Run setPatchPositions() '
'before plotting to see patch positions and patch names.')
xp, yp = radec2xy(RAp[goodInd], Decp[goodInd], midRA, midDec)
plt.scatter(xp, yp, s=100, c=cp, marker='*')
# Set axis labels, etc.
if hasWCSaxes:
RAAxis = ax.coords['ra']
RAAxis.set_axislabel('RA', minpad=0.75)
RAAxis.set_major_formatter('hh:mm:ss')
DecAxis = ax.coords['dec']
DecAxis.set_axislabel('Dec', minpad=0.75)
DecAxis.set_major_formatter('dd:mm:ss')
ax.coords.grid(color='black', alpha=0.5, linestyle='solid')
else:
plt.xlabel("RA (arb. units)")
plt.ylabel("Dec (arb. units)")
if labelBy is not None:
if labelBy.lower() == 'source':
labels = LSM.getColValues('name')
xls = x
yls = y
elif labelBy.lower() == 'patch':
if LSM.hasPatches:
labels = LSM.getPatchNames()
xls = xp
yls = yp
else:
labels = LSM.getColValues('name')
xls = x
yls = y
else:
raise ValueError(
"The lableBy parameter must be one of 'source' or "
"'patch'.")
for label, xl, yl in zip(labels, xls, yls):
plt.annotate(label,
xy=(xl, yl),
xytext=(-2, 2),
textcoords='offset points',
ha='right',
va='bottom')
# Define coodinate formater to show RA and Dec under mouse pointer
RAformatter = FuncFormatter(RAtickformatter)
ax.format_coord = formatCoord
if fileName is not None:
plt.savefig(fileName)
else:
plt.show()
plt.close(fig)
def plot_state(directions_list, trim_names=True):
"""
Plots the facets of a run
"""
global midRA, midDec, fig, at, selected_direction, choose_from_list
selected_direction = None
choose_from_list = False
# Set up coordinate system and figure
points, midRA, midDec = factor.directions.getxy(directions_list)
fig = plt.figure(1, figsize=(10, 9))
if hasWCSaxes:
wcs = factor.directions.makeWCS(midRA, midDec)
ax = WCSAxes(fig, [0.16, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
else:
ax = plt.gca()
field_x = min(points[0])
field_y = max(points[1])
adjust_xy = True
while adjust_xy:
adjust_xy = False
for xy in points:
dist = np.sqrt((xy[0] - field_x)**2 + (xy[1] - field_y)**2)
if dist < 10.0:
field_x -= 1
field_y += 1
adjust_xy = True
break
field_ra, field_dec = factor.directions.xy2radec([field_x], [field_y],
refRA=midRA,
refDec=midDec)
field = Direction('field',
field_ra[0],
field_dec[0],
factor_working_dir=directions_list[0].working_dir)
directions_list.append(field)
ax.set_title('Overview of Factor run in\n{}'.format(
directions_list[0].working_dir))
# Plot facets
markers = []
for direction in directions_list:
if direction.name != 'field':
vertices = read_vertices(direction.vertices_file)
RAverts = vertices[0]
Decverts = vertices[1]
xverts, yverts = factor.directions.radec2xy(RAverts,
Decverts,
refRA=midRA,
refDec=midDec)
xyverts = [np.array([xp, yp]) for xp, yp in zip(xverts, yverts)]
mpl_poly = Polygon(np.array(xyverts),
edgecolor='#a9a9a9',
facecolor='#F2F2F2',
clip_box=ax.bbox,
picker=3.0,
linewidth=2)
else:
xverts = [field_x]
yverts = [field_y]
mpl_poly = Circle((field_x, field_y),
radius=5.0,
edgecolor='#a9a9a9',
facecolor='#F2F2F2',
clip_box=ax.bbox,
picker=3.0,
linewidth=2)
mpl_poly.facet_name = direction.name
mpl_poly.completed_ops = get_completed_ops(direction)
mpl_poly.started_ops = get_started_ops(direction)
mpl_poly.current_op = get_current_op(direction)
set_patch_color(mpl_poly, direction)
ax.add_patch(mpl_poly)
# Add facet names
if direction.name != 'field':
poly_tuple = tuple([(xp, yp) for xp, yp in zip(xverts, yverts)])
xmid = SPolygon(poly_tuple).centroid.x
ymid = SPolygon(poly_tuple).centroid.y
else:
xmid = field_x
ymid = field_y
if trim_names:
name = direction.name.split('_')[-1]
else:
name = direction.name
marker = ax.text(xmid,
ymid,
name,
color='k',
clip_on=True,
clip_box=ax.bbox,
ha='center',
va='bottom')
marker.set_zorder(1001)
markers.append(marker)
# Add info box
at = AnchoredText("Selected direction: None",
prop=dict(size=12),
frameon=True,
loc=3)
at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
at.set_zorder(1002)
ax.add_artist(at)
ax.relim()
ax.autoscale()
ax.set_aspect('equal')
if hasWCSaxes:
RAAxis = ax.coords['ra']
RAAxis.set_axislabel('RA', minpad=0.75)
RAAxis.set_major_formatter('hh:mm:ss')
DecAxis = ax.coords['dec']
DecAxis.set_axislabel('Dec', minpad=0.75)
DecAxis.set_major_formatter('dd:mm:ss')
ax.coords.grid(color='black', alpha=0.5, linestyle='solid')
else:
plt.xlabel("RA (arb. units)")
plt.ylabel("Dec (arb. units)")
# Define coodinate formater to show RA and Dec under mouse pointer
ax.format_coord = formatCoord
# Show legend
not_processed_patch = plt.Rectangle((0, 0),
1,
1,
edgecolor='#a9a9a9',
facecolor='#F2F2F2',
linewidth=2)
processing_patch = plt.Rectangle((0, 0),
1,
1,
edgecolor='#a9a9a9',
facecolor='#F2F5A9',
linewidth=2)
selfcal_ok_patch = plt.Rectangle((0, 0),
1,
1,
edgecolor='#a9a9a9',
facecolor='#A9F5A9',
linewidth=2)
selfcal_not_ok_patch = plt.Rectangle((0, 0),
1,
1,
edgecolor='#a9a9a9',
facecolor='#A4A4A4',
linewidth=2)
processing_error = plt.Rectangle((0, 0),
1,
1,
edgecolor='#a9a9a9',
facecolor='#F5A9A9',
linewidth=2)
patch_list = [
not_processed_patch, processing_patch, processing_error,
selfcal_not_ok_patch, selfcal_ok_patch
]
label_list = [
'Unprocessed', 'Processing', 'Pipeline Error', 'Selfcal Failed',
'Selfcal OK'
]
for i in range(options['reimages']):
label_list.append('Image ' + str(i + 1))
color = (0.66 / (i + 2)**0.5, 0.96 / (i + 2)**0.5, 0.66 / (i + 2)**0.5,
1.0)
reimage_patch = plt.Rectangle((0, 0),
1,
1,
edgecolor='#a9a9a9',
facecolor=color,
linewidth=2)
patch_list.append(reimage_patch)
l = ax.legend(patch_list, label_list, loc="upper right")
l.set_zorder(1002)
# Add check for mouse clicks and key presses
fig.canvas.mpl_connect('pick_event', on_pick)
fig.canvas.mpl_connect('key_press_event', on_press)
# Add timer to update the plot every 60 seconds
timer = fig.canvas.new_timer(interval=60000)
timer.add_callback(update_plot)
timer.start()
# Show plot
plt.show()
plt.close(fig)
# Clean up any temp casacore images
if not hasaplpy:
if os.path.exists('/tmp/tempimage'):
try:
shutil.rmtree('/tmp/tempimage')
except OSError:
pass
def test_update_clip_path_change_wcs(self, tmpdir):
# When WCS is changed, a new frame is created, so we need to make sure
# that the path is carried over to the new frame.
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], aspect='equal')
fig.add_axes(ax)
ax.set_xlim(0., 2.)
ax.set_ylim(0., 2.)
# Force drawing, which freezes the clip path returned by WCSAxes
fig.savefig(tmpdir.join('nothing').strpath)
ax.reset_wcs()
ax.imshow(np.zeros((12, 4)))
ax.set_xlim(-0.5, 3.5)
ax.set_ylim(-0.5, 11.5)
return fig
def plot_image(img_file,
hdu="IMAGE",
stretch='linear',
vmin=None,
vmax=None,
facecolor='black',
center=None,
width=None,
figsize=(10, 10),
cmap=None):
"""
Plot a FITS image created by SOXS using Matplotlib.
Parameters
----------
img_file : str
The on-disk FITS image to plot.
hdu : str or int, optional
The image extension to plot. Default is "IMAGE"
stretch : str, optional
The stretch to apply to the colorbar scale. Options are "linear",
"log", and "sqrt". Default: "linear"
vmin : float, optional
The minimum value of the colorbar. If not set, it will be the minimum
value in the image.
vmax : float, optional
The maximum value of the colorbar. If not set, it will be the maximum
value in the image.
facecolor : str, optional
The color of zero-valued pixels. Default: "black"
center : array-like
A 2-element object giving an (RA, Dec) coordinate for the center
in degrees. If not set, the reference pixel of the image (usually
the center) is used.
width : float, optional
The width of the image in degrees. If not set, the width of the
entire image will be used.
figsize : tuple, optional
A 2-tuple giving the size of the image in inches, e.g. (12, 15).
Default: (10,10)
cmap : str, optional
The colormap to be used. If not set, the default Matplotlib
colormap will be used.
Returns
-------
A tuple of the :class:`~matplotlib.figure.Figure` and the
:class:`~matplotlib.axes.Axes` objects.
"""
import matplotlib.pyplot as plt
from matplotlib.colors import PowerNorm, LogNorm, Normalize
from astropy.wcs.utils import proj_plane_pixel_scales
from astropy.visualization.wcsaxes import WCSAxes
if stretch == "linear":
norm = Normalize(vmin=vmin, vmax=vmax)
elif stretch == "log":
norm = LogNorm(vmin=vmin, vmax=vmax)
elif stretch == "sqrt":
norm = PowerNorm(0.5, vmin=vmin, vmax=vmax)
else:
raise RuntimeError(f"'{stretch}' is not a valid stretch!")
with fits.open(img_file) as f:
hdu = f[hdu]
w = wcs.WCS(hdu.header)
pix_scale = proj_plane_pixel_scales(w)
if center is None:
center = w.wcs.crpix
else:
center = w.wcs_world2pix(center[0], center[1], 0)
if width is None:
dx_pix = 0.5 * hdu.shape[0]
dy_pix = 0.5 * hdu.shape[1]
else:
dx_pix = width / pix_scale[0]
dy_pix = width / pix_scale[1]
fig = plt.figure(figsize=figsize)
ax = WCSAxes(fig, [0.15, 0.1, 0.8, 0.8], wcs=w)
fig.add_axes(ax)
im = ax.imshow(hdu.data, norm=norm, cmap=cmap)
ax.set_xlim(center[0] - 0.5 * dx_pix, center[0] + 0.5 * dx_pix)
ax.set_ylim(center[1] - 0.5 * dy_pix, center[1] + 0.5 * dy_pix)
ax.set_facecolor(facecolor)
cbar = plt.colorbar(im)
return fig, ax
def plot(LSM, fileName=None, labelBy=None):
"""
Shows a simple plot of the sky model.
The circles in the plot are scaled with flux. If the sky model is grouped
into patches, sources are colored by patch and the patch positions are
indicated with stars.
Parameters
----------
LSM : SkyModel object
Input sky model
fileName : str, optional
If given, the plot is saved to a file instead of displayed
labelBy : str, optional
One of 'source' or 'patch': label points using source names ('source') or
patch names ('patch')
Examples:
---------
Plot and display to the screen::
>>> LSM = lsmtool.load('sky.model')
>>> plot(LSM)
Plot and save to a PDF file::
>>> plot(LSM, 'sky_plot.pdf')
"""
try:
import os
if 'DISPLAY' not in os.environ:
import matplotlib
if matplotlib.get_backend() is not 'Agg':
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
except Exception as e:
raise ImportError('PyPlot could not be imported. Plotting is not '
'available: {0}'.format(e.message))
try:
try:
from astropy.visualization.wcsaxes import WCSAxes
hasWCSaxes = True
except:
from wcsaxes import WCSAxes
hasWCSaxes = True
except:
hasWCSaxes = False
import numpy as np
from ..operations_lib import radec2xy, makeWCS
global midRA, midDec, ymin, xmin
if len(LSM) == 0:
log.error('Sky model is empty.')
return
fig = plt.figure(1,figsize=(7.66,7))
plt.clf()
x, y, midRA, midDec = LSM._getXY()
if hasWCSaxes:
wcs = makeWCS(midRA, midDec)
ax = WCSAxes(fig, [0.16, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
else:
ax = plt.gca()
if LSM.hasPatches:
nsrc = len(LSM.getPatchNames())
else:
nsrc = len(LSM)
sm = plt.cm.ScalarMappable(cmap=plt.cm.Set3, norm=plt.Normalize(vmin=0,
vmax=nsrc))
sm._A = []
# Set symbol sizes by flux, making sure no symbol is smaller than 50 or
# larger than 1000
s = []
fluxes = LSM.getColValues('I')
if len(fluxes[fluxes > 0.0]) == 0:
minflux = 0.0
else:
minflux = np.min(fluxes[fluxes > 0.0])
for flux in LSM.getColValues('I'):
if flux > 0.0:
s.append(min(1000.0, (1.0+2.0*np.log10(flux/minflux))*50.0))
else:
s.append(50.0)
# Color sources by patch if grouped
c = [0]*len(LSM)
cp = []
if LSM.hasPatches:
for p, patchName in enumerate(LSM.getPatchNames()):
indices = LSM.getRowIndex(patchName)
cp.append(sm.to_rgba(p))
for ind in indices:
c[ind] = sm.to_rgba(p)
else:
c = [sm.to_rgba(0)] * nsrc
# Plot sources
if hasWCSaxes:
RA = LSM.getColValues('Ra')
Dec = LSM.getColValues('Dec')
ax.set_xlim(np.min(x)-20, np.max(x)+20)
ax.set_ylim(np.min(y)-20, np.max(y)+20)
plt.scatter(x, y, s=s, c=c)
if LSM.hasPatches:
RAp, Decp = LSM.getPatchPositions(asArray=True)
goodInd = np.where( (RAp != 0.0) & (Decp != 0.0) )
if len(goodInd[0]) < len(RAp):
log.info('Some patch positions are unset. Run setPatchPositions() '
'before plotting to see patch positions and patch names.')
xp, yp = radec2xy(RAp[goodInd], Decp[goodInd], midRA, midDec)
plt.scatter(xp, yp, s=100, c=cp, marker='*')
# Set axis labels, etc.
if hasWCSaxes:
RAAxis = ax.coords['ra']
RAAxis.set_axislabel('RA', minpad=0.75)
RAAxis.set_major_formatter('hh:mm:ss')
DecAxis = ax.coords['dec']
DecAxis.set_axislabel('Dec', minpad=0.75)
DecAxis.set_major_formatter('dd:mm:ss')
ax.coords.grid(color='black', alpha=0.5, linestyle='solid')
else:
plt.xlabel("RA (arb. units)")
plt.ylabel("Dec (arb. units)")
if labelBy is not None:
if labelBy.lower() == 'source':
labels = LSM.getColValues('name')
xls = x
yls = y
elif labelBy.lower() == 'patch':
if LSM.hasPatches:
labels = LSM.getPatchNames()
xls = xp
yls = yp
else:
labels = LSM.getColValues('name')
xls = x
yls = y
else:
raise ValueError("The lableBy parameter must be one of 'source' or "
"'patch'.")
for label, xl, yl in zip(labels, xls, yls):
plt.annotate(label, xy = (xl, yl), xytext = (-2, 2), textcoords=
'offset points', ha='right', va='bottom')
# Define coodinate formater to show RA and Dec under mouse pointer
RAformatter = FuncFormatter(RAtickformatter)
ax.format_coord = formatCoord
if fileName is not None:
plt.savefig(fileName)
else:
plt.show()
plt.close(fig)
def test_update_clip_path_rectangular(self, tmpdir):
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], aspect='equal')
fig.add_axes(ax)
ax.set_xlim(0., 2.)
ax.set_ylim(0., 2.)
# Force drawing, which freezes the clip path returned by WCSAxes
fig.savefig(tmpdir.join('nothing').strpath)
ax.imshow(np.zeros((12, 4)))
ax.set_xlim(-0.5, 3.5)
ax.set_ylim(-0.5, 11.5)
return fig
def test_update_clip_path_change_wcs(self, tmpdir):
# When WCS is changed, a new frame is created, so we need to make sure
# that the path is carried over to the new frame.
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], aspect='equal')
fig.add_axes(ax)
ax.set_xlim(0., 2.)
ax.set_ylim(0., 2.)
# Force drawing, which freezes the clip path returned by WCSAxes
fig.savefig(tmpdir.join('nothing').strpath)
ax.reset_wcs()
ax.imshow(np.zeros((12, 4)))
ax.set_xlim(-0.5, 3.5)
ax.set_ylim(-0.5, 11.5)
return fig
def plot(self,
center,
width,
s=None,
c=None,
marker=None,
stride=1,
emin=None,
emax=None,
label=None,
fontsize=18,
fig=None,
ax=None,
**kwargs):
"""
Plot event coordinates from this photon list in a scatter plot,
optionally restricting the photon energies which are plotted
and using only a subset of the photons.
Parameters
----------
center : array-like
The RA, Dec of the center of the plot in degrees.
width : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The width of the plot in arcminutes.
s : integer, optional
Size of the scatter marker in points^2.
c : string, optional
The color of the points.
marker : string, optional
The marker to use for the points in the scatter plot. Default: 'o'
stride : integer, optional
Plot every *stride* events. Default: 1
emin : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The minimum energy of the photons to plot. Default is
the minimum energy in the list.
emax : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The maximum energy of the photons to plot. Default is
the maximum energy in the list.
label : string, optional
The label of the spectrum. Default: None
fontsize : int
Font size for labels and axes. Default: 18
fig : :class:`~matplotlib.figure.Figure`, optional
A Figure instance to plot in. Default: None, one will be
created if not provided.
ax : :class:`~matplotlib.axes.Axes`, optional
An Axes instance to plot in. Default: None, one will be
created if not provided.
"""
import matplotlib.pyplot as plt
from astropy.visualization.wcsaxes import WCSAxes
if fig is None:
fig = plt.figure(figsize=(10, 10))
if ax is None:
wcs = construct_wcs(center[0], center[1])
ax = WCSAxes(fig, [0.15, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
else:
wcs = ax.wcs
if emin is None:
emin = self.energy.value.min()
else:
emin = parse_value(emin, "keV")
if emax is None:
emax = self.energy.value.max()
else:
emax = parse_value(emax, "keV")
idxs = np.logical_and(self.energy.value >= emin,
self.energy.value <= emax)
ra = self.ra[idxs][::stride].value
dec = self.dec[idxs][::stride].value
x, y = wcs.wcs_world2pix(ra, dec, 1)
ax.scatter(x, y, s=s, c=c, marker=marker, label=label, **kwargs)
x0, y0 = wcs.wcs_world2pix(center[0], center[1], 1)
width = parse_value(width, "arcmin") * 60.0
ax.set_xlim(x0 - 0.5 * width, x0 + 0.5 * width)
ax.set_ylim(y0 - 0.5 * width, y0 + 0.5 * width)
ax.set_xlabel("RA")
ax.set_ylabel("Dec")
ax.tick_params(axis='both', labelsize=fontsize)
return fig, ax
def plot_state(directions_list, trim_names=True):
"""
Plots the facets of a run
"""
global midRA, midDec, fig, at, selected_direction, choose_from_list
selected_direction = None
choose_from_list = False
# Set up coordinate system and figure
points, midRA, midDec = factor.directions.getxy(directions_list)
fig = plt.figure(1, figsize=(10,9))
if hasWCSaxes:
wcs = factor.directions.makeWCS(midRA, midDec)
ax = WCSAxes(fig, [0.16, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
else:
ax = plt.gca()
field_x = min(points[0])
field_y = max(points[1])
adjust_xy = True
while adjust_xy:
adjust_xy = False
for xy in points:
dist = np.sqrt( (xy[0] - field_x)**2 + (xy[1] - field_y)**2 )
if dist < 10.0:
field_x -= 1
field_y += 1
adjust_xy = True
break
field_ra, field_dec = factor.directions.xy2radec([field_x], [field_y],
refRA=midRA, refDec=midDec)
field = Direction('field', field_ra[0], field_dec[0],
factor_working_dir=directions_list[0].working_dir)
directions_list.append(field)
ax.set_title('Overview of Factor run in\n{}'.format(directions_list[0].working_dir))
# Plot facets
markers = []
for direction in directions_list:
if direction.name != 'field':
vertices = read_vertices(direction.vertices_file)
RAverts = vertices[0]
Decverts = vertices[1]
xverts, yverts = factor.directions.radec2xy(RAverts, Decverts,
refRA=midRA, refDec=midDec)
xyverts = [np.array([xp, yp]) for xp, yp in zip(xverts, yverts)]
mpl_poly = Polygon(np.array(xyverts), edgecolor='#a9a9a9', facecolor='#F2F2F2',
clip_box=ax.bbox, picker=3.0, linewidth=2)
else:
xverts = [field_x]
yverts = [field_y]
mpl_poly = Circle((field_x, field_y), radius=5.0, edgecolor='#a9a9a9', facecolor='#F2F2F2',
clip_box=ax.bbox, picker=3.0, linewidth=2)
mpl_poly.facet_name = direction.name
mpl_poly.completed_ops = get_completed_ops(direction)
mpl_poly.started_ops = get_started_ops(direction)
mpl_poly.current_op = get_current_op(direction)
set_patch_color(mpl_poly, direction)
ax.add_patch(mpl_poly)
# Add facet names
if direction.name != 'field':
poly_tuple = tuple([(xp, yp) for xp, yp in zip(xverts, yverts)])
xmid = SPolygon(poly_tuple).centroid.x
ymid = SPolygon(poly_tuple).centroid.y
else:
xmid = field_x
ymid = field_y
if trim_names:
name = direction.name.split('_')[-1]
else:
name = direction.name
marker = ax.text(xmid, ymid, name, color='k', clip_on=True,
clip_box=ax.bbox, ha='center', va='bottom')
marker.set_zorder(1001)
markers.append(marker)
# Add info box
at = AnchoredText("Selected direction: None", prop=dict(size=12), frameon=True,
loc=3)
at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2")
at.set_zorder(1002)
ax.add_artist(at)
ax.relim()
ax.autoscale()
ax.set_aspect('equal')
if hasWCSaxes:
RAAxis = ax.coords['ra']
RAAxis.set_axislabel('RA', minpad=0.75)
RAAxis.set_major_formatter('hh:mm:ss')
DecAxis = ax.coords['dec']
DecAxis.set_axislabel('Dec', minpad=0.75)
DecAxis.set_major_formatter('dd:mm:ss')
ax.coords.grid(color='black', alpha=0.5, linestyle='solid')
else:
plt.xlabel("RA (arb. units)")
plt.ylabel("Dec (arb. units)")
# Define coodinate formater to show RA and Dec under mouse pointer
ax.format_coord = formatCoord
# Show legend
not_processed_patch = plt.Rectangle((0, 0), 1, 1, edgecolor='#a9a9a9',
facecolor='#F2F2F2', linewidth=2)
processing_patch = plt.Rectangle((0, 0), 1, 1, edgecolor='#a9a9a9',
facecolor='#F2F5A9', linewidth=2)
selfcal_ok_patch = plt.Rectangle((0, 0), 1, 1, edgecolor='#a9a9a9',
facecolor='#A9F5A9', linewidth=2)
selfcal_not_ok_patch = plt.Rectangle((0, 0), 1, 1, edgecolor='#a9a9a9',
facecolor='#A4A4A4', linewidth=2)
processing_error = plt.Rectangle((0, 0), 1, 1, edgecolor='#a9a9a9',
facecolor='#F5A9A9', linewidth=2)
patch_list=[not_processed_patch, processing_patch, processing_error, selfcal_not_ok_patch, selfcal_ok_patch]
label_list=['Unprocessed', 'Processing', 'Pipeline Error', 'Selfcal Failed', 'Selfcal OK']
for i in range(options['reimages']):
label_list.append('Image '+str(i+1))
color=(0.66/(i+2)**0.5, 0.96/(i+2)**0.5, 0.66/(i+2)**0.5, 1.0)
reimage_patch=plt.Rectangle((0, 0), 1, 1, edgecolor='#a9a9a9',
facecolor=color, linewidth=2)
patch_list.append(reimage_patch)
l = ax.legend(patch_list, label_list, loc="upper right")
l.set_zorder(1002)
# Add check for mouse clicks and key presses
fig.canvas.mpl_connect('pick_event', on_pick)
fig.canvas.mpl_connect('key_press_event', on_press)
# Add timer to update the plot every 60 seconds
timer = fig.canvas.new_timer(interval=60000)
timer.add_callback(update_plot)
timer.start()
# Show plot
plt.show()
plt.close(fig)
# Clean up any temp casacore images
if not hasaplpy:
if os.path.exists('/tmp/tempimage'):
try:
shutil.rmtree('/tmp/tempimage')
except OSError:
pass
def plot(self, center, width, s=None, c=None, marker=None, stride=1,
emin=None, emax=None, label=None, fontsize=18, fig=None,
ax=None, **kwargs):
"""
Plot event coordinates from this photon list in a scatter plot,
optionally restricting the photon energies which are plotted
and using only a subset of the photons.
Parameters
----------
center : array-like
The RA, Dec of the center of the plot in degrees.
width : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The width of the plot in arcminutes.
s : integer, optional
Size of the scatter marker in points^2.
c : string, optional
The color of the points.
marker : string, optional
The marker to use for the points in the scatter plot. Default: 'o'
stride : integer, optional
Plot every *stride* events. Default: 1
emin : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The minimum energy of the photons to plot. Default is
the minimum energy in the list.
emax : float, (value, unit) tuple, or :class:`~astropy.units.Quantity`
The maximum energy of the photons to plot. Default is
the maximum energy in the list.
label : string, optional
The label of the spectrum. Default: None
fontsize : int
Font size for labels and axes. Default: 18
fig : :class:`~matplotlib.figure.Figure`, optional
A Figure instance to plot in. Default: None, one will be
created if not provided.
ax : :class:`~matplotlib.axes.Axes`, optional
An Axes instance to plot in. Default: None, one will be
created if not provided.
"""
import matplotlib.pyplot as plt
from astropy.visualization.wcsaxes import WCSAxes
if fig is None:
fig = plt.figure(figsize=(10, 10))
if ax is None:
wcs = construct_wcs(center[0], center[1])
ax = WCSAxes(fig, [0.15, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
else:
wcs = ax.wcs
if emin is None:
emin = self.energy.value.min()
else:
emin = parse_value(emin, "keV")
if emax is None:
emax = self.energy.value.max()
else:
emax = parse_value(emax, "keV")
idxs = np.logical_and(self.energy.value >= emin, self.energy.value <= emax)
ra = self.ra[idxs][::stride].value
dec = self.dec[idxs][::stride].value
x, y = wcs.wcs_world2pix(ra, dec, 1)
ax.scatter(x, y, s=s, c=c, marker=marker, label=label, **kwargs)
x0, y0 = wcs.wcs_world2pix(center[0], center[1], 1)
width = parse_value(width, "arcmin")*60.0
ax.set_xlim(x0-0.5*width, x0+0.5*width)
ax.set_ylim(y0-0.5*width, y0+0.5*width)
ax.set_xlabel("RA")
ax.set_ylabel("Dec")
ax.tick_params(axis='both', labelsize=fontsize)
return fig, ax
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from astropy.io import fits
import pyregion
# read in the image
xray_name = "pspc_skyview.fits"
f_xray = fits.open(xray_name)
try:
from astropy.wcs import WCS
from astropy.visualization.wcsaxes import WCSAxes
wcs = WCS(f_xray[0].header)
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
except ImportError:
ax = plt.subplot(111)
ax.imshow(f_xray[0].data, cmap=cm.gray, vmin=0., vmax=0.00038, origin="lower")
reg_name = "test.reg"
r = pyregion.open(reg_name).as_imagecoord(header=f_xray[0].header)
from pyregion.mpl_helper import properties_func_default
# Use custom function for patch attribute
def fixed_color(shape, saved_attrs):
attr_list, attr_dict = saved_attrs
def test_rcparams(self):
# Test custom rcParams
with rc_context({
'axes.labelcolor': 'purple',
'axes.labelsize': 14,
'axes.labelweight': 'bold',
'axes.linewidth': 3,
'axes.facecolor': '0.5',
'axes.edgecolor': 'green',
'xtick.color': 'red',
'xtick.labelsize': 8,
'xtick.direction': 'in',
'xtick.minor.visible': True,
'xtick.minor.size': 5,
'xtick.major.size': 20,
'xtick.major.width': 3,
'xtick.major.pad': 10,
'grid.color': 'blue',
'grid.linestyle': ':',
'grid.linewidth': 1,
'grid.alpha': 0.5
}):
fig = plt.figure(figsize=(6, 6))
ax = WCSAxes(fig, [0.15, 0.1, 0.7, 0.7], wcs=None)
fig.add_axes(ax)
ax.set_xlim(-0.5, 2)
ax.set_ylim(-0.5, 2)
ax.grid()
ax.set_xlabel('X label')
ax.set_ylabel('Y label')
ax.coords[0].set_ticklabel(exclude_overlapping=True)
ax.coords[1].set_ticklabel(exclude_overlapping=True)
return fig
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from astropy.io import fits
import pyregion
# read in the image
xray_name = "pspc_skyview.fits"
f_xray = fits.open(xray_name)
try:
from astropy.wcs import WCS
from astropy.visualization.wcsaxes import WCSAxes
wcs = WCS(f_xray[0].header)
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], wcs=wcs)
fig.add_axes(ax)
except ImportError:
ax = plt.subplot(111)
ax.imshow(f_xray[0].data, cmap=cm.gray, vmin=0., vmax=0.00038, origin="lower")
reg_name = "test.reg"
r = pyregion.open(reg_name).as_imagecoord(f_xray[0].header)
patch_list, text_list = r.get_mpl_patches_texts()
for p in patch_list:
ax.add_patch(p)
for t in text_list:
ax.add_artist(t)
import pyregion
region_list = [
"test_text.reg",
"test_context.reg",
]
# Create figure
fig = plt.figure(figsize=(8, 4))
# Parse WCS information
header = Header.fromtextfile('sample_fits01.header')
wcs = WCS(header)
# Create axes
ax1 = WCSAxes(fig, [0.1, 0.1, 0.4, 0.8], wcs=wcs)
fig.add_axes(ax1)
ax2 = WCSAxes(fig, [0.5, 0.1, 0.4, 0.8], wcs=wcs)
fig.add_axes(ax2)
# Hide labels on y axis
ax2.coords[1].set_ticklabel_position('')
for ax, reg_name in zip([ax1, ax2], region_list):
ax.set_xlim(300, 1300)
ax.set_ylim(300, 1300)
ax.set_aspect(1)
r = pyregion.open(reg_name).as_imagecoord(header)
def test_update_clip_path_rectangular(self, tmpdir):
fig = plt.figure()
ax = WCSAxes(fig, [0.1, 0.1, 0.8, 0.8], aspect='equal')
fig.add_axes(ax)
ax.set_xlim(0., 2.)
ax.set_ylim(0., 2.)
# Force drawing, which freezes the clip path returned by WCSAxes
fig.savefig(tmpdir.join('nothing').strpath)
ax.imshow(np.zeros((12, 4)))
ax.set_xlim(-0.5, 3.5)
ax.set_ylim(-0.5, 11.5)
return fig
@pytest.mark.parametrize("test_input, test_kwargs, expected_error", [
(cube[0, 0], {"axes_coordinates": np.arange(10, 10 + cube_unit[0, 0].data.shape[0]),
"axes_units": u.C}, TypeError),
(cube[0, 0], {"data_unit": u.C}, TypeError)
])
def test_cube_plot_1D_errors(test_input, test_kwargs, expected_error):
with pytest.raises(expected_error):
output = test_input.plot(**test_kwargs)
@pytest.mark.parametrize("test_input, test_kwargs, expected_values", [
(cube[0], {},
(np.ma.masked_array(cube[0].data, cube[0].mask), "time [min]", "em.wl [m]",
(-0.5, 3.5, -0.5, 2.5))),
(cube_spatial, {'axes': WCSAxes(plt.figure(), (0, 0, 1, 1), wcs=cube_spatial.wcs)},
(cube_spatial.data,
"custom:pos.helioprojective.lat [deg]",
"custom:pos.helioprojective.lon [deg]",
(-0.5, 3.5, -0.5, 2.5))),
(cube[0], {"axes_coordinates": ["bye", None], "axes_units": [None, u.cm]},
(np.ma.masked_array(cube[0].data, cube[0].mask), "bye [m]", "em.wl [cm]",
(0.0, 3.0, 2e-9, 6e-9))),
(cube[0], {"axes_coordinates": [np.arange(10, 10 + cube[0].data.shape[1]),
u.Quantity(np.arange(10, 10 + cube[0].data.shape[0]), unit=u.m)],
"axes_units": [None, u.cm]},
(np.ma.masked_array(cube[0].data, cube[0].mask), " [None]", " [cm]", (10, 13, 1000, 1200))),
(cube[0], {"axes_coordinates": [np.arange(10, 10 + cube[0].data.shape[1]),
