# use path_effects
my_path_effects = [patheffects.withStroke(linewidth=3,
foreground="w")]
pywcsgrid2.Axes.default_path_effects = my_path_effects
if 1:
f = pyfits.open("radio_21cm.fits")
d, h = f[0].data, f[0].header
plt.figure(1, [4.5,4.])
ax = pywcsgrid2.axes([0.15, 0.15, 0.8, 0.8], header=h)
ax.imshow(d, origin="low",
cmap=plt.cm.gist_heat_r, interpolation="nearest")
ax.set_xlim(20, 52)
ax.set_ylim(20, 52)
# Figure title
t = ax.add_inner_title("Figure 1", loc=2, path_effects=False)
# compass
ax.add_compass(loc=1)
# Beam size
# (major, minor) = 3, 4 in pixel, angle=20
# Now construct a header that is in the equatorial frame (North up, east to the left)
h_equatorial = h_original.copy()
h_equatorial.update(
cd1_1=-np.hypot(h_original["CD1_1"], h_original["CD1_2"]),
cd1_2=0.0,
cd2_1=0.0,
cd2_2=np.hypot(h_original["CD2_1"], h_original["CD2_2"]),
orientat=0.0)
if not grayscale_drawn:
# Define the axis limits if this is the first frame with a valid WCS. This
# first frame defines the axes for all subsequent drawing.
ax = pywcsgrid2.axes(wcs=h_equatorial, aspect=1)
ax.set_xlim(-nx/8, 9*nx/8)
ax.set_ylim(-ny/4, 5*ny/4)
ax.locator_params(axis="x", nbins=5)
ax.locator_params(axis="y", nbins=5)
target = h_original["target"]
ax.set_title(this_image)
# Mark the target as a crosshair in red
result = subprocess.Popen(["coords","-d",target], stdout=subprocess.PIPE)
(sout,serr) = result.communicate()
ra_target,dec_target = string.rstrip(sout).split( );
ra_target = float(ra_target)
dec_target = float(dec_target)
cd=math.cos(dec_target*3.14159/180.)
ax["fk5"].plot([ra_target+6*arcmin, ra_target+10*arcmin], [dec_target, dec_target], "r")
def _make_axis(self):
if self.fig is None:
self.fig = plt.figure()
if self.cmap is None:
self.cmap = plt.cm.gray_r
if self.twin and not self.right:
if self.gs:
gs = self.gs
else:
gs = 121
self.ax = pywcsgrid2.subplot(gs, wcs=self.h1, aspect=self.aspect,adjustable='box',)
elif self.twin and self.right:
if self.gs:
gs = self.gs
else:
gs = 122
self.ax = pywcsgrid2.subplot(gs, wcs=self.h1, aspect=self.aspect,adjustable='box')
elif self.gs:
if 'PACS' in self.filename:
self.ax = plt.subplot(self.gs,projection=self.w0)
else:
self.ax = pywcsgrid2.subplot(self.gs, wcs=self.h1, aspect=self.aspect,adjustable='box')
#if self.h0['CTYPE1'] == 'GLON-CAR':
# self.ax.set_display_coord_system('fk5')
else:
self.ax = pywcsgrid2.axes(wcs=self.h1, aspect=self.aspect) #aspect=1
self.ax.set_xlim(-self.nx/4, 5*self.nx/4)
self.ax.set_ylim(-self.ny/4, 5*self.ny/4)
if self.interp is None:
if 'PACS' in self.filename:
self.im = self.ax.imshow(self.data,origin='lower',vmin=self.vmin,vmax=self.vmax,cmap=self.cmap,norm=self.norm)
else:
self.im = self.ax[self.h0].imshow_affine(self.data,origin='lower',vmin=self.vmin,vmax=self.vmax,cmap=self.cmap,norm=self.norm)
else:
self.im = self.ax[self.h0].imshow(self.data,origin='lower',vmin=self.vmin,vmax=self.vmax,cmap=self.cmap,interpolation=self.interp,norm=self.norm)
if self.xlim:
self.ax.set_xlim(self.xlim)
if self.ylim:
self.ax.set_ylim(self.ylim)
self.ax.grid(color='black', alpha=0.2, linestyle='dashed')
if self.right:
self.ax.axis['left'].major_ticklabels.set_visible(False)
#self.ax.axis['right'].major_ticklabels.set_visible(True)
self.ax.axis['right'].label.set_text(r"$\delta_{2000}$")
plt.setp(self.ax.axis['right'].label,fontsize=14)
self.ax.axis['left'].label.set_text('')
else:
try:
plt.setp(self.ax.axis['left'].label,fontsize=14)
except TypeError:
plt.setp(self.ax.yaxis.label,fontsize=14)
try:
plt.setp(self.ax.axis['bottom'].label,fontsize=14)
except TypeError:
plt.setp(self.ax.xaxis.label,fontsize=14)
return self.ax
[ra0, dec0], = w2.wcs_pix2world([[i0, j0]], 1)
h2.update(crpix1=i0, crpix2=j0, crval1=ra0, crval2=dec0)
# Now construct a header that is in the equatorial frame (North up, east to the left)
h1 = h2.copy()
h1.update(
cd1_1=-np.hypot(h2["CD1_1"], h2["CD1_2"]),
cd1_2=0.0,
cd2_1=0.0,
cd2_2=np.hypot(h2["CD2_1"], h2["CD2_2"]),
orientat=0.0,
)
# Finally plot the image in the new frame
arcsec = 1.0 / 3600
ax = pywcsgrid2.axes(wcs=h1, aspect=1)
# ax.set_xlim(-nx/4, 5*nx/4)
# ax.set_ylim(-ny/4, 5*ny/4)
ax.set_xlim(-nx / 8, 9 * nx / 8)
ax.set_ylim(-ny / 4, 5 * ny / 4)
# Mark a line in red
# ax["fk5"].plot([ra0, ra0], [dec0 + 10*arcsec, dec0 + 15*arcsec], "r")
ax.locator_params(axis="x", nbins=5)
ax.locator_params(axis="y", nbins=5)
ax[h2].imshow_affine(processed_image, origin="lower", cmap=plt.cm.gray_r)
ax.grid()
# ax.figure.savefig("/var/tmp/nice_image.pdf", dpi=150)
ax.figure.savefig("/var/tmp/nice_image.png")
# Email results if requested
if args.mail:
def plot_h2_sd(plot_dict, contour_image=None, limits=None,
filename=None, show=True, vlimits=None, av_vlimits=None,
cloud_names=('california', 'perseus', 'taurus'),):
# Import external modules
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
import pyfits as fits
import matplotlib.pyplot as plt
import myplotting as myplt
import pywcsgrid2
import pywcs
from pylab import cm # colormaps
from matplotlib.patches import Polygon
from mpl_toolkits.axes_grid1.axes_grid import AxesGrid
# Set up plot aesthetics
plt.clf(); plt.close()
cmap = plt.cm.copper
norm = matplotlib.colors.LogNorm()
# Create figure instance
fig = plt.figure(figsize=(3.6, 9))
if 1:
nrows = 3
ncols = 1
nrows_ncols=(3, 1)
ngrids=3
figsize = (3.6, 8)
fig = pywcsgrid2.plt.figure(figsize=figsize)
else:
nrows_ncols=(1,1)
ngrids=1
axes = AxesGrid(fig, (1,1,1),
nrows_ncols=nrows_ncols,
ngrids=ngrids,
cbar_mode="each",
cbar_location='right',
cbar_pad="2%",
cbar_size='3%',
axes_pad=0.1,
axes_class=(wcs.Axes,
dict(header=plot_dict['header'])),
aspect=True,
label_mode='L',
share_all=True)
colorbar_axes = [0.05, 0.97, 0.95, 0.02,]
map_axes = np.array([0.05, 0.69, 0.95, 0.25])
for i, cloud_name in enumerate(cloud_names):
header = plot_dict[cloud_name]['header']
limits = plot_dict[cloud_name]['limits']
contour_image = plot_dict[cloud_name]['contour_image']
contours = plot_dict[cloud_name]['contours']
#ax = pywcsgrid2.subplot(311+i, header=header)
ax = pywcsgrid2.axes(map_axes, header=header)
#ax = fig.add_subplot(311 + i, header=)
h2_sd = plot_dict[cloud_name]['h2_sd']
# create axes
# show the image
im = ax.imshow(h2_sd,
interpolation='nearest',
origin='lower',
cmap=cmap,
vmin=vlimits[0],
vmax=vlimits[1],
#norm=matplotlib.colors.LogNorm()
)
# Asthetics
ax.set_display_coord_system("fk5")
ax.set_ticklabel_type("hms", "dms")
if i == 2:
ax.set_xlabel('Right Ascension [J2000]',)
else:
ax.set_xlabel('')
ax.set_xlabel('Right Ascension [J2000]',)
ax.set_ylabel('Declination [J2000]',)
ax.locator_params(nbins=6)
#cb_axes.colorbar(im)
#cb_axes.axis["right"].toggle(ticklabels=False)
# colorbar
#cb = ax.cax.colorbar(im)
cmap.set_bad(color='w')
# plot limits
if limits is not None:
limits_pix = myplt.convert_wcs_limits(limits, header, frame='fk5')
ax.set_xlim(limits_pix[0],limits_pix[1])
ax.set_ylim(limits_pix[2],limits_pix[3])
# Plot Av contours
if contour_image is not None:
ax.contour(contour_image, levels=contours, colors='w')
# Write label to colorbar
#cb.set_label_text(r'$\Sigma_{\rm H_2} [M_\odot$\,pc$^{-2}$]',)
if 0:
if regions is not None:
for region in props['region_name_pos']:
vertices = np.copy(regions[region]['poly_verts']['pixel'])
rect = ax.add_patch(Polygon(
vertices[:, ::-1],
facecolor='none',
edgecolor='w'))
ax.annotate(cloud_name.capitalize(),
xytext=(0.96, 0.94),
xy=(0.96, 0.94),
textcoords='axes fraction',
xycoords='axes fraction',
size=10,
color='k',
bbox=dict(boxstyle='square',
facecolor='w',
alpha=1),
horizontalalignment='right',
verticalalignment='top',
)
# create new box for plot
map_axes[1] -= 0.3
#map_axes[3] -= 0.3
ax = plt.axes(colorbar_axes,
)
cb = plt.colorbar(im,
cax=ax,
orientation='horizontal',
)
cb.ax.set_xlabel(r'$\Sigma_{\rm H_2} [{\rm M_\odot}$\,pc$^{-2}$]',)
cb.ax.xaxis.set_label_position('top')
if filename is not None:
plt.savefig(filename, bbox_inches='tight')
if show:
fig.show()
nx, ny = h2["naxis1"], h2["naxis2"]
i0, j0 = (float(nx) + 1.0) / 2, (float(ny) + 1.0) / 2
[ra0, dec0], = w2.wcs_pix2world([[i0, j0]], 1)
h2.update(crpix1=i0, crpix2=j0, crval1=ra0, crval2=dec0)
# Now construct a header that is in the equatorial frame (North up, east to the left)
h1 = h2.copy()
h1.update(cd1_1=-np.hypot(h2["CD1_1"], h2["CD1_2"]),
cd1_2=0.0,
cd2_1=0.0,
cd2_2=np.hypot(h2["CD2_1"], h2["CD2_2"]),
orientat=0.0)
# Finally plot the image in the new frame
arcsec = 1. / 3600
ax = pywcsgrid2.axes(wcs=h1, aspect=1)
#ax.set_xlim(-nx/4, 5*nx/4)
#ax.set_ylim(-ny/4, 5*ny/4)
ax.set_xlim(-nx / 8, 9 * nx / 8)
ax.set_ylim(-ny / 4, 5 * ny / 4)
# Mark a line in red
# ax["fk5"].plot([ra0, ra0], [dec0 + 10*arcsec, dec0 + 15*arcsec], "r")
ax.locator_params(axis="x", nbins=5)
ax.locator_params(axis="y", nbins=5)
ax[h2].imshow_affine(processed_image, origin='lower', cmap=plt.cm.gray_r)
ax.grid()
#ax.figure.savefig("/var/tmp/nice_image.pdf", dpi=150)
ax.figure.savefig("/var/tmp/nice_image.png")
# Email results if requested
if args.mail:
def plot_h2_sd(
plot_dict,
contour_image=None,
limits=None,
filename=None,
show=True,
vlimits=None,
av_vlimits=None,
cloud_names=('california', 'perseus', 'taurus'),
):
# Import external modules
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
import pyfits as fits
import matplotlib.pyplot as plt
import myplotting as myplt
import pywcsgrid2
import pywcs
from pylab import cm # colormaps
from matplotlib.patches import Polygon
from mpl_toolkits.axes_grid1.axes_grid import AxesGrid
# Set up plot aesthetics
plt.clf()
plt.close()
cmap = plt.cm.copper
norm = matplotlib.colors.LogNorm()
# Create figure instance
fig = plt.figure(figsize=(3.6, 9))
if 1:
nrows = 3
ncols = 1
nrows_ncols = (3, 1)
ngrids = 3
figsize = (3.6, 8)
fig = pywcsgrid2.plt.figure(figsize=figsize)
else:
nrows_ncols = (1, 1)
ngrids = 1
axes = AxesGrid(fig, (1, 1, 1),
nrows_ncols=nrows_ncols,
ngrids=ngrids,
cbar_mode="each",
cbar_location='right',
cbar_pad="2%",
cbar_size='3%',
axes_pad=0.1,
axes_class=(wcs.Axes,
dict(header=plot_dict['header'])),
aspect=True,
label_mode='L',
share_all=True)
colorbar_axes = [
0.05,
0.97,
0.95,
0.02,
]
map_axes = np.array([0.05, 0.69, 0.95, 0.25])
for i, cloud_name in enumerate(cloud_names):
header = plot_dict[cloud_name]['header']
limits = plot_dict[cloud_name]['limits']
contour_image = plot_dict[cloud_name]['contour_image']
contours = plot_dict[cloud_name]['contours']
#ax = pywcsgrid2.subplot(311+i, header=header)
ax = pywcsgrid2.axes(map_axes, header=header)
#ax = fig.add_subplot(311 + i, header=)
h2_sd = plot_dict[cloud_name]['h2_sd']
# create axes
# show the image
im = ax.imshow(
h2_sd,
interpolation='nearest',
origin='lower',
cmap=cmap,
vmin=vlimits[0],
vmax=vlimits[1],
#norm=matplotlib.colors.LogNorm()
)
# Asthetics
ax.set_display_coord_system("fk5")
ax.set_ticklabel_type("hms", "dms")
if i == 2:
ax.set_xlabel('Right Ascension [J2000]', )
else:
ax.set_xlabel('')
ax.set_xlabel('Right Ascension [J2000]', )
ax.set_ylabel('Declination [J2000]', )
ax.locator_params(nbins=6)
#cb_axes.colorbar(im)
#cb_axes.axis["right"].toggle(ticklabels=False)
# colorbar
#cb = ax.cax.colorbar(im)
cmap.set_bad(color='w')
# plot limits
if limits is not None:
limits_pix = myplt.convert_wcs_limits(limits, header, frame='fk5')
ax.set_xlim(limits_pix[0], limits_pix[1])
ax.set_ylim(limits_pix[2], limits_pix[3])
# Plot Av contours
if contour_image is not None:
ax.contour(contour_image, levels=contours, colors='w')
# Write label to colorbar
#cb.set_label_text(r'$\Sigma_{\rm H_2} [M_\odot$\,pc$^{-2}$]',)
if 0:
if regions is not None:
for region in props['region_name_pos']:
vertices = np.copy(regions[region]['poly_verts']['pixel'])
rect = ax.add_patch(
Polygon(vertices[:, ::-1],
facecolor='none',
edgecolor='w'))
ax.annotate(
cloud_name.capitalize(),
xytext=(0.96, 0.94),
xy=(0.96, 0.94),
textcoords='axes fraction',
xycoords='axes fraction',
size=10,
color='k',
bbox=dict(boxstyle='square', facecolor='w', alpha=1),
horizontalalignment='right',
verticalalignment='top',
)
# create new box for plot
map_axes[1] -= 0.3
#map_axes[3] -= 0.3
ax = plt.axes(colorbar_axes, )
cb = plt.colorbar(
im,
cax=ax,
orientation='horizontal',
)
cb.ax.set_xlabel(r'$\Sigma_{\rm H_2} [{\rm M_\odot}$\,pc$^{-2}$]', )
cb.ax.xaxis.set_label_position('top')
if filename is not None:
plt.savefig(filename, bbox_inches='tight')
if show:
fig.show()
from astropy.io import fits as pyfits
import matplotlib.pyplot as plt
f = pyfits.open("data/lmc.fits")
d, h = f[0].data, f[0].header
plt.figure(1, figsize=[5, 5])
import pywcsgrid2
ax = pywcsgrid2.axes([0.2, 0.15, 0.7, 0.8], header=h)
im1 = ax.imshow(d, origin="low", vmin=0, vmax=2000, cmap=plt.cm.gray_r)
# viewlimits in image coordinate
ax.set_xlim(6, 81)
ax.set_ylim(23, 98)
# draw grids
ax.grid()
# make y ticklabels in absolute degree.
ax.set_ticklabel2_type("absdeg", locs=[-65, -67.5, -70, -72.5])
ax.set_default_label(None,
"absdeg") # update the label using the default values
# change grid density of the x axis
ax.locator_params(axis="x", nbins=6)
plt.show()
