def addImage(col, row, grid, xrange):
filename = mp1_data.getDataFilename(row, 2, snapshots[col])
ax = grid.grid[col][row]
cbar_ax = grid.cgrid[col][row]
data = torch.CFD_Data(filename, axial=True)
vs = data.get_var(torch.VarType("tem", True))
vsi = data.interpolate(vs, "linear")
vsmin = vs.min()
vsmax = vs.max()
im = torch.image(data.x[0], data.x[1],
vsi, vsmin, vsmax, "linear", cmap,
ax)
#cb = cbar_ax.colorbar(im, format=ticker.FuncFormatter(fmt))
formatter = ticker.ScalarFormatter(useOffset=True, useMathText=True)
formatter.set_powerlimits((0, 1))
cb = grid.fig.colorbar(im, cax=cbar_ax, format=ticker.FuncFormatter(fmt), orientation='horizontal')
#cb.ax.xaxis.set_ticks(np.arange(0, 1.01, 0.5))
#labels = cb.ax.get_xticklabels()
#labels[0] = ""
#labels[2] = ""
#cb.ax.set_xticklabels(labels)
if grid.is_visible(col, row):
zcentre = (110.0 / 200.0) * data.dx * data.ny
zmin = zcentre - xrange[col][row]/2.0
zmax = zcentre + xrange[col][row]/2.0
ax.set_xlim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.set_ylim([zmin, zmax])
ax.xaxis.set_ticks(np.arange(-xrange[col][row]/2.0, (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.yaxis.set_ticks(np.arange(zmin, zmax + 0.0001, xrange[col][row]/4.0))
ax.xaxis.get_major_ticks()[0].label1.set_visible(False)
ax.xaxis.get_major_ticks()[2].label1.set_visible(False)
ax.xaxis.get_major_ticks()[-1].label1.set_visible(False)
ax.yaxis.get_major_ticks()[0].label1.set_visible(False)
ax.yaxis.get_major_ticks()[2].label1.set_visible(False)
ax.yaxis.get_major_ticks()[-1].label1.set_visible(False)
# Add column and row labels
if col == 0:
ax.text(-0.15, 0.5, fmt.latexify("M = " + fmt.fmt_mass(mp1_data.masses[row]) + "\ \\mathrm{M_\\odot}"),
fontsize=10, horizontalalignment='right', verticalalignment='center',
rotation='vertical', transform=ax.transAxes)
if row == 0:
ax.text(0.5, 2.4, fmt.latexify("t = " + fmt.fmt_nolatex(mp1_data.times[col], 0) + "\ \\mathrm{yrs}"),
fontsize=10, horizontalalignment='center', verticalalignment='bottom',
rotation='horizontal', transform=ax.transAxes)
nyt = nyticks[irow]
grid[2 * irow + 0].set_ylim([0, ymax])
grid[2 * irow + 1].set_ylim([0, ymax])
if irow == 4:
for icol in range(2):
grid[2 * irow + icol].set_yticks(np.arange(0, ymax + (ymax - 1.0e-8)/ float(nyt), ymax / float(nyt)))
else:
for icol in range(2):
grid[2 * irow + icol].set_yticks(np.arange(ymax / float(nyt), ymax + (ymax - 1.0e-8)/ float(nyt), ymax / float(nyt)))
kx1 = dict(linewidth=1.5, label="CORNISH", color='b')
kx2 = dict(linewidth=1.5, label="Simulated", color='r', linestyle='--')
grid[2 * irow + 0].text(0.04, 0.94, fmt.latexify("n_\\star = " + fmt.fmt_power(mp1_data.densities[irow], '{:3.1f}', 4) + "\ \\mathrm{cm^{-3}}"),
fontsize=fontsize, horizontalalignment='left', verticalalignment='top',
rotation='horizontal', transform=grid[2 * irow + 0].transAxes)
bins0 = np.arange(0, 24, 1)
bins1 = np.arange(0, 1, 0.04)
bincentres0 = 0.5 * (bins0[:-1] + bins0[1:])
bincentres1 = 0.5 * (bins1[:-1] + bins1[1:])
plotter.histstep(grid[2* irow + 0], cornish_survey[:,11], bins0, errorcentres=bincentres0, normed=normed, **kx1)
plotter.histstep(grid[2* irow + 0], simulated_survey[:,7], bins0, normed=normed, **kx2)
plotter.histstep(grid[2* irow + 1], cornish_phy_sizes, bins1, errorcentres=bincentres1, normed=normed, **kx1)
plotter.histstep(grid[2* irow + 1], phy_sizes, bins1, normed=normed, **kx2)
### Legend
def addImage(col, row, grid, xrange):
filename = mp1_data.getRadioDirname(row, 2, snapshots[col], 45, 5) + "/emeasure_ff.fits"
ax = grid.grid[col][row]
cbar_ax = grid.cgrid[col][row]
hdu_list = fits.open(filename)
image_data = hdu_list[0].data
sig = 5
FWHM = sig*hdu_list[0].header['PIXAS']*2.335
image_data = ndimage.gaussian_filter(image_data, sigma=(sig, sig), order=0)
nx = hdu_list[0].header['NAXIS1']
ny = hdu_list[0].header['NAXIS2']
dx = -hdu_list[0].header['CDELT1']*60.0*60.0
dy = hdu_list[0].header['CDELT2']*60.0*60.0
xmax = 0.5 * nx * dx
xmin = -0.5 * nx * dx
ymax = 0.5 * ny * dy
ymin = -0.5 * ny * dy
x = np.arange(xmin + (dx/2.0), xmax, dx)
y = np.arange(ymin + (dy/2.0), ymax, dy)
X, Y = np.meshgrid(x, y)
max = hdu_list[0].header['MPIX']
nlevels = 7
levels = []
for ilev in range(nlevels):
levels.append(max/(math.sqrt(2.0)**(nlevels - ilev)))
im = ax.imshow(image_data, extent=[xmin,xmax,ymin,ymax], origin='lower', cmap='gray_r')
#cb = cbar_ax.colorbar(im, format=ticker.FuncFormatter(fmt))
formatter = ticker.ScalarFormatter(useOffset=True, useMathText=True)
formatter.set_powerlimits((0, 1))
cb = grid.fig.colorbar(im, cax=cbar_ax, format=ticker.FuncFormatter(fmt), orientation='horizontal')
#cb.ax.xaxis.set_ticks_position('top')
xmax = cb.ax.get_xlim()[1]
cb.ax.xaxis.set_ticks(np.arange(0, xmax, xmax/4.0))
labels = cb.ax.get_xticklabels()
labels[0] = ""
labels[2] = ""
cb.ax.set_xticklabels(labels)
ax.contour(X, Y, image_data, levels, colors='black', linewidths=0.5)
ax.set_xlim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.set_ylim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.xaxis.set_ticks(np.arange(-xrange[col][row]/2.0, (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.yaxis.set_ticks(np.arange(-(xrange[col][row]/2.0), (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.xaxis.get_major_ticks()[0].label1.set_visible(False)
ax.xaxis.get_major_ticks()[2].label1.set_visible(False)
ax.xaxis.get_major_ticks()[-1].label1.set_visible(False)
ax.yaxis.get_major_ticks()[0].label1.set_visible(False)
ax.yaxis.get_major_ticks()[2].label1.set_visible(False)
ax.yaxis.get_major_ticks()[-1].label1.set_visible(False)
# Pixel angular size in upper left corner.
ax.text(0.02, 0.96, '{:.2f}'.format(hdu_list[0].header['PIXAS']) + "''",
fontsize=6, horizontalalignment='left', verticalalignment='top',
rotation='horizontal', transform=ax.transAxes)
# FWHM of guassian blur kernal in lower left corner.
ax.text(0.02, 0.04, "FWHM=" + '{:.1f}'.format(FWHM) + "''",
fontsize=6, horizontalalignment='left', verticalalignment='bottom',
rotation='horizontal', transform=ax.transAxes)
# FWHM diameter line to show scale
ax.plot([(0.90)*xrange[col][row]/2.0 - FWHM, (0.90)*xrange[col][row]/2.0], [-(0.90)*xrange[col][row]/2.0, -(0.90)*xrange[col][row]/2.0])
# Peak brightness in mJy/beam in upper right
rbeam_rad = 0.5 * hdu_list[0].header['BMAJ'] * math.pi / 180.0
pix_rad = abs(hdu_list[0].header['CDELT1']) * math.pi / 180.0
intensity_filename = mp1_data.getRadioDirname(row, 2, snapshots[col], 45, 5) + "/intensity_pixel_ff.fits"
hdu_list2 = fits.open(intensity_filename)
peak = hdu_list2[0].header['MPIX'] * math.pi * rbeam_rad * rbeam_rad / (pix_rad * pix_rad)
ax.text(0.98, 0.96, '{:.2f}'.format(peak) + "mJy/b",
fontsize=6, horizontalalignment='right', verticalalignment='top',
rotation='horizontal', transform=ax.transAxes)
# Add column and row labels
def fmt_mass(x):
a = '{:.0f}'.format(x)
return '{}'.format(a)
if col == 0:
ax.text(-0.22, 0.5, fmt.latexify("M = " + fmt.fmt_mass(mp1_data.masses[row]) + "\ \\mathrm{M_\\odot}"),
fontsize=10, horizontalalignment='right', verticalalignment='center',
rotation='vertical', transform=ax.transAxes)
if row == 0:
ax.text(0.5, 1.24, fmt.latexify("t = " + fmt.fmt_nolatex(mp1_data.times[col], 0) + "\ \\mathrm{yrs}"),
fontsize=10, horizontalalignment='center', verticalalignment='bottom',
rotation='horizontal', transform=ax.transAxes)
def addImage(col, row, grid, xrange):
if row % 2 == 1 or col % 2 == 1:
return
filename = mp1_data.getRadioDirname(row, 2, snapshots[col], 45, 5) + "/emeasure_ff.fits"
col /= 2
row /= 2
ax = grid.grid[col][row]
cbar_ax = grid.cgrid[col][row]
hdu_list = fits.open(filename)
image_data = hdu_list[0].data
sig = 5
FWHM = sig*hdu_list[0].header['PIXAS']*2.335
image_data = ndimage.gaussian_filter(image_data, sigma=(sig, sig), order=0)
nx = hdu_list[0].header['NAXIS1']
ny = hdu_list[0].header['NAXIS2']
dx = -hdu_list[0].header['CDELT1']*60.0*60.0
dy = hdu_list[0].header['CDELT2']*60.0*60.0
xmax = 0.5 * nx * dx
xmin = -0.5 * nx * dx
ymax = 0.5 * ny * dy
ymin = -0.5 * ny * dy
x = np.arange(xmin + (dx/2.0), xmax, dx)
y = np.arange(ymin + (dy/2.0), ymax, dy)
X, Y = np.meshgrid(x, y)
max = hdu_list[0].header['MPIX']
nlevels = 7
levels = []
for ilev in range(nlevels):
levels.append(max/(math.sqrt(2.0)**(nlevels - ilev)))
im = ax.imshow(image_data, extent=[xmin,xmax,ymin,ymax], origin='lower', cmap='gray_r', zorder=0)
#cb = cbar_ax.colorbar(im, format=ticker.FuncFormatter(fmt))
formatter = ticker.ScalarFormatter(useOffset=True, useMathText=True)
formatter.set_powerlimits((0, 1))
cb = grid.fig.colorbar(im, cax=cbar_ax, format=ticker.FuncFormatter(fmt.fmt), orientation='horizontal')
#cb.ax.xaxis.set_ticks_position('top')
xmax = cb.ax.get_xlim()[1]
cb.ax.xaxis.set_ticks(np.arange(0, xmax, xmax/4.0))
labels = cb.ax.get_xticklabels()
labels[0] = ""
labels[2] = ""
cb.ax.set_xticklabels(labels)
ax.contour(X, Y, image_data, levels, colors='black', linewidths=0.5, zorder=1)
param_filename = mp1_data.getParamFilename(row, col, 25)
filestring = open(param_filename, 'r').read()
table = lua.eval("{" + filestring + "}")
physical_dx = table["Parameters"]["Grid"]["side_length"] / float(table["Parameters"]["Grid"]["no_cells_x"])
side_length_y = table["Parameters"]["Grid"]["no_cells_y"] * physical_dx
star_vert_phy = table["Parameters"]["Star"]["cell_position_y"] * physical_dx - 0.5 * side_length_y
star_vert_ang = math.degrees(star_vert_phy / (1.5 * 1000 * 3.09e18)) * 60 * 60
star_y = star_vert_ang / math.sqrt(2)
cloud_vert_ang = star_vert_ang + math.degrees(0.35 / 1500.0) * 60 * 60
cloud_y = cloud_vert_ang / math.sqrt(2)
ax.scatter([0], [star_y], c='w', marker='*', linewidths=[0.4], zorder=2)
ax.scatter([0], [cloud_y], c='w', marker='D', linewidths=[0.4], zorder=2)
ax.set_xlim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.set_ylim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.xaxis.set_ticks(np.arange(-xrange[col][row]/2.0, (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.yaxis.set_ticks(np.arange(-(xrange[col][row]/2.0), (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.xaxis.get_major_ticks()[0].label1.set_visible(False)
ax.xaxis.get_major_ticks()[2].label1.set_visible(False)
ax.xaxis.get_major_ticks()[-1].label1.set_visible(False)
ax.yaxis.get_major_ticks()[0].label1.set_visible(False)
ax.yaxis.get_major_ticks()[2].label1.set_visible(False)
ax.yaxis.get_major_ticks()[-1].label1.set_visible(False)
if False:
# Pixel angular size in upper left corner.
ax.text(0.02, 0.96, '{:.2f}'.format(hdu_list[0].header['PIXAS']) + "''",
fontsize=5, horizontalalignment='left', verticalalignment='top',
rotation='horizontal', transform=ax.transAxes)
# FWHM of guassian blur kernal in lower left corner.
ax.text(0.02, 0.04, "FWHM=" + '{:.1f}'.format(FWHM) + "''",
fontsize=5, horizontalalignment='left', verticalalignment='bottom',
rotation='horizontal', transform=ax.transAxes)
# FWHM diameter line to show scale
ax.plot([(0.90)*xrange[col][row]/2.0 - FWHM, (0.90)*xrange[col][row]/2.0], [-(0.90)*xrange[col][row]/2.0, -(0.90)*xrange[col][row]/2.0])
# Peak brightness in mJy/beam in upper right
rbeam_rad = 0.5 * hdu_list[0].header['BMAJ'] * math.pi / 180.0
pix_rad = abs(hdu_list[0].header['CDELT1']) * math.pi / 180.0
intensity_filename = mp1_data.getRadioDirname(row, col, 25, 45) + "/intensity_pixel_ff.fits"
hdu_list2 = fits.open(intensity_filename)
peak = hdu_list2[0].header['MPIX'] * math.pi * rbeam_rad * rbeam_rad / (pix_rad * pix_rad)
ax.text(0.98, 0.96, '{:.2f}'.format(peak) + "mJy/b",
fontsize=5, horizontalalignment='right', verticalalignment='top',
rotation='horizontal', transform=ax.transAxes)
# Add column and row labels
def fmt_mass(x):
a = '{:.0f}'.format(x)
return '{}'.format(a)
if col == 0:
text_str = fmt.latexify("M = " + fmt.fmt_mass(mp1_data.masses[2 * row]) + "\ \\mathrm{M_\\odot}")
ax.text(-0.3, 0.5, text_str,
fontsize=8, horizontalalignment='right', verticalalignment='center',
rotation='vertical', transform=ax.transAxes)
if row == 0:
text_str = fmt.latexify("t = " + fmt.fmt_power(int(mp1_data.times[2 * col] / 1000.0), '{:3.0f}', 0) + "\ \\mathrm{kyr}")
ax.text(0.5, 1.3, text_str,
fontsize=8, horizontalalignment='center', verticalalignment='bottom',
rotation='horizontal', transform=ax.transAxes)
def addImage(index, grid, xrange):
col = index
row = 0
filename = mp1_data.getRadioDirname(5, 2, 25, angles[index], 5) + "/emeasure_ff.fits"
print filename
ax = grid.grid[col][row]
cbar_ax = grid.cgrid[col][row]
hdu_list = fits.open(filename)
image_data = hdu_list[0].data
sig = 5
FWHM = sig*hdu_list[0].header['PIXAS']*2.335
image_data = ndimage.gaussian_filter(image_data, sigma=(sig, sig), order=0)
nx = hdu_list[0].header['NAXIS1']
ny = hdu_list[0].header['NAXIS2']
dx = -hdu_list[0].header['CDELT1']*60.0*60.0
dy = hdu_list[0].header['CDELT2']*60.0*60.0
xmax = 0.5 * nx * dx
xmin = -0.5 * nx * dx
ymax = 0.5 * ny * dy
ymin = -0.5 * ny * dy
x = np.arange(xmin + (dx/2.0), xmax, dx)
y = np.arange(ymin + (dy/2.0), ymax, dy)
X, Y = np.meshgrid(x, y)
max = hdu_list[0].header['MPIX']
nlevels = 7
levels = []
for ilev in range(nlevels):
levels.append(max/(math.sqrt(2.0)**(nlevels - ilev)))
im = ax.imshow(image_data, extent=[xmin,xmax,ymin,ymax], origin='lower', cmap='gray_r')
#cb = cbar_ax.colorbar(im, format=ticker.FuncFormatter(fmt))
formatter = ticker.ScalarFormatter(useOffset=True, useMathText=True)
formatter.set_powerlimits((0, 1))
cb = grid.fig.colorbar(im, cax=cbar_ax, format=ticker.FuncFormatter(fmt.fmt), orientation='horizontal')
#cb.ax.xaxis.set_ticks_position('top')
xmax = cb.ax.get_xlim()[1]
cb.ax.xaxis.set_ticks(np.arange(0, xmax, xmax/4.0))
labels = cb.ax.get_xticklabels()
labels[0] = ""
labels[2] = ""
cb.ax.set_xticklabels(labels)
ax.contour(X, Y, image_data, levels, colors='black', linewidths=0.5)
ax.set_xlim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.set_ylim([-xrange[col][row]/2.0, xrange[col][row]/2.0])
ax.xaxis.set_ticks(np.arange(-xrange[col][row]/2.0, (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.yaxis.set_ticks(np.arange(-(xrange[col][row]/2.0), (xrange[col][row]/2.0) + 0.0001, xrange[col][row]/4.0))
ax.xaxis.get_major_ticks()[0].label1.set_visible(False)
ax.xaxis.get_major_ticks()[2].label1.set_visible(False)
ax.xaxis.get_major_ticks()[-1].label1.set_visible(False)
ax.yaxis.get_major_ticks()[0].label1.set_visible(False)
ax.yaxis.get_major_ticks()[2].label1.set_visible(False)
ax.yaxis.get_major_ticks()[-1].label1.set_visible(False)
if col != 0:
ax.tick_params(labelleft='off')
# Add column and row labels
if row == 0:
ax.text(0.5, 1.24, fmt.latexify("\\theta_\\mathrm{i} = " + str(angles[col]) + "^\\circ"),
fontsize=10, horizontalalignment='center', verticalalignment='bottom',
rotation='horizontal', transform=ax.transAxes)