def plot_im_List(im_List, ipynb=False):
plt.title("Test", fontsize=20)
plt.ion()
plt.clf()
Prior = im_List[0]
for i in range(len(im_List)):
plt.subplot(1, len(im_List), i+1)
plt.imshow(im_List[i].imvec.reshape(Prior.ydim,Prior.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian')
xticks = vb.ticks(Prior.xdim, Prior.psize/RADPERAS/1e-6)
yticks = vb.ticks(Prior.ydim, Prior.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
if i == 0:
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
else:
plt.xlabel('')
plt.ylabel('')
plt.title('')
plt.draw()
if ipynb:
display.clear_output()
display.display(plt.gcf())
def plot_im_List_Set(im_List_List, ipynb=False):
plt.ion()
plt.clf()
Prior = im_List_List[0][0]
xnum = len(im_List_List[0])
ynum = len(im_List_List)
for i in range(xnum*ynum):
plt.subplot(ynum, xnum, i+1)
im = im_List_List[(i-i%xnum)/xnum][i%xnum]
plt.imshow(im.imvec.reshape(im.ydim,im.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian')
xticks = vb.ticks(im.xdim, im.psize/RADPERAS/1e-6)
yticks = vb.ticks(im.ydim, im.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
if i == 0:
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
else:
plt.xlabel('')
plt.ylabel('')
plt.title('')
plt.draw()
if ipynb:
display.clear_output()
display.display(plt.gcf())
def plot_i_dynamic(im_List, Prior, nit, chi2, s, s_dynamic, ipynb=False):
plt.ion()
plt.clf()
for i in range(len(im_List)):
plt.subplot(1, len(im_List), i+1)
plt.imshow(im_List[i].reshape(Prior.ydim,Prior.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian')
xticks = vb.ticks(Prior.xdim, Prior.psize/RADPERAS/1e-6)
yticks = vb.ticks(Prior.ydim, Prior.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
if i == 0:
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
plt.title("step: %i $\chi^2$: %f $s$: %f $s_{t}$: %f" % (nit, chi2, s, s_dynamic), fontsize=20)
else:
plt.xlabel('')
plt.ylabel('')
plt.title('')
plt.draw()
if ipynb:
display.clear_output()
display.display(plt.gcf())
def plot_scatt(im_unscatt, im_ea, im_scatt, im_phase, Prior, nit, chi2, ipynb=False):
# Get vectors and ratio from current image
x = np.array([[i for i in range(Prior.xdim)] for j in range(Prior.ydim)])
y = np.array([[j for i in range(Prior.xdim)] for j in range(Prior.ydim)])
# Create figure and title
plt.ion()
plt.clf()
plt.suptitle("step: %i $\chi^2$: %f " % (nit, chi2), fontsize=20)
# Unscattered Image
plt.subplot(141)
plt.imshow(im_unscatt.reshape(Prior.ydim, Prior.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian', vmin=0)
xticks = vb.ticks(Prior.xdim, Prior.psize/RADPERAS/1e-6)
yticks = vb.ticks(Prior.ydim, Prior.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
plt.title('Unscattered')
# Ensemble Average
plt.subplot(142)
plt.imshow(im_ea.reshape(Prior.ydim, Prior.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian', vmin=0)
xticks = vb.ticks(Prior.xdim, Prior.psize/RADPERAS/1e-6)
yticks = vb.ticks(Prior.ydim, Prior.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
plt.title('Ensemble Average')
# Scattered
plt.subplot(143)
plt.imshow(im_scatt.reshape(Prior.ydim, Prior.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian', vmin=0)
xticks = vb.ticks(Prior.xdim, Prior.psize/RADPERAS/1e-6)
yticks = vb.ticks(Prior.ydim, Prior.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
plt.title('Average Image')
# Phase
plt.subplot(144)
plt.imshow(im_phase.reshape(Prior.ydim, Prior.xdim), cmap=plt.get_cmap('afmhot'), interpolation='gaussian')
xticks = vb.ticks(Prior.xdim, Prior.psize/RADPERAS/1e-6)
yticks = vb.ticks(Prior.ydim, Prior.psize/RADPERAS/1e-6)
plt.xticks(xticks[0], xticks[1])
plt.yticks(yticks[0], yticks[1])
plt.xlabel('Relative RA ($\mu$as)')
plt.ylabel('Relative Dec ($\mu$as)')
plt.title('Phase Screen')
# Display
plt.draw()
if ipynb:
display.clear_output()
display.display(plt.gcf())
