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())