def show_projections()

in c3dm/tools/vis_utils.py [0:0]

• 84 lines of code
• 3 McCabe index (conditional complexity)

def show_projections( viz, 
					  env, 
					  p, 
					  v=None, 
					  image_path=None, 
					  image=None, 
					  title='projs', 
					  cmap__='gist_ncar', 
					  markersize=None,
					  sticks=None, 
					  stickwidth=2,
					  stick_color=None,
					  plot_point_order=False,
					  bbox = None,
					  win=None ):
	
	if image is None:
		try:
			im = Image.open(image_path).convert('RGB')
			im = np.array(im).transpose(2,0,1)
		except:
			im = None
			print('!cant load image %s' % image_path)
	else:
		im = image

	nkp = int(p.shape[2])

	pid = np.linspace(0.,1.,nkp);             

	if v is not None:
		okp = np.where(v > 0)[0]
	else:
		okp = np.where(np.ones(nkp))[0]

	possible_markers = ['.','*','+']
	markers = [possible_markers[i%len(possible_markers)] for i in range(len(p))]

	if markersize is None:
		msz = 50
		if nkp > 40:
			msz = 5
		markersizes = [msz]*nkp
	else:
		markersizes = [markersize]*nkp

	fig = plt.figure(figsize=[11,11])
	
	if im is not None:
		plt.imshow( im.transpose( (1,2,0) ) ); plt.axis('off')

	if sticks is not None:
		if stick_color is not None:
			linecol = stick_color
		else:
			linecol = [0.,0.,0.]
		
		for p_ in p:
			for stick in sticks:
				if v is not None:
					if v[stick[0]]>0 and v[stick[1]]>0:
						linestyle='-'
					else:
						continue
				plt.plot( p_[0,stick], p_[1,stick], linestyle,
						  color=linecol, linewidth=stickwidth, zorder=1 )

	for p_, marker, msz in zip(p, markers, markersizes):        
		plt.scatter( p_[0,okp], p_[1,okp], msz, pid[okp],
					 cmap=cmap__, linewidths=2, marker=marker, zorder=2, \
					 vmin=0., vmax=1. )
		if plot_point_order:
			for ii in okp:
				plt.text( p_[0,ii], p_[1,ii], '%d' % ii, fontsize=int(msz*0.25) )
				
	if bbox is not None:
		import matplotlib.patches as patches
		# Create a Rectangle patch
		rect = patches.Rectangle((bbox[0],bbox[1]),bbox[2],bbox[3],\
					linewidth=1,edgecolor='r',facecolor='none')
		plt.gca().add_patch(rect)

	if im is None:
		plt.gca().invert_yaxis()
		plt.axis('equal')
		plt.gca().axes.get_xaxis().set_visible(False)
		plt.gca().axes.get_yaxis().set_visible(False)
		# plt.gca().set_frame_on(False)
		plt.gca().set_axis_off()
	else: # remove all margins    
		# plt.gca().axes.get_xaxis().set_visible(False)
		# plt.gca().axes.get_yaxis().set_visible(False)
		# plt.gca().set_frame_on(False)
		# plt.gca().set_axis_off()
		pass
		
	# return fig
	improj = np.array(fig2data(fig))  
	if env is not None:
		win = viz.image( np.array(improj).transpose(2,0,1), \
				   env=env, opts={ 'title': title }, win=win )
	else:
		win = None

	plt.close(fig)

	return improj, win