def get_histogram_scale(distances_dict, nbins):
"""Draws histogram to outfile_name.
"""
scale_dict = defaultdict(list)
#draw histograms
for d_dict in distances_dict.values():
for i, (field, data) in enumerate(d_dict.items()):
if len(data) < 1:
continue
histogram = hist(data, bins=nbins)
fig = gcf()
axis = fig.gca()
#get height scale: y/x
ymin, ymax = axis.get_ylim()
xmin, xmax = axis.get_xlim()
scale_dict['ymin'].append(ymin)
scale_dict['ymax'].append(ymax)
scale_dict['xmin'].append(xmin)
scale_dict['xmax'].append(xmax)
clf()
yscale = (min(scale_dict['ymin']), max(scale_dict['ymax']))
xscale = (min(scale_dict['xmin']), max(scale_dict['xmax']))
return xscale, yscale
def get_histogram_scale(distances_dict, nbins):
"""Draws histogram to outfile_name.
"""
scale_dict = defaultdict(list)
#draw histograms
for d_dict in distances_dict.values():
for i, (field, data) in enumerate(d_dict.items()):
if len(data) < 1:
continue
histogram = hist(data,bins=nbins)
fig = gcf()
axis = fig.gca()
#get height scale: y/x
ymin,ymax = axis.get_ylim()
xmin,xmax = axis.get_xlim()
scale_dict['ymin'].append(ymin)
scale_dict['ymax'].append(ymax)
scale_dict['xmin'].append(xmin)
scale_dict['xmax'].append(xmax)
clf()
yscale = (min(scale_dict['ymin']),max(scale_dict['ymax']))
xscale = (min(scale_dict['xmin']),max(scale_dict['xmax']))
return xscale,yscale
def draw_histogram(distances, color, nbins, outfile_name,\
xscale=None, yscale=None, background_color='white',\
title='', **kwargs):
"""Draws histogram to outfile_name.
"""
average = mean(distances)
maximum = max(distances)
histogram = hist(distances,bins=nbins,facecolor=color, \
normed=True,**kwargs)
fig = gcf()
axis = fig.gca()
#set labels
axis.set_xlabel('Distance')
axis.set_ylabel('Normalized Counts of Pairs in Group')
axis.set_title(title)
#get figure scale: width/height
fig_scale = fig.get_figwidth() / float(fig.get_figheight())
if xscale is not None:
axis.set_xlim(xscale)
if yscale is not None:
axis.set_ylim(yscale)
#get height scale: y/x
ylim = axis.get_ylim()
ylen = ylim[1] - ylim[0]
xlim = axis.get_xlim()
xlen = xlim[1] - xlim[0]
height_scale = ylen / float(xlen)
#set width
width = xlen / 20.
height = width * height_scale * fig_scale
#draw circle at average distance
ellipse = Ellipse([average,0.0],width=width, \
height=height, \
edgecolor=color, fill=False)
axis.add_artist(ellipse)
#draw line at center of circle
y1 = -height / 2.
y2 = height / 2.
line = Polygon([[average, y1], [average, y2]], edgecolor=color)
axis.add_artist(line)
transparent = True
if background_color != "white":
axis.set_axis_bgcolor(background_color)
transparent = False
savefig(outfile_name, format='png', dpi=72, transparent=transparent)
close()
return histogram
def draw_histogram(distances, color, nbins, outfile_name,\
xscale=None, yscale=None, background_color='white',\
title='', **kwargs):
"""Draws histogram to outfile_name.
"""
average = mean(distances)
maximum = max(distances)
histogram = hist(distances,bins=nbins,facecolor=color, \
normed=True,**kwargs)
fig = gcf()
axis = fig.gca()
#set labels
axis.set_xlabel('Distance')
axis.set_ylabel('Normalized Counts of Pairs in Group')
axis.set_title(title)
#get figure scale: width/height
fig_scale = fig.get_figwidth()/float(fig.get_figheight())
if xscale is not None:
axis.set_xlim(xscale)
if yscale is not None:
axis.set_ylim(yscale)
#get height scale: y/x
ylim = axis.get_ylim()
ylen = ylim[1]-ylim[0]
xlim = axis.get_xlim()
xlen = xlim[1]-xlim[0]
height_scale = ylen/float(xlen)
#set width
width = xlen/20.
height = width*height_scale*fig_scale
#draw circle at average distance
ellipse = Ellipse([average,0.0],width=width, \
height=height, \
edgecolor=color, fill=False)
axis.add_artist(ellipse)
#draw line at center of circle
y1 = -height/2.
y2 = height/2.
line = Polygon([[average, y1] ,[average, y2]], edgecolor=color)
axis.add_artist(line)
transparent=True
if background_color != "white":
axis.set_axis_bgcolor(background_color)
transparent=False
savefig(outfile_name,format='png',dpi=72, transparent=transparent)
close()
return histogram
