'''
Color control and choice
========================
Colormap Selection
------------------
A number of colormap obtained from SciVis (`https://sciviscolor.org/`).
The presently available colormap are shown below.
.. image:: ../resources/colormap.png
:scale: 100 %
:align: center
Use `make_cmap` to generate a matplotlib class colormap based on the
xml maps in the library above. `make_cmap` can also be used to generate
a matplotlib colormap custom made as a xml file.
Utilities
---------
'''
import os
import sys
from xml.dom import minidom
import matplotlib.pyplot as plt
import matplotlib.colors as col
import numpy as np
from lxml import etree
homedir = os.path.expanduser("~")
COLPATHDIR = homedir + '/Dropbox (CMCC)/ZapataLibrary/Zapata/zapata/SciVis_colormaps'
[docs]
def make_cmap(xml,colpath=COLPATHDIR):
'''
| Convert colormap from `PARAVISION` and `SCIVISION`
| https://sciviscolor.org/outlier-focused-colormaps/
Parameters
==========
xml: str
Name colormap in xml format
colpath: path
Path to the location of xml colormap
Returns
=======
colormap:
Colormap object
'''
print('Using colormap', colpath +'/'+ xml+'.xml')
vals = load_xml(colpath +'/'+ xml+'.xml')
colors = vals['color_vals']
position = vals['data_vals']
if len(position) != len(colors):
sys.exit('position length must be the same as colors')
cdict = {'red':[], 'green':[], 'blue':[]}
if position[0] != 0:
cdict['red'].append((0, colors[0][0], colors[0][0]))
cdict['green'].append((0, colors[0][1], colors[0][1]))
cdict['blue'].append((0, colors[0][2], colors[0][2]))
for pos, color in zip(position, colors):
cdict['red'].append((pos, color[0], color[0]))
cdict['green'].append((pos, color[1], color[1]))
cdict['blue'].append((pos, color[2], color[2]))
if position[-1] != 1:
cdict['red'].append((1, colors[-1][0], colors[-1][0]))
cdict['green'].append((1, colors[-1][1], colors[-1][1]))
cdict['blue'].append((1, colors[-1][2], colors[-1][2]))
cmap = col.LinearSegmentedColormap('my_colormap',cdict,256)
return cmap
[docs]
def load_xml(xml):
'''
Load colormap in `xml` format
Parameters
==========
xml: str
Name colormap in xml format
Returns
=======
dict :
colorvals Colorvalues
data_vals Color scale
'''
try:
xmldoc = etree.parse(xml)
except IOError as e:
print ('The input file is invalid. It must be a colormap xml file. Go to https://sciviscolor.org/home/colormaps/ for some good options')
print ('Go to https://sciviscolor.org/matlab-matplotlib-pv44/ for an example use of this script.')
sys.exit()
data_vals=[]
color_vals=[]
for s in xmldoc.getroot().findall('.//Point'):
data_vals.append(float(s.attrib['x']))
color_vals.append((float(s.attrib['r']),float(s.attrib['g']),float(s.attrib['b'])))
return {'color_vals':color_vals, 'data_vals':data_vals}
[docs]
def plot_cmap(colormap):
'''
Show colormap
'''
gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))
fig=plt.figure(figsize=(8,1))
map=fig.add_subplot(111)
map.set_frame_on(False)
map.get_xaxis().set_visible(False)
plt.title(colormap.name)
map.get_yaxis().set_visible(False)
fig.tight_layout(pad=0)
map.imshow(gradient, aspect='auto', cmap=plt.get_cmap(colormap))
plt.show(fig)
return
[docs]
def viewcmap(DIR):
'''
Show colormaps in directory `DIR`
Colormaps are in `xml` format
'''
for i in sorted(os.listdir(DIR)):
filename, file_extension = os.path.splitext(i)
if file_extension == '.xml':
tt=make_cmap(COLOR +'/'+ i)
tt.name = filename
plot_cmap(tt)
return
def _showcolormap(COLOR,TGTDIR):
'''
Create picture of all colormap in directory COLOR
and puts picture in directory TGTDIR
'''
fil = []
for i in sorted(os.listdir(COLOR)):
filename, file_extension = os.path.splitext(i)
if file_extension == '.xml':
fil.append(i)
nplot=len(fil)
nplot2 = int(nplot/2)
fig,ax=plt.subplots(nrows=int(nplot/2),ncols=2,figsize=(12,32))
for i in range(0,int(nplot/2)):
filename, file_extension = os.path.splitext(fil[i])
tt=make_cmap(filename,colpath=COLOR)
tt.name = filename
gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))
axs = ax[i,0]
axs.set_frame_on(False)
axs.get_xaxis().set_visible(False)
axs.set_title(tt.name)
axs.get_yaxis().set_visible(False)
axs.imshow(gradient, aspect='auto', cmap=tt)
for i in range(0,int(nplot/2)):
filename, file_extension = os.path.splitext(fil[i+nplot2])
tt=make_cmap(filename,colpath=COLOR)
tt.name = filename
gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))
axs = ax[i,1]
axs.set_frame_on(False)
axs.get_xaxis().set_visible(False)
axs.set_title(tt.name)
axs.get_yaxis().set_visible(False)
axs.imshow(gradient, aspect='auto', cmap=tt)
fig.tight_layout(pad=0.5)
fig.show()
plt.savefig(TGTDIR + '/colormap.png')
return
