Python matplotlib example read and use NCL colormaps#
Software requirements:
Python 3
numpy
matplotlib
Run the read and use NCL colormaps:
python read_and_use_NCL_colormaps.py
Script read_and_use_NCL_colormaps.py:
#!/usr/bin/env python
# coding: utf-8
# Use NCL colormaps
#
# NCL provides a large collection of colormaps that former NCL users would
# like to continue using with Python.
#
# The following function `get_NCL_colormap` reads an NCL colormap either from
# local disk or from an existing NCL installation or directly from the colormaps
# URL of NCL. The RGB values are then converted to a Matplotlib Colormap
# object that can be used to create colored plots.
#
# The function `display_colormap_indices` generates a raster plot using the
# given colormap and add the index value to each color box.
#
# 2024 DKRZ, licensed under CC BY-NC-SA 4.0
import os, re
import numpy as np
import matplotlib.colors as mcolors
import matplotlib.pyplot as plt
#---------------------------------------
# Function get_NCL_colormap
#---------------------------------------
def get_NCL_colormap(cmap_name, extend='None'):
'''Read an NCL RGB colormap file and convert it to a Matplotlib colormap
object.
Parameter:
cmap_name NCL RGB colormap name, e.g. 'ncl_default'
extend use NCL behavior of color handling for the colorbar 'under'
and 'over' colors. 'None' or 'ncl', default 'None'
Description:
Read the NCL colormap and convert it to a Matplotlib Colormap object.
It checks if the colormap file is already available or use the
appropriate URL.
If NCL is installed the colormap will be searched in its colormaps
folder $NCARG_ROOT/lib/ncarg/colormaps.
Returns a Matplotlib Colormap object.
'''
from matplotlib.colors import ListedColormap
import requests
import errno
#-- NCL colormaps URL
NCARG_URL = 'https://www.ncl.ucar.edu/Document/Graphics/ColorTables/Files/'
#-- read the NCL colormap RGB file
colormap_file = cmap_name+'.rgb'
cfile = os.path.split(colormap_file)[1]
if os.path.isfile(colormap_file) == False:
#-- if NCL is already installed
if 'NCARG_ROOT' in os.environ:
cpath = os.environ['NCARG_ROOT']+'/lib/ncarg/colormaps/'
if os.path.isfile(cpath + cfile):
colormap_file = cpath + cfile
with open(colormap_file) as f:
lines = [re.sub('\s+',' ',l) for l in f.read().splitlines() if not (l.startswith('#') or l.startswith('n'))]
#-- use URL to read colormap
elif not 'NCARG_ROOT' in os.environ:
url_file = NCARG_URL+'/'+cmap_name+'.rgb'
res = requests.head(url_file)
if not res.status_code == 200:
print(f'{cmap_name} does not exist!')
raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), cmap_name)
content = requests.get(url_file, stream=True).content
lines = [re.sub('\s+',' ',l) for l in content.decode('UTF-8').splitlines() if not (l.startswith('#') or l.startswith('n'))]
else:
raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), colormap_file)
#-- use local colormap file
else:
with open(colormap_file) as f:
lines = [re.sub('\s+',' ',l) for l in f.read().splitlines() if not (l.startswith('#') or l.startswith('n'))]
#-- skip all possible header lines
tmp = [l.split('#', 1)[0] for l in lines]
tmp = [re.sub(r'\s+',' ', s) for s in tmp]
tmp = [ x for x in tmp if ';' not in x ]
tmp = [ x for x in tmp if x != '']
#-- get the RGB values
i = 0
for l in tmp:
new_array = np.array(l.split()).astype(float)
if i == 0:
color_list = new_array
else:
color_list = np.vstack((color_list, new_array))
i += 1
#-- make sure that the RGB values are within range 0 to 1
if (color_list > 1.).any(): color_list = color_list / 255
#-- add alpha-channel RGB -> RGBA
alpha = np.ones((color_list.shape[0],4))
alpha[:,:-1] = color_list
color_list = alpha
#-- convert to Colormap object
if extend == 'ncl':
cmap = ListedColormap(color_list[1:-1,:])
else:
cmap = ListedColormap(color_list)
#-- define the under, over, and bad colors
under = color_list[0,:]
over = color_list[-1,:]
bad = [0.5, 0.5, 0.5, 1.]
cmap.set_extremes(under=color_list[0], bad=bad, over=color_list[-1])
return cmap
#---------------------------------------
# Function display_colormap_indices()
#---------------------------------------
def display_colormap_indices(cmap, colormap_name, txcol='k'):
'''Display an NCL colormap with max 256 colors.
Parameter
cmap Matplotlib Colormap object
colormap_name name of the NCL colormap
txcol Font color
Description
Create a raster plot of 16x16 color boxes using the given colormap.
'''
nx, ny = 16, 16
data = np.arange(0,256).reshape((nx,ny))
fig, ax = plt.subplots(figsize=(8,8))
plot = ax.pcolormesh(np.arange(-0.5,nx+0.5), np.arange(-0.5,ny+0.5), data,
cmap=cmap, vmin=0, vmax=cmap.N)
ax.set_xticks([])
ax.set_yticks([])
n = np.arange(0,cmap.N+2)
k = 0
for i in range(0,data.shape[1]):
for j in range(0,data.shape[0]):
if k >= max(n):
index = ''
else:
index = str(n[k])
ax.text(j,i,index, ha='center', va='center', fontsize=8, color=txcol)
k += 1
tx = ax.set_title(f'NCL colormap', loc='left', weight='bold')
tx = ax.set_title(f'{colormap_name} ({cmap.N} colors)', loc='center',
weight='bold')
tx = ax.set_title(f'max.colors 256', loc='right', fontsize=8)
tx = ax.text(0.905, 0.12,
'Original NCL colormaps https://www.ncl.ucar.edu/Document/Graphics/ColorTables/Files/',
rotation=-90, fontsize=8,
transform=plt.gcf().transFigure)
plt.savefig(colormap_name+'_display.png', bbox_inches='tight', dpi=100)
#---------------------------------------
# Function main()
#---------------------------------------
def main():
# Get NCL colormap
#
# The colormap file can be stored on your lokal machine in any directory.
# If NCL is already installed the colormaps are stored in the directory
# $NCARG_ROOT/lib/ncarg/colormaps.
#
# In this example we want to make sure that we use the original colormap from
# NCL URL. Therefore, to be on the safe side, we unset the environment variable
# NCARG_ROOT.
os.environ.pop('NCARG_ROOT',None)
# Convert NCL colormap
#
# Choose the colormap and convert it to the Matplotlib Colormap object.
# Here are some examples
colormap1 = 'NEO_div_vegetation_a'
cmap1 = get_NCL_colormap(colormap1)
colormap2 = 'BlueWhiteOrangeRed'
cmap2 = get_NCL_colormap(colormap2)
colormap3 = 'cmocean_deep'
cmap3 = get_NCL_colormap(colormap3)
colormap4 = 'GMT_relief'
cmap4 = get_NCL_colormap(colormap4)
# Display colormap with indices
#
# Let's see how the colormap looks in detail now, therefore we create a
# 2-d data array of range 0 to ncolors and plot the data with Matplotlib's
# `pcolormesh`.
display_colormap_indices(cmap1, colormap1)
display_colormap_indices(cmap2, colormap2)
display_colormap_indices(cmap3, colormap3, txcol='white')
display_colormap_indices(cmap4, colormap4, txcol='gray')
#---------------------------------------
if __name__ == '__main__':
main()
Plot result:
