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Added collections of named colormaps, attribute access #5

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merged 5 commits into from
Sep 25, 2017
Merged

Added collections of named colormaps, attribute access #5

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03767e6
Removed outdated files
jbednar Sep 22, 2017
27589b7
Added collections of named colormaps, attribute access
jbednar Sep 22, 2017
02d97a2
Sorted named colormap dictionaries
jbednar Sep 23, 2017
5825e9a
Made dictionaries tab complete
jbednar Sep 23, 2017
5c0b73b
Fixed typo in docs
jbednar Sep 25, 2017
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45 changes: 36 additions & 9 deletions assets/CET_to_py.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,6 @@
Generate Python versions for each of the colormaps provided in
http://peterkovesi.com/projects/colourmaps/CETperceptual_csv_0_1.zip
"""
# The linear_kryw_mycarta map is from
# https://mycarta.wordpress.com/2012/10/14/the-rainbow-is-deadlong-live-the-rainbow-part-4-cie-lab-heated-body/

import os, os.path, csv

Expand All @@ -22,6 +20,11 @@

or as Python attributes:

palette.name
cm.name

or as individually importable Python attributes:

m_name
b_name

Expand All @@ -31,12 +34,25 @@

but some have shorter, more convenient aliases, some of which are
inspired by Matplotlib colormaps of the same name and others
based on the qualitative appearance.
based on the qualitative appearance. The colormaps with
shorter names tend to be the most useful subset, and for
cases like automatic population of a GUI widget these
colormaps are are provided as a separate subset:

palette['name'] or palette_n.name
cm_n['name'] or cm_n.name
"""

__version__ = '0.9.0'
__version__ = '0.9.1'

from collections import OrderedDict

class AttrODict(OrderedDict):
"""Ordered dictionary with attribute access (e.g. for tab completion)"""
def __getattr__(self, name): return self[name]
def __delattr__(self, name): del self[name]
def __setattr__(self, name, value): self[name] = value
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Should this also have a __dir__ method for tab completion or would that be too cluttered:

    def __dir__(self): return self.keys()


try:
from matplotlib.colors import LinearSegmentedColormap
from matplotlib.cm import register_cmap
Expand All @@ -57,10 +73,17 @@ def mpl_cm(name,colorlist):
register_cmap("cet_"+name, cmap=cm[name])
return cm[name]

palette = OrderedDict()
cm = OrderedDict()
palette = AttrODict()
cm = AttrODict()
palette_n = AttrODict()
cm_n = AttrODict()
'''

footer = """
palette_n = AttrODict(sorted(palette_n.items()))
cm_n = AttrODict(sorted(cm_n.items()))
"""

# Here #mpl indicates a colormap name taken from Matplotlib
aliases = dict(
cyclic_mygbm_30_95_c78_s25 = 'colorwheel',
Expand All @@ -75,11 +98,11 @@ def mpl_cm(name,colorlist):
linear_blue_5_95_c73 = 'kbc',
linear_blue_95_50_c20 = 'blues', #mpl
linear_bmw_5_95_c89 = 'bmw',
linear_bmy_10_95_c78 = 'inferno', #mpl
linear_bmy_10_95_c78 = 'bmy',
linear_green_5_95_c69 = 'kgy',
linear_grey_0_100_c0 = 'gray', #mpl
linear_grey_10_95_c0 = 'dimgray',
linear_kryw_0_100_c71 = 'fire', #mpl
linear_kryw_0_100_c71 = 'fire',
linear_ternary_blue_0_44_c57 = 'kb',
linear_ternary_green_0_46_c42 = 'kg',
linear_ternary_red_0_50_c52 = 'kr',
Expand All @@ -93,7 +116,7 @@ def mpl_cm(name,colorlist):
if filename.endswith(".csv"):
base = filename[:-4].replace("-","_").replace("_n256","")
output.write("\n\n"+base+" = [\\\n")
with open(os.path.join(path,filename),'rb') as csvfile:
with open(os.path.join(path,filename),'r') as csvfile:
reader = csv.reader(csvfile)
for row in reader:
output.write("["+', '.join(row)+"],\n")
Expand All @@ -107,8 +130,12 @@ def mpl_cm(name,colorlist):
output.write("m_{0} = m_{1}\n".format(alias,base))
output.write("m_{0}_r = m_{1}_r\n".format(alias,base))
output.write("palette['{0}'] = b_{1}\n".format(alias,base))
output.write("palette_n['{0}'] = b_{1}\n".format(alias,base))
output.write("cm['{0}'] = m_{1}\n".format(alias,base))
output.write("cm['{0}_r'] = m_{1}_r\n".format(alias,base))
output.write("cm_n['{0}'] = mpl_cm('{0}',{1})\n".format(alias,base))
output.write("cm_n['{0}_r'] = mpl_cm('{0}_r',list(reversed({1})))\n".format(alias,base))
output.write("register_cmap('cet_{0}',m_{1})\n".format(alias,base))
output.write("register_cmap('cet_{0}_r',m_{1}_r)\n".format(alias,base))
output.write("\n\n")
output.write(footer)
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