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from __future__ import (print_function, division, unicode_literals,
absolute_import)
import numpy as np
import matplotlib as mpl
import matplotlib.cm as cm
from sympathy.api import node as synode
from sympathy.platform.exceptions import SyError
from sympathy.api.nodeconfig import Port, Ports, Tag, Tags
from sylib.figure import colors
[docs]class ColormapLookup(synode.Node):
version = '0.1'
name = 'Colormap lookup'
icon = 'colourmap.svg'
description = 'Maps input values into colours based on a colourmap.'
nodeid = 'org.sysess.sympathy.visualize.colormap_lookup'
tags = Tags(Tag.Visual.Figure)
inputs = Ports([Port.Table('Input data', name='input')])
outputs = Ports([Port.Table('Output data', name='output')])
parameters = synode.parameters()
parameters.set_string(
'colormap', value='viridis', label='Colormap',
description=(
'Colormap used for converting the input values'),
editor=synode.Util.combo_editor(options=list(colors.COLORMAPS.keys())))
parameters.set_float(
'vmin', value=0.0, label='vmin',
description=(
'First (lowest) value that should be mapped to colors'))
parameters.set_float(
'vmax', value=1.0, label='vmax',
description=(
'Last (highest) value that should be mapped to colors'))
parameters.set_string(
'suffix', value='', label='Suffix',
description=('Suffix added to each column name when '
'generating the output names'))
def execute(self, node_context):
in_tbl = node_context.input['input']
out_tbl = node_context.output['output']
suffix = node_context.parameters['suffix'].value
vmin = node_context.parameters['vmin'].value
vmax = node_context.parameters['vmax'].value
colormap_name = node_context.parameters['colormap'].value
colormap = cm.get_cmap(colors.COLORMAPS[colormap_name])
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
for col in in_tbl.cols():
try:
data = (colormap(norm(col.data)) * 255)[:, :3].astype(int)
except TypeError:
raise SyError("Colormap node requires all input "
"columns to be numerical.")
as_strings = ['#{:0>2X}{:0>2X}{:0>2X}'
.format(*list(c))
for c in data]
out_tbl.set_column_from_array(col.name+suffix,
np.array(as_strings))
