Source code for sunpy.visualization.colormaps.cm

"""
This module provides a set of colormaps specific for solar data.
"""
from copy import deepcopy

import matplotlib
import matplotlib.cm as mplcm
import matplotlib.pyplot as plt
import numpy as np
from packaging import version

import astropy.units as u

from sunpy.visualization.colormaps import color_tables as ct

__all__ = ['show_colormaps', 'cmlist']

# Helper functions for Matplotlib colormap that avoid deprecation warnings
# in MPL >= 3.6 Once MPL 3.5.0 (where matplotlib.colormaps was introduced)
# is our min version these can be removed and we can just use matplotlib.colormaps


def _get_mpl_cmap(name):
    if version.parse(matplotlib.__version__) >= version.parse("3.5"):
        return matplotlib.colormaps[name]
    else:
        return mplcm.get_cmap(name)


def _register_cmap(name, cmap):
    if version.parse(matplotlib.__version__) >= version.parse("3.5"):
        matplotlib.colormaps.register(cmap, name=name)
    else:
        return mplcm.register_cmap(name, cmap)


sdoaia94 = ct.aia_color_table(94*u.angstrom)
sdoaia131 = ct.aia_color_table(131*u.angstrom)
sdoaia171 = ct.aia_color_table(171*u.angstrom)
sdoaia193 = ct.aia_color_table(193*u.angstrom)
sdoaia211 = ct.aia_color_table(211*u.angstrom)
sdoaia304 = ct.aia_color_table(304*u.angstrom)
sdoaia335 = ct.aia_color_table(335*u.angstrom)
sdoaia1600 = ct.aia_color_table(1600*u.angstrom)
sdoaia1700 = ct.aia_color_table(1700*u.angstrom)
sdoaia4500 = ct.aia_color_table(4500*u.angstrom)

sohoeit171 = ct.eit_color_table(171*u.angstrom)
sohoeit195 = ct.eit_color_table(195*u.angstrom)
sohoeit284 = ct.eit_color_table(284*u.angstrom)
sohoeit304 = ct.eit_color_table(304*u.angstrom)

# Solar Orbiter EUI
# These are deliberately the same as AIA
solohri_euv174 = deepcopy(ct.aia_color_table(171*u.angstrom))
solohri_euv174.name = 'SolO EUI HRI 174 angstrom'
solofsi174 = deepcopy(ct.aia_color_table(171*u.angstrom))
solofsi174.name = 'SolO EUI FSI 174 angstrom'
solofsi304 = deepcopy(ct.aia_color_table(304*u.angstrom))
solofsi304.name = 'SolO EUI FSI 304 angstrom'
# Lyman alpha is a modified IDL red color table
solohri_lya1216 = ct.solohri_lya1216_color_table()

goesrsuvi94 = ct.suvi_color_table(94*u.angstrom)
goesrsuvi131 = ct.suvi_color_table(131*u.angstrom)
goesrsuvi171 = ct.suvi_color_table(171*u.angstrom)
goesrsuvi195 = ct.suvi_color_table(195*u.angstrom)
goesrsuvi284 = ct.suvi_color_table(284*u.angstrom)
goesrsuvi304 = ct.suvi_color_table(304*u.angstrom)


# The color tables below returns one of the fundamental color tables for SOHO
# LASCO images. These are not the same as those used in SSWIDL.  This is
# because the SSWIDL color scaling for LASCO level 0.5 and 1.0 is highly
# compressed and does not display the data well.
soholasco2 = deepcopy(_get_mpl_cmap("gist_heat"))
soholasco2.name = 'SOHO LASCO C2'
soholasco3 = deepcopy(_get_mpl_cmap("bone"))
soholasco3.name = 'SOHO LASCO C3'

# These are the SSWIDL color tables.
sswidlsoholasco2 = ct.sswidl_lasco_color_table(2)
sswidlsoholasco3 = ct.sswidl_lasco_color_table(3)

stereocor1 = ct.cor_color_table(1)
stereocor2 = ct.cor_color_table(2)

stereohi1 = ct.stereo_hi_color_table(1)
stereohi2 = ct.stereo_hi_color_table(2)

yohkohsxtal = ct.sxt_color_table('al')
yohkohsxtwh = ct.sxt_color_table('wh')

hinodexrt = ct.xrt_color_table()
hinodesotintensity = ct.sot_color_table('intensity')

trace171 = ct.trace_color_table('171')
trace195 = ct.trace_color_table('195')
trace284 = ct.trace_color_table('284')
trace1216 = ct.trace_color_table('1216')
trace1550 = ct.trace_color_table('1550')
trace1600 = ct.trace_color_table('1600')
trace1700 = ct.trace_color_table('1700')
traceWL = ct.trace_color_table('WL')

hmimag = ct.hmi_mag_color_table()

kcor = deepcopy(_get_mpl_cmap("gist_gray"))
kcor.name = 'MLSO KCor'

rhessi = ct.rhessi_color_table()
std_gamma_2 = ct.std_gamma_2()

euvi195 = ct.euvi_color_table(195*u.angstrom)
euvi284 = ct.euvi_color_table(284*u.angstrom)
euvi304 = ct.euvi_color_table(304*u.angstrom)
euvi171 = ct.euvi_color_table(171*u.angstrom)

cmlist = {
    'goes-rsuvi94': goesrsuvi94,
    'goes-rsuvi131': goesrsuvi131,
    'goes-rsuvi171': goesrsuvi171,
    'goes-rsuvi195': goesrsuvi195,
    'goes-rsuvi284': goesrsuvi284,
    'goes-rsuvi304': goesrsuvi304,
    'sdoaia94': sdoaia94,
    'sdoaia131': sdoaia131,
    'sdoaia171': sdoaia171,
    'sdoaia193': sdoaia193,
    'sdoaia211': sdoaia211,
    'sdoaia304': sdoaia304,
    'sdoaia335': sdoaia335,
    'sdoaia1600': sdoaia1600,
    'sdoaia1700': sdoaia1700,
    'sdoaia4500': sdoaia4500,
    'sohoeit171': sohoeit171,
    'sohoeit195': sohoeit195,
    'sohoeit284': sohoeit284,
    'sohoeit304': sohoeit304,
    'soholasco2': soholasco2,
    'soholasco3': soholasco3,
    'sswidlsoholasco2': sswidlsoholasco2,
    'sswidlsoholasco3': sswidlsoholasco3,
    'stereocor1': stereocor1,
    'stereocor2': stereocor2,
    'stereohi1': stereohi1,
    'stereohi2': stereohi2,
    'yohkohsxtal': yohkohsxtal,
    'yohkohsxtwh': yohkohsxtwh,
    'hinodexrt': hinodexrt,
    'hinodesotintensity': hinodesotintensity,
    'trace171': trace171,
    'trace195': trace195,
    'trace284': trace284,
    'trace1216': trace1216,
    'trace1550': trace1550,
    'trace1600': trace1600,
    'trace1700': trace1700,
    'traceWL': traceWL,
    'hmimag': hmimag,
    'irissji1330': ct.iris_sji_color_table('1330'),
    'irissji1400': ct.iris_sji_color_table('1400'),
    'irissji1600': ct.iris_sji_color_table('1600'),
    'irissji2796': ct.iris_sji_color_table('2796'),
    'irissji2832': ct.iris_sji_color_table('2832'),
    'irissji5000': ct.iris_sji_color_table('5000'),
    'irissjiFUV': ct.iris_sji_color_table('FUV'),
    'irissjiNUV': ct.iris_sji_color_table('NUV'),
    'irissjiSJI_NUV': ct.iris_sji_color_table('SJI_NUV'),
    'kcor': kcor,
    'rhessi': rhessi,
    'std_gamma_2': std_gamma_2,
    'euvi171': euvi171,
    'euvi195': euvi195,
    'euvi284': euvi284,
    'euvi304': euvi304,
    'solar orbiterfsi174': solofsi174,
    'solar orbiterfsi304': solofsi304,
    'solar orbiterhri_euv174': solohri_euv174,
    'solar orbiterhri_lya1216': solohri_lya1216,
}

# Register the colormaps with matplotlib so matplotlib.colormaps['sdoaia171'] works
for name, cmap in cmlist.items():
    _register_cmap(name=name, cmap=cmap)


[docs]def show_colormaps(search=None): """ Displays a plot of the custom color maps supported in SunPy. Parameters ---------- search : str A string to search for in the names of the color maps (e.g. aia, EIT, 171). Case insensitive. Examples -------- >>> import sunpy.visualization.colormaps as cm >>> cm.show_colormaps() # doctest: +IGNORE_WARNINGS >>> cm.show_colormaps(search='aia') # doctest: +IGNORE_WARNINGS >>> cm.show_colormaps(search='171') # doctest: +IGNORE_WARNINGS """ if search is not None: maps = sorted({k: v for (k, v) in cmlist.items() if k.lower().count(search.lower())}) if len(maps) == 0: raise KeyError(f'No color maps found for search term "{search:s}"') else: maps = sorted(cmlist) nmaps = len(maps) + 1 a = np.linspace(0, 1, 256).reshape(1, -1) a = np.vstack((a, a)) fig = plt.figure(figsize=(7, 10), dpi=128) fig.subplots_adjust(top=0.99, bottom=0.01, left=0.3, right=0.99) for i, name in enumerate(maps): ax = plt.subplot(nmaps, 1, i + 1) ax.imshow(a, aspect='auto', cmap=name, origin='lower') ax.xaxis.set_ticks([]) ax.yaxis.set_ticks([]) ax.set_ylabel(name, fontsize=10, horizontalalignment='right', verticalalignment='center', rotation=0) plt.show()