def test_get_plot_params_vel_mpl5(self):
desired = {
'bitmasks': self.bitmasks()['2.0.2'],
'cmap': 'RdBu_r',
'percentile_clip': [10, 90],
'symmetric': True,
'snr_min': None
}
actual = get_plot_params(dapver='2.0.2', prop='stellar_vel')
self.assertDictEqual(actual, desired)
def test_get_plot_params_sigma_mpl5(self):
desired = {
'bitmasks': self.bitmasks()['2.0.2'],
'cmap': 'inferno',
'percentile_clip': [10, 90],
'symmetric': False,
'snr_min': 1
}
actual = get_plot_params(dapver='2.0.2', prop='stellar_sigma')
self.assertDictEqual(actual, desired)
def test_get_plot_params_default_mpl5(self):
desired = {
'bitmasks': self.bitmasks()['2.0.2'],
'cmap': 'linearlab',
'percentile_clip': [5, 95],
'symmetric': False,
'snr_min': 1
}
actual = get_plot_params(dapver='2.0.2', prop='emline_gflux')
self.assertDictEqual(actual, desired)
def test_format_use_masks(self, use_masks, mask, expected, set_release):
if config.release == 'MPL-4':
pytest.skip('Skip MPL-4.')
for prop in [
'stellar_vel', 'stellar_sigma', 'emline_gflux', 'specindex'
]:
params = get_plot_params(dapver=config.lookUpVersions()[1],
prop=prop)
actual = mapplot._format_use_masks(
use_masks, mask, dapmap=None, default_masks=params['bitmasks'])
assert actual == expected
def test_get_plot_params(self, dapver, name, desired):
params = get_default_plot_params(dapver)
if 'vel' in name:
key = 'vel'
elif 'sigma' in name:
key = 'sigma'
else:
key = 'default'
desired['bitmasks'] = params[key]['bitmasks']
actual = get_plot_params(dapver=dapver, prop=name)
assert desired == actual
def plot(*args, **kwargs):
"""Make single panel map or one panel of multi-panel map plot.
Please see the `Plotting Tutorial
<http://sdss-marvin.readthedocs.io/en/latest/tutorials/plotting-tutorial.html>`_
for examples.
Parameters:
dapmap (marvin.tools.quantities.Map):
Marvin Map object. Default is ``None``.
value (array):
Data array. Default is ``None``.
ivar (array):
Inverse variance array. Default is ``None``.
mask (array):
Mask array. Default is ``None``.
cmap (str):
Colormap (see :ref:`marvin-utils-plot-map-default-params` for
defaults).
percentile_clip (tuple-like):
Percentile clip (see :ref:`marvin-utils-plot-map-default-params`
for defaults).
sigma_clip (float):
Sigma clip. Default is ``False``.
cbrange (tuple-like):
If ``None``, set automatically. Default is ``None``.
symmetric (bool):
Draw a colorbar that is symmetric around zero (see
:ref:`marvin-utils-plot-map-default-params` for default).
snr_min (float):
Minimum signal-to-noise for keeping a valid measurement (see
:ref:`marvin-utils-plot-map-default-params` for default).
log_cb (bool):
Draw a log normalized colorbar. Default is ``False``.
title (str):
If ``None``, set automatically from property (and channel) name(s).
For no title, set to ''. Default is ``None``.
title_mode (str):
The mode to generate a title automatically, if ``title`` is not
set. Usually ``'string'`` or ``'latex'``. Default is ``'string'``.
See :func:`~marvin.utils.datamodel.dap.base.Property.to_string`
for details.
cblabel (str):
If ``None``, set automatically from unit. For no colorbar label,
set to ''. Default is ``None``.
sky_coords (bool):
If ``True``, show plot in sky coordinates (i.e., arcsec), otherwise
show in spaxel coordinates. Default is ``False``.
use_masks (bool, str, list):
Use DAP bitmasks. If ``True``, use the recommended DAP masks.
Otherwise provide a mask name as a string or multiple mask names as
a list of strings. Default is ``True``.
plt_style (str):
Matplotlib style sheet to use. Default is 'seaborn-darkgrid'.
fig (matplotlib Figure object):
Use if creating subplot of a multi-panel plot. Default is ``None``.
ax (matplotlib Axis object):
Use if creating subplot of a multi-panel plot. Default is ``None``.
patch_kws (dict):
Keyword args to pass to `matplotlib.patches.Rectangle
<https://matplotlib.org/api/_as_gen/matplotlib.patches.Rectangle.html>`_.
Default is ``None``.
imshow_kws (dict):
Keyword args to pass to `ax.imshow
<http://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.imshow.html#matplotlib.axes.Axes.imshow>`_.
Default is ``None``.
cb_kws (dict):
Keyword args to set and draw colorbar. Default is ``None``.
return_cb (bool):
Return colorbar axis. Default is ``False``.
return_cbrange (bool):
Return colorbar range without drawing plot. Default is ``False``.
Returns:
fig, ax (tuple):
`matplotlib.figure <http://matplotlib.org/api/figure_api.html>`_,
`matplotlib.axes <http://matplotlib.org/api/axes_api.html>`_
Example:
>>> import marvin.utils.plot.map as mapplot
>>> maps = Maps(plateifu='8485-1901')
>>> ha = maps['emline_gflux_ha_6564']
>>> fig, ax = mapplot.plot(dapmap=ha)
"""
valid_kwargs = [
'dapmap', 'value', 'ivar', 'mask', 'cmap', 'percentile_clip',
'sigma_clip', 'cbrange', 'symmetric', 'snr_min', 'log_cb', 'title',
'title_mode', 'cblabel', 'sky_coords', 'use_masks', 'plt_style', 'fig',
'ax', 'patch_kws', 'imshow_kws', 'cb_kws', 'return_cb',
'return_cbrange'
]
assert len(
args) == 0, 'Map.plot() does not accept arguments, only keywords.'
for kw in kwargs:
assert kw in valid_kwargs, 'keyword {0} is not valid'.format(kw)
assert ((kwargs.get('percentile_clip', None) is not None) +
(kwargs.get('sigma_clip', None) is not None) +
(kwargs.get('cbrange', None) is not None) <= 1), \
'Only set one of percentile_clip, sigma_clip, or cbrange!'
dapmap = kwargs.get('dapmap', None)
value = kwargs.get('value', None)
ivar = kwargs.get('ivar', None)
mask = kwargs.get('mask', None)
sigma_clip = kwargs.get('sigma_clip', False)
cbrange = kwargs.get('cbrange', None)
log_cb = kwargs.get('log_cb', False)
title = kwargs.get('title', None)
title_mode = kwargs.get('title_mode', 'string')
cblabel = kwargs.get('cblabel', None)
sky_coords = kwargs.get('sky_coords', False)
use_masks = kwargs.get('use_masks', True)
plt_style = kwargs.get('plt_style', 'seaborn-darkgrid')
fig = kwargs.get('fig', None)
ax = kwargs.get('ax', None)
patch_kws = kwargs.get('patch_kws', {})
imshow_kws = kwargs.get('imshow_kws', {})
cb_kws = kwargs.get('cb_kws', {})
return_cb = kwargs.get('return_cb', False)
return_cbrange = kwargs.get('return_cbrange', False)
assert (value is not None) or (dapmap is not None), \
'Map.plot() requires specifying ``value`` or ``dapmap``.'
# user-defined value, ivar, or mask overrides dapmap attributes
value = value if value is not None else getattr(dapmap, 'value', None)
ivar = ivar if ivar is not None else getattr(dapmap, 'ivar', None)
all_true = np.zeros(value.shape, dtype=bool)
mask = mask if mask is not None else getattr(dapmap, 'mask', all_true)
if title is None:
if getattr(dapmap, 'datamodel', None) is not None:
title = dapmap.datamodel.to_string(title_mode)
else:
title = ''
try:
prop = dapmap.datamodel.full()
except (AttributeError, TypeError):
prop = ''
# get plotparams from datamodel
dapver = dapmap._datamodel.parent.release if dapmap is not None else config.lookUpVersions(
)[1]
params = get_plot_params(dapver, prop)
cmap = kwargs.get('cmap', params['cmap'])
percentile_clip = kwargs.get('percentile_clip', params['percentile_clip'])
symmetric = kwargs.get('symmetric', params['symmetric'])
snr_min = kwargs.get('snr_min', params['snr_min'])
if sigma_clip:
percentile_clip = False
assert (not symmetric) or (
not log_cb), 'Colorbar cannot be both symmetric and logarithmic.'
use_masks = _format_use_masks(use_masks,
mask,
dapmap,
default_masks=params['bitmasks'])
# Create no coverage, bad data, low SNR, and negative value masks.
nocov_conditions = (('NOCOV' in use_masks) or (ivar is not None))
bad_data_conditions = (use_masks and (dapmap is not None)
and (mask is not None))
nocov = _mask_nocov(dapmap, mask, ivar) if nocov_conditions else all_true
bad_data = dapmap.pixmask.get_mask(
use_masks, mask=mask) if bad_data_conditions else all_true
low_snr = mask_low_snr(value, ivar, snr_min) if use_masks else all_true
neg_val = mask_neg_values(value) if log_cb else all_true
# Final masked array to show.
good_spax = np.ma.array(value,
mask=np.logical_or.reduce(
(nocov, bad_data, low_snr, neg_val)))
# setup colorbar
cb_kws['cmap'] = cmap
cb_kws['percentile_clip'] = percentile_clip
cb_kws['sigma_clip'] = sigma_clip
cb_kws['cbrange'] = cbrange
cb_kws['symmetric'] = symmetric
cblabel = cblabel if cblabel is not None else getattr(dapmap, 'unit', '')
if isinstance(cblabel, units.UnitBase):
cb_kws['label'] = cblabel.to_string('latex_inline')
else:
cb_kws['label'] = cblabel
cb_kws['log_cb'] = log_cb
cb_kws = colorbar._set_cb_kws(cb_kws)
cb_kws = colorbar._set_cbrange(good_spax, cb_kws)
if return_cbrange:
return cb_kws['cbrange']
# setup unmasked spaxels
extent = _set_extent(value.shape, sky_coords)
imshow_kws.setdefault('extent', extent)
imshow_kws.setdefault('interpolation', 'nearest')
imshow_kws.setdefault('origin', 'lower')
imshow_kws['norm'] = LogNorm() if log_cb else None
# setup background
nocov_kws = copy.deepcopy(imshow_kws)
nocov_image = np.ma.array(np.ones(value.shape), mask=~nocov.astype(bool))
A8A8A8 = colorbar._one_color_cmap(color='#A8A8A8')
# setup masked spaxels
patch_kws = _set_patch_style(patch_kws, extent=imshow_kws['extent'])
# finish setup of unmasked spaxels and colorbar range
imshow_kws = colorbar._set_vmin_vmax(imshow_kws, cb_kws['cbrange'])
# set hatch color and linewidths (in matplotlib 2.0+)
try:
mpl_rc = {
it: mpl.rcParams[it]
for it in ['hatch.color', 'hatch.linewidth']
}
mpl.rc_context({'hatch.color': 'w', 'hatch.linewidth': '0.5'})
except KeyError as ee:
mpl_rc = {}
with plt.style.context(plt_style):
fig, ax = ax_setup(sky_coords=sky_coords, fig=fig, ax=ax)
# plot hatched regions by putting one large patch as lowest layer
# hatched regions are bad data, low SNR, or negative values if the colorbar is logarithmic
ax.add_patch(mpl.patches.Rectangle(**patch_kws))
# plot regions without IFU coverage as a solid color (gray #A8A8A8)
ax.imshow(nocov_image, cmap=A8A8A8, zorder=1, **nocov_kws)
# plot unmasked spaxels
p = ax.imshow(good_spax, cmap=cb_kws['cmap'], zorder=10, **imshow_kws)
fig, cb = colorbar._draw_colorbar(fig, mappable=p, ax=ax, **cb_kws)
if title is not '':
ax.set_title(label=title)
# restore previous matplotlib rc parameters (as of matplotlib 2.0.2 this
# redraws the hatches with the original rcParam settings)
# mpl.rc_context(mpl_rc)
# turn on to preserve zorder when saving to pdf (or other vector based graphics format)
mpl.rcParams['image.composite_image'] = False
output = (fig, ax) if not return_cb else (fig, ax, cb)
return output
def plot(*args, **kwargs):
"""Make single panel map or one panel of multi-panel map plot.
Parameters:
dapmap (marvin.tools.map.Map):
Marvin Map object. Default is ``None``.
value (array):
Data array. Default is ``None``.
ivar (array):
Inverse variance array. Default is ``None``.
mask (array):
Mask array. Default is ``None``.
cmap (str):
Colormap (see datamodel for defaults).
percentile_clip (tuple-like):
Percentile clip (see datamodel for defaults.
sigma_clip (float):
Sigma clip. Default is ``None``.
cbrange (tuple-like):
If ``None``, set automatically. Default is ``None``.
symmetric (bool):
Draw a colorbar that is symmetric around zero (see datamodel for
default).
snr_min (float):
Minimum signal-to-noise for keeping a valid measurement (see
datamodel for default).
log_cb (bool):
Draw a log normalized colorbar. Default is ``False``.
title (str):
If ``None``, set automatically from property (and channel) name(s).
For no title, set to ''. Default is ``None``.
cblabel (str):
If ``None``, set automatically from unit. For no colorbar label,
set to ''. Default is ``None``.
sky_coords (bool):
If ``True``, show plot in sky coordinates (i.e., arcsec), otherwise
show in spaxel coordinates. Default is ``False``.
use_mask (bool):
Use DAP bitmasks. Default is ``True``.
plt_style (str):
Matplotlib style sheet to use. Default is 'seaborn-darkgrid'.
fig (matplotlib Figure object):
Use if creating subplot of a multi-panel plot. Default is ``None``.
ax (matplotlib Axis object):
Use if creating subplot of a multi-panel plot. Default is ``None``.
imshow_kws (dict):
Keyword args to pass to `ax.imshow
<http://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.imshow.html#matplotlib.axes.Axes.imshow>`_.
Default is ``None``.
cb_kws (dict):
Keyword args to set and draw colorbar. Default is ``None``.
Returns:
fig, ax (tuple):
`matplotlib.figure <http://matplotlib.org/api/figure_api.html>`_,
`matplotlib.axes <http://matplotlib.org/api/axes_api.html>`_
Example:
>>> import marvin.utils.plot.map as mapplot
>>> maps = Maps(plateifu='8485-1901')
>>> ha = maps['emline_gflux_ha_6564']
>>> fig, ax = mapplot.plot(dapmap=ha)
"""
valid_kwargs = ['dapmap', 'value', 'ivar', 'mask', 'cmap', 'percentile_clip', 'sigma_clip',
'cbrange', 'symmetric', 'snr_min', 'log_cb', 'title', 'cblabel', 'sky_coords',
'use_mask', 'plt_style', 'fig', 'ax', 'imshow_kws', 'cb_kws']
assert len(args) == 0, 'Map.plot() does not accept arguments, only keywords.'
for kw in kwargs:
assert kw in valid_kwargs, 'keyword {0} is not valid'.format(kw)
assert ((kwargs.get('percentile_clip', None) is not None) +
(kwargs.get('sigma_clip', None) is not None) +
(kwargs.get('cbrange', None) is not None) <= 1), \
'Only set one of percentile_clip, sigma_clip, or cbrange!'
dapmap = kwargs.get('dapmap', None)
value = kwargs.get('value', None)
ivar = kwargs.get('ivar', None)
mask = kwargs.get('mask', None)
sigma_clip = kwargs.get('sigma_clip', None)
cbrange = kwargs.get('cbrange', None)
log_cb = kwargs.get('log_cb', False)
title = kwargs.get('title', None)
cblabel = kwargs.get('cblabel', None)
sky_coords = kwargs.get('sky_coords', False)
use_mask = kwargs.get('use_mask', True)
plt_style = kwargs.get('plt_style', 'seaborn-darkgrid')
fig = kwargs.get('fig', None)
ax = kwargs.get('ax', None)
imshow_kws = kwargs.get('imshow_kws', {})
cb_kws = kwargs.get('cb_kws', {})
assert (value is not None) or (dapmap is not None), \
'Map.plot() requires specifying ``value`` or ``dapmap``.'
# user-defined value, ivar, or mask overrides dapmap attributes
value = value if value is not None else getattr(dapmap, 'value', None)
ivar = ivar if ivar is not None else getattr(dapmap, 'ivar', None)
mask = mask if mask is not None else getattr(dapmap, 'mask', np.zeros(value.shape, dtype=bool))
title = set_title(title,
property_name=getattr(dapmap, 'property_name', None),
channel=getattr(dapmap, 'channel', None))
# get plotparams from datamodel
dapver = config.lookUpVersions()[1]
prop = _get_prop(title)
params = get_plot_params(dapver, prop)
cmap = kwargs.get('cmap', params['cmap'])
percentile_clip = kwargs.get('percentile_clip', params['percentile_clip'])
symmetric = kwargs.get('symmetric', params['symmetric'])
snr_min = kwargs.get('snr_min', params['snr_min'])
if sigma_clip is not None:
percentile_clip = None
# create no coverage, bad data, low SNR, and log colorbar masks
nocov_mask = no_coverage_mask(value, ivar, mask, params['bitmasks'].get('nocov', None))
badData = params['bitmasks']['badData']
bad_data = bad_data_mask(value, mask, badData) if use_mask else np.zeros(value.shape)
low_snr = low_snr_mask(value, ivar, snr_min) if use_mask else np.zeros(value.shape)
log_cb_mask = log_colorbar_mask(value, log_cb)
# final masked array to show
image = select_good_spaxels(value, nocov_mask, bad_data, low_snr, log_cb_mask)
# setup colorbar
cb_kws['cmap'] = cmap
cb_kws['percentile_clip'] = percentile_clip
cb_kws['sigma_clip'] = sigma_clip
cb_kws['cbrange'] = cbrange
cb_kws['symmetric'] = symmetric
cb_kws['label'] = cblabel if cblabel is not None else getattr(dapmap, 'unit', '')
cb_kws = colorbar.set_cb_kws(cb_kws)
cb_kws = colorbar.set_cbrange(image, cb_kws)
# setup unmasked spaxels
extent = set_extent(value.shape, sky_coords)
imshow_kws.setdefault('extent', extent)
imshow_kws.setdefault('interpolation', 'nearest')
imshow_kws.setdefault('origin', 'lower')
imshow_kws['norm'] = LogNorm() if log_cb else None
# setup background
nocov_kws = copy.deepcopy(imshow_kws)
nocov = np.ma.array(np.ones(value.shape), mask=~nocov_mask)
A8A8A8 = colorbar.one_color_cmap(color='#A8A8A8')
# setup masked spaxels
patch_kws = set_patch_style(extent=extent)
# finish setup of unmasked spaxels and colorbar range
imshow_kws = colorbar.set_vmin_vmax(imshow_kws, cb_kws['cbrange'])
# set hatch color and linewidths (in matplotlib 2.0+)
try:
mpl_rc = {it: mpl.rcParams[it] for it in ['hatch.color', 'hatch.linewidth']}
mpl.rc_context({'hatch.color': 'w', 'hatch.linewidth': '0.5'})
except KeyError as ee:
mpl_rc = {}
with plt.style.context(plt_style):
fig, ax = ax_setup(sky_coords=sky_coords, fig=fig, ax=ax)
# plot hatched regions by putting one large patch as lowest layer
# hatched regions are bad data, low SNR, or negative values if the colorbar is logarithmic
ax.add_patch(mpl.patches.Rectangle(**patch_kws))
# plot regions without IFU coverage as a solid color (gray #A8A8A8)
ax.imshow(nocov, cmap=A8A8A8, zorder=1, **nocov_kws)
# plot unmasked spaxels
p = ax.imshow(image, cmap=cb_kws['cmap'], zorder=10, **imshow_kws)
fig, cb = colorbar.draw_colorbar(fig, mappable=p, ax=ax, **cb_kws)
if title is not '':
ax.set_title(label=title)
# restore previous matplotlib rc parameters (as of matplotlib 2.0.2 this
# redraws the hatches with the original rcParam settings)
# mpl.rc_context(mpl_rc)
# turn on to preserve zorder when saving to pdf (or other vector based graphics format)
mpl.rcParams['image.composite_image'] = False
return fig, ax
def bits(request, set_release):
params = get_plot_params(dapver=config.lookUpVersions()[1],
prop=request.param)
return params['bitmasks']
