Plotting Tutorial¶

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']
ha.plot()

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
spax = maps[17, 17]
spax.flux.plot()

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
# must use Maps.getSpaxel() to get modelcube
# (the bracket slicing of Maps does not return the modelcube)
spax = maps.getSpaxel(x=17, y=17, xyorig='lower', model=True)
# extra arguments to plot are passed to the matplotlib routine
ax = spax.flux.plot(label='observed)
ax.plot(spax.full_fit.wavelength, spax.full_fit.value, label='model')
ax.legend()

import matplotlib.pyplot as plt
from marvin.utils.general.images import showImage
image = showImage(plateifu='8553-12702', show_image=False)
fig, ax = plt.subplots()
ax.imshow(image)
ax.axis('off')

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
masks, fig, axes = maps.get_bpt()

import matplotlib.pyplot as plt
from marvin.tools.maps import Maps
import marvin.utils.plot.map as mapplot
plt.style.use('seaborn-darkgrid')  # set matplotlib style sheet

maps = Maps(plateifu='8485-1901')
stvel = maps['stellar_vel']
ha = maps['emline_gflux_ha_6564']
d4000 = maps['specindex_d4000']

fig, axes = plt.subplots(1, 3, figsize=(15, 4))
for ax, map_ in zip(axes, [stvel, ha, d4000]):
    mapplot.plot(dapmap=map_, fig=fig, ax=ax)

fig.tight_layout()

import matplotlib.pyplot as plt
from marvin.tools.maps import Maps
import marvin.utils.plot.map as mapplot
plt.style.use('seaborn-darkgrid')  # set matplotlib style sheet

plateifus = ['8485-1901', '8485-1902', '8485-12701']
mapnames = ['stellar_vel', 'stellar_sigma']

rows = len(plateifus)
cols = len(mapnames)
fig, axes = plt.subplots(rows, cols, figsize=(8, 12))
for row, plateifu in zip(axes, plateifus):
    maps = Maps(plateifu=plateifu)
    for ax, mapname in zip(row, mapnames):
        mapplot.plot(dapmap=maps[mapname], fig=fig, ax=ax, title=' '.join((plateifu, mapname)))

fig.tight_layout()

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

fig, ax = ha.plot()
ax.axis([13, 21, 13, 21])

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

fig, ax = ha.plot(percentile_clip=(1, 99))
fig, ax = ha.plot(sigma_clip=2)
fig, ax = ha.plot(cbrange=[2, 10])
fig, ax = ha.plot(symmetric=True)
fig, ax = ha.plot(log_cb=True)

import numpy as np
import matplotlib.pyplot as plt
from marvin.tools.maps import Maps
import marvin.utils.plot.map as mapplot

maps = Maps(plateifu='8485-1901')
havel = maps['emline_gvel_ha_6564']
stvel = maps['stellar_vel']
vel_maps = [havel, stvel]

cbranges = [vel_map.plot(return_cbrange=True) for vel_map in vel_maps]
cb_max = np.max(np.abs(cbranges))
cbrange = (-cb_max, cb_max)

fig, axes = plt.subplots(ncols=2, figsize=(10, 4))
for ax, vel_map in zip(axes, vel_maps):
    vel_map.plot(fig=fig, ax=ax, cbrange=cbrange)

fig.tight_layout()

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

# Default is 1 except for velocities, which default to 0.
fig, ax = ha.plot(snr_min=10)

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

# Defaults:
# gray background (facecolor=''#A8A8A8'),
# white lines (edgecolor='w'),
# dense hatching: (hatch= 'xxxx')

# Custom: black background, cyan lines, less dense hatching
fig, ax = ha.plot(patch_kws={'facecolor': 'k',
                             'edgecolor': 'c',
                             'hatch': 'xx'})

import matplotlib.pyplot as plt
from marvin.tools.maps import Maps
plt.style.use('seaborn-darkgrid')  # set matplotlib style sheet

maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

fig = plt.figure()
ax = fig.add_axes([0.12, 0.1, 2 / 3., 5 / 6.])
fig, ax = ha.plot(fig=fig, ax=ax, cb_kws={'axloc': [0.8, 0.1, 0.03, 5 / 6.]})

import matplotlib.pyplot as plt
from marvin.tools.maps import Maps
plt.style.use('seaborn-darkgrid')  # set matplotlib style sheet

maps = Maps(mangaid='1-209232')
spax = maps.getSpaxel(x=0, y=0, xyorig='center', model=True)

fig, ax = plt.subplots()

pObs = ax.plot(spax.flux.wavelength, spax.flux.value)
pModel = ax.plot(spax.full_fit.wavelength, spax.full_fit.value)
pEmline = ax.plot(spax.emline_fit.wavelength, spax.emline_fit.value)
plt.legend(pObs + pEmline + pModel, ['observed', 'emline model', 'model'])

ax.axis([6700, 7100, -0.1, 3])
ax.set_xlabel('observed wavelength [{}]'.format(spax.flux.wavelength.unit.to_string('latex')))
ax.set_ylabel('flux [{}]'.format(spax.flux.unit.to_string('latex')))

import numpy as np
from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']
masks = maps.get_bpt(show_plot=False, return_figure=False)

# Create a bitmask for non-star-forming spaxels by taking the
# complement (`~`) of the BPT global star-forming mask (where True == star-forming)
# and set bit 30 (DONOTUSE) for those spaxels.
mask_non_sf = ~masks['sf']['global'] * ha.pixmask.labels_to_value('DONOTUSE')

# Do a bitwise OR between DAP mask and non-star-forming mask.
mask = ha.mask | mask_non_sf

ha.plot(mask=mask)

from marvin.tools.maps import Maps
maps = Maps(plateifu='8485-1901')
nii_ha = maps.getMapRatio(property_name='emline_gflux', channel_1='nii_6585', channel_2='ha_6564')

# Mask out non-star-forming spaxels
masks, __, __ = maps.get_bpt(show_plot=False)

# Create a bitmask for non-star-forming spaxels by taking the
# complement (`~`) of the BPT global star-forming mask (where True == star-forming)
# and set bit 30 (DONOTUSE) for those spaxels.
mask_non_sf = ~masks['sf']['global'] * ha.pixmask.labels_to_value('DONOTUSE')

# Do a bitwise OR between DAP mask and non-star-forming mask.
mask = nii_ha.mask | mask_non_sf

nii_ha.plot(mask=mask, cblabel='[NII]6585 / Halpha flux ratio')

import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
from marvin.tools.maps import Maps
import marvin.utils.plot.map as mapplot

maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

# divide data into classes
ha_class = np.ones(ha.shape, dtype=int)
ha_class[np.where(ha.value > 5)] = 2
ha_class[np.where(ha.value > 20)] = 3

cmap = ListedColormap(['#104e8b', '#5783ad', '#9fb8d0'])
fig, ax, cb = mapplot.plot(dapmap=ha, value=ha_class, cmap=cmap, cbrange=(0.5, 3.5),
                           title='', cblabel='', return_cb=True)
cb.set_ticks([1, 2, 3])
cb.set_ticklabels(['I', 'II', 'III'])

from marvin.tools.maps import Maps
import marvin.utils.plot.map as mapplot

maps = Maps(plateifu='8485-1901')
ha = maps['emline_gflux_ha_6564']

# Mask spaxels without IFU coverage
# nocov = ha.mask & 2**0
nocov = ha.pixmask.get_mask('NOCOV')

# Mask spaxels with low Halpha flux
low_ha = (ha.value < 6) * ha.pixmask.labels_to_value('DONOTUSE')

# Combine masks using bitwise OR (`|`)
mask = nocov | low_ha

fig, ax = mapplot.plot(dapmap=ha, value=ha.value, mask=mask)