Merge pull request #317 from adonath/astropy_style_docs_plots

Using consistent plotting style in docs

docs/astro/population/plot_radial_distributions.py

@@ -6,16 +6,15 @@
 
 max_radius = 20  # kpc
 r = np.linspace(0, max_radius, 100)
-colors = ['b', 'k', 'k', 'b', 'g', 'g']
 
-for color, key in zip(colors, radial_distributions):
+for key in radial_distributions:
     model = radial_distributions[key]()
     if model.evolved:
         linestyle = '-'
     else:
         linestyle = '--'
     label = model.__class__.__name__
-    plt.plot(r, normalize(model, 0, max_radius)(r), color=color, linestyle=linestyle, label=label)
+    plt.plot(r, normalize(model, 0, max_radius)(r), linestyle=linestyle, label=label)
 plt.xlim(0, max_radius)
 plt.ylim(0, 0.28)
 plt.xlabel('Galactocentric Distance [kpc]')

docs/astro/population/plot_velocity_distributions.py

@@ -6,12 +6,11 @@
 
 v_min, v_max = 10, 3000  # km / s
 v = np.linspace(v_min, v_max, 200)
-colors = ['b', 'k', 'g']
 
-for color, key in zip(colors, velocity_distributions):
+for key in velocity_distributions:
     model = velocity_distributions[key]()
     label = model.__class__.__name__
-    plt.plot(v, normalize(model, v_min, v_max)(v), color=color, linestyle='-', label=label)
+    plt.plot(v, normalize(model, v_min, v_max)(v), linestyle='-', label=label)
 
 plt.xlim(v_min, v_max)
 plt.ylim(0, 0.004)

docs/astro/source/plot_pulsar_spindown.py

@@ -6,7 +6,7 @@
 
 t = Quantity(np.logspace(0, 6, 100), 'yr')
 pulsar = Pulsar(P_0=Quantity(0.01, 's'), logB=12)
-plt.plot(t.value, 1 / pulsar.period(t).cgs.value, color='b')
+plt.plot(t.value, 1 / pulsar.period(t).cgs.value)
 plt.xlabel('time [years]')
 plt.ylabel('frequency [1/s]')
 plt.ylim(1E0, 1E2)

docs/astro/source/plot_snr_brightness_evolution.py

@@ -5,16 +5,15 @@
 from gammapy.astro.source import SNR
 
 densities = Quantity([1, 0.1], 'cm^-3')
-colors = ['b', 'g']
 
 t = Quantity(np.logspace(0, 5, 100), 'yr')
 
-for color, density in zip(colors, densities):
+for density in densities:
     snr = SNR(n_ISM=density)
     F = snr.luminosity_tev(t) / (4 * np.pi * Quantity(1, 'kpc') ** 2)
-    plt.plot(t.value, F.to('ph s^-1 cm^-2').value, color=color, label='n_ISM = {0}'.format(density.value))
-    plt.vlines(snr.sedov_taylor_begin.to('yr').value, 1E-13, 1E-10, linestyle='--', color=color)
-    plt.vlines(snr.sedov_taylor_end.to('yr').value, 1E-13, 1E-10, linestyle='--', color=color)
+    plt.plot(t.value, F.to('ph s^-1 cm^-2').value, label='n_ISM = {0}'.format(density.value))
+    plt.vlines(snr.sedov_taylor_begin.to('yr').value, 1E-13, 1E-10, linestyle='--')
+    plt.vlines(snr.sedov_taylor_end.to('yr').value, 1E-13, 1E-10, linestyle='--')
 plt.xlim(1E2, 1E5)
 plt.ylim(1E-13, 1E-10)
 plt.xlabel('time [years]')

docs/astro/source/plot_snr_radius_evolution.py

@@ -7,15 +7,14 @@
 snr_models = [SNR, SNRTrueloveMcKee]
 densities = Quantity([1, 0.1], 'cm^-3')
 linestyles = ['-', '--']
-colors = ['b', 'g']
 t = Quantity(np.logspace(0, 5, 100), 'yr')
 
-for color, density in zip(colors, densities):
+for density in densities:
     for linestyle, snr_model in zip(linestyles, snr_models):
         snr = snr_model(n_ISM=density)
         plt.plot(t.value, snr.radius(t).to('pc').value,
                  label=snr.__class__.__name__ + ' (n_ISM = {0})'.format(density.value),
-                 linestyle=linestyle, color=color)
+                 linestyle=linestyle)
 plt.xlabel('time [years]')
 plt.ylabel('radius [pc]')
 plt.legend(loc=4)

docs/background/plot_bgcube.py

@@ -10,18 +10,20 @@
 bg_model = CubeBackgroundModel.read(filename, format='table')
 
 fig, axes = plt.subplots(nrows=1, ncols=3)
-fig.set_size_inches(30., 8., forward=True)
+fig.set_size_inches(20, 6., forward=True)
 
 # plot images
 bg_model.plot_image(energy=Quantity(0.5, 'TeV'), ax=axes[0], style_kwargs=dict(norm=LogNorm()))
 bg_model.plot_image(energy=Quantity(50., 'TeV'), ax=axes[1], style_kwargs=dict(norm=LogNorm()))
 
 # plot spectra
 bg_model.plot_spectrum(det=Angle([0., 0.], 'degree'), ax=axes[2],
-                       style_kwargs=dict(color='blue', label='(0, 0) deg'))
+                       style_kwargs=dict(label='(0, 0) deg'))
 bg_model.plot_spectrum(det=Angle([2., 2.], 'degree'), ax=axes[2],
-                       style_kwargs=dict(color='red', label='(2, 2) deg'))
+                       style_kwargs=dict(label='(2, 2) deg'))
 axes[2].set_title('')
 axes[2].legend()
+axes[2].set_aspect(0.4)
 
+plt.tight_layout()
 plt.show()

docs/conf.py

@@ -42,6 +42,12 @@
 from astropy_helpers.sphinx.conf import *
 from astropy.extern import six
 
+# Use the gamapy style when building docs
+from gammapy.utils.mpl_style import gammapy_mpl_style
+
+plot_rcparams = gammapy_mpl_style
+plot_apply_rcparams = True
+
 # Get configuration information from setup.cfg
 from distutils import config
 conf = config.ConfigParser()

docs/image/colormap_example.py

@@ -17,7 +17,7 @@
 
 # Plot with the HESS and Milagro colormap
 vmin, vmax, vtransition = -5, 15, 5
-plt.figure(figsize=(8, 4))
+plt.figure(figsize=(12, 6))
 
 normalize = ImageNormalize(vmin=vmin, vmax=vmax, stretch=LinearStretch())
 transition = normalize(vtransition)
@@ -26,14 +26,14 @@
 cmap = colormap_hess(transition=transition)
 plt.imshow(image, cmap=cmap, norm=normalize)
 plt.axis('off')
-plt.colorbar()
+plt.colorbar(shrink=0.7)
 plt.title('HESS-style colormap')
 
 plt.subplot(122)
 cmap = colormap_milagro(transition=transition)
 plt.imshow(image, cmap=cmap, norm=normalize)
 plt.axis('off')
-plt.colorbar()
+plt.colorbar(shrink=0.7)
 plt.title('MILAGRO-style colormap')
 
 plt.show()

docs/irf/plot_fermi_psf.py

@@ -9,6 +9,8 @@
 filename = FermiGalacticCenter.filenames()['psf']
 fermi_psf = EnergyDependentTablePSF.read(filename)
 
+plt.figure(figsize=(6, 6))
+
 energies = Quantity([1], 'GeV')
 for energy in energies:
     psf = fermi_psf.table_psf_at_energy(energy=energy)

docs/tutorials/background/source_diffuse_estimation.py

@@ -47,6 +47,7 @@
 n_iterations = 4
 
 # *** RUN & PLOT ***
+plt.figure(figsize=(8, 4))
 
 for iteration in range(n_iterations):
     ibe.run_iteration()
@@ -71,4 +72,4 @@
     plt.title('Significance Image, Iteration {0}'.format(iteration),
               fontsize='small')
 
-plt.tight_layout()
+plt.subplots_adjust(wspace=0.05, hspace=0.05, left=0.05, right=0.95)

gammapy/background/models.py

@@ -655,7 +655,7 @@ def plot_image(self, energy, ax=None, style_kwargs=None):
         #import IPython; IPython.embed()
 
         if not 'cmap' in style_kwargs:
-            style_kwargs['cmap'] = 'afmhot'
+            style_kwargs['cmap'] = 'gist_heat'
 
         image = ax.imshow(data.value,
                           extent=extent.value,

gammapy/image/plotting.py

@@ -652,7 +652,7 @@ def illustrate_colormap(cmap, **kwargs):
     import matplotlib.pyplot as plt
     cmap = plt.cm.get_cmap(cmap)
     cmap_gray = grayify_colormap(cmap, **kwargs)
-    figure = plt.figure(figsize=(6, 4))
+    figure = plt.figure(figsize=(8, 6))
     v = np.linspace(0, 1, 4 * cmap.N)
 
     # Show colormap
@@ -673,9 +673,9 @@ def illustrate_colormap(cmap, **kwargs):
 
     # Plot RGB profiles
     plot_rgb = figure.add_axes([0.1, 0.1, 0.8, 0.6])
-    plot_rgb.plot(v, [cmap(_)[0] for _ in v], color='r')
-    plot_rgb.plot(v, [cmap(_)[1] for _ in v], color='g')
-    plot_rgb.plot(v, [cmap(_)[2] for _ in v], color='b')
+    plot_rgb.plot(v, [cmap(_)[0] for _ in v], color='#A60628')
+    plot_rgb.plot(v, [cmap(_)[1] for _ in v], color='#467821')
+    plot_rgb.plot(v, [cmap(_)[2] for _ in v], color='#348ABD')
     plot_rgb.plot(v, [cmap_gray(_)[0] for _ in v], color='k', linestyle='--')
     plot_rgb.set_ylabel('Luminance')
     plot_rgb.set_ylim(-0.005, 1.005)

gammapy/irf/effective_area_table.py

@@ -312,8 +312,8 @@ def plot_area_vs_energy(self, filename=None, show_save_energy=True):
         plt.xlim(0.1, 100)
         plt.ylim(1E3, 1E7)
         plt.loglog()
-        plt.xlabel('Energy [TeV]')
-        plt.ylabel('Effective Area [m^2]')
+        plt.xlabel('Energy (TeV)')
+        plt.ylabel('Effective Area (m2)')
         if filename is not None:
             plt.savefig(filename)
             log.info('Wrote {0}'.format(filename))
@@ -392,6 +392,9 @@ class EffectiveAreaTable2D(object):
         from gammapy.datasets import load_aeff2D_fits_table
         aeff2D = EffectiveAreaTable2D.from_fits(load_aeff2D_fits_table())
         aeff2D.plot_energy_dependence()
+        plt.loglog()
+        plt.xlim(0.8, 100)
+        plt.ylim(2E4, 2E6)
 
     """
 
@@ -566,7 +569,7 @@ def plot_energy_dependence(self, ax=None, offset=None, energy=None, **kwargs):
 
         plt.xlabel('Energy ({0})'.format(self.energy.unit))
         plt.ylabel('Effective Area ({0})'.format(self.eff_area.unit))
-        plt.legend()
+        plt.legend(loc='lower right')
 
         return ax
 

gammapy/irf/psf_analytical.py

@@ -254,9 +254,9 @@ def plot_containment(self, fraction, filename=None, show_save_energy=True):
         # Set up and compute data
         containment = self._containment_radius_array(self.energy_hi, self.theta, fraction)
         # Plotting
-        plt.figure(figsize=(8, 5))
+        plt.figure(figsize=(8, 6))
         plt.imshow(containment.value, origin='lower', interpolation='None',
-                   vmin=0.05, vmax=0.3)
+                   vmin=0.1, vmax=0.2)
 
         if show_save_energy:
             # Log scale transformation for position of energy threshold
@@ -269,14 +269,14 @@ def plot_containment(self, fraction, filename=None, show_save_energy=True):
             plt.text(x + 0.5, 0, 'Safe energy threshold: {0:3.2f}'.format(self.energy_thresh_lo))
 
         # Axes labels and ticks, colobar
-        plt.xlabel('E [TeV]')
-        xticks = ["{0:3.2g}".format(_) for _ in self.energy_hi.value]
-        plt.xticks(np.arange(len(self.energy_hi)) + 0.5, xticks, size=9)
-        plt.ylabel('Theta [deg]')
+        plt.xlabel('E (TeV)')
+        xticks = ["{0:3.2g}".format(_) for _ in self.energy_hi.value[:-1]]
+        plt.xticks(np.arange(len(self.energy_hi)), xticks, size=9)
+        plt.ylabel('Theta (deg)')
         yticks = ["{0:3.2g}".format(_) for _ in self.theta.value]
         plt.yticks(np.arange(len(self.theta)), yticks, size=9)
         cbar = plt.colorbar(fraction=0.1, pad=0.01)
-        cbar.set_label('Containment radius R{0:.0f} [deg]'.format(100 * fraction),
+        cbar.set_label('Containment radius R{0:.0f} (deg)'.format(100 * fraction),
                         labelpad=20)
 
         if filename is not None:

gammapy/utils/__init__.py

@@ -7,3 +7,4 @@
 `gammapy.utils.random` or `gammapy.utils.wcs`.
 Importing `gammapy.utils` directly is not useful.
 """
+from .mpl_style import gammapy_mpl_style

gammapy/utils/mpl_style.py

@@ -0,0 +1,22 @@
+# Licensed under a 3-clause BSD style license - see LICENSE.rst
+
+from astropy.visualization import astropy_mpl_style
+
+__all__ = ['gammapy_mpl_style']
+
+gammapy_mpl_style = astropy_mpl_style
+"""
+Gammapy matplotlib plotting style.
+"""
+
+gammapy_mpl_style['axes.color_cycle'] = [
+                                        '#E24A33',   # orange
+                                        '#348ABD',   # blue
+                                        '#467821',   # green
+                                        '#A60628',   # red
+                                        '#7A68A6',   # purple
+                                        '#CF4457',   # pink
+                                        '#188487'    # turquoise
+                                        ]
+gammapy_mpl_style['interactive'] = False
+gammapy_mpl_style['axes.labelcolor'] = '#565656'