def corr_plot(): #What args
""" """
#fig, ax #how to handle these in general 2d
# Maybe it's helpful to have args for top plots (ie ax1,2,3)
ax1 = plt.subplot2grid((5,5), (0,0), colspan=1) # top left
ax1.plot([0,-1], color='black')
ax1.text(.18, -.78, r'$A(\nu_2)$', size=12)
ax1.text(.55, -.35, r'$A(\nu_1)$', size=12)
ax2 = plt.subplot2grid((5,5), (0,1), colspan=4) # top
ax3 = plt.subplot2grid((5,5), (1,0), colspan=1, rowspan=4) #left
ax4 = plt.subplot2grid((5,5), (1, 1), colspan=4, rowspan=4) #main contour
ax4.yaxis.tick_right()
ax4.xaxis.tick_bottom() #remove top xticks
ax4.yaxis.set_label_position('right')
ax4.set_xlabel('x label')
ax4.set_ylabel('y label')
# Replace with real data
x = np.linspace(0, 100*np.pi, 200)
ax2.plot(np.sin(x), color='black')
# Swap x,y to plot correctly on ax3!!
y = np.cos(x)
ax3.plot(y,x, color='black')
# Contour test data
X, Y = np.meshgrid(x, y)
Z = X * Y
ax4.contour(X,Y,Z)
fig = plt.gcf()
fig.suptitle('Title', fontsize=20)
# Hide axis labels
for ax in [ax1, ax2, ax3]:
pu.hide_axis(ax, axis='both', hide_everything = True)
plt.subplots_adjust(hspace = 0, wspace=0)
return (ax1, ax2, ax3, ax4)
def quad_plot(ts, *plotargs, **plotkwds):
""" Output a matplotlib figure with full spectra, absorbance, area and
stripchart. Figure should be plotly convertable through py.iplot_mpl(fig)
assuming one is signed in to plotly through py.sign_in(user, apikey).
Parameters
-----------
title : str
Title of the overall figure
striplegend : bool (False)
Add a legend to the strip chart
colormap : string ('jet')
Colormap applied to full and absorbance spectra.
'Jet' is applid to strip chart regardless.
tight_layout: bool (False)
Calls mpl.fig.tight_layout()
"""
title = plotkwds.pop('title', '')
tight_layout = plotkwds.pop('tight_layout', False)
f, axes = put.splot(2,2, fig=True, figsize=(8,8))
f.suptitle(title, fontsize=20)
if tight_layout:
f.tight_layout()
cmap = plotkwds.pop('colormap', 'jet')
strip_cmap = 'spectral'
striplegend = plotkwds.pop('striplegend', False)
specplot(ts, *plotargs,
ax=axes[0],
title='Spectra',
colormap = cmap,
fig=f, #for colorbar
**plotkwds)
range_timeplot(ts.wavelength_slices(8),
ax=axes[1],
legend=False,
colormap = strip_cmap,
title='Spectral Slices',
**plotkwds)
normplot(ts, *plotargs,
ax=axes[2],
colormap=cmap,
title='Normalized',
**plotkwds)
areaplot(ts, *plotargs,
ax=axes[3],
title='Area',
fig=f,
**plotkwds)
# Custom legend to strip chart (http://matplotlib.org/users/legend_guide.html#multicolumn-legend)
if striplegend:
axes[1].legend(loc='lower center',
ncol=4,
fontsize=5,
# mode='expand',
bbox_to_anchor=(0.5,-0.1))
for a in (axes[1], axes[3]):
a.yaxis.tick_right()
a.yaxis.set_label_position("right")
# Remove y-axis of area/stripchart
put.hide_axis(axes[0], axis='x')
put.hide_axis(axes[1], axis='x')
#axes[1].get_yaxis().set_ticklabels([])#set_visible(False)
#axes[3].get_yaxis().set_ticklabels([])
#axes[0].get_xaxis().set_ticklabels([])
#axes[1].get_xaxis().set_ticklabels([])
return f
def _gencorr2d(xx, yy, zz, a1_label=r'$\bar{A}(\nu_1)$',
a2_label=r'$\bar{A}(\nu_2)$', **contourkwds):
""" Abstract layout for 2d correlation analysis plot.
**contourkwds
Passed directly to _gen2d; includes keywords like xlabel, ylabel
and so forth.
"""
# Maybe this should take X, Y, Z not ts
#fig, ax #how to handle these in general 2d
# Maybe it's helpful to have args for top plots (ie ax1,2,3)
title = contourkwds.pop('title', '')
cbar = contourkwds.pop('cbar', False)
grid = contourkwds.pop('grid', True) #Adds grid to plot and side plots
cbar_nticks = contourkwds.pop('cbar_nticks', 5) #Number ticks in colorbar
contourkwds.setdefault('contours', 20)
contourkwds.setdefault('fill', True)
ax1 = plt.subplot2grid((5,5), (0,0), colspan=1) # top left
plt.subplots_adjust(hspace = 0, wspace=0) # Remove whitespace
ax1.plot([0,-1], color='black')
ax1.text(.18, -.78, a1_label, size=12)
ax1.text(.55, -.35, a2_label, size=12)
ax2 = plt.subplot2grid((5,5), (0,1), colspan=4) # top
ax3 = plt.subplot2grid((5,5), (1,0), colspan=1, rowspan=4) #left
ax4 = plt.subplot2grid((5,5), (1, 1), colspan=4, rowspan=4) #main contour
ax3.invert_xaxis()
ax4.yaxis.tick_right()
ax4.xaxis.tick_bottom() #remove top xticks
ax4.yaxis.set_label_position('right')
ax4, contours = _gen2d(xx, yy, zz, ax=ax4, **contourkwds)
# plt.colorbar(ax4) #oesn't work http://matplotlib.org/examples/pylab_examples/contourf_demo.html
# Bisecting line
ax4.plot(ax4.get_xlim(), ax4.get_ylim(), ls = '--', color='black', linewidth=1)
fig = plt.gcf()
if grid:
ax2.grid()
ax3.grid()
ax4.grid()
# Hide axis labels
for ax in [ax2, ax3]:
if grid:
pu.hide_axis(ax, axis='both', axislabel=True, ticklabels=True)
else:
pu.hide_axis(ax, axis='both', hide_everything = True)
pu.hide_axis(ax1, axis='both', hide_everything=True)
# Handles its own colorbar (See links below; important)
# http://stackoverflow.com/questions/13784201/matplotlib-2-subplots-1-colorbar
# http://matplotlib.org/api/colorbar_api.html#matplotlib.colorbar.make_axes
if cbar:
if cbar in ['left', 'right', 'top', 'bottom']:
# if bottom or right, should repad this
location = cbar
else:
location = 'top'
cax,kw = mplcbar.make_axes([ax1, ax2, ax3, ax4],
location=location,
pad = 0.05,
aspect = 30, #make skinnier
shrink=0.75)
cb = fig.colorbar(contours, cax=cax,**kw)# ticks=[0,zz.max().max()], **kw)
cb.locator = mplticker.MaxNLocator(nbins=cbar_nticks+1) #Cuts off one usually
cb.update_ticks()
fig.suptitle(title, fontsize='large') # Still overpads
return (ax1, ax2, ax3, ax4)
def _gencorr2d(xx,
yy,
zz,
a1_label=r'$\bar{A}(\nu_1)$',
a2_label=r'$\bar{A}(\nu_2)$',
**contourkwds):
""" Abstract layout for 2d correlation analysis plot.
**contourkwds
Passed directly to _gencontour; includes keywords like xlabel, ylabel
and so forth.
"""
# Maybe this should take X, Y, Z not ts
#fig, ax #how to handle these in general 2d
# Maybe it's helpful to have args for top plots (ie ax1,2,3)
title = contourkwds.pop('title', '')
cbar = contourkwds.pop('cbar', False)
grid = contourkwds.pop('grid', True) #Adds grid to plot and side plots
cbar_nticks = contourkwds.pop('cbar_nticks', 5) #Number ticks in colorbar
contourkwds.setdefault('contours', 20)
contourkwds.setdefault('fill', True)
# This will create a fig
ax1 = plt.subplot2grid((5, 5), (0, 0), colspan=1) # top left
plt.subplots_adjust(hspace=0, wspace=0) # Remove whitespace
ax1.plot([0, -1], color='black')
ax1.text(.18, -.78, a1_label, size=12)
ax1.text(.55, -.35, a2_label, size=12)
ax2 = plt.subplot2grid((5, 5), (0, 1), colspan=4) # top
ax3 = plt.subplot2grid((5, 5), (1, 0), colspan=1, rowspan=4) #left
ax4 = plt.subplot2grid((5, 5), (1, 1), colspan=4, rowspan=4) #main contour
ax3.invert_xaxis()
ax4.yaxis.tick_right()
ax4.xaxis.tick_bottom() #remove top xticks
ax4.yaxis.set_label_position('right')
ax4, contours = _gen2d3d(xx, yy, zz, ax=ax4, **contourkwds)
# plt.colorbar(ax4) #oesn't work http://matplotlib.org/examples/pylab_examples/contourf_demo.html
# Bisecting line
ax4.plot(ax4.get_xlim(),
ax4.get_ylim(),
ls='--',
color='black',
linewidth=1)
# Fig is created by _gen2d in ax4 _gen2d3d
fig = plt.gcf()
if grid:
ax2.grid()
ax3.grid()
ax4.grid()
# Hide axis labels
for ax in [ax2, ax3]:
if grid:
pu.hide_axis(ax, axis='both', axislabel=True, ticklabels=True)
else:
pu.hide_axis(ax, axis='both', hide_everything=True)
pu.hide_axis(ax1, axis='both', hide_everything=True)
# Handles its own colorbar (See links below; important)
# http://stackoverflow.com/questions/13784201/matplotlib-2-subplots-1-colorbar
# http://matplotlib.org/api/colorbar_api.html#matplotlib.colorbar.make_axes
if cbar:
if cbar in ['left', 'right', 'top', 'bottom']:
# if bottom or right, should repad this
location = cbar
else:
location = 'top'
cax, kw = mplcbar.make_axes(
[ax1, ax2, ax3, ax4],
location=location,
pad=0.05,
aspect=30, #make skinnier
shrink=0.75)
cb = fig.colorbar(contours, cax=cax,
**kw) # ticks=[0,zz.max().max()], **kw)
cb.locator = mplticker.MaxNLocator(nbins=cbar_nticks +
1) #Cuts off one usually
cb.update_ticks()
fig.suptitle(title, fontsize='large') # Still overpads
return (ax1, ax2, ax3, ax4)
def quad_plot(ts, *plotargs, **plotkwds):
""" Output a matplotlib figure with full spectra, absorbance, area and
stripchart. Figure should be plotly convertable through py.iplot_mpl(fig)
assuming one is signed in to plotly through py.sign_in(user, apikey).
Parameters
-----------
title : str
Title of the overall figure
striplegend : bool (False)
Add a legend to the strip chart
colormap : string ('jet')
Colormap applied to full and absorbance spectra.
'Jet' is applid to strip chart regardless.
tight_layout: bool (False)
Calls mpl.fig.tight_layout()
"""
title = plotkwds.pop('title', '')
tight_layout = plotkwds.pop('tight_layout', False)
f, axes = put.splot(2, 2, fig=True, figsize=(8, 8))
f.suptitle(title, fontsize=20)
if tight_layout:
f.tight_layout()
cmap = plotkwds.pop('colormap', 'jet')
strip_cmap = 'spectral'
striplegend = plotkwds.pop('striplegend', False)
ts.plot(
*plotargs,
ax=axes[0],
title='Spectra',
colormap=cmap,
fig=f, #for colorbar
**plotkwds)
range_timeplot(ts.wavelength_slices(8),
ax=axes[1],
legend=False,
colormap=strip_cmap,
title='Spectral Slices',
**plotkwds)
ts.plot(*plotargs,
iunit='r',
ax=axes[2],
colormap=cmap,
title='Normalized',
**plotkwds)
areaplot(ts, *plotargs, ax=axes[3], title='Area', fig=f, **plotkwds)
# Custom legend to strip chart (http://matplotlib.org/users/legend_guide.html#multicolumn-legend)
if striplegend:
axes[1].legend(
loc='lower center',
ncol=4,
fontsize=5,
# mode='expand',
bbox_to_anchor=(0.5, -0.1))
for a in (axes[1], axes[3]):
a.yaxis.tick_right()
a.yaxis.set_label_position("right")
# Remove y-axis of area/stripchart
put.hide_axis(axes[0], axis='x')
put.hide_axis(axes[1], axis='x')
#axes[1].get_yaxis().set_ticklabels([])#set_visible(False)
#axes[3].get_yaxis().set_ticklabels([])
#axes[0].get_xaxis().set_ticklabels([])
#axes[1].get_xaxis().set_ticklabels([])
return f
