def plot_3d_scatter(self, fig, ax, x, y, z, title='', xlabel='', ylabel='', zlabel='',
title_font={}, axis_font={}, tick_font={}):
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
cmap = plt.cm.jet
h = plt.scatter(x, y, c=z, cmap=cmap)
ax.set_aspect(1./ax.get_data_ratio()) # make axes square
cbar = plt.colorbar(h, orientation='vertical', aspect=30, shrink=0.9)
if xlabel:
ax.set_xlabel(xlabel.replace("_", " "), labelpad=10, **axis_font)
if ylabel:
ax.set_ylabel(ylabel.replace("_", " "), labelpad=10, **axis_font)
if zlabel:
cbar.ax.set_ylabel(zlabel.replace("_", " "), labelpad=10, **axis_font)
if tick_font:
ax.tick_params(**tick_font)
if title:
ax.set_title(title.replace("_", " "), **title_font)
ax.grid(True)
plt.tight_layout()
def plot_stacked_time_series(self, fig, ax, x, y, z, title='', ylabel='',
cbar_title='', title_font={}, axis_font={}, tick_font = {},
**kwargs):
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
z = np.ma.array(z, mask=np.isnan(z))
h = plt.pcolormesh(x, y, z, shading='gouraud', **kwargs)
# h = plt.pcolormesh(x, y, z, **kwargs)
if ylabel:
ax.set_ylabel(ylabel.replace("_", " "), **axis_font)
if title:
ax.set_title(title.replace("_", " "), **title_font)
plt.axis([x.min(), x.max(), y.min(), y.max()])
ax.xaxis_date()
date_list = mdates.num2date(x)
self.get_time_label(ax, date_list)
fig.autofmt_xdate()
ax.invert_yaxis()
cbar = plt.colorbar(h)
if cbar_title:
cbar.ax.set_ylabel(cbar_title, **axis_font)
ax.grid(True)
if tick_font:
ax.tick_params(**tick_font)
plt.tight_layout()
def plot_stacked_time_series_image(self, fig, ax, x, y, z, title='', ylabel='',
cbar_title='', title_font={}, axis_font={}, tick_font = {},
**kwargs):
'''
This plot is a stacked time series that uses NonUniformImage with regualrly spaced ydata from
a linear interpolation. Designed to support FRF ADCP data.
'''
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
# z = np.ma.array(z, mask=np.isnan(z))
h = NonUniformImage(ax, interpolation='bilinear', extent=(min(x), max(x), min(y), max(y)),
cmap=plt.cm.jet)
h.set_data(x, y, z)
ax.images.append(h)
ax.set_xlim(min(x), max(x))
ax.set_ylim(min(y), max(y))
# h = plt.pcolormesh(x, y, z, shading='gouraud', **kwargs)
# h = plt.pcolormesh(x, y, z, **kwargs)
if ylabel:
ax.set_ylabel(ylabel, **axis_font)
if title:
ax.set_title(title, **title_font)
# plt.axis('tight')
ax.xaxis_date()
date_list = mdates.num2date(x)
self.get_time_label(ax, date_list)
fig.autofmt_xdate()
# if invert:
ax.invert_yaxis()
cbar = plt.colorbar(h)
if cbar_title:
cbar.ax.set_ylabel(cbar_title, **axis_font)
ax.grid(True)
if tick_font:
ax.tick_params(**tick_font)
def plot_3d_scatter(self,
fig,
ax,
x,
y,
z,
title='',
xlabel='',
ylabel='',
zlabel='',
title_font={},
axis_font={},
tick_font={}):
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
cmap = plt.cm.jet
h = plt.scatter(x, y, c=z, cmap=cmap)
ax.set_aspect(1. / ax.get_data_ratio()) # make axes square
cbar = plt.colorbar(h, orientation='vertical', aspect=30, shrink=0.9)
if xlabel:
ax.set_xlabel(xlabel.replace("_", " "), labelpad=10, **axis_font)
if ylabel:
ax.set_ylabel(ylabel.replace("_", " "), labelpad=10, **axis_font)
if zlabel:
cbar.ax.set_ylabel(zlabel.replace("_", " "),
labelpad=10,
**axis_font)
if tick_font:
ax.tick_params(**tick_font)
if title:
ax.set_title(title.replace("_", " "), **title_font)
ax.grid(True)
plt.tight_layout()
def plot_stacked_time_series(self,
fig,
ax,
x,
y,
z,
title='',
ylabel='',
cbar_title='',
title_font={},
axis_font={},
tick_font={},
**kwargs):
if not title_font:
title_font = title_font_default
if not axis_font:
axis_font = axis_font_default
z = np.ma.array(z, mask=np.isnan(z))
h = plt.pcolormesh(x, y, z, shading='gouraud', **kwargs)
# h = plt.pcolormesh(x, y, z, **kwargs)
if ylabel:
ax.set_ylabel(ylabel.replace("_", " "), **axis_font)
if title:
ax.set_title(title.replace("_", " "), **title_font)
plt.axis([x.min(), x.max(), y.min(), y.max()])
ax.xaxis_date()
date_list = mdates.num2date(x)
self.get_time_label(ax, date_list)
fig.autofmt_xdate()
ax.invert_yaxis()
cbar = plt.colorbar(h)
if cbar_title:
cbar.ax.set_ylabel(cbar_title)
ax.grid(True)
if tick_font:
ax.tick_params(**tick_font)
plt.tight_layout()
yellorred = brewer2mpl.get_map('YlOrRd','Sequential',9).mpl_colormap
p = ax1.pcolormesh(alphas2,phis2,eps.T,cmap=yellorred, rasterized=True)
ax1.axis([alphas2.min(),alphas2.max(),phis2.min(),phis2.max()])
#xticks = np.arange(alphas.min(),alphas.max(),0.5)
#xlabels = np.arange(alphas.min(),alphas.max(),0.5)-alphas.min()
#yticks = np.arange(phis.min(),phis.max(),0.5)
#ylabels = np.arange(phis.min(),phis.max(),0.5)-phis.min()
#plt.xticks(xticks,xlabels,axes=ax1)
#plt.yticks(yticks,ylabels,axes=ax1)
cb = plt.colorbar(p, ax=ax1)
cb.set_ticks(np.array([0.3,0.4,0.5]))
cb.set_ticklabels(np.array([0.3,0.4,0.5]))
ax1.set_xlabel(r'$\alpha$')
ax1.set_ylabel(r'$\phi$')
ax1.set_title(r'MMSE ($\epsilon$)')
l1,= ppl.plot( alphas, eps[:,10], label=r'$\phi = '+ str(phis[10]-0.001) + r'$',ax=ax2)
ppl.plot( alphas[np.argmin(eps[:,10])], np.min(eps[:,10]), 'o',color=l1.get_color(),ax=ax2)
l2, = ppl.plot( alphas, eps[:,20], label=r'$\phi = '+ str(phis[20]-0.001) + r'$',ax=ax2)
ppl.plot( alphas[np.argmin(eps[:,20])] , np.min(eps[:,20]), 'o',color=l2.get_color(),ax=ax2)
l3, = ppl.plot( alphas, eps[:,30], label=r'$\phi = '+ str(phis[30]-0.001) + r'$',ax=ax2)
ppl.plot( alphas[np.argmin(eps[:,30])] , np.min(eps[:,30]), 'o',color=l3.get_color(),ax=ax2)
l4, = ppl.plot( alphas, eps[:,40], label=r'$\phi = '+ str(phis[40]-0.001) + r'$',ax=ax2)
ppl.plot( alphas[np.argmin(eps[:,40])] , np.min(eps[:,40]), 'o',color=l4.get_color(),ax=ax2)
dalpha = alphas[1]-alphas[0]
dthetas2,alphas2 = np.meshgrid(np.arange(dthetas.min(),dthetas.max()+0.5*ddtheta,ddtheta)-ddtheta/2,
np.arange(alphas.min(),alphas.max()+0.5*dalpha,dalpha)-dalpha/2)
p1 = ax2.pcolormesh(dthetas2,alphas2,dense_eps.T,cmap=yellorred,rasterized=True)
ax2.axis([dthetas2.min(),dthetas2.max(),alphas2.min(),alphas2.max()])
p2 = ax3.pcolormesh(dthetas2,alphas2,sparse_eps.T,cmap=yellorred,rasterized=True)
ax3.axis([dthetas2.min(),dthetas2.max(),alphas2.min(),alphas2.max()])
p3 = ax4.pcolormesh(dthetas2,alphas2,particle_eps.T,cmap=yellorred,rasterized=True)
ax4.axis([dthetas2.min(),dthetas2.max(),alphas2.min(),alphas2.max()])
ticks = np.array([mintotal,(mintotal+maxtotal)/2,maxtotal])
ticklabels = np.round(ticks,decimals=2)
cb1 = plt.colorbar(p1,ax=ax2)
cb1.set_ticks(ticks)
cb1.set_ticklabels(ticklabels)
cb2 = plt.colorbar(p2,ax=ax3)
cb2.set_ticks(ticks)
cb2.set_ticklabels(ticklabels)
cb3 = plt.colorbar(p3,ax=ax4)
cb3.set_ticks(ticks)
cb3.set_ticklabels(ticklabels)
ax4.set_xlabel(r'$\Delta\theta$')
ax4.set_ylabel(r'$\alpha$')
ax3.set_ylabel(r'$\alpha$')
ax2.set_ylabel(r'$\alpha$')
ax3.axes.get_xaxis().set_ticks([])
