def plot(t_P, q, system, gens, mode_nums=None, verbose=False, tc="x", xmin=False, xmax=False, ymin=False, ymax=False):
""" a wrapper for plotting routines we'll use a lot """
n_l_m = system.network.nlm
ans = []
### amp-time
if verbose:
print "amp_time"
fig, ax = nmp.amp_plot(t_P, q, n_l_m=n_l_m, mode_nums=mode_nums)
ax.set_ylabel(r"$|" + tc + "_i|$")
ax.set_xlabel(r"$t/P_{\mathrm{orb}}$")
if ymin:
ax.set_ylim(ymin=ymin)
if ymax:
ax.set_ylim(ymax=ymax)
if xmin:
ax.set_xlim(xmin=xmin)
if xmax:
ax.set_xlim(xmax=xmax)
ans.append((fig, ax))
### multi-gen-amp-time
if verbose:
print "multi-gen_amp_time"
fig, axs = nmp.multi_gen_amp_plot(t_P, q, gens, n_l_m=n_l_m, mode_nums=mode_nums)
for ax in axs:
ax.set_ylabel(r"$|" + tc + "|$")
ax.set_xlabel(r"$t/P_{\mathrm{orb}}$")
if ymin:
ax.set_ylim(ymin=ymin)
if ymax:
ax.set_ylim(ymax=ymax)
if xmin:
ax.set_xlim(xmin=xmin)
if xmax:
ax.set_xlim(xmax=xmax)
ans.append((fig, axs))
### coupling diagrams
colormap = nmd.plt.get_cmap("jet")
### nl-placement disp
if verbose:
print "nl-placmenet disp"
myE = -np.array([np.mean(_) for _ in nms.viscous_disp(q, network, Eo=1.0)[-1]])
mode_colors = [colormap(_) for _ in myE]
mode_order = myE.argsort()
fig = nmd.plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.750, 0.8])
cbax = fig.add_axes([0.875, 0.1, 0.025, 0.8])
fig, ax = nmd.coupling_tree_nl(
system,
tree_type="placement",
genNos=[],
verbose=verbose,
mode_colors=mode_colors,
mode_order=mode_order,
fig_ax=(fig, ax),
mode_nums=mode_nums,
)
# colorbar = nmd.matplotlib.colorbar.ColorbarBase(cbax, cmap=colormap, orientation='vertical', norm=nmd.matplotlib.colors.LogNorm())
colorbar = nmd.matplotlib.colorbar.ColorbarBase(cbax, cmap=colormap, orientation="vertical")
colorbar.ax.set_ylabel(r"$\gamma_i A_i^2/\mathrm{max}\{\gamma_i A_i^2\}$")
ans.append((fig, ax, colorbar))
### nl-placement E
if verbose:
print "nl-placement E"
mE = np.array([np.mean(_) for _ in nms.compute_E(q, Eo=1.0)])
mode_colors = [colormap(_) for _ in mE / max(mE)]
mode_order = mE.argsort()
fig = nmd.plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.750, 0.8])
cbax = fig.add_axes([0.875, 0.1, 0.025, 0.8])
fig, ax = nmd.coupling_tree_nl(
system,
tree_type="placement",
genNos=[],
verbose=verbose,
mode_colors=mode_colors,
mode_order=mode_order,
fig_ax=(fig, ax),
mode_nums=mode_nums,
)
# colorbar = nmd.matplotlib.colorbar.ColorbarBase(cbax, cmap=colormap, orientation='vertical', norm=nmd.matplotlib.colors.LogNorm())
colorbar = nmd.matplotlib.colorbar.ColorbarBase(cbax, cmap=colormap, orientation="vertical")
colorbar.ax.set_ylabel(r"$A_i^2/\mathrm{max}\{A_i^2\}$")
ans.append((fig, ax, colorbar))
### nl-siblings gens
for genNo in xrange(1, len(gens)):
if verbose:
print "nl-siblings gen%d" % genNo
fig, ax = nmd.coupling_tree_nl(
system, tree_type="siblings", genNos=[genNo], verbose=verbose, mode_nums=mode_nums
)
ans.append((fig, ax))
return ans
##################################################
if plots:
if opts.tag:
opts.tag += "_"
rt_P1 = [t/system1.Porb for t in rt]
n_l_m = [(n,l,m) for (n,l,m,s), i, j in common_nlms]
if opts.verbose: print "generating plots"
###
if opts.res: # plot the residuals
if opts.verbose: print "\tres"
fig, ax = nmp.amp_plot(rt_P1, r, n_l_m=n_l_m)
ax.set_xlabel(r"$t/P_{\mathrm{orb}}^1$")
ax.set_ylabel(r"$|r_i|$")
ax.grid(opts.grid)
if not opts.no_legend:
ax.legend()
figname = "%s/%sres.png" % (opts.output_dir, opts.tag)
if opts.verbose: print "saving %s" % figname
fig.savefig(figname)
nmp.plt.close(fig)
###
if opts.cross_correlation: # compute the cross-correlation between the data. This should be like function of the relative -time between sample points
