def make_pretty_generation_plot(filename, generations, lines_to_plot, x_axis_name, legend_labels, y_errorbar=None, y_logscale = False, vline_x = [], save_figure = True):
if y_errorbar:
assert isinstance(y_errorbar, list), "Please provide a list for error bars"
assert len(y_errorbar) == len(lines_to_plot), "When plotting error bars you must specify an array of error bars for each line that is plotted"
cmap = brewer2mpl.get_map('Set1', 'qualitative', 9)
p = Ppl(cmap, alpha=1)
fig, ax = plt.subplots(1)
ax.set_xlabel('Generation')
ax.set_ylabel(x_axis_name)
if y_logscale:
ax.set_yscale('log')
plt.grid(b=True, which='both', axis='y', color='0.65',linestyle='dashed')
legend_labels = map(lambda s: s + ' (log)', legend_labels)
else: ax.yaxis.get_major_formatter().set_powerlimits((0, 1))
for i, (series, label) in enumerate(zip(lines_to_plot, legend_labels)):
p.plot(ax, generations, series, linewidth=2, label=label, zorder=2)
if y_errorbar:
for i, (series, label) in enumerate(zip(lines_to_plot, legend_labels)):
ax.errorbar(generations, series, yerr=y_errorbar[i], zorder=1, capsize=2, barsabove=True, ecolor = errorbar_color)
if vline_x:
for x in vline_x:
ax.vlines(x = x, ymin = ax.get_ylim()[0], ymax = ax.get_ylim()[1], linewidth = 1, linestyles = 'dashed', alpha = 0.5)
p.legend(ax, loc=0)
if save_figure: fig.savefig(filename)
return fig, ax, filename
def get_pretty_xy_plot(x, y, xlabel, ylabel, filename, y_errorbar=None, save_figure = True):
cmap = brewer2mpl.get_map('Set1', 'qualitative', 9)
p = Ppl(cmap, alpha=1)
fig, ax = plt.subplots(1)
ax.set_xlabel(pfn(xlabel))
ax.set_ylabel(pfn(ylabel))
ax.yaxis.get_major_formatter().set_powerlimits((0, 1))
print "Errorbar: %s"%y_errorbar
if y_errorbar is not None: ax.errorbar(x, y, yerr=y_errorbar, fmt='o')
p.plot(ax, x, y, linewidth=2,)
if save_figure: fig.savefig(filename)
return ax, fig
def multiline_xy_plot(x, ys, xlabel, ylabel, legend_labels, filename, y_errorbars=None, save_figure = True):
assert isinstance(ys, list)
cmap = brewer2mpl.get_map('Set1', 'qualitative', 9)
p = Ppl(cmap, alpha=1)
fig, ax = plt.subplots(1)
ax.set_xlabel(fl(xlabel))
ax.set_ylabel(fl(ylabel))
ax.yaxis.get_major_formatter().set_powerlimits((0, 1))
for i, y in enumerate(ys):
#print "Errorbar: %s"%y_errorbar
#if y_errorbars is not None: ax.errorbar(x, y, yerr=y_errorbar, fmt='o')
#print legend_labels[i]
p.plot(ax, x, y, linewidth=2, label = legend_labels[i])
p.legend(ax, loc=0, frameon = False)
if save_figure: fig.savefig(filename)
return ax, fig
def make_pretty_tradeprice_plot(rounds, prices, filename, format = 'png', **figargs):
from settings import default_parameters as dp
cmap = brewer2mpl.get_map('Set1', 'qualitative', 9)
p = Ppl(cmap, alpha=1)
fig = plt.figure(num=None, **figargs)
ax = fig.add_subplot(1,1,1)
#fig, ax = plt.subplots(1)
"""
if kwargs.has_key('dpi'):
fig.set_dpi(kwargs['dpi'])
if kwargs.has_key('figwidth'):
fig.set_figwidth(kwargs['figwidth'])
if kwargs.has_key('figheight'):
fig.set_figheight(kwargs['figheight'])
"""
p.plot(ax, rounds, prices, zorder=1)
#ax.yaxis.get_major_formatter().set_powerlimits((0, 1))
### Plotting statbility margins
fas = get_fundamental_after_shock()
ax.hlines(y = [fas - settings.stability_margin, fas + settings.stability_margin], xmin=0, xmax=settings.n_simulation_rounds, linestyles = 'dashed')
### Plotting fundamental step function
y = [dp['fundamental_initial_value'], dp['fundamental_initial_value'] + dp['fundamental_shock_size'], ]
xmin = [0, dp['fundamental_shock_round']]
xmax = [dp['fundamental_shock_round'], settings.n_simulation_rounds]
ax.hlines(y, xmin, xmax, linestyles = 'solid', colors='black', linewidth=2, zorder=2)
ax.vlines(x = dp['fundamental_shock_round'], ymin=dp['fundamental_initial_value'] + dp['fundamental_shock_size'], ymax = dp['fundamental_initial_value'], colors='black', linewidth=2, zorder=3)
ax.set_ylabel('Traded price (ticks)')
ax.set_xlabel('Time (rounds)')
ax.set_xlim([0, max(rounds)])
ax.set_ylim([min(fas - settings.stability_margin-2, min(prices)), max(fas + settings.stability_margin, max(prices))])
fig.savefig(filename)
plt.close()
gc.collect()