def production_envelope(self,
dataframe,
grid=None,
width=None,
height=None,
title=None,
points=None,
points_colors=None,
palette=None,
x_axis_label=None,
y_axis_label=None):
palette = self.get_option('palette') if palette is None else palette
width = self.get_option('width') if width is None else width
colors = self._palette(palette, len(dataframe.strain.unique()))
plot = aes(data=dataframe,
ymin="lb",
ymax="ub",
x="value",
color=scale_colour_manual(colors)) + geom_area()
if title:
plot += geom_tile(title)
if x_axis_label:
plot += scale_x_continuous(name=x_axis_label)
if y_axis_label:
plot += scale_y_continuous(name=y_axis_label)
return plot
def plot(self, what='cumulative_payouts', include_ci=True):
import ggplot as gg #This is hacky ... need to DRY out the imports
if what == 'cumulative_payouts':
plt = self._plot_cumulative_payouts(include_ci=include_ci)
elif what == 'avg_accuracy':
plt = self._plot_avg_accuracy(include_ci=include_ci)
elif what == 'all':
summary = self.summary()
p1 = self._plot_cumulative_payouts(include_ci=include_ci, summary=summary)
p2 = self._plot_avg_accuracy(include_ci=include_ci, summary=summary)
d1 = p1.data
d2 = p2.data
d1['Outcome'] = d1['AverageCumulativePayout']
d2['Outcome'] = d2['AverageAccuracy']
d1['Plot'] = 'Cumulative Payouts'
d2['Plot'] = 'Average Accuracy'
df = d1.append(d2, ignore_index=True)
if include_ci:
plt = gg.ggplot(gg.aes(x='Round', y='Outcome', ymin='ymin', ymax='ymax'), data=df) + \
gg.geom_area(alpha=0.5)
else:
plt = gg.ggplot(gg.aes(x='Round', y='Outcome'), data=df)
plt += gg.facet_grid('Plot', scales='free')
else:
raise ValueError('%s is not a valid option' % what)
return plt + gg.geom_line()
def area_chart(self, conn, column1 , column2, table_chosen, title):
data_df = dfile.double_selector(conn=conn, table=table_chosen, col1=column1, col2=column2)
ymin = float(input("Enter the minimum value that should be plotted: "))
ymax = float(input("Enter the maximum value that should be plotted: "))
area_plot = ggplot(aes(x=column2, ymin=ymin, ymax=ymax), data=data_df) + geom_area() + theme_gray() + labs(
title=title)
print(area_plot)
def _plot_cumulative_payouts(self, include_ci=True, summary=None):
import ggplot as gg
if summary is None:
summary = self.summary()
df = pd.DataFrame({'AverageCumulativePayout': summary['CumulativePayout']['Avg'],
'Std': summary['CumulativePayout']['Std'],
'Round': range(self.n_rounds)})
if include_ci:
df['ymin'] = df.AverageCumulativePayout - 1.96 * df.Std
df['ymax'] = df.AverageCumulativePayout + 1.96 * df.Std
plt = gg.ggplot(gg.aes(x='Round', y='AverageCumulativePayout', ymin='ymin', ymax='ymax'), data=df) + \
gg.geom_area(alpha=0.5)
else:
plt = gg.ggplot(gg.aes(x='Round', y='AverageCumulativePayout'), data=df)
return plt + gg.geom_line()
def _plot_avg_accuracy(self, include_ci=True, summary=None):
import ggplot as gg
if summary is None:
summary = self.summary()
df = pd.DataFrame({'AverageAccuracy': summary['Accuracy']['Avg'], 'Round': range(self.n_rounds)})
if include_ci:
from scipy import stats
succ = df.AverageAccuracy * self.n_sim
fail = self.n_sim - succ
interval = stats.beta(succ + 1, fail + 1).interval(0.95)
df['ymin'] = interval[0]
df['ymax'] = interval[1]
plt = gg.ggplot(gg.aes(x='Round', y='AverageAccuracy', ymin='ymin', ymax='ymax'), data=df) + \
gg.geom_area(alpha=0.5)
else:
plt = gg.ggplot(gg.aes(x='Round', y='AverageAccuracy'), data=df)
return plt + gg.geom_line()
