def precision_at_percentages(test_labels, test_predictions, title='Precision at various percentages'):
'''
Plots precision for various percent values
'''
percents = [0.01 * i for i in range(1, 101)]
precs_and_cutoffs = [precision_at(test_labels, test_predictions, percent=p) for p in percents]
precs, cutoffs = zip(*precs_and_cutoffs)
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot(percents, precs)
ax.set_title(title)
ax.set_ylabel('Precision')
ax.set_xlabel('Percentage')
return fig
def precision_at_proportions(y_true, y_score, ax=None, **kwargs):
'''
Plots precision for various proportions
'''
#If not Axes object is passed use the current one in pyplot
if ax is None:
ax = plt.gca()
#Calculate points
proportions = [0.01 * i for i in range(1, 101)]
precs_and_cutoffs = [precision_at(y_true, y_score, proportion=p) for p in proportions]
precs, cutoffs = zip(*precs_and_cutoffs)
#Plot and set nice defaults for title and axis labels
ax.plot(proportions, precs, **kwargs)
ax.set_title('Precision at various proportions')
ax.set_ylabel('Precision')
ax.set_xlabel('Proportion')
return ax
def precision_at_proportions(test_labels, test_predictions, ax=None, **kwargs):
'''
Plots precision for proportions between 0.1 and 1.0
'''
#If not Axes object is passed use the current one in pyplot
if ax is None:
ax = plt.gca()
#Calculate points
percents = [0.01 * i for i in range(1, 101)]
precs_and_cutoffs = [precision_at(test_labels, test_predictions, percent=p) for p in percents]
precs, cutoffs = zip(*precs_and_cutoffs)
#Plot and set nice defaults for title and axis labels
ax.plot(percents, precs, **kwargs)
ax.set_title('Precision at various proportions')
ax.set_ylabel('Precision')
ax.set_xlabel('Proportion')
return ax
def precision_at_proportions(test_labels, test_predictions, ax=None, **kwargs):
'''
Plots precision for proportions between 0.1 and 1.0
'''
#If not Axes object is passed use the current one in pyplot
if ax is None:
ax = plt.gca()
#Calculate points
percents = [0.01 * i for i in range(1, 101)]
precs_and_cutoffs = [
precision_at(test_labels, test_predictions, percent=p)
for p in percents
]
precs, cutoffs = zip(*precs_and_cutoffs)
#Plot and set nice defaults for title and axis labels
ax.plot(percents, precs, **kwargs)
ax.set_title('Precision at various proportions')
ax.set_ylabel('Precision')
ax.set_xlabel('Proportion')
return ax
