def signature_data_plot(sd):
import ggplot as gg
aes = gg.aes(x='set_exp', y='not_exp', color='pearson_r')
return gg.ggplot(aes, data=sd) \
+ gg.geom_point(size=15) \
+ gg.scale_color_gradient(low='yellow', high='red') \
+ gg.scale_x_log() + gg.scale_x_continuous(limits=(0.5, 10000)) \
+ gg.scale_y_log() + gg.scale_y_continuous(limits=(0.05, 10000))
def signature_data_plot(sd):
import ggplot as gg
aes = gg.aes(x='set_exp', y='not_exp', color='pearson_r')
return gg.ggplot(aes, data=sd) \
+ gg.geom_point(size=15) \
+ gg.scale_color_gradient(low='yellow', high='red') \
+ gg.scale_x_log() + gg.scale_x_continuous(limits=(0.5, 10000)) \
+ gg.scale_y_log() + gg.scale_y_continuous(limits=(0.05, 10000))
data = []
for method in methods:
for model in models:
for rtol in rtols:
print('method: {} model: {} rtol: {}'.format(method.name, model.name, rtol), end='')
# Run
tic = time.time()
result = method(model, rtol)
toc = time.time() - tic
# Compare to gold standard
standard = gold_standards[model.name]
diff = result - standard.values
max_rel_diff = np.max(diff/standard.max)
# Append to table
record = (method.name, model.name, rtol, max_rel_diff, toc)
print(' err: {} toc: {}'.format(max_rel_diff, toc))
data.append(record)
data = DataFrame(data, columns=['method', 'model', 'rtol', 'err', 'time'])
print(gg.ggplot(data, gg.aes(x='err', y='time', color='method'))
+ gg.geom_point(size=60.0)
+ gg.geom_line()
+ gg.scale_x_log()
+ gg.scale_y_log()
+ gg.xlim(1e-10, 1e-2))
data = []
for method in methods:
for model in models:
for rtol in rtols:
print('method: {} model: {} rtol: {}'.format(
method.name, model.name, rtol),
end='')
# Run
tic = time.time()
result = method(model, rtol)
toc = time.time() - tic
# Compare to gold standard
standard = gold_standards[model.name]
diff = result - standard.values
max_rel_diff = np.max(diff / standard.max)
# Append to table
record = (method.name, model.name, rtol, max_rel_diff, toc)
print(' err: {} toc: {}'.format(max_rel_diff, toc))
data.append(record)
data = DataFrame(data, columns=['method', 'model', 'rtol', 'err', 'time'])
print(
gg.ggplot(data, gg.aes(x='err', y='time', color='method')) +
gg.geom_point(size=60.0) + gg.geom_line() + gg.scale_x_log() +
gg.scale_y_log() + gg.xlim(1e-10, 1e-2))
def test_scale_y_log_base(self):
p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_y_log(base=100)
self.assertEqual(p.scale_y_log, 100)
def test_scale_y_log_default10(self):
p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_y_log()
self.assertEqual(p.scale_y_log, 10)
def test_scale_y_log_base(self):
p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_y_log(base=100)
self.assertEqual(p.scale_y_log, 100)
def test_scale_y_log_default10(self):
p = gg.ggplot(gg.aes(x='mpg'), gg.mtcars) + gg.scale_y_log()
self.assertEqual(p.scale_y_log, 10)
