def test_funargs():
p = (ggplot(df, aes('x', 'y'))
+ stat_summary(fun_data='mean_cl_normal',
size=2, color='blue')
+ stat_summary(fun_data='mean_cl_normal',
fun_args={'confidence_interval': .5},
size=2, color='green'))
assert p == 'fun_args'
def test_funargs():
p = (ggplot(df, aes('x', 'y')) +
stat_summary(fun_data='mean_cl_normal', size=2, color='blue') +
stat_summary(fun_data='mean_cl_normal',
fun_args={'confidence_interval': .5},
size=2,
color='green'))
assert p == 'fun_args'
def test_summary_functions():
p = (ggplot(df, aes('x', 'y'))
+ stat_summary(fun_y=np.mean,
fun_ymin=np.min,
fun_ymax=np.max,
size=2))
assert p == 'summary_functions'
def test_summary_functions():
p = (ggplot(df, aes('x', 'y'))
+ stat_summary(fun_y=np.mean,
fun_ymin=np.min,
fun_ymax=np.max,
size=2))
assert p == 'summary_functions'
def test_mean_se():
p = (ggplot(df, aes('x', 'y'))
+ stat_summary(fun_data='mean_se', size=2))
assert p == 'mean_se'
def test_median_hilow():
p = (ggplot(df, aes('x', 'y'))
+ stat_summary(fun_data='median_hilow', size=2))
assert p == 'median_hilow'
def test_mean_cl_boot():
p = (ggplot(df, aes('x', 'y'))
+ stat_summary(fun_data='mean_cl_boot',
random_state=random_state, size=2))
assert p == 'mean_cl_boot'
def test_mean_se():
p = (ggplot(df, aes('x', 'y')) + stat_summary(fun_data='mean_se', size=2))
assert p == 'mean_se'
def test_median_hilow():
p = (ggplot(df, aes('x', 'y')) +
stat_summary(fun_data='median_hilow', size=2))
assert p == 'median_hilow'
def test_mean_cl_boot():
p = (ggplot(df, aes('x', 'y')) + stat_summary(
fun_data='mean_cl_boot', random_state=random_state, size=2))
assert p == 'mean_cl_boot'
def test_stat_summary_raises_on_invalid_paremeters():
with pytest.raises(TypeError):
geom_point(stat_summary(funy=np.mean))
with pytest.raises(TypeError):
geom_point(stat_summary(does_not_exist=1))
