def test_calculate_bins():
target = np.array(['2018-01-01 00:00', '2018-01-01 01:00', '2018-01-01 02:00',
'2018-01-01 03:00', '2018-01-01 04:00', '2018-01-01 05:00',
'2018-01-01 06:00', '2018-01-01 07:00', '2018-01-01 08:00'])
df = setup_dataframe.create_dataframe()
bins = EDA_countplot.calculate_bins(df,'H').values
assert (bins == target).all()
def test_punchcard_two_users():
df = setup_dataframe.create_dataframe()
user_list = ['user_1', 'user_2']
columns = ['col_1']
title = 'test_title'
resample = "D"
fig = EDA_punchcard.punchcard_plot(df, user_list, columns, title, resample)
assert (type(fig) == plotly.graph_objs._figure.Figure)
def test_punchcard_one_user():
df = setup_dataframe.create_dataframe()
user_list = ['user_1']
columns = ['col_1']
title = 'test_title'
resample = "D"
fig = EDA_punchcard.punchcard_plot(df, user_list, columns, title, resample)
assert (type(fig) == plotly.graph_objs._figure.Figure)
assert (type(fig) == plotly.graph_objs._figure.Figure)
assert (fig.layout.xaxis.nticks == 31)
assert (fig.layout.title.text == 'test_title')
def test_EDA_countplot_subject():
df = setup_dataframe.create_dataframe()
fig = EDA_countplot.EDA_countplot(df,
fig_title = 'Test_title',
plot_type = 'count',
points = 'all',
aggregation = 'user',
user = None,
column = None,
binning=False)
assert (type(fig) == plotly.graph_objs._figure.Figure)
def test_EDA_countplot_value():
df = setup_dataframe.create_dataframe()
fig = EDA_countplot.EDA_countplot(df,
fig_title = 'Test_title',
plot_type = 'value',
points = 'all',
aggregation = 'group',
user = None,
column='col_1',
binning='H')
assert (type(fig) == plotly.graph_objs._figure.Figure)
def test_punchcard_one_user_two_columns():
df = setup_dataframe.create_dataframe()
user_list = ['user_1']
columns = ['col_1', 'col_2']
title = 'test_title'
resample = "D"
normalize = True
fig = EDA_punchcard.punchcard_plot(df, user_list, columns, title, resample,
normalize)
assert (type(fig) == plotly.graph_objs._figure.Figure)
assert (fig.layout.legend.x == None)
assert (fig.layout.legend.y == None)
def test_punchcard_two_users_timerange():
df = setup_dataframe.create_dataframe()
user_list = ['user_1', 'user_2']
columns = ['col_1']
title = 'test_title'
resample = "D"
normalize = False
agg_function = np.mean
timerange = ('20171231', '20180101')
fig = EDA_punchcard.punchcard_plot(df, user_list, columns, title, resample,
normalize, agg_function, timerange)
assert (type(fig) == plotly.graph_objs._figure.Figure)
assert (fig.data[0].x == datetime.datetime(2018, 1, 1, 0, 0))
def test_timeplot_two_users_and_columns():
df = setup_dataframe.create_dataframe()
fig = EDA_lineplot.timeplot(df,
users=['user_1','user_2'],
columns=['col_1','col_2'],
title='Test title',
xlabel='Xlabel',
ylabel='Ylabel',
resample='H',
interpolate=True,
window=1,
reset_index=False,
by='hour'
)
assert (type(fig) == plotly.graph_objs._figure.Figure)
def test_group_averages():
df = setup_dataframe.create_dataframe()
#df = df.rename_axis('timestamp')
fig = EDA_lineplot.timeplot(df,
users='Group',
columns=['col_1'],
title='Test title',
xlabel='Xlabel',
ylabel='Ylabel',
resample='D',
interpolate=True,
window=1,
reset_index=False,
by='weekday'
)
assert (type(fig) == plotly.graph_objs._figure.Figure)
def test_get_counts():
df = setup_dataframe.create_dataframe()
group_counts = EDA_countplot.get_counts(df,'group')
user_counts = EDA_countplot.get_counts(df,'user')
assert (group_counts['values'].values == np.array([3,3,3])).all()
assert (user_counts['values'].values == np.ones(9)).all()