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Shorten a couple of names

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- rename "total_orders" columns into "n_orders"
- rename `.make_*_time_series()` methods into `.make_*_ts()`
This commit is contained in:
Alexander Hess 2021-01-31 20:19:12 +01:00
commit 7b824a4a12
Signed by: alexander
GPG key ID: 344EA5AB10D868E0
4 changed files with 71 additions and 71 deletions
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46
tests/forecasts/timify/test_aggregate_orders.py
View file

@ -91,9 +91,9 @@ class TestAggregateOrders:
# The resulting `DataFrame` has 12 rows holding `1`s.
assert len(result) == 12
assert result['total_orders'].min() == 1
assert result['total_orders'].max() == 1
assert result['total_orders'].sum() == 12
assert result['n_orders'].min() == 1
assert result['n_orders'].max() == 1
assert result['n_orders'].sum() == 12
def test_evenly_distributed_ad_hoc_orders_with_no_demand_late( # noqa:WPS218
self, db_session, one_pixel_grid, restaurant, make_order,
@ -123,10 +123,10 @@ class TestAggregateOrders:
# Even though there are only 10 orders, there are 12 rows in the `DataFrame`.
# That is so as `0`s are filled in for hours without any demand at the end.
assert len(result) == 12
assert result['total_orders'].min() == 0
assert result['total_orders'].max() == 1
assert result.iloc[:10]['total_orders'].sum() == 10
assert result.iloc[10:]['total_orders'].sum() == 0
assert result['n_orders'].min() == 0
assert result['n_orders'].max() == 1
assert result.iloc[:10]['n_orders'].sum() == 10
assert result.iloc[10:]['n_orders'].sum() == 0
def test_one_ad_hoc_order_every_other_hour(
self, db_session, one_pixel_grid, restaurant, make_order,
@ -155,9 +155,9 @@ class TestAggregateOrders:
# The resulting `DataFrame` has 12 rows, 6 holding `0`s, and 6 holding `1`s.
assert len(result) == 12
assert result['total_orders'].min() == 0
assert result['total_orders'].max() == 1
assert result['total_orders'].sum() == 6
assert result['n_orders'].min() == 0
assert result['n_orders'].max() == 1
assert result['n_orders'].sum() == 6
def test_one_ad_hoc_and_one_pre_order(
self, db_session, one_pixel_grid, restaurant, make_order,
@ -199,9 +199,9 @@ class TestAggregateOrders:
# The resulting `DataFrame` has 12 rows, 11 holding `0`s, and one holding a `1`.
assert len(result) == 12
assert result['total_orders'].min() == 0
assert result['total_orders'].max() == 1
assert result['total_orders'].sum() == 1
assert result['n_orders'].min() == 0
assert result['n_orders'].max() == 1
assert result['n_orders'].sum() == 1
def test_evenly_distributed_ad_hoc_orders_with_half_hour_time_steps( # noqa:WPS218
self, db_session, one_pixel_grid, restaurant, make_order,
@ -234,10 +234,10 @@ class TestAggregateOrders:
# The resulting `DataFrame` has 24 rows for the 24 30-minute time steps.
# The rows' values are `0` and `1` alternating.
assert len(result) == 24
assert result['total_orders'].min() == 0
assert result['total_orders'].max() == 1
assert result.iloc[::2]['total_orders'].sum() == 12
assert result.iloc[1::2]['total_orders'].sum() == 0
assert result['n_orders'].min() == 0
assert result['n_orders'].max() == 1
assert result.iloc[::2]['n_orders'].sum() == 12
assert result.iloc[1::2]['n_orders'].sum() == 0
def test_ad_hoc_orders_over_two_days(
self, db_session, one_pixel_grid, restaurant, make_order,
@ -285,9 +285,9 @@ class TestAggregateOrders:
# The resulting `DataFrame` has 24 rows, 12 for each day.
assert len(result) == 24
assert result['total_orders'].min() == 0
assert result['total_orders'].max() == 1
assert result['total_orders'].sum() == 18
assert result['n_orders'].min() == 0
assert result['n_orders'].max() == 1
assert result['n_orders'].sum() == 18
@pytest.fixture
def two_pixel_grid( # noqa:WPS211
@ -381,6 +381,6 @@ class TestAggregateOrders:
# The resulting `DataFrame` has 24 rows, 12 for each pixel.
assert len(result) == 24
assert result['total_orders'].min() == 0
assert result['total_orders'].max() == 2
assert result['total_orders'].sum() == 30
assert result['n_orders'].min() == 0
assert result['n_orders'].max() == 2
assert result['n_orders'].sum() == 30

58
tests/forecasts/timify/test_make_time_series.py
View file

@ -41,7 +41,7 @@ def order_totals(good_pixel_id):
index = pd.MultiIndex.from_tuples(gen)
index.names = ['pixel_id', 'start_at']
df = pd.DataFrame(data={'total_orders': 0}, index=index)
df = pd.DataFrame(data={'n_orders': 0}, index=index)
# Sanity check: n_pixels * n_time_steps_per_day * n_weekdays * n_weeks.
assert len(df) == 2 * 12 * (7 * 2 + 1)
@ -88,13 +88,13 @@ def bad_predict_at():
class TestMakeHorizontalTimeSeries:
"""Test the `OrderHistory.make_horizontal_time_series()` method."""
"""Test the `OrderHistory.make_horizontal_ts()` method."""
@pytest.mark.parametrize('train_horizon', test_config.TRAIN_HORIZONS)
def test_wrong_pixel(self, order_history, good_predict_at, train_horizon):
"""A `pixel_id` that is not in the `grid`."""
with pytest.raises(LookupError):
order_history.make_horizontal_time_series(
order_history.make_horizontal_ts(
pixel_id=999_999,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -105,7 +105,7 @@ class TestMakeHorizontalTimeSeries:
self, order_history, good_pixel_id, good_predict_at, train_horizon,
):
"""The time series come as a `pd.Series`."""
result = order_history.make_horizontal_time_series(
result = order_history.make_horizontal_ts(
pixel_id=good_pixel_id,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -114,9 +114,9 @@ class TestMakeHorizontalTimeSeries:
training_ts, _, actuals_ts = result
assert isinstance(training_ts, pd.Series)
assert training_ts.name == 'total_orders'
assert training_ts.name == 'n_orders'
assert isinstance(actuals_ts, pd.Series)
assert actuals_ts.name == 'total_orders'
assert actuals_ts.name == 'n_orders'
@pytest.mark.parametrize('train_horizon', test_config.TRAIN_HORIZONS)
def test_time_series_have_correct_length(
@ -126,7 +126,7 @@ class TestMakeHorizontalTimeSeries:
... whereas the time series with the actual order counts has only `1` value.
"""
result = order_history.make_horizontal_time_series(
result = order_history.make_horizontal_ts(
pixel_id=good_pixel_id,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -142,7 +142,7 @@ class TestMakeHorizontalTimeSeries:
self, order_history, good_pixel_id, good_predict_at, train_horizon,
):
"""The `frequency` must be `7`."""
result = order_history.make_horizontal_time_series(
result = order_history.make_horizontal_ts(
pixel_id=good_pixel_id,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -161,7 +161,7 @@ class TestMakeHorizontalTimeSeries:
... the history of order totals is not long enough.
"""
with pytest.raises(RuntimeError):
order_history.make_horizontal_time_series(
order_history.make_horizontal_ts(
pixel_id=good_pixel_id,
predict_at=bad_predict_at,
train_horizon=train_horizon,
@ -175,19 +175,19 @@ class TestMakeHorizontalTimeSeries:
... the history of order totals can never be long enough.
"""
with pytest.raises(RuntimeError):
order_history.make_horizontal_time_series(
order_history.make_horizontal_ts(
pixel_id=good_pixel_id, predict_at=good_predict_at, train_horizon=999,
)
class TestMakeVerticalTimeSeries:
"""Test the `OrderHistory.make_vertical_time_series()` method."""
"""Test the `OrderHistory.make_vertical_ts()` method."""
@pytest.mark.parametrize('train_horizon', test_config.TRAIN_HORIZONS)
def test_wrong_pixel(self, order_history, good_predict_at, train_horizon):
"""A `pixel_id` that is not in the `grid`."""
with pytest.raises(LookupError):
order_history.make_vertical_time_series(
order_history.make_vertical_ts(
pixel_id=999_999,
predict_day=good_predict_at.date(),
train_horizon=train_horizon,
@ -198,7 +198,7 @@ class TestMakeVerticalTimeSeries:
self, order_history, good_pixel_id, good_predict_at, train_horizon,
):
"""The time series come as `pd.Series`."""
result = order_history.make_vertical_time_series(
result = order_history.make_vertical_ts(
pixel_id=good_pixel_id,
predict_day=good_predict_at.date(),
train_horizon=train_horizon,
@ -207,9 +207,9 @@ class TestMakeVerticalTimeSeries:
training_ts, _, actuals_ts = result
assert isinstance(training_ts, pd.Series)
assert training_ts.name == 'total_orders'
assert training_ts.name == 'n_orders'
assert isinstance(actuals_ts, pd.Series)
assert actuals_ts.name == 'total_orders'
assert actuals_ts.name == 'n_orders'
@pytest.mark.parametrize('train_horizon', test_config.TRAIN_HORIZONS)
def test_time_series_have_correct_length(
@ -223,7 +223,7 @@ class TestMakeVerticalTimeSeries:
The time series with the actual order counts always holds one observation
per time step of a day.
"""
result = order_history.make_vertical_time_series(
result = order_history.make_vertical_ts(
pixel_id=good_pixel_id,
predict_day=good_predict_at.date(),
train_horizon=train_horizon,
@ -245,7 +245,7 @@ class TestMakeVerticalTimeSeries:
self, order_history, good_pixel_id, good_predict_at, train_horizon,
):
"""The `frequency` is the number of weekly time steps."""
result = order_history.make_vertical_time_series(
result = order_history.make_vertical_ts(
pixel_id=good_pixel_id,
predict_day=good_predict_at.date(),
train_horizon=train_horizon,
@ -270,7 +270,7 @@ class TestMakeVerticalTimeSeries:
... the history of order totals is not long enough.
"""
with pytest.raises(RuntimeError):
order_history.make_vertical_time_series(
order_history.make_vertical_ts(
pixel_id=good_pixel_id,
predict_day=bad_predict_at.date(),
train_horizon=train_horizon,
@ -284,7 +284,7 @@ class TestMakeVerticalTimeSeries:
... the history of order totals can never be long enough.
"""
with pytest.raises(RuntimeError):
order_history.make_vertical_time_series(
order_history.make_vertical_ts(
pixel_id=good_pixel_id,
predict_day=good_predict_at.date(),
train_horizon=999,
@ -292,13 +292,13 @@ class TestMakeVerticalTimeSeries:
class TestMakeRealTimeTimeSeries:
"""Test the `OrderHistory.make_real_time_time_series()` method."""
"""Test the `OrderHistory.make_realtime_ts()` method."""
@pytest.mark.parametrize('train_horizon', test_config.TRAIN_HORIZONS)
def test_wrong_pixel(self, order_history, good_predict_at, train_horizon):
"""A `pixel_id` that is not in the `grid`."""
with pytest.raises(LookupError):
order_history.make_real_time_time_series(
order_history.make_realtime_ts(
pixel_id=999_999,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -309,7 +309,7 @@ class TestMakeRealTimeTimeSeries:
self, order_history, good_pixel_id, good_predict_at, train_horizon,
):
"""The time series come as `pd.Series`."""
result = order_history.make_real_time_time_series(
result = order_history.make_realtime_ts(
pixel_id=good_pixel_id,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -318,9 +318,9 @@ class TestMakeRealTimeTimeSeries:
training_ts, _, actuals_ts = result
assert isinstance(training_ts, pd.Series)
assert training_ts.name == 'total_orders'
assert training_ts.name == 'n_orders'
assert isinstance(actuals_ts, pd.Series)
assert actuals_ts.name == 'total_orders'
assert actuals_ts.name == 'n_orders'
@pytest.mark.parametrize('train_horizon', test_config.TRAIN_HORIZONS)
def test_time_series_have_correct_length1(
@ -341,7 +341,7 @@ class TestMakeRealTimeTimeSeries:
config.SERVICE_START,
0,
)
result = order_history.make_real_time_time_series(
result = order_history.make_realtime_ts(
pixel_id=good_pixel_id, predict_at=predict_at, train_horizon=train_horizon,
)
@ -372,7 +372,7 @@ class TestMakeRealTimeTimeSeries:
"""
assert good_predict_at.hour == test_config.NOON
result = order_history.make_real_time_time_series(
result = order_history.make_realtime_ts(
pixel_id=good_pixel_id,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -400,7 +400,7 @@ class TestMakeRealTimeTimeSeries:
self, order_history, good_pixel_id, good_predict_at, train_horizon,
):
"""The `frequency` is the number of weekly time steps."""
result = order_history.make_real_time_time_series(
result = order_history.make_realtime_ts(
pixel_id=good_pixel_id,
predict_at=good_predict_at,
train_horizon=train_horizon,
@ -425,7 +425,7 @@ class TestMakeRealTimeTimeSeries:
... the history of order totals is not long enough.
"""
with pytest.raises(RuntimeError):
order_history.make_real_time_time_series(
order_history.make_realtime_ts(
pixel_id=good_pixel_id,
predict_at=bad_predict_at,
train_horizon=train_horizon,
@ -439,6 +439,6 @@ class TestMakeRealTimeTimeSeries:
... the history of order totals can never be long enough.
"""
with pytest.raises(RuntimeError):
order_history.make_real_time_time_series(
order_history.make_realtime_ts(
pixel_id=good_pixel_id, predict_at=good_predict_at, train_horizon=999,
)