def test_sort_index(df_time):
# Shuffle dataframe
Xs = df_time.sample(frac=1)
transformer = ExpandingWindowFeatures(sort_index=False)
df_tr = transformer.fit_transform(Xs)
assert_frame_equal(df_tr[transformer.variables_],
Xs[transformer.variables_])
transformer = ExpandingWindowFeatures(sort_index=True)
df_tr = transformer.fit_transform(Xs)
assert_frame_equal(df_tr[transformer.variables_],
Xs[transformer.variables_].sort_index())
def test_expanding_sum_single_var(df_time):
expected_results = {
"ambient_temp_expanding_sum": [
np.nan,
31.31,
62.82,
94.97,
127.36,
159.98,
192.48,
225.00,
257.68,
291.44,
325.57,
359.65,
393.35,
427.24,
461.28,
],
}
expected_df = df_time.copy()
expected_df["ambient_temp_expanding_sum"] = expected_results[
"ambient_temp_expanding_sum"]
transformer = ExpandingWindowFeatures(variables=["ambient_temp"],
functions="sum")
df_tr = transformer.fit_transform(df_time)
assert_frame_equal(df_tr, expected_df)
def test_expanding_sum_and_mean_single_var(df_time):
expected_results = {
"ambient_temp_expanding_sum": [
np.nan,
31.31,
62.82,
94.97,
127.36,
159.98,
192.48,
225.00,
257.68,
291.44,
325.57,
359.65,
393.35,
427.24,
461.28,
],
"ambient_temp_expanding_mean": [
np.nan,
31.3100,
31.4100,
31.6567,
31.8400,
31.9960,
32.0800,
32.1429,
32.2100,
32.3822,
32.5570,
32.6955,
32.7792,
32.8646,
32.9486,
],
}
expected_df = df_time.copy()
expected_df["ambient_temp_expanding_sum"] = expected_results[
"ambient_temp_expanding_sum"]
expected_df["ambient_temp_expanding_mean"] = expected_results[
"ambient_temp_expanding_mean"]
transformer = ExpandingWindowFeatures(variables=["ambient_temp"],
functions=["sum", "mean"])
df_tr = transformer.fit_transform(df_time)
assert_frame_equal(df_tr, expected_df)
def test_expanding_sum_multiple_vars(df_time):
expected_results = {
"ambient_temp_expanding_sum": [
np.nan,
31.31,
62.82,
94.97,
127.36,
159.98,
192.48,
225.00,
257.68,
291.44,
325.57,
359.65,
393.35,
427.24,
461.28,
],
"irradiation_expanding_sum": [
np.nan,
0.51,
1.3,
1.95,
2.71,
3.13,
3.62,
4.19,
4.75,
5.49,
6.38,
6.85,
7.39,
7.79,
8.24,
],
}
expected_df = df_time.copy()
expected_df["ambient_temp_expanding_sum"] = expected_results[
"ambient_temp_expanding_sum"]
expected_df["irradiation_expanding_sum"] = expected_results[
"irradiation_expanding_sum"]
transformer = ExpandingWindowFeatures(
variables=["ambient_temp", "irradiation"], functions="sum")
df_tr = transformer.fit_transform(df_time)
assert_frame_equal(df_tr, expected_df)
def test_expanding_sum_and_mean_multiple_vars(df_time):
expected_results = {
"ambient_temp_expanding_sum": [
np.nan,
31.31,
62.82,
94.97,
127.36,
159.98,
192.48,
225.00,
257.68,
291.44,
325.57,
359.65,
393.35,
427.24,
461.28,
],
"ambient_temp_expanding_mean": [
np.nan,
31.3100,
31.4100,
31.6567,
31.8400,
31.9960,
32.0800,
32.1429,
32.2100,
32.3822,
32.5570,
32.6955,
32.7792,
32.8646,
32.9486,
],
"irradiation_expanding_sum": [
np.nan,
0.51,
1.3,
1.95,
2.71,
3.13,
3.62,
4.19,
4.75,
5.49,
6.38,
6.85,
7.39,
7.79,
8.24,
],
"irradiation_expanding_mean": [
np.nan,
0.51000,
0.65000,
0.65000,
0.67750,
0.62600,
0.60333,
0.59857,
0.59375,
0.61000,
0.63800,
0.62273,
0.61583,
0.59923,
0.58857,
],
}
expected_df = df_time.copy()
expected_df["ambient_temp_expanding_sum"] = expected_results[
"ambient_temp_expanding_sum"]
expected_df["ambient_temp_expanding_mean"] = expected_results[
"ambient_temp_expanding_mean"]
expected_df["irradiation_expanding_sum"] = expected_results[
"irradiation_expanding_sum"]
expected_df["irradiation_expanding_mean"] = expected_results[
"irradiation_expanding_mean"]
transformer = ExpandingWindowFeatures(
variables=["ambient_temp", "irradiation"], functions=["sum", "mean"])
df_tr = transformer.fit_transform(df_time)
assert_frame_equal(df_tr, expected_df)