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BaptisteDEBaptisteDE
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Merge pull request #12 from BuildingEnergySimulationTools/units_operations
Units operations
2 parents b57d2f6 + a727286 commit 4045f4d

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11 files changed

+249
-103
lines changed

11 files changed

+249
-103
lines changed

‎tests/test_base.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -29,7 +29,7 @@ def test_base_processing(self):
2929
"text__°C__meteo": np.random.randn(24),
3030
"hr__%hr__meteo": np.random.randn(24),
3131
},
32-
index=pd.date_range("2024-12-05 00:00:00", freq="h", periods=24),
32+
index=pd.date_range("2024-12-05 00:00:00", freq="h", periods=24, tz="UTC"),
3333
)
3434

3535
dp = DumbProcessor(required_columns=["text__°C__meteo"], keep_required=False)

‎tests/test_math.py‎

Lines changed: 12 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -8,15 +8,17 @@ def test_time_gradient(self):
88
test = (
99
pd.Series(
1010
[0, 1, 2, 2, 2, 3],
11-
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6),
11+
index=pd.date_range(
12+
"2009-01-01 00:00:00", freq="10s", periods=6, tz="UTC"
13+
),
1214
name="cpt1",
1315
)
1416
* 3600
1517
)
1618

1719
ref = pd.DataFrame(
1820
{"cpt1": [360.0, 360.0, 180.0, -5.68e-14, 180.0, 360.0]},
19-
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6),
21+
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6, tz="UTC"),
2022
)
2123

2224
to_test = time_gradient(test)
@@ -26,7 +28,9 @@ def test_time_gradient(self):
2628
test = (
2729
pd.DataFrame(
2830
{"cpt1": [0, 1, 2, 2, 2, 3], "cpt2": [0, 1, 2, 2, 2, 3]},
29-
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6),
31+
index=pd.date_range(
32+
"2009-01-01 00:00:00", freq="10s", periods=6, tz="UTC"
33+
),
3034
)
3135
* 3600
3236
)
@@ -36,7 +40,7 @@ def test_time_gradient(self):
3640
"cpt1": [360.0, 360.0, 180.0, -5.68e-14, 180.0, 360.0],
3741
"cpt2": [360.0, 360.0, 180.0, -5.68e-14, 180.0, 360.0],
3842
},
39-
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6),
43+
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6, tz="UTC"),
4044
)
4145

4246
to_test = time_gradient(test)
@@ -46,7 +50,7 @@ def test_time_gradient(self):
4650
def test_time_integrate(self):
4751
test = pd.Series(
4852
[360.0, 360.0, 180.0, -5.68e-14, 180.0, 360.0],
49-
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6),
53+
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6, tz="UTC"),
5054
name="cpt",
5155
)
5256

@@ -59,7 +63,7 @@ def test_time_integrate(self):
5963
"cpt1": [360.0, 360.0, 180.0, -5.68e-14, 180.0, 360.0],
6064
"cpt2": [360.0, 360.0, 180.0, -5.68e-14, 180.0, 360.0],
6165
},
62-
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6),
66+
index=pd.date_range("2009-01-01 00:00:00", freq="10s", periods=6, tz="UTC"),
6367
)
6468

6569
ref = pd.Series({"cpt1": 3.0, "cpt2": 3.0})
@@ -69,11 +73,11 @@ def test_time_integrate(self):
6973
def test_aggregate_time_series(self):
7074
sim_res = pd.DataFrame(
7175
{"a": [1, 2], "b": [3, 4]},
72-
index=pd.date_range("2009-01-01", freq="h", periods=2),
76+
index=pd.date_range("2009-01-01", freq="h", periods=2, tz="UTC"),
7377
)
7478
ref_df = pd.DataFrame(
7579
{"a": [1, 1], "b": [3, 4]},
76-
index=pd.date_range("2009-01-01", freq="h", periods=2),
80+
index=pd.date_range("2009-01-01", freq="h", periods=2, tz="UTC"),
7781
)
7882

7983
expected_default = pd.Series([1.5, 3.5], index=["a", "b"])

‎tests/test_plot.py‎

Lines changed: 11 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -52,7 +52,7 @@ def test_plot_gaps_heatmap(self):
5252
"a": np.random.randn(24),
5353
"b": np.random.randn(24),
5454
},
55-
index=pd.date_range("2009", freq="h", periods=24),
55+
index=pd.date_range("2009", freq="h", periods=24, tz="UTC"),
5656
)
5757

5858
df.loc["2009-01-01 05:00:00":"2009-01-01 09:00:00", :] = np.nan
@@ -71,7 +71,7 @@ def test_add_multi_axis_scatter(self):
7171
"b__W": np.random.randn(24) * 100,
7272
"e__Wh": np.random.randn(24) * 100,
7373
},
74-
index=pd.date_range("2009", freq="h", periods=24),
74+
index=pd.date_range("2009", freq="h", periods=24, tz="UTC"),
7575
)
7676
df["e__Wh"] = abs(df).cumsum()["e__Wh"]
7777

@@ -94,14 +94,12 @@ def test_add_multi_axis_scatter(self):
9494
y_title_standoff=1,
9595
)
9696

97-
assert True
98-
9997
def test_get_gaps_scatter_dict(self):
10098
np.random.seed(42)
10199
measure = pd.Series(
102100
np.random.randn(24),
103101
name="name",
104-
index=pd.date_range("2009", freq="h", periods=24),
102+
index=pd.date_range("2009", freq="h", periods=24, tz="UTC"),
105103
)
106104

107105
measure.loc["2009-01-01 02:00:00":"2009-01-01 05:00:00"] = np.nan
@@ -114,10 +112,10 @@ def test_get_gaps_scatter_dict(self):
114112
assert gap_dict == [
115113
{
116114
"x": [
117-
pd.Timestamp("2009-01-01 01:00:00"),
118-
pd.Timestamp("2009-01-01 01:00:00"),
119-
pd.Timestamp("2009-01-01 06:00:00"),
120-
pd.Timestamp("2009-01-01 06:00:00"),
115+
pd.Timestamp("2009-01-01 01:00:00", tz="UTC"),
116+
pd.Timestamp("2009-01-01 01:00:00", tz="UTC"),
117+
pd.Timestamp("2009-01-01 06:00:00", tz="UTC"),
118+
pd.Timestamp("2009-01-01 06:00:00", tz="UTC"),
121119
],
122120
"y": [
123121
-1.913280244657798,
@@ -133,10 +131,10 @@ def test_get_gaps_scatter_dict(self):
133131
},
134132
{
135133
"x": [
136-
pd.Timestamp("2009-01-01 11:00:00"),
137-
pd.Timestamp("2009-01-01 11:00:00"),
138-
pd.Timestamp("2009-01-01 13:00:00"),
139-
pd.Timestamp("2009-01-01 13:00:00"),
134+
pd.Timestamp("2009-01-01 11:00:00", tz="UTC"),
135+
pd.Timestamp("2009-01-01 11:00:00", tz="UTC"),
136+
pd.Timestamp("2009-01-01 13:00:00", tz="UTC"),
137+
pd.Timestamp("2009-01-01 13:00:00", tz="UTC"),
140138
],
141139
"y": [
142140
-1.913280244657798,

‎tests/test_plumbing.py‎

Lines changed: 6 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -24,7 +24,7 @@
2424
"light__DIMENSIONLESS__building": [100, 200, 300],
2525
"mass_flwr__m3/h__hvac": [300, 500, 600],
2626
},
27-
index=pd.date_range("2009", freq="h", periods=3),
27+
index=pd.date_range("2009", freq="h", periods=3, tz="UTC"),
2828
)
2929

3030
TEST_DF_2 = pd.DataFrame(
@@ -33,7 +33,7 @@
3333
"b__°C__zone_1": np.random.randn(24),
3434
"c__Wh__zone_2": np.random.randn(24) * 100,
3535
},
36-
index=pd.date_range("2009", freq="h", periods=24),
36+
index=pd.date_range("2009", freq="h", periods=24, tz="UTC"),
3737
)
3838

3939
TEST_DF_2["c__Wh__zone_2"] = abs(TEST_DF_2).cumsum()["c__Wh__zone_2"]
@@ -73,7 +73,7 @@ def test__get_all_data_step(self):
7373
test_df = TEST_DF.copy()
7474
test_df.iloc[1, 0] = np.nan
7575
test_df.iloc[0, 1] = np.nan
76-
pipe = _get_pipe_from_proc_list(test_df.columns, PIPE_DICT["common"])
76+
pipe = _get_pipe_from_proc_list(test_df.columns, PIPE_DICT["common"], tz="UTC")
7777

7878
res = pipe.fit_transform(test_df)
7979

@@ -86,6 +86,7 @@ def test__get_column_wise_transformer(self):
8686
col_trans = _get_column_wise_transformer(
8787
proc_dict=PIPE_DICT["pre_processing"],
8888
data_columns=TEST_DF.columns,
89+
tz="UTC",
8990
process_name="test",
9091
)
9192

@@ -99,6 +100,7 @@ def test__get_column_wise_transformer(self):
99100
data_columns=TEST_DF[
100101
[col for col in TEST_DF.columns if col != "radiation__W/m2__outdoor"]
101102
].columns,
103+
tz="UTC",
102104
process_name="test",
103105
)
104106

@@ -122,6 +124,7 @@ def test__get_column_wise_transformer(self):
122124
col_trans = _get_column_wise_transformer(
123125
proc_dict=PIPE_DICT["pre_processing"],
124126
data_columns=cols_none,
127+
tz="UTC",
125128
process_name="test",
126129
)
127130

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