From 31762a1a31a58439fbc512ab5239333edebefa96 Mon Sep 17 00:00:00 2001
From: Bert Palm <bert.palm@ufz.de>
Date: Fri, 26 Mar 2021 00:23:31 +0100
Subject: [PATCH] prepared flagger refactoring
---
saqc/__main__.py | 10 +++++-----
saqc/core/register.py | 6 +++---
saqc/funcs/breaks.py | 4 ++--
tests/core/test_core.py | 4 ++--
tests/funcs/test_constants_detection.py | 4 ++--
tests/funcs/test_modelling.py | 12 ++++++------
6 files changed, 20 insertions(+), 20 deletions(-)
diff --git a/saqc/__main__.py b/saqc/__main__.py
index 8fbb3cb7c..7b7a3c5b0 100644
--- a/saqc/__main__.py
+++ b/saqc/__main__.py
@@ -95,12 +95,12 @@ def main(config, data, flagger, outfile, nodata, log_level, fail):
data_result, flagger_result = saqc.readConfig(config).getResult(raw=True)
if outfile:
- data_result = data_result.to_df()
- flags = flagger_result.toFrame()
- unflagged = (flags == UNFLAGGED) | flags.isna()
- flags[unflagged] = GOOD
+ data_frame = data_result.to_df()
+ flags_frame = flagger_result.toFrame()
+ unflagged = (flags_frame == UNFLAGGED) | flags_frame.isna()
+ flags_frame[unflagged] = GOOD
- fields = {"data": data_result, "flags": flags}
+ fields = {"data": data_frame, "flags": flags_frame}
out = (
pd.concat(fields.values(), axis=1, keys=fields.keys())
diff --git a/saqc/core/register.py b/saqc/core/register.py
index c3b3945fa..5d991e803 100644
--- a/saqc/core/register.py
+++ b/saqc/core/register.py
@@ -249,14 +249,14 @@ def _maskData(data, flagger, columns, thresh) -> Tuple[dios.DictOfSeries, dios.D
return data, mask
-def _isflagged(flags: Union[np.array, pd.Series], thresh: float) -> Union[np.array, pd.Series]:
+def _isflagged(flagscol: Union[np.array, pd.Series], thresh: float) -> Union[np.array, pd.Series]:
"""
Return a mask of flags accordingly to `thresh`. Return type is same as flags.
"""
if thresh == UNFLAGGED:
- return flags > UNFLAGGED
+ return flagscol > UNFLAGGED
- return flags >= thresh
+ return flagscol >= thresh
def _prepareFlags(flagger: Flagger, masking) -> Flagger:
diff --git a/saqc/funcs/breaks.py b/saqc/funcs/breaks.py
index aede9d631..d9cbbc6d0 100644
--- a/saqc/funcs/breaks.py
+++ b/saqc/funcs/breaks.py
@@ -124,7 +124,7 @@ def flagIsolated(
mask = data[field].isna()
- flags = pd.Series(data=0, index=mask.index, dtype=bool)
+ bools = pd.Series(data=0, index=mask.index, dtype=bool)
for srs in groupConsecutives(mask):
if np.all(~srs):
start = srs.index[0]
@@ -134,7 +134,7 @@ def flagIsolated(
if left.all():
right = mask[stop: stop + gap_window].iloc[1:]
if right.all():
- flags[start:stop] = True
+ bools[start:stop] = True
flagger[mask, field] = flag
return data, flagger
diff --git a/tests/core/test_core.py b/tests/core/test_core.py
index c13f8a5b8..a784cdbac 100644
--- a/tests/core/test_core.py
+++ b/tests/core/test_core.py
@@ -86,10 +86,10 @@ def test_dtypes(data, flags):
Test if the categorical dtype is preserved through the core functionality
"""
flagger = initFlagsLike(data)
- flags = flagger.toDios()
+ flags_raw = flagger.toDios()
var1, var2 = data.columns[:2]
- pdata, pflagger = SaQC(data, flags=flags).flagAll(var1).flagAll(var2).getResult(raw=True)
+ pdata, pflagger = SaQC(data, flags=flags_raw).flagAll(var1).flagAll(var2).getResult(raw=True)
for c in pflagger.columns:
assert pflagger[c].dtype == flagger[c].dtype
diff --git a/tests/funcs/test_constants_detection.py b/tests/funcs/test_constants_detection.py
index 6fcde58d1..d6b7a68f8 100644
--- a/tests/funcs/test_constants_detection.py
+++ b/tests/funcs/test_constants_detection.py
@@ -23,8 +23,8 @@ def test_constants_flagBasic(data):
field, *_ = data.columns
flagger = initFlagsLike(data)
data, flagger_result = flagConstants(data, field, flagger, window="15Min", thresh=0.1, flag=BAD)
- flags = flagger_result[field]
- assert np.all(flags[expected] == BAD)
+ flagscol = flagger_result[field]
+ assert np.all(flagscol[expected] == BAD)
def test_constants_flagVarianceBased(data):
diff --git a/tests/funcs/test_modelling.py b/tests/funcs/test_modelling.py
index 95574936a..de9f1efb8 100644
--- a/tests/funcs/test_modelling.py
+++ b/tests/funcs/test_modelling.py
@@ -54,20 +54,20 @@ def test_modelling_mask(dat):
common = dict(data=data, field=field, flagger=flagger, mode='periodic')
data_seasonal, flagger_seasonal = mask(**common, period_start="20:00", period_end="40:00", include_bounds=False)
- flags = flagger_seasonal[field]
- m = (20 <= flags.index.minute) & (flags.index.minute <= 40)
+ flagscol = flagger_seasonal[field]
+ m = (20 <= flagscol.index.minute) & (flagscol.index.minute <= 40)
assert all(flagger_seasonal[field][m] == UNFLAGGED)
assert all(data_seasonal[field][m].isna())
data_seasonal, flagger_seasonal = mask(**common, period_start="15:00:00", period_end="02:00:00")
- flags = flagger_seasonal[field]
- m = (15 <= flags.index.hour) & (flags.index.hour <= 2)
+ flagscol = flagger_seasonal[field]
+ m = (15 <= flagscol.index.hour) & (flagscol.index.hour <= 2)
assert all(flagger_seasonal[field][m] == UNFLAGGED)
assert all(data_seasonal[field][m].isna())
data_seasonal, flagger_seasonal = mask(**common, period_start="03T00:00:00", period_end="10T00:00:00")
- flags = flagger_seasonal[field]
- m = (3 <= flags.index.hour) & (flags.index.hour <= 10)
+ flagscol = flagger_seasonal[field]
+ m = (3 <= flagscol.index.hour) & (flagscol.index.hour <= 10)
assert all(flagger_seasonal[field][m] == UNFLAGGED)
assert all(data_seasonal[field][m].isna())
--
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