Sourcery refactored master branch #32
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| bads = [] | ||
| for i, row in df.iterrows(): | ||
| # print(_row_stats(row)) | ||
| if not _check_row_signal_quality(row, max_uv_abs, max_std): | ||
| bads.append(i) | ||
| bads = [ | ||
| i | ||
| for i, row in df.iterrows() | ||
| if not _check_row_signal_quality(row, max_uv_abs, max_std) | ||
| ] |
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Function _clean_signal_quality refactored with the following changes:
- Convert for loop into list comprehension (
list-comprehension)
This removes the following comments ( why? ):
# print(_row_stats(row))
| catmap = dict(((cls, i) for i, cls in enumerate(df["class"].cat.categories))) | ||
| catmap = {cls: i for i, cls in enumerate(df["class"].cat.categories)} |
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Function signal_ndarray refactored with the following changes:
- Replace list(), dict() or set() with comprehension (
collection-builtin-to-comprehension)
| assert all([v1 == v2 - 1 == v3 - 2 for v1, v2, v3 in zip(sa, sb, sc)]) | ||
| assert all(v1 == v2 - 1 == v3 - 2 for v1, v2, v3 in zip(sa, sb, sc)) |
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Function test_unison_shuffled_copies refactored with the following changes:
- Replace unneeded comprehension with generator (
comprehension-to-generator)
| votes.append(vote > 0.5) | ||
| else: | ||
| # Use the mean probability | ||
| vote = np.mean(predicted_proba[test][i_start : i_stop + 1, 1]) | ||
| votes.append(vote > 0.5) | ||
|
|
||
| votes.append(vote > 0.5) |
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Function aggregate_windows_to_epochs refactored with the following changes:
- Hoist repeated code outside conditional statement (
hoist-statement-from-if)
| raw = mne.io.RawArray(eeg_data, info) | ||
| return raw | ||
| return mne.io.RawArray(eeg_data, info) |
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Function load_demo refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| bads = [ch for ch, ok in checked.items() if not ok] | ||
| return bads | ||
| return [ch for ch, ok in checked.items() if not ok] |
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Function BrainflowDevice.check refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| # Subtract five seconds of settling time from beginning | ||
| # total_data = total_data[5 * self.sfreq :] | ||
| df = pd.DataFrame( | ||
| return pd.DataFrame( | ||
| total_data, | ||
| columns=["timestamps"] + ch_names + (["stim"] if self.markers else []), | ||
| ) | ||
| return df |
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Function BrainflowDevice.get_data refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
This removes the following comments ( why? ):
# total_data = total_data[5 * self.sfreq :]
# Subtract five seconds of settling time from beginning
| if self.stream_process: | ||
| return self.stream_process.exitcode is None | ||
| return False | ||
| return self.stream_process.exitcode is None if self.stream_process else False |
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Function MuseDevice.started refactored with the following changes:
- Lift code into else after jump in control flow (
reintroduce-else) - Replace if statement with if expression (
assign-if-exp)
| for i in range(5): | ||
| for _ in range(5): | ||
| for inlet in inlets: | ||
| inlet.pull(timeout=0.5) # type: ignore | ||
| inlets = [inlet for inlet in inlets if inlet.buffer.any()] # type: ignore | ||
| if inlets: | ||
| break | ||
| else: | ||
| logger.info("No inlets with data, trying again in a second...") | ||
| sleep(1) | ||
| logger.info("No inlets with data, trying again in a second...") | ||
| sleep(1) |
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Function MuseDevice._read_buffer refactored with the following changes:
- Replace unused for index with underscore (
for-index-underscore) - Remove unnecessary else after guard condition (
remove-unnecessary-else)
| bads = [ch for ch, ok in checked.items() if not ok] | ||
| return bads | ||
| return [ch for ch, ok in checked.items() if not ok] |
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Function MuseDevice.check refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
Sourcery Code Quality Report✅ Merging this PR will increase code quality in the affected files by 0.06%.
Here are some functions in these files that still need a tune-up:
Legend and ExplanationThe emojis denote the absolute quality of the code:
The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request. Please see our documentation here for details on how these metrics are calculated. We are actively working on this report - lots more documentation and extra metrics to come! Help us improve this quality report! |
Codecov Report
@@ Coverage Diff @@
## master #32 +/- ##
==========================================
- Coverage 65.93% 65.53% -0.40%
==========================================
Files 22 22
Lines 1224 1213 -11
==========================================
- Hits 807 795 -12
- Misses 417 418 +1
Continue to review full report at Codecov.
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Branch
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