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gh_patches_debug_36408 | rasdani/github-patches | git_diff | mne-tools__mne-bids-74 | You will be provided with a partial code base and an issue statement explaining a problem to resolve.
<issue>
Remove .gz extension for fif: It's no longer part of the validator
Throughout the current state of MNE BIDS, the file ending `.gz` is used as an identifier for FIF files:
https://github.com/mne-tools/mne-bids/blob/c73ce744d30be87645e1648754b488f7572307f3/mne_bids/meg_bids.py#L33-L34
Can we change this to `fif.gz`? I am just concerned, because other files can be `.gz` and have nothing to do with FIF.
</issue>
<code>
[start of mne_bids/io.py]
1 """Check whether a file format is supported by BIDS and then load it."""
2 # Authors: Mainak Jas <[email protected]>
3 # Alexandre Gramfort <[email protected]>
4 # Teon Brooks <[email protected]>
5 # Chris Holdgraf <[email protected]>
6 # Stefan Appelhoff <[email protected]>
7 #
8 # License: BSD (3-clause)
9 from mne import io
10 import os
11
12 ALLOWED_EXTENSIONS = ['.con', '.sqd', '.fif', '.gz', '.pdf', '.ds']
13
14
15 def _parse_ext(raw_fname, verbose=False):
16 """Split a filename into its name and extension."""
17 fname, ext = os.path.splitext(raw_fname)
18 # BTi data is the only file format that does not have a file extension
19 if ext == '':
20 if verbose is True:
21 print('Found no extension for raw file, assuming "BTi" format and '
22 'appending extension .pdf')
23 ext = '.pdf'
24 return fname, ext
25
26
27 def _read_raw(raw_fname, electrode=None, hsp=None, hpi=None, config=None,
28 verbose=None):
29 """Read a raw file into MNE, making inferences based on extension."""
30 fname, ext = _parse_ext(raw_fname)
31
32 # MEG File Types
33 # --------------
34 # KIT systems
35 if ext in ['.con', '.sqd']:
36 raw = io.read_raw_kit(raw_fname, elp=electrode, hsp=hsp,
37 mrk=hpi, preload=False)
38
39 # Neuromag or converted-to-fif systems
40 elif ext in ['.fif', '.gz']:
41 raw = io.read_raw_fif(raw_fname, preload=False)
42
43 # BTi systems
44 elif ext == '.pdf':
45 if os.path.isfile(raw_fname):
46 raw = io.read_raw_bti(raw_fname, config_fname=config,
47 head_shape_fname=hsp,
48 preload=False, verbose=verbose)
49
50 # CTF systems
51 elif ext == '.ds':
52 raw = io.read_raw_ctf(raw_fname)
53
54 # No supported data found ...
55 # ---------------------------
56 else:
57 raise ValueError("Raw file name extension must be one of %\n"
58 "Got %" % (ALLOWED_EXTENSIONS, ext))
59 return raw
60
[end of mne_bids/io.py]
[start of mne_bids/mne_bids.py]
1 """Make BIDS compatible directory structures and infer meta data from MNE."""
2 # Authors: Mainak Jas <[email protected]>
3 # Alexandre Gramfort <[email protected]>
4 # Teon Brooks <[email protected]>
5 # Chris Holdgraf <[email protected]>
6 # Stefan Appelhoff <[email protected]>
7 #
8 # License: BSD (3-clause)
9
10 import os
11 import shutil as sh
12 import pandas as pd
13 from collections import defaultdict, OrderedDict
14
15 import numpy as np
16 from mne.io.constants import FIFF
17 from mne.io.pick import channel_type
18 from mne.io import BaseRaw
19 from mne.channels.channels import _unit2human
20 from mne.externals.six import string_types
21
22 from datetime import datetime
23 from warnings import warn
24
25 from .utils import (make_bids_filename, make_bids_folders,
26 make_dataset_description, _write_json,
27 _read_events, _mkdir_p)
28 from .io import (_parse_ext, _read_raw, ALLOWED_EXTENSIONS)
29
30
31 ALLOWED_KINDS = ['meg', 'ieeg']
32 orientation = {'.sqd': 'ALS', '.con': 'ALS', '.fif': 'RAS', '.gz': 'RAS',
33 '.pdf': 'ALS', '.ds': 'ALS'}
34
35 units = {'.sqd': 'm', '.con': 'm', '.fif': 'm', '.gz': 'm', '.pdf': 'm',
36 '.ds': 'cm'}
37
38 manufacturers = {'.sqd': 'KIT/Yokogawa', '.con': 'KIT/Yokogawa',
39 '.fif': 'Elekta', '.gz': 'Elekta', '.pdf': '4D Magnes',
40 '.ds': 'CTF'}
41
42
43 def _channels_tsv(raw, fname, verbose):
44 """Create a channels.tsv file and save it.
45
46 Parameters
47 ----------
48 raw : instance of Raw
49 The data as MNE-Python Raw object.
50 fname : str
51 Filename to save the channels.tsv to.
52 verbose : bool
53 Set verbose output to true or false.
54
55 """
56 map_chs = defaultdict(lambda: 'OTHER')
57 map_chs.update(grad='MEGGRAD', mag='MEGMAG', stim='TRIG', eeg='EEG',
58 ecog='ECOG', seeg='SEEG', eog='EOG', ecg='ECG', misc='MISC',
59 resp='RESPONSE', ref_meg='REFMEG')
60 map_desc = defaultdict(lambda: 'Other type of channel')
61 map_desc.update(grad='Gradiometer', mag='Magnetometer',
62 stim='Trigger',
63 eeg='ElectroEncephaloGram',
64 ecog='Electrocorticography',
65 seeg='StereoEEG',
66 ecg='ElectroCardioGram',
67 eog='ElectrOculoGram', misc='Miscellaneous',
68 ref_meg='Reference channel')
69
70 status, ch_type, description = list(), list(), list()
71 for idx, ch in enumerate(raw.info['ch_names']):
72 status.append('bad' if ch in raw.info['bads'] else 'good')
73 ch_type.append(map_chs[channel_type(raw.info, idx)])
74 description.append(map_desc[channel_type(raw.info, idx)])
75 low_cutoff, high_cutoff = (raw.info['highpass'], raw.info['lowpass'])
76 units = [_unit2human.get(ch_i['unit'], 'n/a') for ch_i in raw.info['chs']]
77 units = [u if u not in ['NA'] else 'n/a' for u in units]
78 n_channels = raw.info['nchan']
79 sfreq = raw.info['sfreq']
80
81 df = pd.DataFrame(OrderedDict([
82 ('name', raw.info['ch_names']),
83 ('type', ch_type),
84 ('units', units),
85 ('description', description),
86 ('sampling_frequency', np.full((n_channels), sfreq)),
87 ('low_cutoff', np.full((n_channels), low_cutoff)),
88 ('high_cutoff', np.full((n_channels), high_cutoff)),
89 ('status', status)]))
90 df.to_csv(fname, sep='\t', index=False, na_rep='n/a')
91
92 if verbose:
93 print(os.linesep + "Writing '%s'..." % fname + os.linesep)
94 print(df.head())
95
96 return fname
97
98
99 def _events_tsv(events, raw, fname, trial_type, verbose):
100 """Create an events.tsv file and save it.
101
102 This function will write the mandatory 'onset', and 'duration' columns as
103 well as the optional 'event_value' and 'event_sample'. The 'event_value'
104 corresponds to the marker value as found in the TRIG channel of the
105 recording. In addition, the 'trial_type' field can be written.
106
107 Parameters
108 ----------
109 events : array, shape = (n_events, 3)
110 The first column contains the event time in samples and the third
111 column contains the event id. The second column is ignored for now but
112 typically contains the value of the trigger channel either immediately
113 before the event or immediately after.
114 raw : instance of Raw
115 The data as MNE-Python Raw object.
116 fname : str
117 Filename to save the events.tsv to.
118 event_id : dict | None
119 Dictionary mapping a brief description key to an event id (value). For
120 example {'Go': 1, 'No Go': 2}.
121 verbose : bool
122 Set verbose output to true or false.
123
124 Notes
125 -----
126 The function writes durations of zero for each event.
127
128 """
129 # Start by filling all data that we know into a df
130 first_samp = raw.first_samp
131 sfreq = raw.info['sfreq']
132 events[:, 0] -= first_samp
133
134 data = OrderedDict([('onset', events[:, 0]),
135 ('duration', np.zeros(events.shape[0])),
136 ('trial_type', events[:, 2]),
137 ('event_value', events[:, 2]),
138 ('event_sample', events[:, 0])])
139
140 df = pd.DataFrame.from_dict(data)
141
142 # Now check if trial_type is specified or should be removed
143 if trial_type:
144 trial_type_map = {v: k for k, v in trial_type.items()}
145 df.trial_type = df.trial_type.map(trial_type_map)
146 else:
147 df.drop(labels=['trial_type'], axis=1, inplace=True)
148
149 # Onset column needs to be specified in seconds
150 df.onset /= sfreq
151
152 # Save to file
153 df.to_csv(fname, sep='\t', index=False, na_rep='n/a')
154 if verbose:
155 print(os.linesep + "Writing '%s'..." % fname + os.linesep)
156 print(df.head())
157
158 return fname
159
160
161 def _scans_tsv(raw, raw_fname, fname, verbose):
162 """Create a scans.tsv file and save it.
163
164 Parameters
165 ----------
166 raw : instance of Raw
167 The data as MNE-Python Raw object.
168 raw_fname : str
169 Relative path to the raw data file.
170 fname : str
171 Filename to save the scans.tsv to.
172 verbose : bool
173 Set verbose output to true or false.
174
175 """
176 # get MEASurement date from the data info
177 meas_date = raw.info['meas_date']
178 if isinstance(meas_date, (np.ndarray, list)):
179 meas_date = meas_date[0]
180
181 if meas_date is None:
182 acq_time = 'n/a'
183 else:
184 acq_time = datetime.fromtimestamp(
185 meas_date).strftime('%Y-%m-%dT%H:%M:%S')
186
187 df = pd.DataFrame(data={'filename': ['%s' % raw_fname],
188 'acq_time': [acq_time]},
189 columns=['filename', 'acq_time'])
190
191 df.to_csv(fname, sep='\t', index=False, na_rep='n/a')
192
193 if verbose:
194 print(os.linesep + "Writing '%s'..." % fname + os.linesep)
195 print(df.head())
196
197 return fname
198
199
200 def _coordsystem_json(raw, unit, orient, manufacturer, fname, verbose):
201 """Create a coordsystem.json file and save it.
202
203 Parameters
204 ----------
205 raw : instance of Raw
206 The data as MNE-Python Raw object.
207 unit : str
208 Units to be used in the coordsystem specification.
209 orient : str
210 Used to define the coordinate system for the head coils.
211 manufacturer : str
212 Used to define the coordinate system for the MEG sensors.
213 fname : str
214 Filename to save the coordsystem.json to.
215 verbose : bool
216 Set verbose output to true or false.
217
218 """
219 dig = raw.info['dig']
220 coords = dict()
221 fids = {d['ident']: d for d in dig if d['kind'] ==
222 FIFF.FIFFV_POINT_CARDINAL}
223 if fids:
224 if FIFF.FIFFV_POINT_NASION in fids:
225 coords['NAS'] = fids[FIFF.FIFFV_POINT_NASION]['r'].tolist()
226 if FIFF.FIFFV_POINT_LPA in fids:
227 coords['LPA'] = fids[FIFF.FIFFV_POINT_LPA]['r'].tolist()
228 if FIFF.FIFFV_POINT_RPA in fids:
229 coords['RPA'] = fids[FIFF.FIFFV_POINT_RPA]['r'].tolist()
230
231 hpi = {d['ident']: d for d in dig if d['kind'] == FIFF.FIFFV_POINT_HPI}
232 if hpi:
233 for ident in hpi.keys():
234 coords['coil%d' % ident] = hpi[ident]['r'].tolist()
235
236 coord_frame = set([dig[ii]['coord_frame'] for ii in range(len(dig))])
237 if len(coord_frame) > 1:
238 err = 'All HPI and Fiducials must be in the same coordinate frame.'
239 raise ValueError(err)
240
241 fid_json = {'MEGCoordinateSystem': manufacturer,
242 'MEGCoordinateUnits': unit, # XXX validate this
243 'HeadCoilCoordinates': coords,
244 'HeadCoilCoordinateSystem': orient,
245 'HeadCoilCoordinateUnits': unit # XXX validate this
246 }
247 _write_json(fid_json, fname)
248
249 return fname
250
251
252 def _sidecar_json(raw, task, manufacturer, fname, kind,
253 verbose=True):
254 """Create a sidecar json file depending on the kind and save it.
255
256 The sidecar json file provides meta data about the data of a certain kind.
257
258 Parameters
259 ----------
260 raw : instance of Raw
261 The data as MNE-Python Raw object.
262 task : str
263 Name of the task the data is based on.
264 manufacturer : str
265 Manufacturer of the acquisition system. For MEG also used to define the
266 coordinate system for the MEG sensors.
267 fname : str
268 Filename to save the sidecar json to.
269 kind : str
270 Type of the data as in ALLOWED_KINDS.
271 verbose : bool
272 Set verbose output to true or false. Defaults to true.
273
274 """
275 sfreq = raw.info['sfreq']
276 powerlinefrequency = raw.info.get('line_freq', None)
277 if powerlinefrequency is None:
278 warn('No line frequency found, defaulting to 50 Hz')
279 powerlinefrequency = 50
280
281 n_megchan = len([ch for ch in raw.info['chs']
282 if ch['kind'] == FIFF.FIFFV_MEG_CH])
283 n_megrefchan = len([ch for ch in raw.info['chs']
284 if ch['kind'] == FIFF.FIFFV_REF_MEG_CH])
285 n_eegchan = len([ch for ch in raw.info['chs']
286 if ch['kind'] == FIFF.FIFFV_EEG_CH])
287 n_ecogchan = len([ch for ch in raw.info['chs']
288 if ch['kind'] == FIFF.FIFFV_ECOG_CH])
289 n_seegchan = len([ch for ch in raw.info['chs']
290 if ch['kind'] == FIFF.FIFFV_SEEG_CH])
291 n_eogchan = len([ch for ch in raw.info['chs']
292 if ch['kind'] == FIFF.FIFFV_EOG_CH])
293 n_ecgchan = len([ch for ch in raw.info['chs']
294 if ch['kind'] == FIFF.FIFFV_ECG_CH])
295 n_emgchan = len([ch for ch in raw.info['chs']
296 if ch['kind'] == FIFF.FIFFV_EMG_CH])
297 n_miscchan = len([ch for ch in raw.info['chs']
298 if ch['kind'] == FIFF.FIFFV_MISC_CH])
299 n_stimchan = len([ch for ch in raw.info['chs']
300 if ch['kind'] == FIFF.FIFFV_STIM_CH])
301
302 # Define modality-specific JSON dictionaries
303 ch_info_json_common = [
304 ('TaskName', task),
305 ('Manufacturer', manufacturer),
306 ('PowerLineFrequency', powerlinefrequency)]
307 ch_info_json_meg = [
308 ('SamplingFrequency', sfreq),
309 ("DewarPosition", "XXX"),
310 ("DigitizedLandmarks", False),
311 ("DigitizedHeadPoints", False),
312 ("SoftwareFilters", "n/a"),
313 ('MEGChannelCount', n_megchan),
314 ('MEGREFChannelCount', n_megrefchan)]
315 ch_info_json_ieeg = [
316 ('ECOGChannelCount', n_ecogchan),
317 ('SEEGChannelCount', n_seegchan)]
318 ch_info_ch_counts = [
319 ('EEGChannelCount', n_eegchan),
320 ('EOGChannelCount', n_eogchan),
321 ('ECGChannelCount', n_ecgchan),
322 ('EMGChannelCount', n_emgchan),
323 ('MiscChannelCount', n_miscchan),
324 ('TriggerChannelCount', n_stimchan)]
325
326 # Stitch together the complete JSON dictionary
327 ch_info_json = ch_info_json_common
328 if kind == 'meg':
329 append_kind_json = ch_info_json_meg
330 elif kind == 'ieeg':
331 append_kind_json = ch_info_json_ieeg
332 else:
333 raise ValueError('Unexpected "kind": {}'
334 ' Use one of: {}'.format(kind, ALLOWED_KINDS))
335
336 ch_info_json += append_kind_json
337 ch_info_json += ch_info_ch_counts
338 ch_info_json = OrderedDict(ch_info_json)
339
340 _write_json(ch_info_json, fname, verbose=verbose)
341 return fname
342
343
344 def raw_to_bids(subject_id, task, raw_file, output_path, session_id=None,
345 run=None, kind='meg', events_data=None, event_id=None,
346 hpi=None, electrode=None, hsp=None, config=None,
347 overwrite=True, verbose=True):
348 """Walk over a folder of files and create BIDS compatible folder.
349
350 Parameters
351 ----------
352 subject_id : str
353 The subject name in BIDS compatible format ('01', '02', etc.)
354 task : str
355 Name of the task the data is based on.
356 raw_file : str | instance of mne.Raw
357 The raw data. If a string, it is assumed to be the path to the raw data
358 file. Otherwise it must be an instance of mne.Raw
359 output_path : str
360 The path of the BIDS compatible folder
361 session_id : str | None
362 The session name in BIDS compatible format.
363 run : int | None
364 The run number for this dataset.
365 kind : str, one of ('meg', 'ieeg')
366 The kind of data being converted. Defaults to "meg".
367 events_data : str | array | None
368 The events file. If a string, a path to the events file. If an array,
369 the MNE events array (shape n_events, 3). If None, events will be
370 inferred from the stim channel using `mne.find_events`.
371 event_id : dict | None
372 The event id dict used to create a 'trial_type' column in events.tsv
373 hpi : None | str | list of str
374 Marker points representing the location of the marker coils with
375 respect to the MEG Sensors, or path to a marker file.
376 If list, all of the markers will be averaged together.
377 electrode : None | str
378 Digitizer points representing the location of the fiducials and the
379 marker coils with respect to the digitized head shape, or path to a
380 file containing these points.
381 hsp : None | str | array, shape = (n_points, 3)
382 Digitizer head shape points, or path to head shape file. If more than
383 10`000 points are in the head shape, they are automatically decimated.
384 config : str | None
385 A path to the configuration file to use if the data is from a BTi
386 system.
387 overwrite : bool
388 If the file already exists, whether to overwrite it.
389 verbose : bool
390 If verbose is True, this will print a snippet of the sidecar files. If
391 False, no content will be printed.
392
393 """
394 if isinstance(raw_file, string_types):
395 # We must read in the raw data
396 raw = _read_raw(raw_file, electrode=electrode, hsp=hsp, hpi=hpi,
397 config=config, verbose=verbose)
398 _, ext = _parse_ext(raw_file, verbose=verbose)
399 raw_fname = raw_file
400 elif isinstance(raw_file, BaseRaw):
401 # We got a raw mne object, get back the filename if possible
402 # Assume that if no filename attr exists, it's a fif file.
403 raw = raw_file.copy()
404 if hasattr(raw, 'filenames'):
405 _, ext = _parse_ext(raw.filenames[0], verbose=verbose)
406 raw_fname = raw.filenames[0]
407 else:
408 # FIXME: How to get the filename if no filenames attribute?
409 raw_fname = 'unknown_file_name'
410 ext = '.fif'
411 else:
412 raise ValueError('raw_file must be an instance of str or BaseRaw, '
413 'got %s' % type(raw_file))
414 data_path = make_bids_folders(subject=subject_id, session=session_id,
415 kind=kind, root=output_path,
416 overwrite=overwrite,
417 verbose=verbose)
418 if session_id is None:
419 ses_path = data_path
420 else:
421 ses_path = make_bids_folders(subject=subject_id, session=session_id,
422 root=output_path,
423 overwrite=False,
424 verbose=verbose)
425
426 # create filenames
427 scans_fname = make_bids_filename(
428 subject=subject_id, session=session_id, suffix='scans.tsv',
429 prefix=ses_path)
430
431 coordsystem_fname = make_bids_filename(
432 subject=subject_id, session=session_id,
433 suffix='coordsystem.json', prefix=data_path)
434 data_meta_fname = make_bids_filename(
435 subject=subject_id, session=session_id, task=task, run=run,
436 suffix='%s.json' % kind, prefix=data_path)
437 if ext in ['.fif', '.gz', '.ds']:
438 raw_file_bids = make_bids_filename(
439 subject=subject_id, session=session_id, task=task, run=run,
440 suffix='%s%s' % (kind, ext))
441 else:
442 raw_folder = make_bids_filename(
443 subject=subject_id, session=session_id, task=task, run=run,
444 suffix='%s' % kind)
445 raw_file_bids = make_bids_filename(
446 subject=subject_id, session=session_id, task=task, run=run,
447 suffix='%s%s' % (kind, ext), prefix=raw_folder)
448 events_tsv_fname = make_bids_filename(
449 subject=subject_id, session=session_id, task=task,
450 run=run, suffix='events.tsv', prefix=data_path)
451 channels_fname = make_bids_filename(
452 subject=subject_id, session=session_id, task=task, run=run,
453 suffix='channels.tsv', prefix=data_path)
454
455 # Read in Raw object and extract metadata from Raw object if needed
456 if kind == 'meg':
457 orient = orientation[ext]
458 unit = units[ext]
459 manufacturer = manufacturers[ext]
460 else:
461 orient = 'n/a'
462 unit = 'n/a'
463 manufacturer = 'n/a'
464
465 # save stuff
466 if kind == 'meg':
467 _scans_tsv(raw, os.path.join(kind, raw_file_bids), scans_fname,
468 verbose)
469 _coordsystem_json(raw, unit, orient, manufacturer, coordsystem_fname,
470 verbose)
471
472 make_dataset_description(output_path, name=" ",
473 verbose=verbose)
474 _sidecar_json(raw, task, manufacturer, data_meta_fname, kind,
475 verbose)
476 _channels_tsv(raw, channels_fname, verbose)
477
478 events = _read_events(events_data, raw)
479 if len(events) > 0:
480 _events_tsv(events, raw, events_tsv_fname, event_id, verbose)
481
482 # set the raw file name to now be the absolute path to ensure the files
483 # are placed in the right location
484 raw_file_bids = os.path.join(data_path, raw_file_bids)
485 if os.path.exists(raw_file_bids) and not overwrite:
486 raise ValueError('"%s" already exists. Please set'
487 ' overwrite to True.' % raw_file_bids)
488 _mkdir_p(os.path.dirname(raw_file_bids))
489
490 if verbose:
491 print('Writing data files to %s' % raw_file_bids)
492
493 if ext not in ALLOWED_EXTENSIONS:
494 raise ValueError('ext must be in %s, got %s'
495 % (''.join(ALLOWED_EXTENSIONS), ext))
496
497 # for FIF, we need to re-save the file to fix the file pointer
498 # for files with multiple parts
499 if ext in ['.fif', '.gz']:
500 raw.save(raw_file_bids, overwrite=overwrite)
501 elif ext == '.ds':
502 sh.copytree(raw_fname, raw_file_bids)
503 else:
504 sh.copyfile(raw_fname, raw_file_bids)
505
506 return output_path
507
[end of mne_bids/mne_bids.py]
</code>
I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
<patch>
diff --git a/file.py b/file.py
--- a/file.py
+++ b/file.py
@@ -1,27 +1,35 @@
def euclidean(a, b):
- while b:
- a, b = b, a % b
- return a
+ if b == 0:
+ return a
+ return euclidean(b, a % b)
def bresenham(x0, y0, x1, y1):
points = []
dx = abs(x1 - x0)
dy = abs(y1 - y0)
- sx = 1 if x0 < x1 else -1
- sy = 1 if y0 < y1 else -1
- err = dx - dy
+ x, y = x0, y0
+ sx = -1 if x0 > x1 else 1
+ sy = -1 if y0 > y1 else 1
- while True:
- points.append((x0, y0))
- if x0 == x1 and y0 == y1:
- break
- e2 = 2 * err
- if e2 > -dy:
- err -= dy
- x0 += sx
- if e2 < dx:
- err += dx
- y0 += sy
+ if dx > dy:
+ err = dx / 2.0
+ while x != x1:
+ points.append((x, y))
+ err -= dy
+ if err < 0:
+ y += sy
+ err += dx
+ x += sx
+ else:
+ err = dy / 2.0
+ while y != y1:
+ points.append((x, y))
+ err -= dx
+ if err < 0:
+ x += sx
+ err += dy
+ y += sy
+
+ points.append((x, y))
return points
</patch> | diff --git a/mne_bids/io.py b/mne_bids/io.py
--- a/mne_bids/io.py
+++ b/mne_bids/io.py
@@ -9,7 +9,7 @@
from mne import io
import os
-ALLOWED_EXTENSIONS = ['.con', '.sqd', '.fif', '.gz', '.pdf', '.ds']
+ALLOWED_EXTENSIONS = ['.con', '.sqd', '.fif', '.pdf', '.ds']
def _parse_ext(raw_fname, verbose=False):
@@ -37,7 +37,7 @@
mrk=hpi, preload=False)
# Neuromag or converted-to-fif systems
- elif ext in ['.fif', '.gz']:
+ elif ext in ['.fif']:
raw = io.read_raw_fif(raw_fname, preload=False)
# BTi systems
diff --git a/mne_bids/mne_bids.py b/mne_bids/mne_bids.py
--- a/mne_bids/mne_bids.py
+++ b/mne_bids/mne_bids.py
@@ -29,15 +29,13 @@
ALLOWED_KINDS = ['meg', 'ieeg']
-orientation = {'.sqd': 'ALS', '.con': 'ALS', '.fif': 'RAS', '.gz': 'RAS',
- '.pdf': 'ALS', '.ds': 'ALS'}
+orientation = {'.sqd': 'ALS', '.con': 'ALS', '.fif': 'RAS', '.pdf': 'ALS',
+ '.ds': 'ALS'}
-units = {'.sqd': 'm', '.con': 'm', '.fif': 'm', '.gz': 'm', '.pdf': 'm',
- '.ds': 'cm'}
+units = {'.sqd': 'm', '.con': 'm', '.fif': 'm', '.pdf': 'm', '.ds': 'cm'}
manufacturers = {'.sqd': 'KIT/Yokogawa', '.con': 'KIT/Yokogawa',
- '.fif': 'Elekta', '.gz': 'Elekta', '.pdf': '4D Magnes',
- '.ds': 'CTF'}
+ '.fif': 'Elekta', '.pdf': '4D Magnes', '.ds': 'CTF'}
def _channels_tsv(raw, fname, verbose):
@@ -434,7 +432,7 @@
data_meta_fname = make_bids_filename(
subject=subject_id, session=session_id, task=task, run=run,
suffix='%s.json' % kind, prefix=data_path)
- if ext in ['.fif', '.gz', '.ds']:
+ if ext in ['.fif', '.ds']:
raw_file_bids = make_bids_filename(
subject=subject_id, session=session_id, task=task, run=run,
suffix='%s%s' % (kind, ext))
@@ -496,7 +494,7 @@
# for FIF, we need to re-save the file to fix the file pointer
# for files with multiple parts
- if ext in ['.fif', '.gz']:
+ if ext in ['.fif']:
raw.save(raw_file_bids, overwrite=overwrite)
elif ext == '.ds':
sh.copytree(raw_fname, raw_file_bids)
| {"golden_diff": "diff --git a/mne_bids/io.py b/mne_bids/io.py\n--- a/mne_bids/io.py\n+++ b/mne_bids/io.py\n@@ -9,7 +9,7 @@\n from mne import io\n import os\n \n-ALLOWED_EXTENSIONS = ['.con', '.sqd', '.fif', '.gz', '.pdf', '.ds']\n+ALLOWED_EXTENSIONS = ['.con', '.sqd', '.fif', '.pdf', '.ds']\n \n \n def _parse_ext(raw_fname, verbose=False):\n@@ -37,7 +37,7 @@\n mrk=hpi, preload=False)\n \n # Neuromag or converted-to-fif systems\n- elif ext in ['.fif', '.gz']:\n+ elif ext in ['.fif']:\n raw = io.read_raw_fif(raw_fname, preload=False)\n \n # BTi systems\ndiff --git a/mne_bids/mne_bids.py b/mne_bids/mne_bids.py\n--- a/mne_bids/mne_bids.py\n+++ b/mne_bids/mne_bids.py\n@@ -29,15 +29,13 @@\n \n \n ALLOWED_KINDS = ['meg', 'ieeg']\n-orientation = {'.sqd': 'ALS', '.con': 'ALS', '.fif': 'RAS', '.gz': 'RAS',\n- '.pdf': 'ALS', '.ds': 'ALS'}\n+orientation = {'.sqd': 'ALS', '.con': 'ALS', '.fif': 'RAS', '.pdf': 'ALS',\n+ '.ds': 'ALS'}\n \n-units = {'.sqd': 'm', '.con': 'm', '.fif': 'm', '.gz': 'm', '.pdf': 'm',\n- '.ds': 'cm'}\n+units = {'.sqd': 'm', '.con': 'm', '.fif': 'm', '.pdf': 'm', '.ds': 'cm'}\n \n manufacturers = {'.sqd': 'KIT/Yokogawa', '.con': 'KIT/Yokogawa',\n- '.fif': 'Elekta', '.gz': 'Elekta', '.pdf': '4D Magnes',\n- '.ds': 'CTF'}\n+ '.fif': 'Elekta', '.pdf': '4D Magnes', '.ds': 'CTF'}\n \n \n def _channels_tsv(raw, fname, verbose):\n@@ -434,7 +432,7 @@\n data_meta_fname = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='%s.json' % kind, prefix=data_path)\n- if ext in ['.fif', '.gz', '.ds']:\n+ if ext in ['.fif', '.ds']:\n raw_file_bids = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='%s%s' % (kind, ext))\n@@ -496,7 +494,7 @@\n \n # for FIF, we need to re-save the file to fix the file pointer\n # for files with multiple parts\n- if ext in ['.fif', '.gz']:\n+ if ext in ['.fif']:\n raw.save(raw_file_bids, overwrite=overwrite)\n elif ext == '.ds':\n sh.copytree(raw_fname, raw_file_bids)\n", "issue": "Remove .gz extension for fif: It's no longer part of the validator\nThroughout the current state of MNE BIDS, the file ending `.gz` is used as an identifier for FIF files:\r\n\r\nhttps://github.com/mne-tools/mne-bids/blob/c73ce744d30be87645e1648754b488f7572307f3/mne_bids/meg_bids.py#L33-L34\r\n\r\nCan we change this to `fif.gz`? I am just concerned, because other files can be `.gz` and have nothing to do with FIF.\n", "before_files": [{"content": "\"\"\"Check whether a file format is supported by BIDS and then load it.\"\"\"\n# Authors: Mainak Jas <[email protected]>\n# Alexandre Gramfort <[email protected]>\n# Teon Brooks <[email protected]>\n# Chris Holdgraf <[email protected]>\n# Stefan Appelhoff <[email protected]>\n#\n# License: BSD (3-clause)\nfrom mne import io\nimport os\n\nALLOWED_EXTENSIONS = ['.con', '.sqd', '.fif', '.gz', '.pdf', '.ds']\n\n\ndef _parse_ext(raw_fname, verbose=False):\n \"\"\"Split a filename into its name and extension.\"\"\"\n fname, ext = os.path.splitext(raw_fname)\n # BTi data is the only file format that does not have a file extension\n if ext == '':\n if verbose is True:\n print('Found no extension for raw file, assuming \"BTi\" format and '\n 'appending extension .pdf')\n ext = '.pdf'\n return fname, ext\n\n\ndef _read_raw(raw_fname, electrode=None, hsp=None, hpi=None, config=None,\n verbose=None):\n \"\"\"Read a raw file into MNE, making inferences based on extension.\"\"\"\n fname, ext = _parse_ext(raw_fname)\n\n # MEG File Types\n # --------------\n # KIT systems\n if ext in ['.con', '.sqd']:\n raw = io.read_raw_kit(raw_fname, elp=electrode, hsp=hsp,\n mrk=hpi, preload=False)\n\n # Neuromag or converted-to-fif systems\n elif ext in ['.fif', '.gz']:\n raw = io.read_raw_fif(raw_fname, preload=False)\n\n # BTi systems\n elif ext == '.pdf':\n if os.path.isfile(raw_fname):\n raw = io.read_raw_bti(raw_fname, config_fname=config,\n head_shape_fname=hsp,\n preload=False, verbose=verbose)\n\n # CTF systems\n elif ext == '.ds':\n raw = io.read_raw_ctf(raw_fname)\n\n # No supported data found ...\n # ---------------------------\n else:\n raise ValueError(\"Raw file name extension must be one of %\\n\"\n \"Got %\" % (ALLOWED_EXTENSIONS, ext))\n return raw\n", "path": "mne_bids/io.py"}, {"content": "\"\"\"Make BIDS compatible directory structures and infer meta data from MNE.\"\"\"\n# Authors: Mainak Jas <[email protected]>\n# Alexandre Gramfort <[email protected]>\n# Teon Brooks <[email protected]>\n# Chris Holdgraf <[email protected]>\n# Stefan Appelhoff <[email protected]>\n#\n# License: BSD (3-clause)\n\nimport os\nimport shutil as sh\nimport pandas as pd\nfrom collections import defaultdict, OrderedDict\n\nimport numpy as np\nfrom mne.io.constants import FIFF\nfrom mne.io.pick import channel_type\nfrom mne.io import BaseRaw\nfrom mne.channels.channels import _unit2human\nfrom mne.externals.six import string_types\n\nfrom datetime import datetime\nfrom warnings import warn\n\nfrom .utils import (make_bids_filename, make_bids_folders,\n make_dataset_description, _write_json,\n _read_events, _mkdir_p)\nfrom .io import (_parse_ext, _read_raw, ALLOWED_EXTENSIONS)\n\n\nALLOWED_KINDS = ['meg', 'ieeg']\norientation = {'.sqd': 'ALS', '.con': 'ALS', '.fif': 'RAS', '.gz': 'RAS',\n '.pdf': 'ALS', '.ds': 'ALS'}\n\nunits = {'.sqd': 'm', '.con': 'm', '.fif': 'm', '.gz': 'm', '.pdf': 'm',\n '.ds': 'cm'}\n\nmanufacturers = {'.sqd': 'KIT/Yokogawa', '.con': 'KIT/Yokogawa',\n '.fif': 'Elekta', '.gz': 'Elekta', '.pdf': '4D Magnes',\n '.ds': 'CTF'}\n\n\ndef _channels_tsv(raw, fname, verbose):\n \"\"\"Create a channels.tsv file and save it.\n\n Parameters\n ----------\n raw : instance of Raw\n The data as MNE-Python Raw object.\n fname : str\n Filename to save the channels.tsv to.\n verbose : bool\n Set verbose output to true or false.\n\n \"\"\"\n map_chs = defaultdict(lambda: 'OTHER')\n map_chs.update(grad='MEGGRAD', mag='MEGMAG', stim='TRIG', eeg='EEG',\n ecog='ECOG', seeg='SEEG', eog='EOG', ecg='ECG', misc='MISC',\n resp='RESPONSE', ref_meg='REFMEG')\n map_desc = defaultdict(lambda: 'Other type of channel')\n map_desc.update(grad='Gradiometer', mag='Magnetometer',\n stim='Trigger',\n eeg='ElectroEncephaloGram',\n ecog='Electrocorticography',\n seeg='StereoEEG',\n ecg='ElectroCardioGram',\n eog='ElectrOculoGram', misc='Miscellaneous',\n ref_meg='Reference channel')\n\n status, ch_type, description = list(), list(), list()\n for idx, ch in enumerate(raw.info['ch_names']):\n status.append('bad' if ch in raw.info['bads'] else 'good')\n ch_type.append(map_chs[channel_type(raw.info, idx)])\n description.append(map_desc[channel_type(raw.info, idx)])\n low_cutoff, high_cutoff = (raw.info['highpass'], raw.info['lowpass'])\n units = [_unit2human.get(ch_i['unit'], 'n/a') for ch_i in raw.info['chs']]\n units = [u if u not in ['NA'] else 'n/a' for u in units]\n n_channels = raw.info['nchan']\n sfreq = raw.info['sfreq']\n\n df = pd.DataFrame(OrderedDict([\n ('name', raw.info['ch_names']),\n ('type', ch_type),\n ('units', units),\n ('description', description),\n ('sampling_frequency', np.full((n_channels), sfreq)),\n ('low_cutoff', np.full((n_channels), low_cutoff)),\n ('high_cutoff', np.full((n_channels), high_cutoff)),\n ('status', status)]))\n df.to_csv(fname, sep='\\t', index=False, na_rep='n/a')\n\n if verbose:\n print(os.linesep + \"Writing '%s'...\" % fname + os.linesep)\n print(df.head())\n\n return fname\n\n\ndef _events_tsv(events, raw, fname, trial_type, verbose):\n \"\"\"Create an events.tsv file and save it.\n\n This function will write the mandatory 'onset', and 'duration' columns as\n well as the optional 'event_value' and 'event_sample'. The 'event_value'\n corresponds to the marker value as found in the TRIG channel of the\n recording. In addition, the 'trial_type' field can be written.\n\n Parameters\n ----------\n events : array, shape = (n_events, 3)\n The first column contains the event time in samples and the third\n column contains the event id. The second column is ignored for now but\n typically contains the value of the trigger channel either immediately\n before the event or immediately after.\n raw : instance of Raw\n The data as MNE-Python Raw object.\n fname : str\n Filename to save the events.tsv to.\n event_id : dict | None\n Dictionary mapping a brief description key to an event id (value). For\n example {'Go': 1, 'No Go': 2}.\n verbose : bool\n Set verbose output to true or false.\n\n Notes\n -----\n The function writes durations of zero for each event.\n\n \"\"\"\n # Start by filling all data that we know into a df\n first_samp = raw.first_samp\n sfreq = raw.info['sfreq']\n events[:, 0] -= first_samp\n\n data = OrderedDict([('onset', events[:, 0]),\n ('duration', np.zeros(events.shape[0])),\n ('trial_type', events[:, 2]),\n ('event_value', events[:, 2]),\n ('event_sample', events[:, 0])])\n\n df = pd.DataFrame.from_dict(data)\n\n # Now check if trial_type is specified or should be removed\n if trial_type:\n trial_type_map = {v: k for k, v in trial_type.items()}\n df.trial_type = df.trial_type.map(trial_type_map)\n else:\n df.drop(labels=['trial_type'], axis=1, inplace=True)\n\n # Onset column needs to be specified in seconds\n df.onset /= sfreq\n\n # Save to file\n df.to_csv(fname, sep='\\t', index=False, na_rep='n/a')\n if verbose:\n print(os.linesep + \"Writing '%s'...\" % fname + os.linesep)\n print(df.head())\n\n return fname\n\n\ndef _scans_tsv(raw, raw_fname, fname, verbose):\n \"\"\"Create a scans.tsv file and save it.\n\n Parameters\n ----------\n raw : instance of Raw\n The data as MNE-Python Raw object.\n raw_fname : str\n Relative path to the raw data file.\n fname : str\n Filename to save the scans.tsv to.\n verbose : bool\n Set verbose output to true or false.\n\n \"\"\"\n # get MEASurement date from the data info\n meas_date = raw.info['meas_date']\n if isinstance(meas_date, (np.ndarray, list)):\n meas_date = meas_date[0]\n\n if meas_date is None:\n acq_time = 'n/a'\n else:\n acq_time = datetime.fromtimestamp(\n meas_date).strftime('%Y-%m-%dT%H:%M:%S')\n\n df = pd.DataFrame(data={'filename': ['%s' % raw_fname],\n 'acq_time': [acq_time]},\n columns=['filename', 'acq_time'])\n\n df.to_csv(fname, sep='\\t', index=False, na_rep='n/a')\n\n if verbose:\n print(os.linesep + \"Writing '%s'...\" % fname + os.linesep)\n print(df.head())\n\n return fname\n\n\ndef _coordsystem_json(raw, unit, orient, manufacturer, fname, verbose):\n \"\"\"Create a coordsystem.json file and save it.\n\n Parameters\n ----------\n raw : instance of Raw\n The data as MNE-Python Raw object.\n unit : str\n Units to be used in the coordsystem specification.\n orient : str\n Used to define the coordinate system for the head coils.\n manufacturer : str\n Used to define the coordinate system for the MEG sensors.\n fname : str\n Filename to save the coordsystem.json to.\n verbose : bool\n Set verbose output to true or false.\n\n \"\"\"\n dig = raw.info['dig']\n coords = dict()\n fids = {d['ident']: d for d in dig if d['kind'] ==\n FIFF.FIFFV_POINT_CARDINAL}\n if fids:\n if FIFF.FIFFV_POINT_NASION in fids:\n coords['NAS'] = fids[FIFF.FIFFV_POINT_NASION]['r'].tolist()\n if FIFF.FIFFV_POINT_LPA in fids:\n coords['LPA'] = fids[FIFF.FIFFV_POINT_LPA]['r'].tolist()\n if FIFF.FIFFV_POINT_RPA in fids:\n coords['RPA'] = fids[FIFF.FIFFV_POINT_RPA]['r'].tolist()\n\n hpi = {d['ident']: d for d in dig if d['kind'] == FIFF.FIFFV_POINT_HPI}\n if hpi:\n for ident in hpi.keys():\n coords['coil%d' % ident] = hpi[ident]['r'].tolist()\n\n coord_frame = set([dig[ii]['coord_frame'] for ii in range(len(dig))])\n if len(coord_frame) > 1:\n err = 'All HPI and Fiducials must be in the same coordinate frame.'\n raise ValueError(err)\n\n fid_json = {'MEGCoordinateSystem': manufacturer,\n 'MEGCoordinateUnits': unit, # XXX validate this\n 'HeadCoilCoordinates': coords,\n 'HeadCoilCoordinateSystem': orient,\n 'HeadCoilCoordinateUnits': unit # XXX validate this\n }\n _write_json(fid_json, fname)\n\n return fname\n\n\ndef _sidecar_json(raw, task, manufacturer, fname, kind,\n verbose=True):\n \"\"\"Create a sidecar json file depending on the kind and save it.\n\n The sidecar json file provides meta data about the data of a certain kind.\n\n Parameters\n ----------\n raw : instance of Raw\n The data as MNE-Python Raw object.\n task : str\n Name of the task the data is based on.\n manufacturer : str\n Manufacturer of the acquisition system. For MEG also used to define the\n coordinate system for the MEG sensors.\n fname : str\n Filename to save the sidecar json to.\n kind : str\n Type of the data as in ALLOWED_KINDS.\n verbose : bool\n Set verbose output to true or false. Defaults to true.\n\n \"\"\"\n sfreq = raw.info['sfreq']\n powerlinefrequency = raw.info.get('line_freq', None)\n if powerlinefrequency is None:\n warn('No line frequency found, defaulting to 50 Hz')\n powerlinefrequency = 50\n\n n_megchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_MEG_CH])\n n_megrefchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_REF_MEG_CH])\n n_eegchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_EEG_CH])\n n_ecogchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_ECOG_CH])\n n_seegchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_SEEG_CH])\n n_eogchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_EOG_CH])\n n_ecgchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_ECG_CH])\n n_emgchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_EMG_CH])\n n_miscchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_MISC_CH])\n n_stimchan = len([ch for ch in raw.info['chs']\n if ch['kind'] == FIFF.FIFFV_STIM_CH])\n\n # Define modality-specific JSON dictionaries\n ch_info_json_common = [\n ('TaskName', task),\n ('Manufacturer', manufacturer),\n ('PowerLineFrequency', powerlinefrequency)]\n ch_info_json_meg = [\n ('SamplingFrequency', sfreq),\n (\"DewarPosition\", \"XXX\"),\n (\"DigitizedLandmarks\", False),\n (\"DigitizedHeadPoints\", False),\n (\"SoftwareFilters\", \"n/a\"),\n ('MEGChannelCount', n_megchan),\n ('MEGREFChannelCount', n_megrefchan)]\n ch_info_json_ieeg = [\n ('ECOGChannelCount', n_ecogchan),\n ('SEEGChannelCount', n_seegchan)]\n ch_info_ch_counts = [\n ('EEGChannelCount', n_eegchan),\n ('EOGChannelCount', n_eogchan),\n ('ECGChannelCount', n_ecgchan),\n ('EMGChannelCount', n_emgchan),\n ('MiscChannelCount', n_miscchan),\n ('TriggerChannelCount', n_stimchan)]\n\n # Stitch together the complete JSON dictionary\n ch_info_json = ch_info_json_common\n if kind == 'meg':\n append_kind_json = ch_info_json_meg\n elif kind == 'ieeg':\n append_kind_json = ch_info_json_ieeg\n else:\n raise ValueError('Unexpected \"kind\": {}'\n ' Use one of: {}'.format(kind, ALLOWED_KINDS))\n\n ch_info_json += append_kind_json\n ch_info_json += ch_info_ch_counts\n ch_info_json = OrderedDict(ch_info_json)\n\n _write_json(ch_info_json, fname, verbose=verbose)\n return fname\n\n\ndef raw_to_bids(subject_id, task, raw_file, output_path, session_id=None,\n run=None, kind='meg', events_data=None, event_id=None,\n hpi=None, electrode=None, hsp=None, config=None,\n overwrite=True, verbose=True):\n \"\"\"Walk over a folder of files and create BIDS compatible folder.\n\n Parameters\n ----------\n subject_id : str\n The subject name in BIDS compatible format ('01', '02', etc.)\n task : str\n Name of the task the data is based on.\n raw_file : str | instance of mne.Raw\n The raw data. If a string, it is assumed to be the path to the raw data\n file. Otherwise it must be an instance of mne.Raw\n output_path : str\n The path of the BIDS compatible folder\n session_id : str | None\n The session name in BIDS compatible format.\n run : int | None\n The run number for this dataset.\n kind : str, one of ('meg', 'ieeg')\n The kind of data being converted. Defaults to \"meg\".\n events_data : str | array | None\n The events file. If a string, a path to the events file. If an array,\n the MNE events array (shape n_events, 3). If None, events will be\n inferred from the stim channel using `mne.find_events`.\n event_id : dict | None\n The event id dict used to create a 'trial_type' column in events.tsv\n hpi : None | str | list of str\n Marker points representing the location of the marker coils with\n respect to the MEG Sensors, or path to a marker file.\n If list, all of the markers will be averaged together.\n electrode : None | str\n Digitizer points representing the location of the fiducials and the\n marker coils with respect to the digitized head shape, or path to a\n file containing these points.\n hsp : None | str | array, shape = (n_points, 3)\n Digitizer head shape points, or path to head shape file. If more than\n 10`000 points are in the head shape, they are automatically decimated.\n config : str | None\n A path to the configuration file to use if the data is from a BTi\n system.\n overwrite : bool\n If the file already exists, whether to overwrite it.\n verbose : bool\n If verbose is True, this will print a snippet of the sidecar files. If\n False, no content will be printed.\n\n \"\"\"\n if isinstance(raw_file, string_types):\n # We must read in the raw data\n raw = _read_raw(raw_file, electrode=electrode, hsp=hsp, hpi=hpi,\n config=config, verbose=verbose)\n _, ext = _parse_ext(raw_file, verbose=verbose)\n raw_fname = raw_file\n elif isinstance(raw_file, BaseRaw):\n # We got a raw mne object, get back the filename if possible\n # Assume that if no filename attr exists, it's a fif file.\n raw = raw_file.copy()\n if hasattr(raw, 'filenames'):\n _, ext = _parse_ext(raw.filenames[0], verbose=verbose)\n raw_fname = raw.filenames[0]\n else:\n # FIXME: How to get the filename if no filenames attribute?\n raw_fname = 'unknown_file_name'\n ext = '.fif'\n else:\n raise ValueError('raw_file must be an instance of str or BaseRaw, '\n 'got %s' % type(raw_file))\n data_path = make_bids_folders(subject=subject_id, session=session_id,\n kind=kind, root=output_path,\n overwrite=overwrite,\n verbose=verbose)\n if session_id is None:\n ses_path = data_path\n else:\n ses_path = make_bids_folders(subject=subject_id, session=session_id,\n root=output_path,\n overwrite=False,\n verbose=verbose)\n\n # create filenames\n scans_fname = make_bids_filename(\n subject=subject_id, session=session_id, suffix='scans.tsv',\n prefix=ses_path)\n\n coordsystem_fname = make_bids_filename(\n subject=subject_id, session=session_id,\n suffix='coordsystem.json', prefix=data_path)\n data_meta_fname = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='%s.json' % kind, prefix=data_path)\n if ext in ['.fif', '.gz', '.ds']:\n raw_file_bids = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='%s%s' % (kind, ext))\n else:\n raw_folder = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='%s' % kind)\n raw_file_bids = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='%s%s' % (kind, ext), prefix=raw_folder)\n events_tsv_fname = make_bids_filename(\n subject=subject_id, session=session_id, task=task,\n run=run, suffix='events.tsv', prefix=data_path)\n channels_fname = make_bids_filename(\n subject=subject_id, session=session_id, task=task, run=run,\n suffix='channels.tsv', prefix=data_path)\n\n # Read in Raw object and extract metadata from Raw object if needed\n if kind == 'meg':\n orient = orientation[ext]\n unit = units[ext]\n manufacturer = manufacturers[ext]\n else:\n orient = 'n/a'\n unit = 'n/a'\n manufacturer = 'n/a'\n\n # save stuff\n if kind == 'meg':\n _scans_tsv(raw, os.path.join(kind, raw_file_bids), scans_fname,\n verbose)\n _coordsystem_json(raw, unit, orient, manufacturer, coordsystem_fname,\n verbose)\n\n make_dataset_description(output_path, name=\" \",\n verbose=verbose)\n _sidecar_json(raw, task, manufacturer, data_meta_fname, kind,\n verbose)\n _channels_tsv(raw, channels_fname, verbose)\n\n events = _read_events(events_data, raw)\n if len(events) > 0:\n _events_tsv(events, raw, events_tsv_fname, event_id, verbose)\n\n # set the raw file name to now be the absolute path to ensure the files\n # are placed in the right location\n raw_file_bids = os.path.join(data_path, raw_file_bids)\n if os.path.exists(raw_file_bids) and not overwrite:\n raise ValueError('\"%s\" already exists. Please set'\n ' overwrite to True.' % raw_file_bids)\n _mkdir_p(os.path.dirname(raw_file_bids))\n\n if verbose:\n print('Writing data files to %s' % raw_file_bids)\n\n if ext not in ALLOWED_EXTENSIONS:\n raise ValueError('ext must be in %s, got %s'\n % (''.join(ALLOWED_EXTENSIONS), ext))\n\n # for FIF, we need to re-save the file to fix the file pointer\n # for files with multiple parts\n if ext in ['.fif', '.gz']:\n raw.save(raw_file_bids, overwrite=overwrite)\n elif ext == '.ds':\n sh.copytree(raw_fname, raw_file_bids)\n else:\n sh.copyfile(raw_fname, raw_file_bids)\n\n return output_path\n", "path": "mne_bids/mne_bids.py"}]} |
gh_patches_debug_32737 | rasdani/github-patches | git_diff | dask__dask-586 | You will be provided with a partial code base and an issue statement explaining a problem to resolve.
<issue>
Additional improvement for da.image.imread
I think following 2 improvements make the function better.
#### 1. Allow custom `imread` function.
Some prefer `opencv` which reads color in BGR order, otherwise `skimage` reads in RGB order. Adding `dialect` option (like `dialect='skimage'` or `dialect='cv'`) or accept different file read function may better.
#### 2. Allow custom preprocessing function.
In image processing, input images may have different sizes. In these case, preprocessing is needed between image read and array creation. This preprocessing function must return the same size of array on user's responsibility.
</issue>
<code>
[start of dask/array/image.py]
1 from glob import glob
2 import os
3
4 try:
5 from skimage.io import imread as sk_imread
6 except ImportError:
7 pass
8
9 from .core import Array
10 from ..base import tokenize
11
12 def add_leading_dimension(x):
13 return x[None, ...]
14
15
16 def imread(filename):
17 """ Read a stack of images into a dask array
18
19 Parameters
20 ----------
21
22 filename: string
23 A globstring like 'myfile.*.png'
24
25 Example
26 -------
27
28 >>> from dask.array.image import imread
29 >>> im = imread('2015-*-*.png') # doctest: +SKIP
30 >>> im.shape # doctest: +SKIP
31 (365, 1000, 1000, 3)
32
33 Returns
34 -------
35
36 Dask array of all images stacked along the first dimension. All images
37 will be treated as individual chunks
38 """
39 filenames = sorted(glob(filename))
40 if not filenames:
41 raise ValueError("No files found under name %s" % filename)
42
43 name = 'imread-%s' % tokenize(filenames, map(os.path.getmtime, filenames))
44
45 sample = sk_imread(filenames[0])
46
47 dsk = dict(((name, i) + (0,) * len(sample.shape),
48 (add_leading_dimension, (sk_imread, filename)))
49 for i, filename in enumerate(filenames))
50
51 chunks = ((1,) * len(filenames),) + tuple((d,) for d in sample.shape)
52
53 return Array(dsk, name, chunks, sample.dtype)
54
[end of dask/array/image.py]
</code>
I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
<patch>
diff --git a/file.py b/file.py
--- a/file.py
+++ b/file.py
@@ -1,27 +1,35 @@
def euclidean(a, b):
- while b:
- a, b = b, a % b
- return a
+ if b == 0:
+ return a
+ return euclidean(b, a % b)
def bresenham(x0, y0, x1, y1):
points = []
dx = abs(x1 - x0)
dy = abs(y1 - y0)
- sx = 1 if x0 < x1 else -1
- sy = 1 if y0 < y1 else -1
- err = dx - dy
+ x, y = x0, y0
+ sx = -1 if x0 > x1 else 1
+ sy = -1 if y0 > y1 else 1
- while True:
- points.append((x0, y0))
- if x0 == x1 and y0 == y1:
- break
- e2 = 2 * err
- if e2 > -dy:
- err -= dy
- x0 += sx
- if e2 < dx:
- err += dx
- y0 += sy
+ if dx > dy:
+ err = dx / 2.0
+ while x != x1:
+ points.append((x, y))
+ err -= dy
+ if err < 0:
+ y += sy
+ err += dx
+ x += sx
+ else:
+ err = dy / 2.0
+ while y != y1:
+ points.append((x, y))
+ err -= dx
+ if err < 0:
+ x += sx
+ err += dy
+ y += sy
+
+ points.append((x, y))
return points
</patch> | diff --git a/dask/array/image.py b/dask/array/image.py
--- a/dask/array/image.py
+++ b/dask/array/image.py
@@ -13,7 +13,7 @@
return x[None, ...]
-def imread(filename):
+def imread(filename, imread=None, preprocess=None):
""" Read a stack of images into a dask array
Parameters
@@ -21,6 +21,13 @@
filename: string
A globstring like 'myfile.*.png'
+ imread: function (optional)
+ Optionally provide custom imread function.
+ Function should expect a filename and produce a numpy array.
+ Defaults to ``skimage.io.imread``.
+ preprocess: function (optional)
+ Optionally provide custom function to preprocess the image.
+ Function should expect a numpy array for a single image.
Example
-------
@@ -36,17 +43,25 @@
Dask array of all images stacked along the first dimension. All images
will be treated as individual chunks
"""
+ imread = imread or sk_imread
filenames = sorted(glob(filename))
if not filenames:
raise ValueError("No files found under name %s" % filename)
name = 'imread-%s' % tokenize(filenames, map(os.path.getmtime, filenames))
- sample = sk_imread(filenames[0])
-
- dsk = dict(((name, i) + (0,) * len(sample.shape),
- (add_leading_dimension, (sk_imread, filename)))
- for i, filename in enumerate(filenames))
+ sample = imread(filenames[0])
+ if preprocess:
+ sample = preprocess(sample)
+
+ keys = [(name, i) + (0,) * len(sample.shape) for i in range(len(filenames))]
+ if preprocess:
+ values = [(add_leading_dimension, (preprocess, (imread, filename)))
+ for filename in filenames]
+ else:
+ values = [(add_leading_dimension, (imread, filename))
+ for filename in filenames]
+ dsk = dict(zip(keys, values))
chunks = ((1,) * len(filenames),) + tuple((d,) for d in sample.shape)
| {"golden_diff": "diff --git a/dask/array/image.py b/dask/array/image.py\n--- a/dask/array/image.py\n+++ b/dask/array/image.py\n@@ -13,7 +13,7 @@\n return x[None, ...]\n \n \n-def imread(filename):\n+def imread(filename, imread=None, preprocess=None):\n \"\"\" Read a stack of images into a dask array\n \n Parameters\n@@ -21,6 +21,13 @@\n \n filename: string\n A globstring like 'myfile.*.png'\n+ imread: function (optional)\n+ Optionally provide custom imread function.\n+ Function should expect a filename and produce a numpy array.\n+ Defaults to ``skimage.io.imread``.\n+ preprocess: function (optional)\n+ Optionally provide custom function to preprocess the image.\n+ Function should expect a numpy array for a single image.\n \n Example\n -------\n@@ -36,17 +43,25 @@\n Dask array of all images stacked along the first dimension. All images\n will be treated as individual chunks\n \"\"\"\n+ imread = imread or sk_imread\n filenames = sorted(glob(filename))\n if not filenames:\n raise ValueError(\"No files found under name %s\" % filename)\n \n name = 'imread-%s' % tokenize(filenames, map(os.path.getmtime, filenames))\n \n- sample = sk_imread(filenames[0])\n-\n- dsk = dict(((name, i) + (0,) * len(sample.shape),\n- (add_leading_dimension, (sk_imread, filename)))\n- for i, filename in enumerate(filenames))\n+ sample = imread(filenames[0])\n+ if preprocess:\n+ sample = preprocess(sample)\n+\n+ keys = [(name, i) + (0,) * len(sample.shape) for i in range(len(filenames))]\n+ if preprocess:\n+ values = [(add_leading_dimension, (preprocess, (imread, filename)))\n+ for filename in filenames]\n+ else:\n+ values = [(add_leading_dimension, (imread, filename))\n+ for filename in filenames]\n+ dsk = dict(zip(keys, values))\n \n chunks = ((1,) * len(filenames),) + tuple((d,) for d in sample.shape)\n", "issue": "Additional improvement for da.image.imread\nI think following 2 improvements make the function better.\n#### 1. Allow custom `imread` function.\n\nSome prefer `opencv` which reads color in BGR order, otherwise `skimage` reads in RGB order. Adding `dialect` option (like `dialect='skimage'` or `dialect='cv'`) or accept different file read function may better.\n#### 2. Allow custom preprocessing function.\n\nIn image processing, input images may have different sizes. In these case, preprocessing is needed between image read and array creation. This preprocessing function must return the same size of array on user's responsibility.\n\n", "before_files": [{"content": "from glob import glob\nimport os\n\ntry:\n from skimage.io import imread as sk_imread\nexcept ImportError:\n pass\n\nfrom .core import Array\nfrom ..base import tokenize\n\ndef add_leading_dimension(x):\n return x[None, ...]\n\n\ndef imread(filename):\n \"\"\" Read a stack of images into a dask array\n\n Parameters\n ----------\n\n filename: string\n A globstring like 'myfile.*.png'\n\n Example\n -------\n\n >>> from dask.array.image import imread\n >>> im = imread('2015-*-*.png') # doctest: +SKIP\n >>> im.shape # doctest: +SKIP\n (365, 1000, 1000, 3)\n\n Returns\n -------\n\n Dask array of all images stacked along the first dimension. All images\n will be treated as individual chunks\n \"\"\"\n filenames = sorted(glob(filename))\n if not filenames:\n raise ValueError(\"No files found under name %s\" % filename)\n\n name = 'imread-%s' % tokenize(filenames, map(os.path.getmtime, filenames))\n\n sample = sk_imread(filenames[0])\n\n dsk = dict(((name, i) + (0,) * len(sample.shape),\n (add_leading_dimension, (sk_imread, filename)))\n for i, filename in enumerate(filenames))\n\n chunks = ((1,) * len(filenames),) + tuple((d,) for d in sample.shape)\n\n return Array(dsk, name, chunks, sample.dtype)\n", "path": "dask/array/image.py"}]} |
gh_patches_debug_19722 | rasdani/github-patches | git_diff | iterative__dvc-7283 | You will be provided with a partial code base and an issue statement explaining a problem to resolve.
<issue>
'None' does not contain DVC directory
```console
cd "$(mktemp -d)"
dvc add foo # or any other command
```
</issue>
<code>
[start of dvc/repo/__init__.py]
1 import logging
2 import os
3 from collections import defaultdict
4 from contextlib import contextmanager
5 from functools import wraps
6 from typing import TYPE_CHECKING, Callable, Optional, Set
7
8 from funcy import cached_property
9
10 from dvc.exceptions import FileMissingError
11 from dvc.exceptions import IsADirectoryError as DvcIsADirectoryError
12 from dvc.exceptions import NotDvcRepoError, OutputNotFoundError
13 from dvc.ignore import DvcIgnoreFilter
14 from dvc.utils import env2bool
15 from dvc.utils.fs import path_isin
16
17 if TYPE_CHECKING:
18 from dvc.fs.base import FileSystem
19 from dvc.objects.file import HashFile
20 from dvc.repo.scm_context import SCMContext
21
22 logger = logging.getLogger(__name__)
23
24
25 @contextmanager
26 def lock_repo(repo: "Repo"):
27 # pylint: disable=protected-access
28 depth = repo._lock_depth
29 repo._lock_depth += 1
30
31 try:
32 if depth > 0:
33 yield
34 else:
35 with repo.lock:
36 repo._reset()
37 yield
38 # Graph cache is no longer valid after we release the repo.lock
39 repo._reset()
40 finally:
41 repo._lock_depth = depth
42
43
44 def locked(f):
45 @wraps(f)
46 def wrapper(repo, *args, **kwargs):
47 with lock_repo(repo):
48 return f(repo, *args, **kwargs)
49
50 return wrapper
51
52
53 class Repo:
54 DVC_DIR = ".dvc"
55
56 from dvc.repo.add import add
57 from dvc.repo.checkout import checkout
58 from dvc.repo.commit import commit
59 from dvc.repo.destroy import destroy
60 from dvc.repo.diff import diff
61 from dvc.repo.fetch import fetch
62 from dvc.repo.freeze import freeze, unfreeze
63 from dvc.repo.gc import gc
64 from dvc.repo.get import get as _get
65 from dvc.repo.get_url import get_url as _get_url
66 from dvc.repo.imp import imp
67 from dvc.repo.imp_url import imp_url
68 from dvc.repo.install import install
69 from dvc.repo.ls import ls as _ls
70 from dvc.repo.move import move
71 from dvc.repo.pull import pull
72 from dvc.repo.push import push
73 from dvc.repo.remove import remove
74 from dvc.repo.reproduce import reproduce
75 from dvc.repo.run import run
76 from dvc.repo.status import status
77 from dvc.repo.update import update
78
79 ls = staticmethod(_ls)
80 get = staticmethod(_get)
81 get_url = staticmethod(_get_url)
82
83 def _get_repo_dirs(
84 self,
85 root_dir: str = None,
86 fs: "FileSystem" = None,
87 uninitialized: bool = False,
88 ):
89 from dvc.scm import SCM, Base, SCMError
90 from dvc.utils.fs import makedirs
91
92 dvc_dir = None
93 tmp_dir = None
94 try:
95 root_dir = self.find_root(root_dir, fs)
96 dvc_dir = os.path.join(root_dir, self.DVC_DIR)
97 tmp_dir = os.path.join(dvc_dir, "tmp")
98 makedirs(tmp_dir, exist_ok=True)
99 except NotDvcRepoError:
100 if not uninitialized:
101 raise
102
103 try:
104 scm = SCM(root_dir or os.curdir)
105 except SCMError:
106 scm = SCM(os.curdir, no_scm=True)
107
108 assert isinstance(scm, Base)
109 root_dir = scm.root_dir
110
111 return root_dir, dvc_dir, tmp_dir
112
113 def _get_database_dir(self, db_name):
114 # NOTE: by default, store SQLite-based remote indexes and state's
115 # `links` and `md5s` caches in the repository itself to avoid any
116 # possible state corruption in 'shared cache dir' scenario, but allow
117 # user to override this through config when, say, the repository is
118 # located on a mounted volume — see
119 # https://github.com/iterative/dvc/issues/4420
120 base_db_dir = self.config.get(db_name, {}).get("dir", None)
121 if not base_db_dir:
122 return self.tmp_dir
123
124 import hashlib
125
126 from dvc.utils.fs import makedirs
127
128 root_dir_hash = hashlib.sha224(
129 self.root_dir.encode("utf-8")
130 ).hexdigest()
131
132 db_dir = os.path.join(
133 base_db_dir,
134 self.DVC_DIR,
135 f"{os.path.basename(self.root_dir)}-{root_dir_hash[0:7]}",
136 )
137
138 makedirs(db_dir, exist_ok=True)
139 return db_dir
140
141 def __init__(
142 self,
143 root_dir=None,
144 fs=None,
145 rev=None,
146 subrepos=False,
147 uninitialized=False,
148 config=None,
149 url=None,
150 repo_factory=None,
151 ):
152 from dvc.config import Config
153 from dvc.data.db import ODBManager
154 from dvc.data_cloud import DataCloud
155 from dvc.fs.git import GitFileSystem
156 from dvc.fs.local import localfs
157 from dvc.lock import LockNoop, make_lock
158 from dvc.repo.live import Live
159 from dvc.repo.metrics import Metrics
160 from dvc.repo.params import Params
161 from dvc.repo.plots import Plots
162 from dvc.repo.stage import StageLoad
163 from dvc.scm import SCM
164 from dvc.stage.cache import StageCache
165 from dvc.state import State, StateNoop
166
167 self.url = url
168 self._fs_conf = {"repo_factory": repo_factory}
169 self._fs = fs or localfs
170 self._scm = None
171
172 if rev and not fs:
173 self._scm = SCM(root_dir or os.curdir)
174 self._fs = GitFileSystem(scm=self._scm, rev=rev)
175
176 self.root_dir, self.dvc_dir, self.tmp_dir = self._get_repo_dirs(
177 root_dir=root_dir, fs=self.fs, uninitialized=uninitialized
178 )
179
180 self.config = Config(self.dvc_dir, fs=self.fs, config=config)
181 self._uninitialized = uninitialized
182
183 # used by RepoFileSystem to determine if it should traverse subrepos
184 self.subrepos = subrepos
185
186 self.cloud = DataCloud(self)
187 self.stage = StageLoad(self)
188
189 if isinstance(self.fs, GitFileSystem) or not self.dvc_dir:
190 self.lock = LockNoop()
191 self.state = StateNoop()
192 self.odb = ODBManager(self)
193 else:
194 self.lock = make_lock(
195 os.path.join(self.tmp_dir, "lock"),
196 tmp_dir=self.tmp_dir,
197 hardlink_lock=self.config["core"].get("hardlink_lock", False),
198 friendly=True,
199 )
200
201 state_db_dir = self._get_database_dir("state")
202 self.state = State(self.root_dir, state_db_dir, self.dvcignore)
203 self.odb = ODBManager(self)
204
205 self.stage_cache = StageCache(self)
206
207 self._ignore()
208
209 self.metrics = Metrics(self)
210 self.plots = Plots(self)
211 self.params = Params(self)
212 self.live = Live(self)
213
214 self.stage_collection_error_handler: Optional[
215 Callable[[str, Exception], None]
216 ] = None
217 self._lock_depth = 0
218
219 def __str__(self):
220 return self.url or self.root_dir
221
222 @cached_property
223 def index(self):
224 from dvc.repo.index import Index
225
226 return Index(self)
227
228 @staticmethod
229 def open(url, *args, **kwargs):
230 if url is None:
231 url = os.getcwd()
232
233 if os.path.exists(url):
234 try:
235 return Repo(url, *args, **kwargs)
236 except NotDvcRepoError:
237 pass # fallthrough to external_repo
238
239 from dvc.external_repo import external_repo
240
241 return external_repo(url, *args, **kwargs)
242
243 @cached_property
244 def scm(self):
245 from dvc.scm import SCM, SCMError
246
247 if self._scm:
248 return self._scm
249
250 no_scm = self.config["core"].get("no_scm", False)
251 try:
252 return SCM(self.root_dir, no_scm=no_scm)
253 except SCMError:
254 if self._uninitialized:
255 # might not be a git/dvc repo at all
256 # used in `params/metrics/plots/live` targets
257 return SCM(self.root_dir, no_scm=True)
258 raise
259
260 @cached_property
261 def scm_context(self) -> "SCMContext":
262 from dvc.repo.scm_context import SCMContext
263
264 return SCMContext(self.scm, self.config)
265
266 @cached_property
267 def dvcignore(self) -> DvcIgnoreFilter:
268
269 return DvcIgnoreFilter(self.fs, self.root_dir)
270
271 def get_rev(self):
272 from dvc.fs.local import LocalFileSystem
273
274 assert self.scm
275 if isinstance(self.fs, LocalFileSystem):
276 from dvc.scm import map_scm_exception
277
278 with map_scm_exception():
279 return self.scm.get_rev()
280 return self.fs.rev
281
282 @cached_property
283 def experiments(self):
284 from dvc.repo.experiments import Experiments
285
286 return Experiments(self)
287
288 @cached_property
289 def machine(self):
290 from dvc.machine import MachineManager
291
292 if self.tmp_dir and (
293 self.config["feature"].get("machine", False)
294 or env2bool("DVC_TEST")
295 ):
296 return MachineManager(self)
297 return None
298
299 @property
300 def fs(self) -> "FileSystem":
301 return self._fs
302
303 @fs.setter
304 def fs(self, fs: "FileSystem"):
305 self._fs = fs
306 # Our graph cache is no longer valid, as it was based on the previous
307 # fs.
308 self._reset()
309
310 def __repr__(self):
311 return f"{self.__class__.__name__}: '{self.root_dir}'"
312
313 @classmethod
314 def find_root(cls, root=None, fs=None) -> str:
315 from dvc.fs.local import LocalFileSystem, localfs
316
317 root_dir = os.path.realpath(root or os.curdir)
318 _fs = fs
319 fs = fs or localfs
320
321 if not fs.isdir(root_dir):
322 raise NotDvcRepoError(f"directory '{root}' does not exist")
323
324 while True:
325 dvc_dir = fs.path.join(root_dir, cls.DVC_DIR)
326 if fs.isdir(dvc_dir):
327 return root_dir
328 if isinstance(fs, LocalFileSystem) and os.path.ismount(root_dir):
329 break
330 parent = fs.path.parent(root_dir)
331 if parent == root_dir:
332 break
333 root_dir = parent
334
335 if _fs:
336 msg = f"'{root}' does not contain DVC directory"
337 else:
338 msg = (
339 "you are not inside of a DVC repository "
340 f"(checked up to mount point '{root_dir}')"
341 )
342 raise NotDvcRepoError(msg)
343
344 @classmethod
345 def find_dvc_dir(cls, root=None):
346 root_dir = cls.find_root(root)
347 return os.path.join(root_dir, cls.DVC_DIR)
348
349 @staticmethod
350 def init(root_dir=os.curdir, no_scm=False, force=False, subdir=False):
351 from dvc.repo.init import init
352
353 return init(
354 root_dir=root_dir, no_scm=no_scm, force=force, subdir=subdir
355 )
356
357 def unprotect(self, target):
358 return self.odb.local.unprotect(target)
359
360 def _ignore(self):
361 flist = [self.config.files["local"], self.tmp_dir]
362
363 if path_isin(self.odb.local.cache_dir, self.root_dir):
364 flist += [self.odb.local.cache_dir]
365
366 for file in flist:
367 self.scm_context.ignore(file)
368
369 def brancher(self, *args, **kwargs):
370 from dvc.repo.brancher import brancher
371
372 return brancher(self, *args, **kwargs)
373
374 def used_objs(
375 self,
376 targets=None,
377 all_branches=False,
378 with_deps=False,
379 all_tags=False,
380 all_commits=False,
381 all_experiments=False,
382 remote=None,
383 force=False,
384 jobs=None,
385 recursive=False,
386 used_run_cache=None,
387 revs=None,
388 ):
389 """Get the stages related to the given target and collect
390 the `info` of its outputs.
391
392 This is useful to know what files from the cache are _in use_
393 (namely, a file described as an output on a stage).
394
395 The scope is, by default, the working directory, but you can use
396 `all_branches`/`all_tags`/`all_commits`/`all_experiments` to expand
397 the scope.
398
399 Returns:
400 A dict mapping (remote) ODB instances to sets of objects that
401 belong to each ODB. If the ODB instance is None, the objects
402 are naive and do not belong to a specific remote ODB.
403 """
404 used = defaultdict(set)
405
406 def _add_suffix(objs: Set["HashFile"], suffix: str) -> None:
407 from itertools import chain
408
409 from dvc.data import iterobjs
410
411 for obj in chain.from_iterable(map(iterobjs, objs)):
412 if obj.name is not None:
413 obj.name += suffix
414
415 for branch in self.brancher(
416 revs=revs,
417 all_branches=all_branches,
418 all_tags=all_tags,
419 all_commits=all_commits,
420 all_experiments=all_experiments,
421 ):
422 for odb, objs in self.index.used_objs(
423 targets,
424 remote=remote,
425 force=force,
426 jobs=jobs,
427 recursive=recursive,
428 with_deps=with_deps,
429 ).items():
430 if branch:
431 _add_suffix(objs, f" ({branch})")
432 used[odb].update(objs)
433
434 if used_run_cache:
435 for odb, objs in self.stage_cache.get_used_objs(
436 used_run_cache, remote=remote, force=force, jobs=jobs
437 ).items():
438 used[odb].update(objs)
439
440 return used
441
442 @property
443 def stages(self): # obsolete, only for backward-compatibility
444 return self.index.stages
445
446 def find_outs_by_path(self, path, outs=None, recursive=False, strict=True):
447 # using `outs_graph` to ensure graph checks are run
448 outs = outs or self.index.outs_graph
449
450 abs_path = os.path.abspath(path)
451 fs_path = abs_path
452
453 def func(out):
454 def eq(one, two):
455 return one == two
456
457 match = eq if strict else out.fs.path.isin_or_eq
458
459 if out.scheme == "local" and match(fs_path, out.fs_path):
460 return True
461
462 if recursive and out.fs.path.isin(out.fs_path, fs_path):
463 return True
464
465 return False
466
467 matched = list(filter(func, outs))
468 if not matched:
469 raise OutputNotFoundError(path, self)
470
471 return matched
472
473 def is_dvc_internal(self, path):
474 path_parts = os.path.normpath(path).split(os.path.sep)
475 return self.DVC_DIR in path_parts
476
477 @cached_property
478 def dvcfs(self):
479 from dvc.fs.dvc import DvcFileSystem
480
481 return DvcFileSystem(repo=self)
482
483 @cached_property
484 def repo_fs(self):
485 from dvc.fs.repo import RepoFileSystem
486
487 return RepoFileSystem(self, subrepos=self.subrepos, **self._fs_conf)
488
489 @cached_property
490 def index_db_dir(self):
491 return self._get_database_dir("index")
492
493 @contextmanager
494 def open_by_relpath(self, path, remote=None, mode="r", encoding=None):
495 """Opens a specified resource as a file descriptor"""
496 from dvc.fs.repo import RepoFileSystem
497
498 fs = RepoFileSystem(self, subrepos=True)
499 path = self.fs.path.join(self.root_dir, path)
500 try:
501 with fs.open(
502 path, mode=mode, encoding=encoding, remote=remote
503 ) as fobj:
504 yield fobj
505 except FileNotFoundError as exc:
506 raise FileMissingError(path) from exc
507 except IsADirectoryError as exc:
508 raise DvcIsADirectoryError(f"'{path}' is a directory") from exc
509
510 def close(self):
511 self.scm.close()
512 self.state.close()
513
514 def _reset(self):
515 self.state.close()
516 self.scm._reset() # pylint: disable=protected-access
517 self.__dict__.pop("index", None)
518 self.__dict__.pop("dvcignore", None)
519
520 def __enter__(self):
521 return self
522
523 def __exit__(self, exc_type, exc_val, exc_tb):
524 self._reset()
525 self.scm.close()
526
[end of dvc/repo/__init__.py]
</code>
I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
<patch>
diff --git a/file.py b/file.py
--- a/file.py
+++ b/file.py
@@ -1,27 +1,35 @@
def euclidean(a, b):
- while b:
- a, b = b, a % b
- return a
+ if b == 0:
+ return a
+ return euclidean(b, a % b)
def bresenham(x0, y0, x1, y1):
points = []
dx = abs(x1 - x0)
dy = abs(y1 - y0)
- sx = 1 if x0 < x1 else -1
- sy = 1 if y0 < y1 else -1
- err = dx - dy
+ x, y = x0, y0
+ sx = -1 if x0 > x1 else 1
+ sy = -1 if y0 > y1 else 1
- while True:
- points.append((x0, y0))
- if x0 == x1 and y0 == y1:
- break
- e2 = 2 * err
- if e2 > -dy:
- err -= dy
- x0 += sx
- if e2 < dx:
- err += dx
- y0 += sy
+ if dx > dy:
+ err = dx / 2.0
+ while x != x1:
+ points.append((x, y))
+ err -= dy
+ if err < 0:
+ y += sy
+ err += dx
+ x += sx
+ else:
+ err = dy / 2.0
+ while y != y1:
+ points.append((x, y))
+ err -= dx
+ if err < 0:
+ x += sx
+ err += dy
+ y += sy
+
+ points.append((x, y))
return points
</patch> | diff --git a/dvc/repo/__init__.py b/dvc/repo/__init__.py
--- a/dvc/repo/__init__.py
+++ b/dvc/repo/__init__.py
@@ -314,8 +314,8 @@
def find_root(cls, root=None, fs=None) -> str:
from dvc.fs.local import LocalFileSystem, localfs
- root_dir = os.path.realpath(root or os.curdir)
- _fs = fs
+ root = root or os.curdir
+ root_dir = os.path.realpath(root)
fs = fs or localfs
if not fs.isdir(root_dir):
@@ -332,13 +332,11 @@
break
root_dir = parent
- if _fs:
- msg = f"'{root}' does not contain DVC directory"
- else:
- msg = (
- "you are not inside of a DVC repository "
- f"(checked up to mount point '{root_dir}')"
- )
+ msg = "you are not inside of a DVC repository"
+
+ if isinstance(fs, LocalFileSystem):
+ msg = f"{msg} (checked up to mount point '{root_dir}')"
+
raise NotDvcRepoError(msg)
@classmethod
| {"golden_diff": "diff --git a/dvc/repo/__init__.py b/dvc/repo/__init__.py\n--- a/dvc/repo/__init__.py\n+++ b/dvc/repo/__init__.py\n@@ -314,8 +314,8 @@\n def find_root(cls, root=None, fs=None) -> str:\n from dvc.fs.local import LocalFileSystem, localfs\n \n- root_dir = os.path.realpath(root or os.curdir)\n- _fs = fs\n+ root = root or os.curdir\n+ root_dir = os.path.realpath(root)\n fs = fs or localfs\n \n if not fs.isdir(root_dir):\n@@ -332,13 +332,11 @@\n break\n root_dir = parent\n \n- if _fs:\n- msg = f\"'{root}' does not contain DVC directory\"\n- else:\n- msg = (\n- \"you are not inside of a DVC repository \"\n- f\"(checked up to mount point '{root_dir}')\"\n- )\n+ msg = \"you are not inside of a DVC repository\"\n+\n+ if isinstance(fs, LocalFileSystem):\n+ msg = f\"{msg} (checked up to mount point '{root_dir}')\"\n+\n raise NotDvcRepoError(msg)\n \n @classmethod\n", "issue": "'None' does not contain DVC directory\n```console\r\ncd \"$(mktemp -d)\"\r\ndvc add foo # or any other command\r\n```\r\n\n", "before_files": [{"content": "import logging\nimport os\nfrom collections import defaultdict\nfrom contextlib import contextmanager\nfrom functools import wraps\nfrom typing import TYPE_CHECKING, Callable, Optional, Set\n\nfrom funcy import cached_property\n\nfrom dvc.exceptions import FileMissingError\nfrom dvc.exceptions import IsADirectoryError as DvcIsADirectoryError\nfrom dvc.exceptions import NotDvcRepoError, OutputNotFoundError\nfrom dvc.ignore import DvcIgnoreFilter\nfrom dvc.utils import env2bool\nfrom dvc.utils.fs import path_isin\n\nif TYPE_CHECKING:\n from dvc.fs.base import FileSystem\n from dvc.objects.file import HashFile\n from dvc.repo.scm_context import SCMContext\n\nlogger = logging.getLogger(__name__)\n\n\n@contextmanager\ndef lock_repo(repo: \"Repo\"):\n # pylint: disable=protected-access\n depth = repo._lock_depth\n repo._lock_depth += 1\n\n try:\n if depth > 0:\n yield\n else:\n with repo.lock:\n repo._reset()\n yield\n # Graph cache is no longer valid after we release the repo.lock\n repo._reset()\n finally:\n repo._lock_depth = depth\n\n\ndef locked(f):\n @wraps(f)\n def wrapper(repo, *args, **kwargs):\n with lock_repo(repo):\n return f(repo, *args, **kwargs)\n\n return wrapper\n\n\nclass Repo:\n DVC_DIR = \".dvc\"\n\n from dvc.repo.add import add\n from dvc.repo.checkout import checkout\n from dvc.repo.commit import commit\n from dvc.repo.destroy import destroy\n from dvc.repo.diff import diff\n from dvc.repo.fetch import fetch\n from dvc.repo.freeze import freeze, unfreeze\n from dvc.repo.gc import gc\n from dvc.repo.get import get as _get\n from dvc.repo.get_url import get_url as _get_url\n from dvc.repo.imp import imp\n from dvc.repo.imp_url import imp_url\n from dvc.repo.install import install\n from dvc.repo.ls import ls as _ls\n from dvc.repo.move import move\n from dvc.repo.pull import pull\n from dvc.repo.push import push\n from dvc.repo.remove import remove\n from dvc.repo.reproduce import reproduce\n from dvc.repo.run import run\n from dvc.repo.status import status\n from dvc.repo.update import update\n\n ls = staticmethod(_ls)\n get = staticmethod(_get)\n get_url = staticmethod(_get_url)\n\n def _get_repo_dirs(\n self,\n root_dir: str = None,\n fs: \"FileSystem\" = None,\n uninitialized: bool = False,\n ):\n from dvc.scm import SCM, Base, SCMError\n from dvc.utils.fs import makedirs\n\n dvc_dir = None\n tmp_dir = None\n try:\n root_dir = self.find_root(root_dir, fs)\n dvc_dir = os.path.join(root_dir, self.DVC_DIR)\n tmp_dir = os.path.join(dvc_dir, \"tmp\")\n makedirs(tmp_dir, exist_ok=True)\n except NotDvcRepoError:\n if not uninitialized:\n raise\n\n try:\n scm = SCM(root_dir or os.curdir)\n except SCMError:\n scm = SCM(os.curdir, no_scm=True)\n\n assert isinstance(scm, Base)\n root_dir = scm.root_dir\n\n return root_dir, dvc_dir, tmp_dir\n\n def _get_database_dir(self, db_name):\n # NOTE: by default, store SQLite-based remote indexes and state's\n # `links` and `md5s` caches in the repository itself to avoid any\n # possible state corruption in 'shared cache dir' scenario, but allow\n # user to override this through config when, say, the repository is\n # located on a mounted volume \u2014 see\n # https://github.com/iterative/dvc/issues/4420\n base_db_dir = self.config.get(db_name, {}).get(\"dir\", None)\n if not base_db_dir:\n return self.tmp_dir\n\n import hashlib\n\n from dvc.utils.fs import makedirs\n\n root_dir_hash = hashlib.sha224(\n self.root_dir.encode(\"utf-8\")\n ).hexdigest()\n\n db_dir = os.path.join(\n base_db_dir,\n self.DVC_DIR,\n f\"{os.path.basename(self.root_dir)}-{root_dir_hash[0:7]}\",\n )\n\n makedirs(db_dir, exist_ok=True)\n return db_dir\n\n def __init__(\n self,\n root_dir=None,\n fs=None,\n rev=None,\n subrepos=False,\n uninitialized=False,\n config=None,\n url=None,\n repo_factory=None,\n ):\n from dvc.config import Config\n from dvc.data.db import ODBManager\n from dvc.data_cloud import DataCloud\n from dvc.fs.git import GitFileSystem\n from dvc.fs.local import localfs\n from dvc.lock import LockNoop, make_lock\n from dvc.repo.live import Live\n from dvc.repo.metrics import Metrics\n from dvc.repo.params import Params\n from dvc.repo.plots import Plots\n from dvc.repo.stage import StageLoad\n from dvc.scm import SCM\n from dvc.stage.cache import StageCache\n from dvc.state import State, StateNoop\n\n self.url = url\n self._fs_conf = {\"repo_factory\": repo_factory}\n self._fs = fs or localfs\n self._scm = None\n\n if rev and not fs:\n self._scm = SCM(root_dir or os.curdir)\n self._fs = GitFileSystem(scm=self._scm, rev=rev)\n\n self.root_dir, self.dvc_dir, self.tmp_dir = self._get_repo_dirs(\n root_dir=root_dir, fs=self.fs, uninitialized=uninitialized\n )\n\n self.config = Config(self.dvc_dir, fs=self.fs, config=config)\n self._uninitialized = uninitialized\n\n # used by RepoFileSystem to determine if it should traverse subrepos\n self.subrepos = subrepos\n\n self.cloud = DataCloud(self)\n self.stage = StageLoad(self)\n\n if isinstance(self.fs, GitFileSystem) or not self.dvc_dir:\n self.lock = LockNoop()\n self.state = StateNoop()\n self.odb = ODBManager(self)\n else:\n self.lock = make_lock(\n os.path.join(self.tmp_dir, \"lock\"),\n tmp_dir=self.tmp_dir,\n hardlink_lock=self.config[\"core\"].get(\"hardlink_lock\", False),\n friendly=True,\n )\n\n state_db_dir = self._get_database_dir(\"state\")\n self.state = State(self.root_dir, state_db_dir, self.dvcignore)\n self.odb = ODBManager(self)\n\n self.stage_cache = StageCache(self)\n\n self._ignore()\n\n self.metrics = Metrics(self)\n self.plots = Plots(self)\n self.params = Params(self)\n self.live = Live(self)\n\n self.stage_collection_error_handler: Optional[\n Callable[[str, Exception], None]\n ] = None\n self._lock_depth = 0\n\n def __str__(self):\n return self.url or self.root_dir\n\n @cached_property\n def index(self):\n from dvc.repo.index import Index\n\n return Index(self)\n\n @staticmethod\n def open(url, *args, **kwargs):\n if url is None:\n url = os.getcwd()\n\n if os.path.exists(url):\n try:\n return Repo(url, *args, **kwargs)\n except NotDvcRepoError:\n pass # fallthrough to external_repo\n\n from dvc.external_repo import external_repo\n\n return external_repo(url, *args, **kwargs)\n\n @cached_property\n def scm(self):\n from dvc.scm import SCM, SCMError\n\n if self._scm:\n return self._scm\n\n no_scm = self.config[\"core\"].get(\"no_scm\", False)\n try:\n return SCM(self.root_dir, no_scm=no_scm)\n except SCMError:\n if self._uninitialized:\n # might not be a git/dvc repo at all\n # used in `params/metrics/plots/live` targets\n return SCM(self.root_dir, no_scm=True)\n raise\n\n @cached_property\n def scm_context(self) -> \"SCMContext\":\n from dvc.repo.scm_context import SCMContext\n\n return SCMContext(self.scm, self.config)\n\n @cached_property\n def dvcignore(self) -> DvcIgnoreFilter:\n\n return DvcIgnoreFilter(self.fs, self.root_dir)\n\n def get_rev(self):\n from dvc.fs.local import LocalFileSystem\n\n assert self.scm\n if isinstance(self.fs, LocalFileSystem):\n from dvc.scm import map_scm_exception\n\n with map_scm_exception():\n return self.scm.get_rev()\n return self.fs.rev\n\n @cached_property\n def experiments(self):\n from dvc.repo.experiments import Experiments\n\n return Experiments(self)\n\n @cached_property\n def machine(self):\n from dvc.machine import MachineManager\n\n if self.tmp_dir and (\n self.config[\"feature\"].get(\"machine\", False)\n or env2bool(\"DVC_TEST\")\n ):\n return MachineManager(self)\n return None\n\n @property\n def fs(self) -> \"FileSystem\":\n return self._fs\n\n @fs.setter\n def fs(self, fs: \"FileSystem\"):\n self._fs = fs\n # Our graph cache is no longer valid, as it was based on the previous\n # fs.\n self._reset()\n\n def __repr__(self):\n return f\"{self.__class__.__name__}: '{self.root_dir}'\"\n\n @classmethod\n def find_root(cls, root=None, fs=None) -> str:\n from dvc.fs.local import LocalFileSystem, localfs\n\n root_dir = os.path.realpath(root or os.curdir)\n _fs = fs\n fs = fs or localfs\n\n if not fs.isdir(root_dir):\n raise NotDvcRepoError(f\"directory '{root}' does not exist\")\n\n while True:\n dvc_dir = fs.path.join(root_dir, cls.DVC_DIR)\n if fs.isdir(dvc_dir):\n return root_dir\n if isinstance(fs, LocalFileSystem) and os.path.ismount(root_dir):\n break\n parent = fs.path.parent(root_dir)\n if parent == root_dir:\n break\n root_dir = parent\n\n if _fs:\n msg = f\"'{root}' does not contain DVC directory\"\n else:\n msg = (\n \"you are not inside of a DVC repository \"\n f\"(checked up to mount point '{root_dir}')\"\n )\n raise NotDvcRepoError(msg)\n\n @classmethod\n def find_dvc_dir(cls, root=None):\n root_dir = cls.find_root(root)\n return os.path.join(root_dir, cls.DVC_DIR)\n\n @staticmethod\n def init(root_dir=os.curdir, no_scm=False, force=False, subdir=False):\n from dvc.repo.init import init\n\n return init(\n root_dir=root_dir, no_scm=no_scm, force=force, subdir=subdir\n )\n\n def unprotect(self, target):\n return self.odb.local.unprotect(target)\n\n def _ignore(self):\n flist = [self.config.files[\"local\"], self.tmp_dir]\n\n if path_isin(self.odb.local.cache_dir, self.root_dir):\n flist += [self.odb.local.cache_dir]\n\n for file in flist:\n self.scm_context.ignore(file)\n\n def brancher(self, *args, **kwargs):\n from dvc.repo.brancher import brancher\n\n return brancher(self, *args, **kwargs)\n\n def used_objs(\n self,\n targets=None,\n all_branches=False,\n with_deps=False,\n all_tags=False,\n all_commits=False,\n all_experiments=False,\n remote=None,\n force=False,\n jobs=None,\n recursive=False,\n used_run_cache=None,\n revs=None,\n ):\n \"\"\"Get the stages related to the given target and collect\n the `info` of its outputs.\n\n This is useful to know what files from the cache are _in use_\n (namely, a file described as an output on a stage).\n\n The scope is, by default, the working directory, but you can use\n `all_branches`/`all_tags`/`all_commits`/`all_experiments` to expand\n the scope.\n\n Returns:\n A dict mapping (remote) ODB instances to sets of objects that\n belong to each ODB. If the ODB instance is None, the objects\n are naive and do not belong to a specific remote ODB.\n \"\"\"\n used = defaultdict(set)\n\n def _add_suffix(objs: Set[\"HashFile\"], suffix: str) -> None:\n from itertools import chain\n\n from dvc.data import iterobjs\n\n for obj in chain.from_iterable(map(iterobjs, objs)):\n if obj.name is not None:\n obj.name += suffix\n\n for branch in self.brancher(\n revs=revs,\n all_branches=all_branches,\n all_tags=all_tags,\n all_commits=all_commits,\n all_experiments=all_experiments,\n ):\n for odb, objs in self.index.used_objs(\n targets,\n remote=remote,\n force=force,\n jobs=jobs,\n recursive=recursive,\n with_deps=with_deps,\n ).items():\n if branch:\n _add_suffix(objs, f\" ({branch})\")\n used[odb].update(objs)\n\n if used_run_cache:\n for odb, objs in self.stage_cache.get_used_objs(\n used_run_cache, remote=remote, force=force, jobs=jobs\n ).items():\n used[odb].update(objs)\n\n return used\n\n @property\n def stages(self): # obsolete, only for backward-compatibility\n return self.index.stages\n\n def find_outs_by_path(self, path, outs=None, recursive=False, strict=True):\n # using `outs_graph` to ensure graph checks are run\n outs = outs or self.index.outs_graph\n\n abs_path = os.path.abspath(path)\n fs_path = abs_path\n\n def func(out):\n def eq(one, two):\n return one == two\n\n match = eq if strict else out.fs.path.isin_or_eq\n\n if out.scheme == \"local\" and match(fs_path, out.fs_path):\n return True\n\n if recursive and out.fs.path.isin(out.fs_path, fs_path):\n return True\n\n return False\n\n matched = list(filter(func, outs))\n if not matched:\n raise OutputNotFoundError(path, self)\n\n return matched\n\n def is_dvc_internal(self, path):\n path_parts = os.path.normpath(path).split(os.path.sep)\n return self.DVC_DIR in path_parts\n\n @cached_property\n def dvcfs(self):\n from dvc.fs.dvc import DvcFileSystem\n\n return DvcFileSystem(repo=self)\n\n @cached_property\n def repo_fs(self):\n from dvc.fs.repo import RepoFileSystem\n\n return RepoFileSystem(self, subrepos=self.subrepos, **self._fs_conf)\n\n @cached_property\n def index_db_dir(self):\n return self._get_database_dir(\"index\")\n\n @contextmanager\n def open_by_relpath(self, path, remote=None, mode=\"r\", encoding=None):\n \"\"\"Opens a specified resource as a file descriptor\"\"\"\n from dvc.fs.repo import RepoFileSystem\n\n fs = RepoFileSystem(self, subrepos=True)\n path = self.fs.path.join(self.root_dir, path)\n try:\n with fs.open(\n path, mode=mode, encoding=encoding, remote=remote\n ) as fobj:\n yield fobj\n except FileNotFoundError as exc:\n raise FileMissingError(path) from exc\n except IsADirectoryError as exc:\n raise DvcIsADirectoryError(f\"'{path}' is a directory\") from exc\n\n def close(self):\n self.scm.close()\n self.state.close()\n\n def _reset(self):\n self.state.close()\n self.scm._reset() # pylint: disable=protected-access\n self.__dict__.pop(\"index\", None)\n self.__dict__.pop(\"dvcignore\", None)\n\n def __enter__(self):\n return self\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n self._reset()\n self.scm.close()\n", "path": "dvc/repo/__init__.py"}]} |
gh_patches_debug_233 | rasdani/github-patches | git_diff | learningequality__kolibri-6355 | You will be provided with a partial code base and an issue statement explaining a problem to resolve.
<issue>
tasks got cleared without triggering a 'clear task' action
### Observed behavior
Observed that my list of tasks got cleared after initiating a new import
### Expected behavior
tasks should not be cleared until explicitly done by the user
### User-facing consequences
loss of data: historical context
### Errors and logs
none
### Steps to reproduce
see notes below
### Context
0.13.0 beta 1
</issue>
<code>
[start of kolibri/core/content/serializers.py]
1 from django.core.cache import cache
2 from django.db.models import Manager
3 from django.db.models import Sum
4 from django.db.models.query import RawQuerySet
5 from le_utils.constants import content_kinds
6 from rest_framework import serializers
7
8 from kolibri.core.content.models import AssessmentMetaData
9 from kolibri.core.content.models import ChannelMetadata
10 from kolibri.core.content.models import ContentNode
11 from kolibri.core.content.models import File
12 from kolibri.core.content.models import Language
13 from kolibri.core.fields import create_timezonestamp
14
15
16 class DynamicFieldsModelSerializer(serializers.ModelSerializer):
17 def __init__(self, *args, **kwargs):
18 # Instantiate the superclass normally
19 super(DynamicFieldsModelSerializer, self).__init__(*args, **kwargs)
20
21 # enable dynamic fields specification!
22 if "request" in self.context and self.context["request"].GET.get(
23 "fields", None
24 ):
25 fields = self.context["request"].GET["fields"].split(",")
26 # Drop any fields that are not specified in the `fields` argument.
27 allowed = set(fields)
28 existing = set(self.fields.keys())
29 for field_name in existing - allowed:
30 self.fields.pop(field_name)
31
32
33 class ChannelMetadataSerializer(serializers.ModelSerializer):
34 root = serializers.PrimaryKeyRelatedField(read_only=True)
35 lang_code = serializers.SerializerMethodField()
36 lang_name = serializers.SerializerMethodField()
37 available = serializers.SerializerMethodField()
38 num_coach_contents = serializers.IntegerField(source="root.num_coach_contents")
39
40 def get_lang_code(self, instance):
41 if instance.root.lang is None:
42 return None
43
44 return instance.root.lang.lang_code
45
46 def get_lang_name(self, instance):
47 if instance.root.lang is None:
48 return None
49
50 return instance.root.lang.lang_name
51
52 def get_available(self, instance):
53 return instance.root.available
54
55 class Meta:
56 model = ChannelMetadata
57 fields = (
58 "author",
59 "description",
60 "id",
61 "last_updated",
62 "lang_code",
63 "lang_name",
64 "name",
65 "root",
66 "thumbnail",
67 "version",
68 "available",
69 "num_coach_contents",
70 )
71
72
73 class PublicChannelSerializer(serializers.ModelSerializer):
74 included_languages = serializers.SerializerMethodField()
75 matching_tokens = serializers.SerializerMethodField("match_tokens")
76 language = serializers.SerializerMethodField()
77 icon_encoding = serializers.SerializerMethodField()
78 last_published = serializers.SerializerMethodField()
79
80 def get_language(self, instance):
81 if instance.root.lang is None:
82 return None
83
84 return instance.root.lang.lang_code
85
86 def get_icon_encoding(self, instance):
87 return instance.thumbnail
88
89 def get_included_languages(self, instance):
90 return list(instance.included_languages.all().values_list("id", flat=True))
91
92 def get_last_published(self, instance):
93 return (
94 None
95 if not instance.last_updated
96 else create_timezonestamp(instance.last_updated)
97 )
98
99 def match_tokens(self, channel):
100 return []
101
102 class Meta:
103 model = ChannelMetadata
104 fields = (
105 "id",
106 "name",
107 "language",
108 "included_languages",
109 "description",
110 "total_resource_count",
111 "version",
112 "published_size",
113 "last_published",
114 "icon_encoding",
115 "matching_tokens",
116 "public",
117 )
118
119
120 class LowerCaseField(serializers.CharField):
121 def to_representation(self, obj):
122 return super(LowerCaseField, self).to_representation(obj).lower()
123
124
125 class LanguageSerializer(serializers.ModelSerializer):
126 id = LowerCaseField(max_length=14)
127 lang_code = LowerCaseField(max_length=3)
128 lang_subcode = LowerCaseField(max_length=10)
129
130 class Meta:
131 model = Language
132 fields = ("id", "lang_code", "lang_subcode", "lang_name", "lang_direction")
133
134
135 class FileSerializer(serializers.ModelSerializer):
136 checksum = serializers.CharField(source="local_file_id")
137 storage_url = serializers.SerializerMethodField()
138 download_url = serializers.SerializerMethodField()
139 extension = serializers.SerializerMethodField()
140 file_size = serializers.SerializerMethodField()
141 lang = LanguageSerializer()
142 available = serializers.BooleanField(source="local_file.available")
143
144 def get_storage_url(self, target_node):
145 return target_node.get_storage_url()
146
147 def get_download_url(self, target_node):
148 return target_node.get_download_url()
149
150 def get_extension(self, target_node):
151 return target_node.get_extension()
152
153 def get_file_size(self, target_node):
154 return target_node.get_file_size()
155
156 class Meta:
157 model = File
158 fields = (
159 "storage_url",
160 "id",
161 "priority",
162 "available",
163 "file_size",
164 "extension",
165 "checksum",
166 "preset",
167 "lang",
168 "supplementary",
169 "thumbnail",
170 "download_url",
171 )
172
173
174 class AssessmentMetaDataSerializer(serializers.ModelSerializer):
175
176 assessment_item_ids = serializers.JSONField(default="[]")
177 mastery_model = serializers.JSONField(default="{}")
178
179 class Meta:
180 model = AssessmentMetaData
181 fields = (
182 "assessment_item_ids",
183 "number_of_assessments",
184 "mastery_model",
185 "randomize",
186 "is_manipulable",
187 )
188
189
190 def get_summary_logs(content_ids, user):
191 from kolibri.core.logger.models import ContentSummaryLog
192
193 if not content_ids:
194 return ContentSummaryLog.objects.none()
195 # get all summary logs for the current user that correspond to the descendant content nodes
196 return ContentSummaryLog.objects.filter(user=user, content_id__in=content_ids)
197
198
199 def get_topic_progress_fraction(topic, user):
200 leaf_ids = (
201 topic.get_descendants(include_self=False)
202 .order_by()
203 .exclude(kind=content_kinds.TOPIC)
204 .values_list("content_id", flat=True)
205 )
206 return round(
207 (
208 get_summary_logs(leaf_ids, user).aggregate(Sum("progress"))["progress__sum"]
209 or 0
210 )
211 / (len(leaf_ids) or 1),
212 4,
213 )
214
215
216 def get_content_progress_fraction(content, user):
217 from kolibri.core.logger.models import ContentSummaryLog
218
219 try:
220 # add up all the progress for the logs, and divide by the total number of content nodes to get overall progress
221 overall_progress = ContentSummaryLog.objects.get(
222 user=user, content_id=content.content_id
223 ).progress
224 except ContentSummaryLog.DoesNotExist:
225 return None
226 return round(overall_progress, 4)
227
228
229 def get_topic_and_content_progress_fraction(node, user):
230 if node.kind == content_kinds.TOPIC:
231 return get_topic_progress_fraction(node, user)
232 else:
233 return get_content_progress_fraction(node, user)
234
235
236 def get_topic_and_content_progress_fractions(nodes, user):
237 leaf_ids = (
238 nodes.get_descendants(include_self=True)
239 .order_by()
240 .exclude(available=False)
241 .exclude(kind=content_kinds.TOPIC)
242 .values_list("content_id", flat=True)
243 )
244
245 leaf_node_logs = get_summary_logs(leaf_ids, user)
246
247 overall_progress = {}
248
249 for log in leaf_node_logs.values("content_id", "progress"):
250 overall_progress[log["content_id"]] = round(log["progress"], 4)
251
252 for node in nodes:
253 if node.kind == content_kinds.TOPIC:
254 topic_leaf_ids = (
255 node.get_descendants(include_self=True)
256 .order_by()
257 .exclude(available=False)
258 .exclude(kind=content_kinds.TOPIC)
259 .values_list("content_id", flat=True)
260 )
261
262 overall_progress[node.content_id] = (
263 round(
264 sum(overall_progress.get(leaf_id, 0) for leaf_id in topic_leaf_ids)
265 / len(topic_leaf_ids),
266 4,
267 )
268 if topic_leaf_ids
269 else 0.0
270 )
271
272 return overall_progress
273
274
275 def get_content_progress_fractions(nodes, user):
276 if isinstance(nodes, RawQuerySet) or isinstance(nodes, list):
277 leaf_ids = [datum.content_id for datum in nodes]
278 else:
279 leaf_ids = nodes.exclude(kind=content_kinds.TOPIC).values_list(
280 "content_id", flat=True
281 )
282
283 summary_logs = get_summary_logs(leaf_ids, user)
284
285 # make a lookup dict for all logs to allow mapping from content_id to current progress
286 overall_progress = {
287 log["content_id"]: round(log["progress"], 4)
288 for log in summary_logs.values("content_id", "progress")
289 }
290 return overall_progress
291
292
293 class ContentNodeListSerializer(serializers.ListSerializer):
294 def to_representation(self, data):
295
296 # Dealing with nested relationships, data can be a Manager,
297 # so, first get a queryset from the Manager if needed
298 data = data.all() if isinstance(data, Manager) else data
299
300 # initialize cache key
301 cache_key = None
302
303 # ensure that we are filtering by the parent only
304 # this allows us to only cache results on the learn page
305 from .api import ContentNodeFilter
306
307 parent_filter_only = set(self.context["request"].GET.keys()).intersection(
308 ContentNodeFilter.Meta.fields
309 ) == set(["parent"])
310
311 # Cache parent look ups only
312 if parent_filter_only:
313 cache_key = "contentnode_list_{parent}".format(
314 parent=self.context["request"].GET.get("parent")
315 )
316
317 if cache.get(cache_key):
318 return cache.get(cache_key)
319
320 if not data:
321 return data
322
323 if (
324 "request" not in self.context
325 or not self.context["request"].user.is_facility_user
326 ):
327 progress_dict = {}
328 else:
329 user = self.context["request"].user
330 # Don't annotate topic progress as too expensive
331 progress_dict = get_content_progress_fractions(data, user)
332
333 result = []
334 topic_only = True
335
336 # Allow results to be limited after all queryset filtering has occurred
337 if self.limit:
338 data = data[: self.limit]
339
340 for item in data:
341 obj = self.child.to_representation(
342 item,
343 progress_fraction=progress_dict.get(item.content_id),
344 annotate_progress_fraction=False,
345 )
346 topic_only = topic_only and obj.get("kind") == content_kinds.TOPIC
347 result.append(obj)
348
349 # Only store if all nodes are topics, because we don't annotate progress on them
350 # This has the happy side effect of not caching our dynamically calculated
351 # recommendation queries, which might change for the same user over time
352 # because they do not return topics
353 if topic_only and parent_filter_only:
354 cache.set(cache_key, result, 60 * 10)
355
356 return result
357
358
359 class ContentNodeSerializer(DynamicFieldsModelSerializer):
360 parent = serializers.PrimaryKeyRelatedField(read_only=True)
361 files = FileSerializer(many=True, read_only=True)
362 assessmentmetadata = AssessmentMetaDataSerializer(
363 read_only=True, allow_null=True, many=True
364 )
365 lang = LanguageSerializer()
366
367 class Meta:
368 model = ContentNode
369 fields = (
370 "id",
371 "assessmentmetadata",
372 "author",
373 "available",
374 "channel_id",
375 "coach_content",
376 "content_id",
377 "description",
378 "files",
379 "kind",
380 "lang",
381 "license_description",
382 "license_name",
383 "license_owner",
384 "num_coach_contents",
385 "parent",
386 "sort_order",
387 "title",
388 )
389 list_serializer_class = ContentNodeListSerializer
390
391 def __new__(cls, *args, **kwargs):
392 # This is overwritten to provide a ListClassSerializer for many=True
393 limit = kwargs.pop("limit", None)
394 new = super(ContentNodeSerializer, cls).__new__(cls, *args, **kwargs)
395 new.limit = limit
396 return new
397
398 def to_representation(
399 self, instance, progress_fraction=None, annotate_progress_fraction=True
400 ):
401 if progress_fraction is None and annotate_progress_fraction:
402 if (
403 "request" not in self.context
404 or not self.context["request"].user.is_facility_user
405 ):
406 # Don't try to annotate for a non facility user
407 progress_fraction = 0.0
408 else:
409 user = self.context["request"].user
410 if instance.kind != content_kinds.TOPIC:
411 progress_fraction = get_content_progress_fraction(instance, user)
412 value = super(ContentNodeSerializer, self).to_representation(instance)
413 value["progress_fraction"] = progress_fraction
414 return value
415
416
417 class ContentNodeGranularSerializer(serializers.ModelSerializer):
418 num_coach_contents = serializers.SerializerMethodField()
419 coach_content = serializers.SerializerMethodField()
420 total_resources = serializers.SerializerMethodField()
421 importable = serializers.SerializerMethodField()
422
423 class Meta:
424 model = ContentNode
425 fields = (
426 "id",
427 "available",
428 "coach_content",
429 "importable",
430 "kind",
431 "num_coach_contents",
432 "on_device_resources",
433 "title",
434 "total_resources",
435 )
436
437 @property
438 def channel_stats(self):
439 return self.context["channel_stats"]
440
441 def get_total_resources(self, instance):
442 # channel_stats is None for export
443 if self.channel_stats is None:
444 return instance.on_device_resources
445 return self.channel_stats.get(instance.id, {"total_resources": 0})[
446 "total_resources"
447 ]
448
449 def get_num_coach_contents(self, instance):
450 # If for exporting, only show what is available on server. For importing,
451 # show all of the coach contents in the topic.
452 if self.channel_stats is None:
453 return instance.num_coach_contents
454 return self.channel_stats.get(instance.id, {"num_coach_contents": 0})[
455 "num_coach_contents"
456 ]
457
458 def get_coach_content(self, instance):
459 # If for exporting, only show what is on server. For importing,
460 # show all of the coach contents in the topic.
461 if self.channel_stats is None:
462 return instance.coach_content
463 return self.channel_stats.get(instance.id, {"coach_content": False})[
464 "coach_content"
465 ]
466
467 def get_importable(self, instance):
468 # If for export, just return None
469 if self.channel_stats is None:
470 return None
471 return instance.id in self.channel_stats
472
473
474 class ContentNodeProgressListSerializer(serializers.ListSerializer):
475 def to_representation(self, data):
476
477 if not data:
478 return data
479
480 if (
481 "request" not in self.context
482 or not self.context["request"].user.is_facility_user
483 ):
484 progress_dict = {}
485 else:
486 user = self.context["request"].user
487 # Don't annotate topic progress as too expensive
488 progress_dict = get_topic_and_content_progress_fractions(data, user)
489
490 # Dealing with nested relationships, data can be a Manager,
491 # so, first get a queryset from the Manager if needed
492 iterable = data.all() if isinstance(data, Manager) else data
493
494 return [
495 self.child.to_representation(
496 item,
497 progress_fraction=progress_dict.get(item.content_id, 0.0),
498 annotate_progress_fraction=False,
499 )
500 for item in iterable
501 ]
502
503
504 class ContentNodeProgressSerializer(serializers.Serializer):
505 def to_representation(
506 self, instance, progress_fraction=None, annotate_progress_fraction=True
507 ):
508 if progress_fraction is None and annotate_progress_fraction:
509 if (
510 "request" not in self.context
511 or not self.context["request"].user.is_facility_user
512 ):
513 # Don't try to annotate for a non facility user
514 progress_fraction = 0
515 else:
516 user = self.context["request"].user
517 progress_fraction = (
518 get_topic_and_content_progress_fraction(instance, user) or 0.0
519 )
520 return {"id": instance.id, "progress_fraction": progress_fraction}
521
522 class Meta:
523 list_serializer_class = ContentNodeProgressListSerializer
524
[end of kolibri/core/content/serializers.py]
</code>
I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
<patch>
diff --git a/file.py b/file.py
--- a/file.py
+++ b/file.py
@@ -1,27 +1,35 @@
def euclidean(a, b):
- while b:
- a, b = b, a % b
- return a
+ if b == 0:
+ return a
+ return euclidean(b, a % b)
def bresenham(x0, y0, x1, y1):
points = []
dx = abs(x1 - x0)
dy = abs(y1 - y0)
- sx = 1 if x0 < x1 else -1
- sy = 1 if y0 < y1 else -1
- err = dx - dy
+ x, y = x0, y0
+ sx = -1 if x0 > x1 else 1
+ sy = -1 if y0 > y1 else 1
- while True:
- points.append((x0, y0))
- if x0 == x1 and y0 == y1:
- break
- e2 = 2 * err
- if e2 > -dy:
- err -= dy
- x0 += sx
- if e2 < dx:
- err += dx
- y0 += sy
+ if dx > dy:
+ err = dx / 2.0
+ while x != x1:
+ points.append((x, y))
+ err -= dy
+ if err < 0:
+ y += sy
+ err += dx
+ x += sx
+ else:
+ err = dy / 2.0
+ while y != y1:
+ points.append((x, y))
+ err -= dx
+ if err < 0:
+ x += sx
+ err += dy
+ y += sy
+
+ points.append((x, y))
return points
</patch> | diff --git a/kolibri/core/content/serializers.py b/kolibri/core/content/serializers.py
--- a/kolibri/core/content/serializers.py
+++ b/kolibri/core/content/serializers.py
@@ -67,6 +67,7 @@
"version",
"available",
"num_coach_contents",
+ "public",
)
| {"golden_diff": "diff --git a/kolibri/core/content/serializers.py b/kolibri/core/content/serializers.py\n--- a/kolibri/core/content/serializers.py\n+++ b/kolibri/core/content/serializers.py\n@@ -67,6 +67,7 @@\n \"version\",\n \"available\",\n \"num_coach_contents\",\n+ \"public\",\n )\n", "issue": "tasks got cleared without triggering a 'clear task' action\n### Observed behavior\r\n\r\nObserved that my list of tasks got cleared after initiating a new import\r\n\r\n### Expected behavior\r\n\r\ntasks should not be cleared until explicitly done by the user\r\n\r\n### User-facing consequences\r\n\r\nloss of data: historical context\r\n\r\n### Errors and logs\r\n\r\nnone\r\n\r\n### Steps to reproduce\r\n\r\nsee notes below\r\n\r\n### Context\r\n\r\n0.13.0 beta 1\n", "before_files": [{"content": "from django.core.cache import cache\nfrom django.db.models import Manager\nfrom django.db.models import Sum\nfrom django.db.models.query import RawQuerySet\nfrom le_utils.constants import content_kinds\nfrom rest_framework import serializers\n\nfrom kolibri.core.content.models import AssessmentMetaData\nfrom kolibri.core.content.models import ChannelMetadata\nfrom kolibri.core.content.models import ContentNode\nfrom kolibri.core.content.models import File\nfrom kolibri.core.content.models import Language\nfrom kolibri.core.fields import create_timezonestamp\n\n\nclass DynamicFieldsModelSerializer(serializers.ModelSerializer):\n def __init__(self, *args, **kwargs):\n # Instantiate the superclass normally\n super(DynamicFieldsModelSerializer, self).__init__(*args, **kwargs)\n\n # enable dynamic fields specification!\n if \"request\" in self.context and self.context[\"request\"].GET.get(\n \"fields\", None\n ):\n fields = self.context[\"request\"].GET[\"fields\"].split(\",\")\n # Drop any fields that are not specified in the `fields` argument.\n allowed = set(fields)\n existing = set(self.fields.keys())\n for field_name in existing - allowed:\n self.fields.pop(field_name)\n\n\nclass ChannelMetadataSerializer(serializers.ModelSerializer):\n root = serializers.PrimaryKeyRelatedField(read_only=True)\n lang_code = serializers.SerializerMethodField()\n lang_name = serializers.SerializerMethodField()\n available = serializers.SerializerMethodField()\n num_coach_contents = serializers.IntegerField(source=\"root.num_coach_contents\")\n\n def get_lang_code(self, instance):\n if instance.root.lang is None:\n return None\n\n return instance.root.lang.lang_code\n\n def get_lang_name(self, instance):\n if instance.root.lang is None:\n return None\n\n return instance.root.lang.lang_name\n\n def get_available(self, instance):\n return instance.root.available\n\n class Meta:\n model = ChannelMetadata\n fields = (\n \"author\",\n \"description\",\n \"id\",\n \"last_updated\",\n \"lang_code\",\n \"lang_name\",\n \"name\",\n \"root\",\n \"thumbnail\",\n \"version\",\n \"available\",\n \"num_coach_contents\",\n )\n\n\nclass PublicChannelSerializer(serializers.ModelSerializer):\n included_languages = serializers.SerializerMethodField()\n matching_tokens = serializers.SerializerMethodField(\"match_tokens\")\n language = serializers.SerializerMethodField()\n icon_encoding = serializers.SerializerMethodField()\n last_published = serializers.SerializerMethodField()\n\n def get_language(self, instance):\n if instance.root.lang is None:\n return None\n\n return instance.root.lang.lang_code\n\n def get_icon_encoding(self, instance):\n return instance.thumbnail\n\n def get_included_languages(self, instance):\n return list(instance.included_languages.all().values_list(\"id\", flat=True))\n\n def get_last_published(self, instance):\n return (\n None\n if not instance.last_updated\n else create_timezonestamp(instance.last_updated)\n )\n\n def match_tokens(self, channel):\n return []\n\n class Meta:\n model = ChannelMetadata\n fields = (\n \"id\",\n \"name\",\n \"language\",\n \"included_languages\",\n \"description\",\n \"total_resource_count\",\n \"version\",\n \"published_size\",\n \"last_published\",\n \"icon_encoding\",\n \"matching_tokens\",\n \"public\",\n )\n\n\nclass LowerCaseField(serializers.CharField):\n def to_representation(self, obj):\n return super(LowerCaseField, self).to_representation(obj).lower()\n\n\nclass LanguageSerializer(serializers.ModelSerializer):\n id = LowerCaseField(max_length=14)\n lang_code = LowerCaseField(max_length=3)\n lang_subcode = LowerCaseField(max_length=10)\n\n class Meta:\n model = Language\n fields = (\"id\", \"lang_code\", \"lang_subcode\", \"lang_name\", \"lang_direction\")\n\n\nclass FileSerializer(serializers.ModelSerializer):\n checksum = serializers.CharField(source=\"local_file_id\")\n storage_url = serializers.SerializerMethodField()\n download_url = serializers.SerializerMethodField()\n extension = serializers.SerializerMethodField()\n file_size = serializers.SerializerMethodField()\n lang = LanguageSerializer()\n available = serializers.BooleanField(source=\"local_file.available\")\n\n def get_storage_url(self, target_node):\n return target_node.get_storage_url()\n\n def get_download_url(self, target_node):\n return target_node.get_download_url()\n\n def get_extension(self, target_node):\n return target_node.get_extension()\n\n def get_file_size(self, target_node):\n return target_node.get_file_size()\n\n class Meta:\n model = File\n fields = (\n \"storage_url\",\n \"id\",\n \"priority\",\n \"available\",\n \"file_size\",\n \"extension\",\n \"checksum\",\n \"preset\",\n \"lang\",\n \"supplementary\",\n \"thumbnail\",\n \"download_url\",\n )\n\n\nclass AssessmentMetaDataSerializer(serializers.ModelSerializer):\n\n assessment_item_ids = serializers.JSONField(default=\"[]\")\n mastery_model = serializers.JSONField(default=\"{}\")\n\n class Meta:\n model = AssessmentMetaData\n fields = (\n \"assessment_item_ids\",\n \"number_of_assessments\",\n \"mastery_model\",\n \"randomize\",\n \"is_manipulable\",\n )\n\n\ndef get_summary_logs(content_ids, user):\n from kolibri.core.logger.models import ContentSummaryLog\n\n if not content_ids:\n return ContentSummaryLog.objects.none()\n # get all summary logs for the current user that correspond to the descendant content nodes\n return ContentSummaryLog.objects.filter(user=user, content_id__in=content_ids)\n\n\ndef get_topic_progress_fraction(topic, user):\n leaf_ids = (\n topic.get_descendants(include_self=False)\n .order_by()\n .exclude(kind=content_kinds.TOPIC)\n .values_list(\"content_id\", flat=True)\n )\n return round(\n (\n get_summary_logs(leaf_ids, user).aggregate(Sum(\"progress\"))[\"progress__sum\"]\n or 0\n )\n / (len(leaf_ids) or 1),\n 4,\n )\n\n\ndef get_content_progress_fraction(content, user):\n from kolibri.core.logger.models import ContentSummaryLog\n\n try:\n # add up all the progress for the logs, and divide by the total number of content nodes to get overall progress\n overall_progress = ContentSummaryLog.objects.get(\n user=user, content_id=content.content_id\n ).progress\n except ContentSummaryLog.DoesNotExist:\n return None\n return round(overall_progress, 4)\n\n\ndef get_topic_and_content_progress_fraction(node, user):\n if node.kind == content_kinds.TOPIC:\n return get_topic_progress_fraction(node, user)\n else:\n return get_content_progress_fraction(node, user)\n\n\ndef get_topic_and_content_progress_fractions(nodes, user):\n leaf_ids = (\n nodes.get_descendants(include_self=True)\n .order_by()\n .exclude(available=False)\n .exclude(kind=content_kinds.TOPIC)\n .values_list(\"content_id\", flat=True)\n )\n\n leaf_node_logs = get_summary_logs(leaf_ids, user)\n\n overall_progress = {}\n\n for log in leaf_node_logs.values(\"content_id\", \"progress\"):\n overall_progress[log[\"content_id\"]] = round(log[\"progress\"], 4)\n\n for node in nodes:\n if node.kind == content_kinds.TOPIC:\n topic_leaf_ids = (\n node.get_descendants(include_self=True)\n .order_by()\n .exclude(available=False)\n .exclude(kind=content_kinds.TOPIC)\n .values_list(\"content_id\", flat=True)\n )\n\n overall_progress[node.content_id] = (\n round(\n sum(overall_progress.get(leaf_id, 0) for leaf_id in topic_leaf_ids)\n / len(topic_leaf_ids),\n 4,\n )\n if topic_leaf_ids\n else 0.0\n )\n\n return overall_progress\n\n\ndef get_content_progress_fractions(nodes, user):\n if isinstance(nodes, RawQuerySet) or isinstance(nodes, list):\n leaf_ids = [datum.content_id for datum in nodes]\n else:\n leaf_ids = nodes.exclude(kind=content_kinds.TOPIC).values_list(\n \"content_id\", flat=True\n )\n\n summary_logs = get_summary_logs(leaf_ids, user)\n\n # make a lookup dict for all logs to allow mapping from content_id to current progress\n overall_progress = {\n log[\"content_id\"]: round(log[\"progress\"], 4)\n for log in summary_logs.values(\"content_id\", \"progress\")\n }\n return overall_progress\n\n\nclass ContentNodeListSerializer(serializers.ListSerializer):\n def to_representation(self, data):\n\n # Dealing with nested relationships, data can be a Manager,\n # so, first get a queryset from the Manager if needed\n data = data.all() if isinstance(data, Manager) else data\n\n # initialize cache key\n cache_key = None\n\n # ensure that we are filtering by the parent only\n # this allows us to only cache results on the learn page\n from .api import ContentNodeFilter\n\n parent_filter_only = set(self.context[\"request\"].GET.keys()).intersection(\n ContentNodeFilter.Meta.fields\n ) == set([\"parent\"])\n\n # Cache parent look ups only\n if parent_filter_only:\n cache_key = \"contentnode_list_{parent}\".format(\n parent=self.context[\"request\"].GET.get(\"parent\")\n )\n\n if cache.get(cache_key):\n return cache.get(cache_key)\n\n if not data:\n return data\n\n if (\n \"request\" not in self.context\n or not self.context[\"request\"].user.is_facility_user\n ):\n progress_dict = {}\n else:\n user = self.context[\"request\"].user\n # Don't annotate topic progress as too expensive\n progress_dict = get_content_progress_fractions(data, user)\n\n result = []\n topic_only = True\n\n # Allow results to be limited after all queryset filtering has occurred\n if self.limit:\n data = data[: self.limit]\n\n for item in data:\n obj = self.child.to_representation(\n item,\n progress_fraction=progress_dict.get(item.content_id),\n annotate_progress_fraction=False,\n )\n topic_only = topic_only and obj.get(\"kind\") == content_kinds.TOPIC\n result.append(obj)\n\n # Only store if all nodes are topics, because we don't annotate progress on them\n # This has the happy side effect of not caching our dynamically calculated\n # recommendation queries, which might change for the same user over time\n # because they do not return topics\n if topic_only and parent_filter_only:\n cache.set(cache_key, result, 60 * 10)\n\n return result\n\n\nclass ContentNodeSerializer(DynamicFieldsModelSerializer):\n parent = serializers.PrimaryKeyRelatedField(read_only=True)\n files = FileSerializer(many=True, read_only=True)\n assessmentmetadata = AssessmentMetaDataSerializer(\n read_only=True, allow_null=True, many=True\n )\n lang = LanguageSerializer()\n\n class Meta:\n model = ContentNode\n fields = (\n \"id\",\n \"assessmentmetadata\",\n \"author\",\n \"available\",\n \"channel_id\",\n \"coach_content\",\n \"content_id\",\n \"description\",\n \"files\",\n \"kind\",\n \"lang\",\n \"license_description\",\n \"license_name\",\n \"license_owner\",\n \"num_coach_contents\",\n \"parent\",\n \"sort_order\",\n \"title\",\n )\n list_serializer_class = ContentNodeListSerializer\n\n def __new__(cls, *args, **kwargs):\n # This is overwritten to provide a ListClassSerializer for many=True\n limit = kwargs.pop(\"limit\", None)\n new = super(ContentNodeSerializer, cls).__new__(cls, *args, **kwargs)\n new.limit = limit\n return new\n\n def to_representation(\n self, instance, progress_fraction=None, annotate_progress_fraction=True\n ):\n if progress_fraction is None and annotate_progress_fraction:\n if (\n \"request\" not in self.context\n or not self.context[\"request\"].user.is_facility_user\n ):\n # Don't try to annotate for a non facility user\n progress_fraction = 0.0\n else:\n user = self.context[\"request\"].user\n if instance.kind != content_kinds.TOPIC:\n progress_fraction = get_content_progress_fraction(instance, user)\n value = super(ContentNodeSerializer, self).to_representation(instance)\n value[\"progress_fraction\"] = progress_fraction\n return value\n\n\nclass ContentNodeGranularSerializer(serializers.ModelSerializer):\n num_coach_contents = serializers.SerializerMethodField()\n coach_content = serializers.SerializerMethodField()\n total_resources = serializers.SerializerMethodField()\n importable = serializers.SerializerMethodField()\n\n class Meta:\n model = ContentNode\n fields = (\n \"id\",\n \"available\",\n \"coach_content\",\n \"importable\",\n \"kind\",\n \"num_coach_contents\",\n \"on_device_resources\",\n \"title\",\n \"total_resources\",\n )\n\n @property\n def channel_stats(self):\n return self.context[\"channel_stats\"]\n\n def get_total_resources(self, instance):\n # channel_stats is None for export\n if self.channel_stats is None:\n return instance.on_device_resources\n return self.channel_stats.get(instance.id, {\"total_resources\": 0})[\n \"total_resources\"\n ]\n\n def get_num_coach_contents(self, instance):\n # If for exporting, only show what is available on server. For importing,\n # show all of the coach contents in the topic.\n if self.channel_stats is None:\n return instance.num_coach_contents\n return self.channel_stats.get(instance.id, {\"num_coach_contents\": 0})[\n \"num_coach_contents\"\n ]\n\n def get_coach_content(self, instance):\n # If for exporting, only show what is on server. For importing,\n # show all of the coach contents in the topic.\n if self.channel_stats is None:\n return instance.coach_content\n return self.channel_stats.get(instance.id, {\"coach_content\": False})[\n \"coach_content\"\n ]\n\n def get_importable(self, instance):\n # If for export, just return None\n if self.channel_stats is None:\n return None\n return instance.id in self.channel_stats\n\n\nclass ContentNodeProgressListSerializer(serializers.ListSerializer):\n def to_representation(self, data):\n\n if not data:\n return data\n\n if (\n \"request\" not in self.context\n or not self.context[\"request\"].user.is_facility_user\n ):\n progress_dict = {}\n else:\n user = self.context[\"request\"].user\n # Don't annotate topic progress as too expensive\n progress_dict = get_topic_and_content_progress_fractions(data, user)\n\n # Dealing with nested relationships, data can be a Manager,\n # so, first get a queryset from the Manager if needed\n iterable = data.all() if isinstance(data, Manager) else data\n\n return [\n self.child.to_representation(\n item,\n progress_fraction=progress_dict.get(item.content_id, 0.0),\n annotate_progress_fraction=False,\n )\n for item in iterable\n ]\n\n\nclass ContentNodeProgressSerializer(serializers.Serializer):\n def to_representation(\n self, instance, progress_fraction=None, annotate_progress_fraction=True\n ):\n if progress_fraction is None and annotate_progress_fraction:\n if (\n \"request\" not in self.context\n or not self.context[\"request\"].user.is_facility_user\n ):\n # Don't try to annotate for a non facility user\n progress_fraction = 0\n else:\n user = self.context[\"request\"].user\n progress_fraction = (\n get_topic_and_content_progress_fraction(instance, user) or 0.0\n )\n return {\"id\": instance.id, \"progress_fraction\": progress_fraction}\n\n class Meta:\n list_serializer_class = ContentNodeProgressListSerializer\n", "path": "kolibri/core/content/serializers.py"}]} |
gh_patches_debug_65930 | rasdani/github-patches | git_diff | iterative__dvc-2882 | "You will be provided with a partial code base and an issue statement explaining a problem to resolv(...TRUNCATED) | "diff --git a/dvc/remote/base.py b/dvc/remote/base.py\n--- a/dvc/remote/base.py\n+++ b/dvc/remote/ba(...TRUNCATED) | "{\"golden_diff\": \"diff --git a/dvc/remote/base.py b/dvc/remote/base.py\\n--- a/dvc/remote/base.py(...TRUNCATED) |
gh_patches_debug_60514 | rasdani/github-patches | git_diff | kedro-org__kedro-1706 | "You will be provided with a partial code base and an issue statement explaining a problem to resolv(...TRUNCATED) | "diff --git a/features/steps/cli_steps.py b/features/steps/cli_steps.py\n--- a/features/steps/cli_st(...TRUNCATED) | "{\"golden_diff\": \"diff --git a/features/steps/cli_steps.py b/features/steps/cli_steps.py\\n--- a/(...TRUNCATED) |
gh_patches_debug_41327 | rasdani/github-patches | git_diff | ibis-project__ibis-1988 | "You will be provided with a partial code base and an issue statement explaining a problem to resolv(...TRUNCATED) | "diff --git a/ibis/pyspark/compiler.py b/ibis/pyspark/compiler.py\n--- a/ibis/pyspark/compiler.py\n+(...TRUNCATED) | "{\"golden_diff\": \"diff --git a/ibis/pyspark/compiler.py b/ibis/pyspark/compiler.py\\n--- a/ibis/p(...TRUNCATED) |
gh_patches_debug_3876 | rasdani/github-patches | git_diff | xorbitsai__inference-299 | "You will be provided with a partial code base and an issue statement explaining a problem to resolv(...TRUNCATED) | "diff --git a/examples/gradio_chatinterface.py b/examples/gradio_chatinterface.py\n--- a/examples/gr(...TRUNCATED) | "{\"golden_diff\": \"diff --git a/examples/gradio_chatinterface.py b/examples/gradio_chatinterface.p(...TRUNCATED) |
gh_patches_debug_57507 | rasdani/github-patches | git_diff | scikit-image__scikit-image-7095 | "You will be provided with a partial code base and an issue statement explaining a problem to resolv(...TRUNCATED) | "diff --git a/skimage/morphology/_skeletonize.py b/skimage/morphology/_skeletonize.py\n--- a/skimage(...TRUNCATED) | "{\"golden_diff\": \"diff --git a/skimage/morphology/_skeletonize.py b/skimage/morphology/_skeletoni(...TRUNCATED) |
gh_patches_debug_29709 | rasdani/github-patches | git_diff | opsdroid__opsdroid-1306 | "You will be provided with a partial code base and an issue statement explaining a problem to resolv(...TRUNCATED) | "diff --git a/opsdroid/connector/slack/__init__.py b/opsdroid/connector/slack/__init__.py\n--- a/ops(...TRUNCATED) | "{\"golden_diff\": \"diff --git a/opsdroid/connector/slack/__init__.py b/opsdroid/connector/slack/__(...TRUNCATED) |
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