Search is not available for this dataset
id int64 0 10.8M | vector listlengths 1.54k 1.54k | ast_depth int64 3 164 | ast_data stringlengths 297 510k | full_path stringlengths 0 319 | code stringlengths 60 56.5k |
|---|---|---|---|---|---|
10,201 | [
0.02377312257885933,
0.04451477527618408,
-0.023100728169083595,
-0.04964320361614227,
-0.030907340347766876,
-0.01251336932182312,
-0.028126589953899384,
-0.017402473837137222,
-0.009031735360622406,
0.03523801267147064,
-0.004572850186377764,
0.016866836696863174,
0.029425792396068573,
-... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def run(self):
model_path = self.arguments[0]
module_name, model_name = model_path.rsplit(".", 1)
try:
module = importlib.import_module(module_name)
except ImportError:
pass
model = getattr(module, model_name, None)
if model is None:
... | |
10,202 | [
0.01027498859912157,
-0.012756363488733768,
0.026421399787068367,
-0.052982594817876816,
0.005513195414096117,
0.0035065438132733107,
-0.020153889432549477,
0.004589960910379887,
0.018266648054122925,
-0.0026998058892786503,
0.010816697962582111,
-0.0014147040201351047,
0.02052667923271656,
... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class Test(unittest.TestCase):
def test_all(self):
data = '76 A9 14 89 AB CD EF AB BA AB BA AB BA AB BA AB BA AB BA AB BA AB BA 88 AC'.replace(' ', '').decode('hex')
self.assertEquals(
list(script.parse(data)),
[('UNK_118', None), ('UNK_169', None), ('PUSH', '\x89\xab\xcd\... | |
10,203 | [
-0.004483853932470083,
-0.03362126275897026,
0.04359760880470276,
-0.017666446045041084,
-0.0010865781223401427,
-0.06117847189307213,
-0.002854750957340002,
-0.0048873089253902435,
-0.009640133008360863,
-0.0012692026793956757,
0.016957342624664307,
-0.060885049402713776,
0.0274594016373157... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "appId", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "ids", "annotation": null, "type_comment": null}}, {"_type": "arg... | def _merge_data(appId, ids, group_by, ext):
eStatAPI._['appId'] = appId
aggregate = request.args.get('aggregate') if request.args.get(
'aggregate') is not None else ''
data = eStatAPI.merge_data(ids, group_by, aggregate)
eStatAPI.path['tmp_merge'] = eStatAPI.path['tmp'] + '.'.join(
[eSta... | |
10,204 | [
0.023419784381985664,
0.00321421236731112,
0.03683372586965561,
-0.04139970988035202,
-0.0007305028266273439,
0.03550107032060623,
-0.033469319343566895,
-0.033753328025341034,
-0.016734659671783447,
-0.011327573098242283,
0.011207415722310543,
-0.014571825042366982,
0.00790854636579752,
-... | 14 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "data", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def readdate(data):
datepos = -1
if data[:5] == 'DATE ':
datepos = 0
else:
datepos = data.find('\nDATE ')
if datepos >= 0:
datepos = datepos + 1
if datepos < 0:
return None
datestr = ''
datepos = datepos + 5
while True:
if datepos >= len(... | |
10,205 | [
0.00166787370108068,
-0.007606427185237408,
0.017555957660079002,
-0.009655199013650417,
0.022738484665751457,
-0.01940273866057396,
0.021422654390335083,
0.03605838865041733,
-0.019760550931096077,
0.0032520650420337915,
-0.004293764475733042,
-0.014358718879520893,
0.01192327681928873,
0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "review_request", "annotation": null, "type_comment": null}}], "kw... | def setup_review_request_child_test(self, review_request):
if not review_request.repository_id:
# The group tests don't create a repository by default.
review_request.repository = self.create_repository()
review_request.save()
diffset = self.create_diffset(review_req... | |
10,206 | [
-0.0010642227716743946,
0.012730658985674381,
0.029179556295275688,
-0.0005755882593803108,
-0.006550009828060865,
-0.0308539941906929,
0.0244147926568985,
0.014060359448194504,
-0.02243255265057087,
0.03250380977988243,
0.000038739668525522575,
-0.018886683508753777,
-0.025535188615322113,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}, {"_type": "arg... | def setup_basic_get_test(self, user, with_local_site, local_site_name,
populate_items):
review_request = self.create_review_request(
create_repository=True,
with_local_site=with_local_site,
submitter=user,
publish=True)
diffset... | |
10,207 | [
0.020553598180413246,
-0.00009374372893944383,
-0.02517108991742134,
-0.0018035442335531116,
0.00925069022923708,
0.024982621893286705,
0.017098331823945045,
0.006811062339693308,
0.054069679230451584,
-0.01242848765105009,
0.016522454097867012,
-0.0034264721907675266,
0.02766307070851326,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "item_rsp", "annotation": null, "type_comment": null}}, {"_type": ... | def compare_item(self, item_rsp, comment):
self.assertEqual(item_rsp['id'], comment.pk)
self.assertEqual(item_rsp['text'], comment.text)
if comment.rich_text:
self.assertEqual(item_rsp['text_type'], 'markdown')
else:
self.assertEqual(item_rsp['text_type'], 'plain... | |
10,208 | [
-0.018458807840943336,
-0.0010941758519038558,
0.03442017361521721,
0.0018668988486751914,
-0.003365981625393033,
-0.018495898693799973,
0.01604791171848774,
0.012598476372659206,
-0.006422874052077532,
0.03884633257985115,
0.014910463243722916,
-0.01181339006870985,
-0.04260485619306564,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}, {"_type": "arg... | def setup_basic_post_test(self, user, with_local_site, local_site_name,
post_valid_data):
review_request = self.create_review_request(
create_repository=True,
with_local_site=with_local_site,
submitter=user,
publish=True)
diff... | |
10,209 | [
0.0016578205395489931,
-0.0076008690521121025,
0.017544906586408615,
-0.00965547002851963,
0.022681409493088722,
-0.01939173974096775,
0.021388627588748932,
0.03605940192937851,
-0.01971493475139141,
0.003229070920497179,
-0.004290999379009008,
-0.01439374964684248,
0.011912068352103233,
0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "review_request", "annotation": null, "type_comment": null}}], "kw... | def setup_review_request_child_test(self, review_request):
if not review_request.repository_id:
# The group tests don't create a repository by default.
review_request.repository = self.create_repository()
review_request.save()
diffset = self.create_diffset(review_req... | |
10,210 | [
0.020544297993183136,
-0.0001226263993885368,
-0.02517252415418625,
-0.0017774691805243492,
0.00926168728619814,
0.02494215965270996,
0.017130719497799873,
0.006790508050471544,
0.05411464348435402,
-0.012429195456206799,
0.016554808244109154,
-0.0034004896879196167,
0.027685588225722313,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "item_rsp", "annotation": null, "type_comment": null}}, {"_type": ... | def compare_item(self, item_rsp, comment):
self.assertEqual(item_rsp['id'], comment.pk)
self.assertEqual(item_rsp['text'], comment.text)
if comment.rich_text:
self.assertEqual(item_rsp['text_type'], 'markdown')
else:
self.assertEqual(item_rsp['text_type'], 'plain... | |
10,211 | [
0.0048063937574625015,
0.024488849565386772,
0.024342646822333336,
-0.019225575029850006,
-0.018896618857979774,
0.0007264416199177504,
0.02677934803068638,
0.032408129423856735,
-0.011275836266577244,
0.02543916366994381,
0.012683031149208546,
-0.03472299501299858,
-0.03976696729660034,
-... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}, {"_type": "arg... | def setup_basic_delete_test(self, user, with_local_site, local_site_name):
review_request = self.create_review_request(
create_repository=True,
with_local_site=with_local_site,
submitter=user,
publish=True)
diffset = self.create_diffset(review_request)
... | |
10,212 | [
-0.009295868687331676,
0.011249973438680172,
0.033756084740161896,
-0.0030020475387573242,
-0.005584917962551117,
-0.024078024551272392,
0.0237081628292799,
0.014843800105154514,
-0.027443770319223404,
0.026260212063789368,
0.0018246531253680587,
-0.023609532043337822,
-0.041720449924468994,... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}, {"_type": "arg... | def setup_basic_get_test(self, user, with_local_site, local_site_name):
review_request = self.create_review_request(
create_repository=True,
with_local_site=with_local_site,
submitter=user,
publish=True)
diffset = self.create_diffset(review_request)
... | |
10,213 | [
-0.0035083601251244545,
0.007166410330682993,
0.030686456710100174,
-0.006767237093299627,
-0.003336840309202671,
-0.01606673002243042,
0.030337180942296982,
0.020357845351099968,
-0.001127353054471314,
0.015368176624178886,
0.025484729558229446,
0.004175728186964989,
-0.028391210362315178,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "user", "annotation": null, "type_comment": null}}, {"_type": "arg... | def setup_basic_put_test(self, user, with_local_site, local_site_name,
put_valid_data):
review_request = self.create_review_request(
create_repository=True,
with_local_site=with_local_site,
submitter=user,
publish=True)
diffset... | |
10,214 | [
0.02973681129515171,
0.025662977248430252,
0.07010480016469955,
-0.02165449783205986,
-0.03899552300572395,
-0.020946478471159935,
0.04627178609371185,
-0.010794571600854397,
0.010740107856690884,
-0.03483454883098602,
-0.016186410561203957,
-0.051848798990249634,
0.03744877502322197,
-0.0... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "config", "annotation":... | class Base10xPipeline(object):
def __init__(self, config):
self.config = config
self.summary_filename = self.config.data_10x.data_10x_cell_summary
self.bam_filename = self.config.data_10x.data_10x_bam
self.bai_filename = self.config.data_10x.data_10x_bai
assert os.path.exis... | |
10,215 | [
0.03886988013982773,
0.02043924294412136,
0.08577419072389603,
-0.012967662885785103,
-0.04670565575361252,
-0.0184637438505888,
0.05337158963084221,
-0.01541772298514843,
-0.0038461536169052124,
0.007670234423130751,
0.018507888540625572,
-0.015406686812639236,
0.03513960540294647,
-0.062... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "config", "annotation": null, "type_comment": null}}], "kwarg": nu... | def __init__(self, config):
self.config = config
self.summary_filename = self.config.data_10x.data_10x_cell_summary
self.bam_filename = self.config.data_10x.data_10x_bam
self.bai_filename = self.config.data_10x.data_10x_bai
assert os.path.exists(self.summary_filename), self.summ... | |
10,216 | [
0.038156043738126755,
0.024477461352944374,
0.0963306576013565,
-0.0034515776205807924,
-0.08165346831083298,
-0.0023223399184644222,
0.017626559361815453,
-0.03601949289441109,
-0.03518344834446907,
0.032652098685503006,
0.04451925680041313,
-0.03834183141589165,
-0.003190314397215843,
0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "segment_len", "annotation": null, "type_comment": null}}], "kwarg... | def _build_segment_regions(self, segment_len=50_000_000):
with pysam.AlignmentFile(self.bam_filename, 'rb') as samfile:
assert samfile.check_index(), \
(self.bam_filename, self.bai_filename)
print(samfile.get_index_statistics())
sam_stats = samfile.ge... | |
10,217 | [
0.021512141451239586,
0.035249676555395126,
0.0957908183336258,
-0.01131397020071745,
-0.03232220187783241,
0.015561209060251713,
0.00735468091443181,
0.018980596214532852,
-0.004391212482005358,
0.008278515189886093,
0.020828263834118843,
-0.04456000775098801,
-0.006964750587940216,
-0.05... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "config", "annotation":... | class Extract10xPipeline(Base10xPipeline):
def __init__(self, config):
super(Extract10xPipeline, self).__init__(config)
self.reads_dirname = self.config.reads.reads_dir
def _build_segment_regions(self, segment_len=50_000_000):
with pysam.AlignmentFile(self.bam_filename, 'rb') ... | |
10,218 | [
0.027995562180876732,
0.027614019811153412,
0.08064819872379303,
-0.012638541869819164,
-0.06366963684558868,
-0.004992819856852293,
0.019780509173870087,
-0.01788472756743431,
-0.02496708184480667,
0.00838793721050024,
0.05198494344949722,
-0.015905484557151794,
-0.0066233109682798386,
0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "segment", "annotation": null, "type_comment": null}}, {"_type": "... | def _process_segment(self, segment, region):
with pysam.AlignmentFile(self.bam_filename, 'rb') as samfile:
assert samfile.check_index(), \
(self.bam_filename, self.bai_filename)
chrom, begin, end = region
mapped = 0
cell_records = defaultdict(lamb... | |
10,219 | [
0.01379632018506527,
0.005223207641392946,
0.051482755690813065,
-0.035394392907619476,
-0.046149350702762604,
-0.04299779608845711,
0.037289734929800034,
-0.02501409500837326,
-0.02499205619096756,
-0.001359521527774632,
0.018567731603980064,
-0.0077301268465816975,
0.01939418725669384,
-... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "cell_id", "annotation": null, "type_comment": null}}], "kwarg": n... | def _cell_fragments(self, cell_id):
cell_name = self._cell_name(cell_id)
pattern = f"{cell_name}_*{self.config.reads.reads_suffix}"
pattern = os.path.join(
self.reads_dirname,
cell_name,
pattern
)
print(colored(
"merging fastq cell... | |
10,220 | [
0.026036206632852554,
0.05179169774055481,
0.07640094310045242,
0.011339668184518814,
-0.058388471603393555,
0.0009254783508367836,
0.03906600549817085,
0.023813888430595398,
-0.028773166239261627,
0.016831131651997566,
0.042621713131666183,
-0.0012866049073636532,
0.01518193818628788,
-0.... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "dry_run", "annotation": null, "type_comment": null}}, {"_type": "... | def _split_once(self, dry_run, segment):
segment_index, region = segment
contig, begin, end = region
print(colored(
"processing 10x bam file {} segment {}, {}:{}-{}".format(
self.bam_filename,
segment_index,
contig,
begi... | |
10,221 | [
0.032235827296972275,
0.04257696494460106,
0.04402710124850273,
-0.04336146265268326,
-0.05011292174458504,
-0.028099369257688522,
-0.018697254359722137,
-0.012153809890151024,
-0.020385118201375008,
-0.035849280655384064,
0.04096041992306709,
0.010638297535479069,
-0.014002139680087566,
-... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "barcode", "annotation": null, "type_comment": null}}, {"_type": "... | def _write_to_fastq(self, barcode, segment, records):
cell = self.barcodes[barcode]
filename = self._cell_segment_filename(cell, segment)
os.makedirs(os.path.dirname(filename), exist_ok=True)
with gzip.open(filename, "at") as outfile:
for rec in records:
ass... | |
10,222 | [
0.0281571876257658,
0.028845814988017082,
0.055141158401966095,
-0.03511996939778328,
-0.056008320301771164,
-0.025224147364497185,
0.05200408026576042,
-0.028437739238142967,
-0.024407997727394104,
0.02363010309636593,
0.015812912955880165,
-0.009608895517885685,
0.01659080758690834,
-0.0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "dry_run", "annotation": null, "type_comment": null}}, {"_type": "... | def _merge_cell(self, dry_run, cell_id):
filenames = self._cell_fragments(cell_id)
if not filenames:
print(colored(
f"can't find segments for cell {cell_id}", 'red'))
return []
cell_name = self._cell_name(cell_id)
outfile = os.path.join(
... | |
10,223 | [
0.023461895063519478,
0.028352368623018265,
0.06705521047115326,
-0.015649516135454178,
-0.01995808631181717,
0.022384751588106155,
0.012801899574697018,
0.03771236538887024,
-0.012579042464494705,
0.024836178869009018,
0.020465705543756485,
-0.008078567683696747,
0.0032933319453150034,
-0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "dask_client", "annotation": null, "type_comment": null}}], "kwarg... | def run(self, dask_client):
try:
self.config.check_nonempty_workdir(self.reads_dirname)
except ValueError:
return
command = "rm -rf {}/*".format(self.reads_dirname)
print(colored(command, 'yellow'))
os.system(command)
os.makedirs(self.reads_dirnam... | |
10,224 | [
0.0046239616349339485,
0.00951071921736002,
0.0497310496866703,
-0.011631859466433525,
-0.025240948423743248,
-0.0015525310300290585,
-0.008459534496068954,
0.0028516515158116817,
0.013665401376783848,
-0.0009448148775845766,
0.019321776926517487,
0.0007441980997100472,
-0.022850753739476204... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_basic_toc(self) -> None:
header = "# Header\n\n<!-- toc -->"
toc = (
"\n\n## Table of contents\n\n"
"- [Section](#section)\n"
" - [More](#more)\n"
" - [Even more](#even-more)\n"
"- [Other section](#other-section)\n"
... | |
10,225 | [
0.00106605957262218,
0.015402945689857006,
0.05432381108403206,
-0.01767720654606819,
-0.022923510521650314,
0.03491506725549698,
0.00047488106065429747,
-0.017793502658605576,
0.023802202194929123,
0.029772136360406876,
0.029074352234601974,
0.005969933699816465,
-0.010763971135020256,
0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestMarkdownToc(file_test_case.FileTestCase):
def setUp(self) -> None:
self.setup_helper(
lambda filename: markdown_toc.main(argv=["bin", filename])
)
def test_wrong_ext(self) -> None:
contents = "<!-- toc --><!-- tocstop -->\n"
self.assert_exit_code(contents, ... | |
10,226 | [
0.017931636422872543,
-0.003633207641541958,
0.024612050503492355,
-0.008356377482414246,
-0.024846451357007027,
0.007266415283083916,
-0.00015400844858959317,
-0.03401150926947594,
0.0480520986020565,
-0.015892352908849716,
0.032792627811431885,
0.010823442600667477,
-0.020428001880645752,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_codeblock_toc(self) -> None:
header = "# Header\n\n<!-- toc -->"
toc = (
"\n\n## Table of contents\n\n"
"- [Section](#section)\n"
" - [More](#more)\n"
"\n"
)
body = (
"<!-- tocstop -->\n\n"
"## Sectio... | |
10,227 | [
0.011814306490123272,
0.014480337500572205,
0.0383748896420002,
-0.004441168624907732,
-0.025928979739546776,
0.0003037513524759561,
-0.0017751377308741212,
-0.013749007135629654,
0.014520227909088135,
0.007393083069473505,
0.034545376896858215,
0.015982888638973236,
-0.014294181019067764,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_weird_toc(self) -> None:
header = "# Header\n\n<!-- toc -->"
toc = (
"\n\n## Table of contents\n\n"
"- [Advanced Find & Replace](#advanced-find--replace)\n"
"- [Package as `package`](#package-as-package)\n"
"- [Something _italicized_](#somet... | |
10,228 | [
-0.005982803646475077,
-0.01930244453251362,
0.04208839684724808,
0.03111296519637108,
0.014924202114343643,
-0.01210280042141676,
0.007664907723665237,
0.04843505844473839,
0.05716768652200699,
-0.018872970715165138,
0.028416825458407402,
-0.03485892713069916,
0.03266384080052376,
0.00718... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_rpc_consumer_isolation(self):
class NeverCalled(object):
def __getattribute__(*args):
assert False, "I should never get called."
server = rpc.get_server(messaging.Target(topic='compute',
server=CONF.host),
... | |
10,229 | [
0.030246535316109657,
0.02530965395271778,
0.070028156042099,
-0.030324691906571388,
-0.03097599372267723,
0.02451506443321705,
-0.002706166123971343,
-0.0070731560699641705,
0.014875772409141064,
-0.005669597070664167,
0.02382468245923519,
0.003201156621798873,
0.00009586373198544607,
-0.... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_repeating_toc(self) -> None:
header = "# Header\n\n<!-- toc -->"
toc = (
"\n\n## Table of contents\n\n"
"- [Bork](#bork)\n"
"- [Bork](#bork-1)\n"
"- [Bork](#bork-2)\n"
"\n"
)
body = "<!-- tocstop -->\n\n## Bork\n\... | |
10,230 | [
0.01790856197476387,
-0.03145093843340874,
0.005574684590101242,
-0.031235026195645332,
0.0030452352948486805,
0.042558323591947556,
0.01136527955532074,
-0.03658480569720268,
0.04798007011413574,
-0.009697971865534782,
0.0321226567029953,
-0.04706845059990883,
0.014993772841989994,
-0.014... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class JsonTestCase(test.TestCase):
def test_json_equal(self):
expected = {
"employees": [
{"firstName": "Anna", "lastName": "Smith"},
{"firstName": "John", "lastName": "Doe"},
{"firstName": "Peter", "lastName": "Jones"}
],
"... | |
10,231 | [
0.04527176171541214,
-0.012990429997444153,
-0.02334611676633358,
-0.04211007058620453,
-0.019554378464818,
0.04467608407139778,
0.01253221370279789,
-0.03145654499530792,
0.035649221390485764,
0.026714006438851357,
0.006672773975878954,
-0.0425453782081604,
0.010327048599720001,
-0.004055... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_json_equal_fail_on_length(self):
expected = {
'top': {
'l1': {
'l2': ['a', 'b', 'c']
}
}
}
observed = {
'top': {
'l1': {
'l2': ['c', 'a', 'b', 'd']
... | |
10,232 | [
0.039084017276763916,
-0.015325476415455341,
-0.01574249565601349,
-0.02865852415561676,
0.008415690623223782,
0.047910936176776886,
0.019553594291210175,
-0.011699721217155457,
0.03977905213832855,
0.0030465610325336456,
0.014167088083922863,
-0.030511945486068726,
0.01102206390351057,
-0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_json_equal_fail_on_inner(self):
expected = {
'top': {
'l1': {
'l2': ['a', 'b', 'c']
}
}
}
observed = {
'top': {
'l1': {
'l2': ['c', 'a', 'd']
}
... | |
10,233 | [
-0.02750605344772339,
-0.006759271025657654,
-0.005038868170231581,
-0.05085255578160286,
-0.004715177696198225,
0.005729577969759703,
0.011877150274813175,
-0.022571682929992676,
-0.002485026139765978,
0.032053012400865555,
-0.03413278982043266,
-0.05811138078570366,
0.04082069545984268,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class MatchTypeTestCase(test.TestCase):
def test_match_type_simple(self):
matcher = test.MatchType(dict)
self.assertEqual(matcher, {})
self.assertEqual(matcher, {"hello": "world"})
self.assertEqual(matcher, {"hello": ["world"]})
self.assertNotEqual(matcher, [])
self... | |
10,234 | [
-0.009045160375535488,
-0.0010876101441681385,
-0.023223215714097023,
-0.04152218997478485,
0.00582145294174552,
-0.006468281149864197,
0.02405783161520958,
-0.014751853421330452,
0.01340603455901146,
0.033113427460193634,
-0.03054697811603546,
-0.05679567903280258,
0.05107855424284935,
-0... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_match_type_simple(self):
matcher = test.MatchType(dict)
self.assertEqual(matcher, {})
self.assertEqual(matcher, {"hello": "world"})
self.assertEqual(matcher, {"hello": ["world"]})
self.assertNotEqual(matcher, [])
self.assertNotEqual(matcher, [{"hello": "world"}]... | |
10,235 | [
-0.006209380924701691,
0.0008727778331376612,
0.012450741603970528,
-0.03782125934958458,
0.00610278220847249,
-0.001387117081321776,
-0.012141604907810688,
-0.030508581548929214,
0.019752761349081993,
0.03072177805006504,
-0.03018878400325775,
-0.05312884971499443,
0.03072177805006504,
-0... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_match_type_object(self):
class Hello(object):
pass
class World(object):
pass
matcher = test.MatchType(Hello)
self.assertEqual(matcher, Hello())
self.assertNotEqual(matcher, World())
self.assertNotEqual(matcher, 123)
self.assertN... | |
10,236 | [
0.008464899845421314,
0.01799813285470009,
-0.010994013398885727,
-0.028757765889167786,
0.010203665122389793,
0.020538147538900375,
-0.048402003943920135,
0.0027062606532126665,
0.04534962400794029,
0.04718105122447014,
0.014019138179719448,
-0.0667162761092186,
-0.0028643303085118532,
-0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"a... | def main():
argument_spec = openstack_full_argument_spec(
name=dict(required=False, default=None),
filters=dict(required=False, type='dict', default=None)
)
module = AnsibleModule(argument_spec)
shade, cloud = openstack_cloud_from_module(module)
try:
subnets = cloud.search_... | |
10,237 | [
-0.021145127713680267,
-0.022456739097833633,
0.012895463034510612,
-0.0034230591263622046,
-0.012313205748796463,
-0.002981769386678934,
0.002715156879276037,
0.027997374534606934,
-0.020385129377245903,
0.0034475750289857388,
-0.024087058380246162,
-0.018264487385749817,
-0.002436286304146... | 15 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TORRENTPROJECTProvider(generic.TorrentProvider):
def __init__(self):
generic.TorrentProvider.__init__(self, "TorrentProject")
self.supportsBacklog = True
self.public = True
self.ratio = 0
self.urls = {'api': u'https://torrentproject.se/',}
self.url = self.urls... | |
10,238 | [
0.022129816934466362,
-0.002487386344000697,
-0.025323810055851936,
-0.03584371134638786,
-0.004220635164529085,
-0.0002964663435705006,
0.010805079713463783,
0.053638823330402374,
-0.008529992774128914,
0.02930362895131111,
-0.008156091906130314,
-0.05120530351996422,
-0.008853194303810596,... | 14 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "search_strings", "annotation": null, "type_comment": null}}, {"_t... | def _doSearch(self, search_strings, search_mode='eponly', epcount=0, age=0, epObj=None):
results = []
items = {'Season': [], 'Episode': [], 'RSS': []}
for mode in search_strings.keys(): # Mode = RSS, Season, Episode
logger.log(u"Search Mode: %s" % mode, logger.DEBUG)
f... | |
10,239 | [
-0.01600148342549801,
-0.03580847755074501,
0.011582734994590282,
0.034753937274217606,
-0.021274177357554436,
-0.03223221376538277,
0.008797377347946167,
0.0037023487966507673,
-0.009124054573476315,
-0.00905528012663126,
-0.012436682358384132,
0.0017881313106045127,
-0.009691442362964153,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def __init__(self):
generic.TorrentProvider.__init__(self, "TorrentProject")
self.supportsBacklog = True
self.public = True
self.ratio = 0
self.urls = {'api': u'https://torrentproject.se/',}
self.url = self.urls['api']
self.headers.update({'User-Agent': USER_AGEN... | |
10,240 | [
-0.004360293038189411,
-0.019216157495975494,
0.053301043808460236,
-0.0200650654733181,
0.02708783745765686,
0.02886282466351986,
0.0029358018655329943,
0.021209802478551865,
0.018688807263970375,
0.006868426222354174,
0.05649087578058243,
0.006328212562948465,
0.020193686708807945,
-0.02... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Name", "_fields": {"id": "TimedeltaIndex", "ctx": {"_type": "Load", "_fields": {}}}}, "targets": [{"_type": "Name", "_fields": {"id": "_holder", "ctx": {"_type": "Store", "_fields": {}... | class TestTimedeltaIndex(DatetimeLike):
_holder = TimedeltaIndex
def setup_method(self, method):
self.indices = dict(index=tm.makeTimedeltaIndex(10))
self.setup_indices()
def create_index(self):
return pd.to_timedelta(range(5), unit='d') + pd.offsets.Hour(1)
def test_numeric_c... | |
10,241 | [
-0.01909104362130165,
-0.008480805903673172,
0.04224401339888573,
-0.024359237402677536,
0.01030251756310463,
0.009022395126521587,
0.016124607995152473,
0.03409554809331894,
0.04601052403450012,
0.004280406516045332,
0.05238651484251022,
0.008179238997399807,
0.0009777852101251483,
-0.017... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_fillna_timedelta(self):
# GH 11343
idx = pd.TimedeltaIndex(['1 day', pd.NaT, '3 day'])
exp = pd.TimedeltaIndex(['1 day', '2 day', '3 day'])
tm.assert_index_equal(idx.fillna(pd.Timedelta('2 day')), exp)
exp = pd.TimedeltaIndex(['1 day', '3 hour', '3 day'])
idx.f... | |
10,242 | [
-0.009611358866095543,
-0.0003199232742190361,
0.031120244413614273,
-0.011909342370927334,
0.015607381239533424,
0.007904116995632648,
-0.0009097413858398795,
0.022696275264024734,
0.013008120469748974,
0.0048706610687077045,
0.037854693830013275,
-0.016469864174723625,
0.034546542912721634... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_isin(self):
index = tm.makeTimedeltaIndex(4)
result = index.isin(index)
assert result.all()
result = index.isin(list(index))
assert result.all()
assert_almost_equal(index.isin([index[2], 5]),
np.array([False, False, True, False])) | |
10,243 | [
-0.0038545599672943354,
-0.023871062323451042,
0.03949487954378128,
-0.028925826773047447,
0.021887853741645813,
0.04014788568019867,
0.011584841646254063,
-0.018429331481456757,
0.05519125238060951,
0.02280690148472786,
0.020376261323690414,
-0.008477008901536465,
-0.00743098696693778,
0.... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_difference_freq(self):
# GH14323: Difference of TimedeltaIndex should not preserve frequency
index = timedelta_range("0 days", "5 days", freq="D")
other = timedelta_range("1 days", "4 days", freq="D")
expected = TimedeltaIndex(["0 days", "5 days"], freq=None)
idx_diff ... | |
10,244 | [
0.02323720045387745,
-0.015511277131736279,
0.06123685836791992,
-0.0034736942034214735,
0.04780563712120056,
-0.003946164157241583,
0.027123935520648956,
0.04048383980989456,
0.02845517173409462,
0.016402730718255043,
-0.020931309089064598,
-0.027219023555517197,
0.010459711775183678,
0.0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_does_not_convert_mixed_integer(self):
df = tm.makeCustomDataframe(10, 10,
data_gen_f=lambda *args, **kwargs: randn(),
r_idx_type='i', c_idx_type='td')
str(df)
cols = df.columns.join(df.index, how='outer')
j... | |
10,245 | [
-0.022387981414794922,
-0.017200229689478874,
0.04193533957004547,
-0.016357671469449997,
0.025276754051446915,
0.014347567223012447,
0.006319188512861729,
0.013131875544786453,
0.038637325167655945,
0.04845914617180824,
0.044800035655498505,
0.022255579009652138,
-0.009370453655719757,
0.... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_factorize(self):
idx1 = TimedeltaIndex(['1 day', '1 day', '2 day', '2 day', '3 day',
'3 day'])
exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp)
exp_idx = TimedeltaIndex(['1 day', '2 day', '3 day'])
arr, idx = idx1.factorize()
tm.asse... | |
10,246 | [
0.015764683485031128,
-0.0009626596583984792,
0.009880087338387966,
-0.037661418318748474,
0.033171020448207855,
0.035609353333711624,
-0.03799940645694733,
-0.012185642495751381,
0.026628555729985237,
0.00513016153126955,
0.032350193709135056,
0.004303299821913242,
0.0007340657175518572,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_sort_values(self):
idx = TimedeltaIndex(['4d', '1d', '2d'])
ordered = idx.sort_values()
assert ordered.is_monotonic
ordered = idx.sort_values(ascending=False)
assert ordered[::-1].is_monotonic
ordered, dexer = idx.sort_values(return_indexer=True)
asse... | |
10,247 | [
-0.013451870530843735,
-0.03411581367254257,
0.056219711899757385,
-0.0383002944290638,
-0.02035626210272312,
0.049524545669555664,
-0.0024183830246329308,
0.0372418649494648,
0.04543852433562279,
0.012578052468597889,
0.009630456566810608,
-0.0017414818285033107,
0.006695167161524296,
-0.... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_get_duplicates(self):
idx = TimedeltaIndex(['1 day', '2 day', '2 day', '3 day', '3day',
'4day'])
with tm.assert_produces_warning(FutureWarning):
# Deprecated - see GH20239
result = idx.get_duplicates()
ex = TimedeltaIndex(['2 day',... | |
10,248 | [
-0.009489448741078377,
0.0048368857242167,
0.07718677818775177,
-0.013423788361251354,
0.0043919687159359455,
0.02867809310555458,
0.004957648925483227,
0.0005422428366728127,
0.037067960947752,
0.017847536131739616,
0.015292440541088581,
-0.01268649660050869,
0.026669608429074287,
-0.0268... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_misc_coverage(self):
rng = timedelta_range('1 day', periods=5)
result = rng.groupby(rng.days)
assert isinstance(list(result.values())[0][0], Timedelta)
idx = TimedeltaIndex(['3d', '1d', '2d'])
assert not idx.equals(list(idx))
non_td = Index(list('abc'))
... | |
10,249 | [
0.004712620284408331,
0.007159611210227013,
0.05575903132557869,
-0.016596011817455292,
0.007053584326058626,
0.033705417066812515,
0.02477683126926422,
0.019631732255220413,
0.02235495112836361,
0.014787973836064339,
0.028258981183171272,
-0.005920769646763802,
0.03468756377696991,
-0.026... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_map(self):
# test_map_dictlike generally tests
rng = timedelta_range('1 day', periods=10)
f = lambda x: x.days
result = rng.map(f)
exp = Int64Index([f(x) for x in rng])
tm.assert_index_equal(result, exp) | |
10,250 | [
0.004313354380428791,
0.01831255853176117,
0.03465511277318001,
-0.023576492443680763,
0.02609724923968315,
0.013578196056187153,
0.018079547211527824,
0.020081326365470886,
0.021712403744459152,
0.0020653260871767998,
0.012084806337952614,
-0.002253323793411255,
0.014192498289048672,
-0.0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_pass_TimedeltaIndex_to_index(self):
rng = timedelta_range('1 days', '10 days')
idx = Index(rng, dtype=object)
expected = Index(rng.to_pytimedelta(), dtype=object)
tm.assert_numpy_array_equal(idx.values, expected.values) | |
10,251 | [
0.010828105732798576,
-0.00029098495724610984,
0.07653601467609406,
-0.021036531776189804,
0.0074905273504555225,
0.041725173592567444,
0.0009023422026075423,
0.02741815708577633,
0.007148072123527527,
-0.011926136910915375,
-0.0026907192077487707,
-0.0048867808654904366,
-0.0005714381113648... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_append_join_nondatetimeindex(self):
rng = timedelta_range('1 days', periods=10)
idx = Index(['a', 'b', 'c', 'd'])
result = rng.append(idx)
assert isinstance(result[0], Timedelta)
# it works
rng.join(idx, how='outer') | |
10,252 | [
-0.0157499760389328,
0.02327425591647625,
0.07529380917549133,
-0.030403191223740578,
0.03879467770457268,
0.013428926467895508,
0.014232366345822811,
0.018440861254930496,
0.020634381100535393,
0.018581144511699677,
0.03904973715543747,
-0.0025952388532459736,
-0.0038035872858017683,
-0.0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_fields(self):
rng = timedelta_range('1 days, 10:11:12.100123456', periods=2,
freq='s')
tm.assert_index_equal(rng.days, Index([1, 1], dtype='int64'))
tm.assert_index_equal(
rng.seconds,
Index([10 * 3600 + 11 * 60 + 12, 10 * 3600 + 11 ... | |
10,253 | [
0.02471107617020607,
-0.050338272005319595,
0.032256994396448135,
-0.004026097245514393,
-0.00381213566288352,
0.04599876329302788,
0.031123902648687363,
-0.023529766127467155,
0.01328370999544859,
0.015742763876914978,
-0.0056383442133665085,
-0.02207121066749096,
0.017394186928868294,
0.... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_append_numpy_bug_1681(self):
td = timedelta_range('1 days', '10 days', freq='2D')
a = DataFrame()
c = DataFrame({'A': 'foo', 'B': td}, index=td)
str(c)
result = a.append(c)
assert (result['B'] == td).all() | |
10,254 | [
0.004441473167389631,
-0.01234509702771902,
0.009680724702775478,
-0.008698844350874424,
0.06909981369972229,
-0.010851820930838585,
-0.04426642879843712,
0.023258285596966743,
0.024608369916677475,
0.012478060089051723,
0.01296900026500225,
-0.004709956236183643,
0.02847452275454998,
0.04... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "request", "annotation": null, "type_comment": null}}, {"_type": "... | def has_permission(self, request, view):
# session-based auth has all scopes for a logged in user
if not request.auth:
return request.user.is_authenticated()
allowed_scopes = set(self.scope_map.get(request.method, []))
current_scopes = request.auth.get_scopes()
retur... | |
10,255 | [
-0.03529835864901543,
-0.06415613740682602,
0.04535863921046257,
-0.043361563235521317,
0.03003106452524662,
0.030779968947172165,
0.013505241833627224,
0.0022529540583491325,
0.0569167323410511,
0.018872389569878578,
0.03352595120668411,
0.015327575616538525,
-0.023116180673241615,
-0.009... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_freq_conversion(self):
# doc example
# series
td = Series(date_range('20130101', periods=4)) - \
Series(date_range('20121201', periods=4))
td[2] += timedelta(minutes=5, seconds=3)
td[3] = np.nan
result = td / np.timedelta64(1, 'D')
expected... | |
10,256 | [
-0.06046301871538162,
-0.0588381290435791,
0.027003109455108643,
-0.01649477332830429,
0.0024774230550974607,
-0.0008077681995928288,
-0.003664020448923111,
0.006109373643994331,
0.01263565942645073,
0.04968743398785591,
-0.015874749049544334,
-0.03127913549542427,
-0.006307139527052641,
-... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class URLTests(TestCase):
def setUp(self):
self.client = Client()
self.client.login(
username=settings.TEST_USERNAME,
password=settings.TEST_PASSWORD)
def test_urls(self):
urls = [
"/date/",
"/date/month/",
"/date/month/add/",
... | |
10,257 | [
-0.04766402021050453,
-0.04974818602204323,
0.020331965759396553,
-0.04870610311627388,
0.019357843324542046,
0.005626687314361334,
-0.03176090866327286,
0.012640932574868202,
0.04331444948911667,
0.04938572272658348,
-0.001810904243029654,
-0.0588550940155983,
-0.021838456392288208,
-0.04... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_urls(self):
urls = [
"/date/",
"/date/month/",
"/date/month/add/",
"/date/month/1/",
"/date/season/",
"/date/season/add/",
"/date/season/5/",
"/date/weekday/",
"/date/weekday/add/",
"... | |
10,258 | [
-0.005406240466982126,
0.025617847219109535,
0.0437823086977005,
-0.039244361221790314,
0.019267257302999496,
-0.01452649850398302,
-0.05993131175637245,
-0.0012691672891378403,
0.01105332188308239,
0.031892381608486176,
-0.0072378977201879025,
-0.04079081490635872,
0.03997955843806267,
-0... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "src"}}, {"_type": ... | class TestKind(util.F2PyTest):
sources = [_path('src', 'kind', 'foo.f90')]
@dec.slow
def test_all(self):
selectedrealkind = self.module.selectedrealkind
selectedintkind = self.module.selectedintkind
for i in range(40):
assert_(selectedintkind(i) in [selected_int_kind(i)... | |
10,259 | [
0.03941787779331207,
0.02126593329012394,
0.037445686757564545,
-0.015647782012820244,
0.009653357788920403,
0.008174214512109756,
-0.027896128594875336,
0.008809986524283886,
-0.011041677556931973,
0.04663194715976715,
-0.002538223285228014,
-0.04663194715976715,
-0.006883207708597183,
0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_all(self):
selectedrealkind = self.module.selectedrealkind
selectedintkind = self.module.selectedintkind
for i in range(40):
assert_(selectedintkind(i) in [selected_int_kind(i), -1],
'selectedintkind(%s): expected %r but got %r' %
(i,... | |
10,260 | [
-0.004837772808969021,
-0.030642298981547356,
0.013773062266409397,
-0.013662484474480152,
0.0015189071418717504,
-0.014633110724389553,
-0.03499168902635574,
-0.013121883384883404,
0.0033234732691198587,
0.020702596753835678,
-0.002186980564147234,
-0.01795044168829918,
-0.01723782904446125... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestShapiro(TestCase):
def test_basic(self):
x1 = [0.11,7.87,4.61,10.14,7.95,3.14,0.46,
4.43,0.21,4.75,0.71,1.52,3.24,
0.93,0.42,4.97,9.53,4.55,0.47,6.66]
w,pw = stats.shapiro(x1)
assert_almost_equal(w,0.90047299861907959,6)
assert_almost_equal(pw,0.... | |
10,261 | [
0.005843997001647949,
-0.04564448446035385,
0.0204226765781641,
-0.033910345286130905,
-0.004947456065565348,
-0.01421281136572361,
-0.010593686252832413,
-0.0095982626080513,
0.00605494761839509,
0.021978437900543213,
0.020554520189762115,
0.017311152070760727,
-0.04725298285484314,
0.020... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_basic(self):
x1 = [0.11,7.87,4.61,10.14,7.95,3.14,0.46,
4.43,0.21,4.75,0.71,1.52,3.24,
0.93,0.42,4.97,9.53,4.55,0.47,6.66]
w,pw = stats.shapiro(x1)
assert_almost_equal(w,0.90047299861907959,6)
assert_almost_equal(pw,0.042089745402336121,6)
x2 ... | |
10,262 | [
0.017948487773537636,
-0.056044578552246094,
0.004911801777780056,
0.003191683441400528,
-0.0062088859267532825,
0.015973232686519623,
0.0048986333422362804,
-0.005955394823104143,
0.017487594857811928,
0.04424571990966797,
-0.026126043871045113,
-0.031130025163292885,
-0.002409811597317457,... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_normal(self):
rs = RandomState(1234567890)
x1 = rs.standard_exponential(size=50)
x2 = rs.standard_normal(size=50)
A,crit,sig = stats.anderson(x1)
assert_array_less(crit[:-1], A)
A,crit,sig = stats.anderson(x2)
assert_array_less(A, crit[-2:]) | |
10,263 | [
-0.001921966322697699,
-0.031487394124269485,
-0.006153577473014593,
0.007135916035622358,
0.0007482526707462966,
0.018043486401438713,
-0.01682131178677082,
-0.009271434508264065,
0.022669347003102303,
0.035508736968040466,
-0.01985703408718109,
-0.039109550416469574,
0.015467721968889236,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestAnderson(TestCase):
def test_normal(self):
rs = RandomState(1234567890)
x1 = rs.standard_exponential(size=50)
x2 = rs.standard_normal(size=50)
A,crit,sig = stats.anderson(x1)
assert_array_less(crit[:-1], A)
A,crit,sig = stats.anderson(x2)
assert_arra... | |
10,264 | [
0.014567079022526741,
-0.05855577811598778,
0.010528254322707653,
-0.0028296930249780416,
-0.018584344536066055,
0.010269539430737495,
0.0004179411625955254,
0.010183300822973251,
0.02431918866932392,
0.04225674644112587,
-0.008839421905577183,
-0.03696746751666069,
0.01726202480494976,
0.... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_expon(self):
rs = RandomState(1234567890)
x1 = rs.standard_exponential(size=50)
x2 = rs.standard_normal(size=50)
A,crit,sig = stats.anderson(x1,'expon')
assert_array_less(A, crit[-2:])
olderr = np.seterr(all='ignore')
try:
A,crit,sig = stats.a... | |
10,265 | [
-0.009957813657820225,
-0.03700987249612808,
0.027715913951396942,
-0.026070108637213707,
0.013491453602910042,
0.012440351769328117,
-0.015545252710580826,
-0.01929326355457306,
0.010759970173239708,
0.058806419372558594,
0.004014243371784687,
-0.04431226849555969,
0.02725951373577118,
0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestAndersonKSamp(TestCase):
def test_example1a(self):
# Example data from Scholz & Stephens (1987), originally
# published in Lehmann (1995, Nonparametrics, Statistical
# Methods Based on Ranks, p. 309)
# Pass a mixture of lists and arrays
t1 = [38.7, 41.5, 43.8, 44.5,... | |
10,266 | [
-0.019425740465521812,
-0.0301032904535532,
0.0267335195094347,
-0.026244573295116425,
0.008305495604872704,
0.00118850520811975,
-0.006283632479608059,
0.01591060683131218,
-0.006049070041626692,
0.05766934156417847,
-0.001143079367466271,
0.0036109413485974073,
0.005619589239358902,
0.02... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_example1b(self):
# Example data from Scholz & Stephens (1987), originally
# published in Lehmann (1995, Nonparametrics, Statistical
# Methods Based on Ranks, p. 309)
# Pass arrays
t1 = np.array([38.7, 41.5, 43.8, 44.5, 45.5, 46.0, 47.7, 58.0])
t2 = np.array([39.2... | |
10,267 | [
-0.032050006091594696,
-0.029932992532849312,
0.028834287077188492,
-0.03046894632279873,
0.00826038047671318,
-0.006940595339983702,
-0.0013758926652371883,
0.026677075773477554,
-0.007851716130971909,
0.06640461832284927,
0.00028660940006375313,
-0.003828716464340687,
0.001318110153079033,... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_example1a(self):
# Example data from Scholz & Stephens (1987), originally
# published in Lehmann (1995, Nonparametrics, Statistical
# Methods Based on Ranks, p. 309)
# Pass a mixture of lists and arrays
t1 = [38.7, 41.5, 43.8, 44.5, 45.5, 46.0, 47.7, 58.0]
t2 = n... | |
10,268 | [
-0.013651003129780293,
-0.02405848354101181,
0.01611890085041523,
-0.047806717455387115,
0.005200214218348265,
0.02405848354101181,
0.013721514493227005,
0.010104280896484852,
0.001659661647863686,
0.03776589408516884,
0.01425740122795105,
0.015315071679651737,
-0.00525662349537015,
0.0044... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_example2b(self):
# Example data taken from an earlier technical report of
# Scholz and Stephens
t1 = [194, 15, 41, 29, 33, 181]
t2 = [413, 14, 58, 37, 100, 65, 9, 169, 447, 184, 36, 201, 118]
t3 = [34, 31, 18, 18, 67, 57, 62, 7, 22, 34]
t4 = [90, 10, 60, 186, 61,... | |
10,269 | [
-0.014951921999454498,
-0.02648421749472618,
0.018257083371281624,
-0.04549963027238846,
0.007225569803267717,
0.020245904102921486,
0.007490268908441067,
0.010888433083891869,
0.0018850868800655007,
0.043668195605278015,
0.01420074887573719,
0.009858253411948681,
0.004957742523401976,
0.0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_example2a(self):
# Example data taken from an earlier technical report of
# Scholz and Stephens
# Pass lists instead of arrays
t1 = [194, 15, 41, 29, 33, 181]
t2 = [413, 14, 58, 37, 100, 65, 9, 169, 447, 184, 36, 201, 118]
t3 = [34, 31, 18, 18, 67, 57, 62, 7, 22,... | |
10,270 | [
-0.020328868180513382,
-0.04656461253762245,
0.016800083220005035,
-0.05477287247776985,
-0.02601839415729046,
-0.0011139324633404613,
-0.0395326167345047,
-0.03779379278421402,
0.012299604713916779,
0.03815178573131561,
0.01827041059732437,
-0.05119294673204422,
-0.010183611884713173,
0.0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestAnsari(TestCase):
def test_small(self):
x = [1,2,3,3,4]
y = [3,2,6,1,6,1,4,1]
W, pval = stats.ansari(x,y)
assert_almost_equal(W,23.5,11)
assert_almost_equal(pval,0.13499256881897437,11)
def test_approx(self):
ramsay = np.array((111, 107, 100, 99, 102, ... | |
10,271 | [
-0.029668040573596954,
-0.03015752136707306,
0.021442025899887085,
-0.03624885156750679,
-0.021006930619478226,
-0.015309905633330345,
-0.009368139319121838,
0.0028791052754968405,
0.013542331755161285,
0.03358389437198639,
0.022801697254180908,
-0.02103412337601185,
-0.03554182127118111,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_approx(self):
ramsay = np.array((111, 107, 100, 99, 102, 106, 109, 108, 104, 99,
101, 96, 97, 102, 107, 113, 116, 113, 110, 98))
parekh = np.array((107, 108, 106, 98, 105, 103, 110, 105, 104,
100, 96, 108, 103, 104, 114, 114, 113, 108, 106, ... | |
10,272 | [
-0.004436441697180271,
-0.00913385022431612,
0.04718760773539543,
-0.010806412436068058,
-0.014602298848330975,
-0.006595351733267307,
-0.03399690240621567,
-0.04915672168135643,
0.0006157193565741181,
-0.02683216892182827,
0.0017555971862748265,
-0.012822977267205715,
0.04697408899664879,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestBartlett(TestCase):
def test_data(self):
args = [g1, g2, g3, g4, g5, g6, g7, g8, g9, g10]
T, pval = stats.bartlett(*args)
assert_almost_equal(T,20.78587342806484,7)
assert_almost_equal(pval,0.0136358632781,7)
def test_bad_arg(self):
# Too few args raises Value... | |
10,273 | [
-0.024405373260378838,
-0.008569628931581974,
0.052527692168951035,
-0.02031414955854416,
0.005714161321520805,
0.023166390135884285,
-0.042099591344594955,
-0.02192740887403488,
0.0034330138005316257,
0.05725131556391716,
0.01968175172805786,
-0.018687985837459564,
-0.009518224745988846,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestLevene(TestCase):
def test_data(self):
args = [g1, g2, g3, g4, g5, g6, g7, g8, g9, g10]
W, pval = stats.levene(*args)
assert_almost_equal(W,1.7059176930008939,7)
assert_almost_equal(pval,0.0990829755522,7)
def test_trimmed1(self):
# Test that center='trimmed' ... | |
10,274 | [
0.01273252721875906,
-0.02222873643040657,
0.026109740138053894,
-0.048815540969371796,
-0.00046981414197944105,
0.025735821574926376,
0.0003590089036151767,
0.01797381602227688,
0.010959643870592117,
0.06544841080904007,
0.03027440421283245,
-0.007968305610120296,
-0.04164664447307587,
0.... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_trimmed2(self):
x = [1.2, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 100.0]
y = [0.0, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 200.0]
np.random.seed(1234)
x2 = np.random.permutation(x)
# Use center='trimmed'
W0, pval0 = stats.levene(x, y, center='trimmed', proportiontocut=0.125)
... | |
10,275 | [
-0.005602774675935507,
-0.029022542759776115,
0.048461318016052246,
-0.030152702704072,
0.022704940289258957,
0.0031927055679261684,
0.006803570780903101,
-0.00871354341506958,
0.01887369342148304,
0.04495781660079956,
0.009826752357184887,
-0.007283889688551426,
-0.04927503317594528,
0.03... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_equal_mean_median(self):
x = np.linspace(-1,1,21)
np.random.seed(1234)
x2 = np.random.permutation(x)
y = x**3
W1, pval1 = stats.levene(x, y, center='mean')
W2, pval2 = stats.levene(x2, y, center='median')
assert_almost_equal(W1, W2)
assert_almost_... | |
10,276 | [
0.008742243982851505,
-0.02489560842514038,
0.05621898174285889,
-0.013131354004144669,
-0.0009803544962778687,
-0.030819706618785858,
-0.0005377709167078137,
-0.025255370885133743,
0.02378034219145775,
0.004739879164844751,
-0.009953446686267853,
-0.030196117237210274,
0.017052771523594856,... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestBinomP(TestCase):
def test_data(self):
pval = stats.binom_test(100,250)
assert_almost_equal(pval,0.0018833009350757682,11)
pval = stats.binom_test(201,405)
assert_almost_equal(pval,0.92085205962670713,11)
pval = stats.binom_test([682,243],p=3.0/4)
assert_al... | |
10,277 | [
0.01903551258146763,
-0.008760346099734306,
0.04417486488819122,
-0.017464999109506607,
-0.02004910632967949,
0.007251093629747629,
-0.05186035484075546,
-0.05751865729689598,
-0.003483532229438424,
0.06130571290850639,
-0.02352428436279297,
-0.04700401425361633,
0.03167758882045746,
0.033... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestFindRepeats(TestCase):
def test_basic(self):
a = [1,2,3,4,1,2,3,4,1,2,5]
res,nums = stats.find_repeats(a)
assert_array_equal(res,[1,2,3,4])
assert_array_equal(nums,[3,3,2,2])
def test_empty_result(self):
# Check that empty arrays are returned when there are no... | |
10,278 | [
0.005301395431160927,
-0.01653670333325863,
0.000681829231325537,
-0.04942752793431282,
0.008040123619139194,
0.02511805109679699,
0.00145739468280226,
0.0012943751644343138,
0.024166017770767212,
0.07506723701953888,
0.01540208701044321,
0.0023817154578864574,
-0.01598895713686943,
0.0362... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_trimmed2(self):
x = [1.2, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 100.0]
y = [0.0, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 200.0]
# Use center='trimmed'
Xsq1, pval1 = stats.fligner(x, y, center='trimmed', proportiontocut=0.125)
# Trim the data here, and use center='mean'
Xsq2, pval2... | |
10,279 | [
-0.0067647043615579605,
0.0018208803376182914,
0.011393890716135502,
-0.026683930307626724,
0.033766619861125946,
0.011139502748847008,
-0.0433262400329113,
-0.028223644942045212,
0.014326043426990509,
0.0729958787560463,
0.009104401804506779,
-0.004632533527910709,
-0.01665569841861725,
0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestFligner(TestCase):
def test_data(self):
# numbers from R: fligner.test in package stats
x1 = np.arange(5)
assert_array_almost_equal(stats.fligner(x1,x1**2),
(3.2282229927203536, 0.072379187848207877), 11)
def test_trimmed1(self):
# Test that... | |
10,280 | [
0.09297609329223633,
-0.024955162778496742,
-0.020758498460054398,
0.0015315950149670243,
-0.006757128518074751,
0.004084253218024969,
-0.004733737092465162,
-0.010691501200199127,
0.01853526569902897,
0.013764058239758015,
0.01997162401676178,
-0.008043605834245682,
0.007687638979405165,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_mood_order_of_args(self):
# z should change sign when the order of arguments changes, pvalue
# should not change
np.random.seed(1234)
x1 = np.random.randn(10, 1)
x2 = np.random.randn(15, 1)
z1, p1 = stats.mood(x1, x2)
z2, p2 = stats.mood(x2, x1)
a... | |
10,281 | [
0.05651431903243065,
-0.036417633295059204,
-0.00978647731244564,
-0.018160097301006317,
0.009256655350327492,
0.024237822741270065,
-0.003882314544171095,
-0.03646635264158249,
0.027794327586889267,
0.0257481187582016,
0.011759607121348381,
-0.039876699447631836,
0.017441488802433014,
0.0... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestMood(TestCase):
def test_mood(self):
# numbers from R: mood.test in package stats
x1 = np.arange(5)
assert_array_almost_equal(stats.mood(x1, x1**2),
(-1.3830857299399906, 0.16663858066771478), 11)
def test_mood_order_of_args(self):
# z... | |
10,282 | [
0.05986177176237106,
-0.036286767572164536,
-0.011078478768467903,
0.006583781912922859,
-0.0022821666207164526,
0.024549908936023712,
0.02901928499341011,
-0.04304780438542366,
0.0298295971006155,
0.03555242344737053,
-0.0002866556460503489,
-0.020776895806193352,
0.0017076684162020683,
0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_mood_2d(self):
# Test if the results of mood test in 2-D case are consistent with the
# R result for the same inputs. Numbers from R mood.test().
ny = 5
np.random.seed(1234)
x1 = np.random.randn(10, ny)
x2 = np.random.randn(15, ny)
z_vectest, pval_vectes... | |
10,283 | [
0.058954425156116486,
-0.05016297474503517,
-0.016713157296180725,
-0.00675225630402565,
0.011541715823113918,
0.011071584187448025,
-0.01878173276782036,
-0.050727132707834244,
0.07597316801548004,
0.034343067556619644,
-0.012975615449249744,
-0.030041370540857315,
0.002359469886869192,
0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_mood_with_axis_none(self):
#Test with axis = None, compare with results from R
x1 = [-0.626453810742332, 0.183643324222082, -0.835628612410047,
1.59528080213779, 0.329507771815361, -0.820468384118015,
0.487429052428485, 0.738324705129217, 0.575781351653492,
... | |
10,284 | [
0.036680132150650024,
-0.048709239810705185,
0.0021149739623069763,
-0.0016780851874500513,
0.0020563104189932346,
0.009484963491559029,
0.02069895714521408,
-0.017080344259738922,
0.019315732643008232,
-0.0016364031471312046,
0.005431006196886301,
-0.016993893310427666,
0.02402116358280182,... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_mood_3d(self):
shape = (10, 5, 6)
np.random.seed(1234)
x1 = np.random.randn(*shape)
x2 = np.random.randn(*shape)
for axis in range(3):
z_vectest, pval_vectest = stats.mood(x1, x2, axis=axis)
# Tests that result for 3-D arrays is equal to that for... | |
10,285 | [
0.023136965930461884,
-0.009039080701768398,
0.02045348845422268,
-0.017564577981829643,
-0.019002612680196762,
-0.03697805851697922,
-0.008917104452848434,
-0.006631655152887106,
0.014842581935226917,
0.042678844183683395,
0.009982791729271412,
-0.006512889172881842,
-0.004680035635828972,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_basic(self):
np.random.seed(12345)
x = stats.norm.rvs(size=20)
osm, osr = stats.probplot(x, fit=False)
osm_expected = [-1.8241636, -1.38768012, -1.11829229, -0.91222575,
-0.73908135, -0.5857176, -0.44506467, -0.31273668,
-0.1856892... | |
10,286 | [
0.02365514263510704,
-0.003415002953261137,
0.028422050178050995,
-0.028601450845599174,
-0.025679796934127808,
-0.04021117836236954,
-0.006170071195811033,
-0.008406161330640316,
0.042030803859233856,
0.026294881477952003,
0.007848740555346012,
-0.03716138377785683,
0.0009114149725064635,
... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_sparams_keyword(self):
np.random.seed(123456)
x = stats.norm.rvs(size=100)
# Check that None, () and 0 (loc=0, for normal distribution) all work
# and give the same results
osm1, osr1 = stats.probplot(x, sparams=None, fit=False)
osm2, osr2 = stats.probplot(x, spa... | |
10,287 | [
0.013618208467960358,
-0.027765147387981415,
0.016865158453583717,
-0.027344875037670135,
-0.007917405106127262,
-0.039858169853687286,
-0.013225049711763859,
-0.011550734750926495,
0.0014980706619098783,
0.021108562126755714,
0.03188653662800789,
0.00041561294347047806,
0.004375586751848459... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_plot_kwarg(self):
np.random.seed(7654321)
fig = plt.figure()
fig.add_subplot(111)
x = stats.t.rvs(3, size=100)
res1, fitres1 = stats.probplot(x, plot=plt)
plt.close()
res2, fitres2 = stats.probplot(x, plot=None)
res3 = stats.probplot(x, fit=False,... | |
10,288 | [
0.02192872017621994,
-0.030723536387085915,
0.059674110263586044,
-0.017286362126469612,
-0.014591929502785206,
-0.015303446911275387,
-0.010935199446976185,
0.01651652529835701,
-0.014941856265068054,
0.046306923031806946,
0.014743564650416374,
0.041804537177085876,
-0.018744388595223427,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_moments_normal_distribution(self):
np.random.seed(32149)
data = np.random.randn(12345)
moments = []
for n in [1, 2, 3, 4]:
moments.append(stats.kstat(data, n))
expected = [0.011315, 1.017931, 0.05811052, 0.0754134]
assert_allclose(moments, expected, ... | |
10,289 | [
-0.009242205880582333,
-0.002256746171042323,
0.03802648186683655,
-0.008547348901629448,
0.0028486039955168962,
0.015237648971378803,
-0.04830789566040039,
-0.010822542943060398,
0.014327570796012878,
0.04439702257514,
0.027892645448446274,
-0.019000941887497902,
0.011554294265806675,
0.0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestKstat(TestCase):
# Note: `kstat` still needs review. Statistics Review issue gh-675.
def test_moments_normal_distribution(self):
np.random.seed(32149)
data = np.random.randn(12345)
moments = []
for n in [1, 2, 3, 4]:
moments.append(stats.kstat(data, n))
... | |
10,290 | [
-0.008199444971978664,
-0.02751491591334343,
0.027245881035923958,
-0.03502343222498894,
0.0419205017387867,
-0.005668072495609522,
-0.02614528499543667,
-0.0019077007891610265,
0.040917735546827316,
0.0555679015815258,
0.020691215991973877,
-0.005588585045188665,
0.027735035866498947,
0.0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_2d_input(self):
# Note: boxcox_llf() was already working with 2-D input (sort of), so
# keep it like that. boxcox() doesn't work with 2-D input though, due
# to brent() returning a scalar.
np.random.seed(54321)
x = stats.norm.rvs(size=100, loc=10)
lmbda = 1
... | |
10,291 | [
-0.020174527540802956,
-0.035903818905353546,
0.02204299159348011,
0.000742271775379777,
0.044061560183763504,
-0.008774453774094582,
-0.04501410946249962,
-0.0125663373619318,
0.03150743246078491,
0.039982687681913376,
0.0069120959378778934,
-0.02176211215555668,
0.029309241101145744,
0.0... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestBoxcox_llf(TestCase):
def test_basic(self):
np.random.seed(54321)
x = stats.norm.rvs(size=10000, loc=10)
lmbda = 1
llf = stats.boxcox_llf(lmbda, x)
llf_expected = -x.size / 2. * np.log(np.sum(x.std()**2))
assert_allclose(llf, llf_expected)
def test_arr... | |
10,292 | [
-0.011870821006596088,
-0.045936599373817444,
0.02693812921643257,
0.0032850983552634716,
0.016936220228672028,
-0.000944928964599967,
-0.03513557091355324,
-0.002444087527692318,
0.05217490345239639,
0.04052319377660751,
0.021962953731417656,
-0.024618098512291908,
0.01526064332574606,
0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestBoxcox(TestCase):
def test_fixed_lmbda(self):
np.random.seed(12345)
x = stats.loggamma.rvs(5, size=50) + 5
xt = stats.boxcox(x, lmbda=1)
assert_allclose(xt, x - 1)
xt = stats.boxcox(x, lmbda=-1)
assert_allclose(xt, 1 - 1/x)
xt = stats.boxcox(x, lmb... | |
10,293 | [
0.0009351136977784336,
-0.0438251718878746,
0.030185436829924583,
-0.008554286323487759,
-0.015184348449110985,
-0.0317300520837307,
0.00324794533662498,
0.011270451359450817,
0.05455893650650978,
0.04317067191004753,
0.020957019180059433,
-0.009981091134250164,
0.003769907169044018,
0.024... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_fixed_lmbda(self):
np.random.seed(12345)
x = stats.loggamma.rvs(5, size=50) + 5
xt = stats.boxcox(x, lmbda=1)
assert_allclose(xt, x - 1)
xt = stats.boxcox(x, lmbda=-1)
assert_allclose(xt, 1 - 1/x)
xt = stats.boxcox(x, lmbda=0)
assert_allclose(xt,... | |
10,294 | [
0.03531639650464058,
-0.027172600850462914,
0.051550764590501785,
-0.018975578248500824,
-0.01996028609573841,
-0.029301699250936508,
0.0011119542177766562,
-0.004357995465397835,
0.02946138195693493,
0.03124449960887432,
0.01626097969710827,
-0.0030655672308057547,
-0.02900894731283188,
0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_alpha(self):
np.random.seed(1234)
x = stats.loggamma.rvs(5, size=50) + 5
# Some regular values for alpha, on a small sample size
_, _, interval = stats.boxcox(x, alpha=0.75)
assert_allclose(interval, [4.004485780226041, 5.138756355035744])
_, _, interval = stats... | |
10,295 | [
0.023986799642443657,
-0.04071752727031708,
0.05747435614466667,
-0.012136955745518208,
-0.0030717591289430857,
-0.025252697989344597,
-0.007706314325332642,
0.03265232592821121,
0.039595186710357666,
0.04139615222811699,
0.011060290038585663,
-0.015047214925289154,
-0.03166048973798752,
0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_lmbda_None(self):
np.random.seed(1234567)
# Start from normal rv's, do inverse transform to check that
# optimization function gets close to the right answer.
np.random.seed(1245)
lmbda = 2.5
x = stats.norm.rvs(loc=10, size=50000)
x_inv = (x * lmbda + 1)*... | |
10,296 | [
0.0021683424711227417,
0.006243464536964893,
0.028898851945996284,
-0.004154055379331112,
0.014164647087454796,
0.0014687773073092103,
-0.013471272774040699,
-0.009026248008012772,
0.014077975414693356,
0.021147917956113815,
-0.002502647927030921,
-0.013743669725954533,
-0.019563062116503716... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestBoxcoxNormmax(TestCase):
def setUp(self):
np.random.seed(12345)
self.x = stats.loggamma.rvs(5, size=50) + 5
def test_pearsonr(self):
maxlog = stats.boxcox_normmax(self.x)
assert_allclose(maxlog, 1.804465, rtol=1e-6)
def test_mle(self):
maxlog = stats.boxco... | |
10,297 | [
-0.00012591063568834215,
-0.0041404422372579575,
0.013356265611946583,
0.005132622085511684,
0.02037784457206726,
0.0054506282322108746,
-0.034700848162174225,
-0.03520965948700905,
0.02507161907851696,
0.026966936886310577,
-0.014462927356362343,
-0.013190901838243008,
0.004782814998179674,... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestBoxcoxNormplot(TestCase):
def setUp(self):
np.random.seed(7654321)
self.x = stats.loggamma.rvs(5, size=500) + 5
def test_basic(self):
N = 5
lmbdas, ppcc = stats.boxcox_normplot(self.x, -10, 10, N=N)
ppcc_expected = [0.57783375, 0.83610988, 0.97524311, 0.9975605... | |
10,298 | [
0.009762303903698921,
-0.02445506490767002,
0.012979426421225071,
-0.02590954862535,
0.0009498832514509559,
0.03384758532047272,
-0.03278753533959389,
-0.034710414707660675,
0.04844173416495323,
0.05098092183470726,
0.029138997197151184,
-0.024516694247722626,
-0.016541682183742523,
0.0720... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs... | class TestCircFuncs(TestCase):
def test_circfuncs(self):
x = np.array([355,5,2,359,10,350])
M = stats.circmean(x, high=360)
Mval = 0.167690146
assert_allclose(M, Mval, rtol=1e-7)
V = stats.circvar(x, high=360)
Vval = 42.51955609
assert_allclose(V, Vval, rtol=... | |
10,299 | [
-0.0035129552707076073,
0.0020564778242260218,
0.003292229725047946,
-0.004768914543092251,
0.026114003732800484,
0.032679811120033264,
-0.049442511051893234,
-0.023291204124689102,
0.012895343825221062,
0.011993788182735443,
0.024646645411849022,
-0.029968926683068275,
0.004653888288885355,... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_plot_kwarg(self):
# Check with the matplotlib.pyplot module
fig = plt.figure()
fig.add_subplot(111)
stats.boxcox_normplot(self.x, -20, 20, plot=plt)
plt.close()
# Check that a Matplotlib Axes object is accepted
fig.add_subplot(111)
ax = fig.add_s... | |
10,300 | [
0.015048051252961159,
-0.0018392063211649656,
0.019420988857746124,
-0.03529218211770058,
-0.008044919930398464,
0.016424240544438362,
-0.03320860490202904,
-0.010417881421744823,
0.06050088256597519,
0.04864250496029854,
0.051369160413742065,
-0.013376045972108841,
-0.035883814096450806,
... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def test_circfuncs(self):
x = np.array([355,5,2,359,10,350])
M = stats.circmean(x, high=360)
Mval = 0.167690146
assert_allclose(M, Mval, rtol=1e-7)
V = stats.circvar(x, high=360)
Vval = 42.51955609
assert_allclose(V, Vval, rtol=1e-7)
S = stats.circstd(x,... |