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 |
|---|---|---|---|---|---|
16,001 | [
-0.004625449422746897,
-0.003369881771504879,
0.015972061082720757,
0.0061197299510240555,
0.024640128016471863,
0.01708812080323696,
0.027157464995980263,
0.012747887521982193,
-0.006063926964998245,
0.014248368330299854,
0.04045098274946213,
-0.06339222192764282,
-0.012933897785842419,
-... | 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):
_opener.OpenerDirector.__init__(self)
ua_handlers = self._ua_handlers = {}
for scheme in (self.default_schemes+
self.default_others+
self.default_features):
klass = self.handler_classes[scheme]
ua_handlers... | |
16,002 | [
0.0319780670106411,
0.033239103853702545,
-0.006935718934983015,
0.014882649295032024,
-0.017892489209771156,
0.03105013072490692,
0.0244356207549572,
0.022972337901592255,
0.04501673951745033,
0.05957818031311035,
0.024744931608438492,
-0.012669880874454975,
0.026529422029852867,
-0.01462... | 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):
self.supports_check_mode = True
argument_spec = dict(
reset=dict(
type='bool',
default=False
),
merge_content=dict(),
verify=dict(
type='bool',
default=False
),... | |
16,003 | [
-0.018956603482365608,
0.03415645658969879,
0.017884893342852592,
0.010094823315739632,
-0.026550767943263054,
-0.010647964663803577,
0.010037204250693321,
-0.002232730621472001,
0.06255102902650833,
0.053700774908065796,
0.043052807450294495,
-0.02800276316702366,
0.005773409269750118,
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": "name", "annotation": null, "type_comment": null}}, {"_type": "arg... | def _replace_handler(self, name, newhandler=None):
# first, if handler was previously added, remove it
if name is not None:
handler = self._ua_handlers.get(name)
if handler:
try:
self.handlers.remove(handler)
except ValueError:
... | |
16,004 | [
0.026981284841895103,
0.02126830816268921,
-0.022992225363850594,
-0.025778554379940033,
-0.02832433581352234,
0.0025858734734356403,
0.0025595638435333967,
0.002405463717877865,
0.05255938321352005,
0.040171246975660324,
0.02970747835934162,
-0.01523460354655981,
0.012638707645237446,
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}}, {"_type": "arg", "_fields": {"arg": "name", "annotation": null, "type_comment": null}}, {"_type": "arg... | def _set_handler(self, name, handle=None, obj=None,
constructor_args=(), constructor_kwds={}):
if handle is None:
handle = obj is not None
if handle:
handler_class = self.handler_classes[name]
if obj is not None:
newhandler = handl... | |
16,005 | [
0.018203753978013992,
-0.03032059222459793,
-0.02348136156797409,
-0.016357161104679108,
0.009546427056193352,
-0.03574638441205025,
-0.042790792882442474,
-0.028154835104942322,
-0.009734505787491798,
0.07235907018184662,
0.008492046035826206,
-0.013085729442536831,
0.05480504035949707,
0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "For", "_fields": {"body": [{"_type": "Assert", "_fields": {"ms... | def test_to_list():
for scalar in ('string', 1, True, False, None):
assert isinstance(to_list(scalar), list)
for container in ([1, 2, 3], {'one': 1}):
assert isinstance(to_list(container), list)
test_list = [1, 2, 3]
assert id(test_list) != id(to_list(test_list)) | |
16,006 | [
-0.048090558499097824,
0.02690727636218071,
0.019729750230908394,
0.02058609575033188,
0.044913068413734436,
-0.02120581828057766,
-0.01700296439230442,
-0.01018600445240736,
0.015876194462180138,
-0.004842295777052641,
0.029273495078086853,
-0.007295838091522455,
0.004245107527822256,
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}}, {"_type": "arg", "_fields": {"arg": "fullurl", "annotation": null, "type_comment": null}}, {"_type": "... | def open(self, fullurl, data=None,
timeout=_sockettimeout._GLOBAL_DEFAULT_TIMEOUT):
if self._seekable:
def bound_open(fullurl, data=None,
timeout=_sockettimeout._GLOBAL_DEFAULT_TIMEOUT):
return UserAgentBase.open(self, fullurl, data, timeout)
... | |
16,007 | [
0.02907523512840271,
0.004049843177199364,
-0.03393944725394249,
-0.049214400351047516,
-0.0028668048325926065,
0.016815654933452606,
0.04333772510290146,
0.02226313389837742,
-0.022626299411058426,
0.0010165877174586058,
-0.011082043871283531,
-0.032706886529922485,
0.006702050566673279,
... | 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 test_dict_merge():
base = dict(obj2=dict(), b1=True, b2=False, b3=False,
one=1, two=2, three=3, obj1=dict(key1=1, key2=2),
l1=[1, 3], l2=[1, 2, 3], l4=[4],
nested=dict(n1=dict(n2=2)))
other = dict(b1=True, b2=False, b3=True, b4=True,
one=1, t... | |
16,008 | [
0.033524539321660995,
0.012976505793631077,
-0.0166140329092741,
-0.05341120436787605,
0.0054933493956923485,
0.047572918236255646,
0.03507533669471741,
0.0009293367620557547,
0.015120252035558224,
0.009817901067435741,
-0.0034921395126730204,
-0.030103668570518494,
-0.0010597574291750789,
... | 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 test_dict_diff():
base = dict(obj2=dict(), b1=True, b2=False, b3=False,
one=1, two=2, three=3, obj1=dict(key1=1, key2=2),
l1=[1, 3], l2=[1, 2, 3], l4=[4],
nested=dict(n1=dict(n2=2)))
other = dict(b1=True, b2=False, b3=True, b4=True,
one=1, th... | |
16,009 | [
0.012053044512867928,
0.012585707008838654,
0.029655691236257553,
0.004595765378326178,
0.01786278560757637,
0.04382700100541115,
0.03215796872973442,
0.01698327250778675,
0.05123472958803177,
0.04409952461719513,
0.03032461740076542,
-0.04137427359819412,
-0.006552991457283497,
0.01287062... | 6 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assert", "_fields": {"msg": null, "test": {"_type": "Call", "_... | def test_conditional():
assert conditional(10, 10)
assert conditional('10', '10')
assert conditional('foo', 'foo')
assert conditional(True, True)
assert conditional(False, False)
assert conditional(None, None)
assert conditional("ge(1)", 1)
assert conditional("gt(1)", 2)
assert condi... | |
16,010 | [
0.029857492074370384,
0.003371007274836302,
0.028852472081780434,
-0.015368442982435226,
0.019043050706386566,
-0.04396965727210045,
0.026821492239832878,
-0.018927890807390213,
0.0033500692807137966,
0.0042032902128994465,
0.015556883998215199,
-0.02142997458577156,
-0.02296891249716282,
... | 9 | {"_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 test_render():
outfile = io.StringIO()
e = Element("this is some text")
e.append("and this is some more text")
# with open("test1.html", 'w') as outfile:
e.render(outfile, "")
(outfile.seek(0))
file_contents = outfile.read()
assert("this is some text") in file_contents
assert("... | |
16,011 | [
0.03608063608407974,
0.01329286489635706,
0.03642590343952179,
-0.042921282351017,
0.03800119459629059,
-0.0444965735077858,
0.022679872810840607,
0.0036172347608953714,
0.04244653508067131,
-0.030103160068392754,
0.0395549051463604,
-0.010541501455008984,
-0.04669766500592232,
-0.04540290... | 9 | {"_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 test_html_body():
outfile = io.StringIO()
h = Html()
b = Body("PythonClass - Session 6")
h.append(b)
h.render(outfile)
file_output = outfile.getvalue()
print(file_output)
assert file_output.strip().startswith("<html>")
assert file_output.strip().endswith("</html>") | |
16,012 | [
0.016041463240981102,
0.020550062879920006,
0.04157929867506027,
-0.03761521726846695,
0.043060384690761566,
-0.03513222187757492,
0.029621711000800133,
0.01972239650785923,
0.059940405189991,
-0.02422010526061058,
0.03410853073000908,
0.010019108653068542,
-0.05148950591683388,
-0.0371142... | 9 | {"_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 test_html_body_p():
outfile = io.StringIO()
h = Html()
b = Body("PythonClass - Session 6")
p = P("Here is a paragraph of text -- there could be more of them, but this is enough to show that we can do some text")
h.append(b)
b.append(p)
b.append("Adding plain text for verification.")
... | |
16,013 | [
0.009087027981877327,
0.04385975003242493,
0.02552587166428566,
-0.06356353312730789,
0.010719496756792068,
-0.029361601918935776,
0.027443736791610718,
0.007968273013830185,
0.012877094559371471,
-0.0017195144901052117,
0.03602846711874008,
0.03497820720076561,
0.021381912752985954,
0.024... | 8 | {"_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 test_indent():
outfile = io.StringIO()
p = P("Test contents")
p.render(outfile, " ")
file_output = outfile.getvalue()
lines = file_output.split("\n")
print(file_output)
assert file_output.startswith(" ")
assert lines[1].startswith(" T")
assert lines[2].startswith(" <") | |
16,014 | [
0.04235781729221344,
0.04720059037208557,
0.02192394994199276,
-0.016412831842899323,
-0.012687623500823975,
-0.004738685209304094,
0.03396514058113098,
-0.02159525640308857,
0.03683574125170708,
-0.019612129777669907,
0.01432014163583517,
0.036397483199834824,
-0.01402431633323431,
0.0184... | 9 | {"_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 test_indent_subtag():
outfile = io.StringIO()
b = Body()
b.append(P("Test contents."))
b.render(outfile)
file_output = outfile.getvalue()
lines = file_output.split("\n")
print(file_output)
assert file_output.startswith("<body>")
assert lines[1].startswith(Element.ind + "<p>")
... | |
16,015 | [
0.031028756871819496,
0.02294563502073288,
0.0007292735972441733,
-0.06987988948822021,
0.01482992060482502,
-0.027269670739769936,
0.03157197684049606,
0.018567277118563652,
-0.0033190774265676737,
-0.012135546654462814,
0.0368303507566452,
-0.009854020550847054,
-0.0269002802670002,
0.00... | 7 | {"_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 test_meta():
outfile = io.StringIO()
encode_attributes = dict(charset="UTF-8")
e = Encoding(**encode_attributes)
e.render(outfile)
file_output = outfile.getvalue()
print(file_output)
assert 'meta charset="UTF-8"/' in file_output | |
16,016 | [
0.006909510120749474,
0.012263443320989609,
0.04912874102592468,
-0.04712960496544838,
0.04877889156341553,
-0.019091738387942314,
0.023302417248487473,
-0.0021865537855774164,
-0.007527992594987154,
-0.030511796474456787,
0.044730644673109055,
-0.024139555171132088,
-0.04210678115487099,
... | 9 | {"_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 test_full_rendering():
outfile = io.StringIO()
dt = Doctype()
h = Html()
hd = Head()
encode_attributes = dict(charset="UTF-8")
e = Encoding(**encode_attributes)
t = Title("PythonClass - Session6")
b = Body()
header = Header(2, "Text for header")
p_attributes = dict(style="tex... | |
16,017 | [
-0.007692677900195122,
0.03448524326086044,
0.06432133167982101,
-0.006626247428357601,
0.008866949938237667,
0.02566622383892536,
-0.03156154602766037,
0.021376537159085274,
-0.002628631191328168,
0.015013902448117733,
0.002152332104742527,
-0.03611484542489052,
0.00458025885745883,
0.024... | 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}}, {"_type": "arg", "_fields": {"arg": "part", "annotation": n... | class QueryParseTest(_common.TestCase):
def pqp(self, part):
return beets.library.parse_query_part(
part,
{'year': dbcore.query.NumericQuery},
{':': dbcore.query.RegexpQuery},
)
def test_one_basic_term(self):
q = 'test'
r = (None, 'test', dbco... | |
16,018 | [
0.03141704201698303,
-0.04011010378599167,
0.006055914331227541,
0.022520629689097404,
-0.0010580375092104077,
0.005789021961390972,
0.0016744316089898348,
-0.02879895456135273,
0.031798314303159714,
0.02661297842860222,
0.04636301100254059,
-0.020525291562080383,
-0.016166049987077713,
0.... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "inverse_scale", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonly... | def check_exponential(inverse_scale):
rng = check_random_state(1)
p_carl = Exponential(inverse_scale=inverse_scale)
p_scipy = st.expon(scale=1. / inverse_scale)
X = rng.rand(50, 1)
assert_array_almost_equal(p_carl.pdf(X),
p_scipy.pdf(X.ravel()))
assert_array_almos... | |
16,019 | [
0.039746735244989395,
0.023163501173257828,
0.04451923817396164,
-0.019993886351585388,
-0.0028713340871036053,
0.02213910035789013,
-0.020692888647317886,
0.01146725844591856,
-0.029816078022122383,
-0.0006108740926720202,
0.017125563696026802,
-0.021922169253230095,
0.012341012246906757,
... | 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 AnyFieldQueryTest(_common.LibTestCase):
def test_no_restriction(self):
q = dbcore.query.AnyFieldQuery('title', beets.library.ITEM_KEYS,
dbcore.query.SubstringQuery)
self.assertEqual(self.lib.items(q).get().title, 'the title')
def test_restriction_com... | |
16,020 | [
0.027363231405615807,
-0.04778758063912392,
0.060365840792655945,
-0.04683133587241173,
-0.02682381309568882,
-0.01667293719947338,
-0.010966134257614613,
-0.004689263645559549,
-0.005599532276391983,
-0.019382288679480553,
-0.005198033060878515,
-0.047738540917634964,
-0.0069634029641747475... | 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 DummyDataTestCase(_common.TestCase, AssertsMixin):
def setUp(self):
super(DummyDataTestCase, self).setUp()
self.lib = beets.library.Library(':memory:')
items = [_common.item() for _ in range(3)]
items[0].title = 'foo bar'
items[0].artist = 'one'
items[0].album =... | |
16,021 | [
0.009231380186975002,
-0.06558870524168015,
0.05008406564593315,
-0.03743554279208183,
-0.027388129383325577,
-0.02056659758090973,
-0.008561978116631508,
0.009556518867611885,
-0.019992824643850327,
-0.01670318841934204,
0.02213491126894951,
-0.045697882771492004,
-0.03164680302143097,
-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 setUp(self):
super(DummyDataTestCase, self).setUp()
self.lib = beets.library.Library(':memory:')
items = [_common.item() for _ in range(3)]
items[0].title = 'foo bar'
items[0].artist = 'one'
items[0].album = 'baz'
items[0].year = 2001
items[0].comp = T... | |
16,022 | [
0.0132645508274436,
0.017088327556848526,
0.05664464086294174,
-0.028243208304047585,
0.016982844099402428,
-0.002233283594250679,
-0.025553379207849503,
0.02017372101545334,
0.011273549869656563,
0.027135631069540977,
0.012710762210190296,
-0.056328192353248596,
-0.020252833142876625,
0.0... | 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 GetTest(DummyDataTestCase):
def test_get_empty(self):
q = ''
results = self.lib.items(q)
self.assert_matched_all(results)
def test_get_none(self):
q = None
results = self.lib.items(q)
self.assert_matched_all(results)
def test_get_one_keyed_term(self):
... | |
16,023 | [
-0.003668857039883733,
-0.001289997948333621,
0.022261159494519234,
-0.010434919036924839,
-0.02402753382921219,
-0.023567793890833855,
-0.030076762661337852,
0.022515228018164635,
-0.004258656874299049,
-0.028286190703511238,
0.007785356603562832,
-0.039755526930093765,
-0.00979370065033435... | 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_unicode_query(self):
item = self.lib.items().get()
item.title = u'caf\xe9'
item.store()
q = u'title:caf\xe9'
results = self.lib.items(q)
self.assert_matched(results, [u'caf\xe9']) | |
16,024 | [
-0.0002594298857729882,
0.0030818514060229063,
0.03723878413438797,
-0.022455671802163124,
-0.009932786226272583,
0.008326191455125809,
0.00011616121628321707,
-0.022822193801403046,
-0.01740986481308937,
0.012571754865348339,
-0.0029581498820334673,
-0.03740982711315155,
0.01562611758708954... | 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 MatchTest(_common.TestCase):
def setUp(self):
super(MatchTest, self).setUp()
self.item = _common.item()
def test_regex_match_positive(self):
q = dbcore.query.RegexpQuery('album', '^the album$')
self.assertTrue(q.match(self.item))
def test_regex_match_negative(self):
... | |
16,025 | [
-0.008501826785504818,
0.008605366572737694,
0.02144438959658146,
-0.044016219675540924,
0.005758002866059542,
0.0032500214874744415,
0.014484167098999023,
-0.020213408395648003,
0.014495671726763248,
0.020903678610920906,
0.018418706953525543,
-0.02793292887508869,
0.011700077913701534,
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 PathQueryTest(_common.LibTestCase, AssertsMixin):
def setUp(self):
super(PathQueryTest, self).setUp()
self.i.path = '/a/b/c.mp3'
self.i.title = 'path item'
self.i.store()
def test_path_exact_match(self):
q = 'path:/a/b/c.mp3'
results = self.lib.items(q)
... | |
16,026 | [
0.011775607243180275,
-0.003127721603959799,
0.031661566346883774,
-0.023372964933514595,
0.0018117389408871531,
-0.03435758873820305,
-0.010655976831912994,
0.008316452614963055,
-0.0038824966177344322,
0.009931839071214199,
0.004562072921544313,
-0.0798557698726654,
-0.017178794369101524,
... | 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 DefaultSearchFieldsTest(DummyDataTestCase):
def test_albums_matches_album(self):
albums = list(self.lib.albums('baz'))
self.assertEqual(len(albums), 1)
def test_albums_matches_albumartist(self):
albums = list(self.lib.albums(['album artist']))
self.assertEqual(len(albums),... | |
16,027 | [
-0.0016261968994513154,
0.022741040214896202,
-0.0074409013614058495,
-0.05771670490503311,
0.007893526926636696,
0.02608773112297058,
0.00654593575745821,
0.020807091146707535,
0.03818519413471222,
-0.005551529582589865,
0.06408090144395828,
-0.0211088415235281,
-0.012200335040688515,
0.0... | 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 testSwitch( self ) :
# Build a scene with a sphere, a plane, and
# a filter switch controlling an attribute
# assignment. Index 0 should assign to the
# plane and index 1 should assign to the
# sphere.
script = Gaffer.ScriptNode()
script["plane"] = GafferScene.Plane()
script["sphere"] = GafferSce... | |
16,028 | [
-0.014588815160095692,
0.024301068857312202,
-0.0007917599286884069,
-0.05693860352039337,
-0.002193089807406068,
0.011680587194859982,
-0.008840467780828476,
0.027270594611763954,
0.05710206553339958,
-0.012695401906967163,
0.05960845202207565,
-0.012334427796304226,
-0.006521377246826887,
... | 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 FilterSwitchTest( GafferSceneTest.SceneTestCase ) :
def testConstruct( self ) :
f = GafferScene.FilterSwitch()
self.assertEqual( f.getName(), "FilterSwitch" )
def testSwitch( self ) :
# Build a scene with a sphere, a plane, and
# a filter switch controlling an attribute
# assignment. Index 0 shoul... | |
16,029 | [
-0.026557505130767822,
0.015149908140301704,
-0.00015112404071260244,
-0.04230102151632309,
-0.004048793576657772,
-0.029886871576309204,
0.013104541227221489,
0.04000401496887207,
0.05941241607069969,
0.0031212810426950455,
0.02487991750240326,
-0.006500652525573969,
-0.008755717426538467,
... | 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 testConnectWithoutInputs( self ) :
s = Gaffer.ScriptNode()
s["i"] = GafferScene.Isolate()
s["p"] = GafferScene.PathFilter()
s["s"] = Gaffer.Switch()
s["s"].setup( s["p"]["out"] )
s["s"]["in"][0].setInput( s["p"]["out"] )
s["s"]["in"][0].setInput( None )
s["i"]["filter"].setInput( s["s"]["out"] ) | |
16,030 | [
-0.005797283258289099,
0.0016674981452524662,
0.003934118431061506,
-0.013485437259078026,
-0.014337367378175259,
0.015944261103868484,
-0.010548700578510761,
-0.023133723065257072,
0.05324912071228027,
-0.024075696244835854,
0.03604428097605705,
-0.029755232855677605,
-0.0262921005487442,
... | 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 testSwitchConnectionSerializationProblem( self ):
s = Gaffer.ScriptNode()
b1 = Gaffer.Box()
s.addChild( b1 )
b2 = Gaffer.Box()
b1.addChild( b2 )
fs = Gaffer.Switch( "FilterSwitch" )
fs.setup( GafferScene.FilterPlug() )
b2.addChild( fs )
f1 = GafferScene.PathFilter()
b2.addChild( f1 )
f2 = ... | |
16,031 | [
-0.0009528746595606208,
0.021038945764303207,
0.006237296853214502,
-0.07120063900947571,
-0.023250799626111984,
-0.02654225006699562,
-0.0013815859565511346,
0.03070264309644699,
0.04389477148652077,
-0.022171204909682274,
0.008663095533847809,
-0.01130283810198307,
-0.021881558001041412,
... | 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 testCompatibilityWithIntPlugs( self ) :
s = Gaffer.ScriptNode()
s["p"] = GafferScene.PathFilter()
s["d"] = Gaffer.Dot()
s["d"].setup( Gaffer.IntPlug() )
s["d"]["in"].setInput( s["p"]["out"] )
s["s"] = Gaffer.Switch()
s["s"].setup( s["p"]["out"] )
# We use `execute()` here because the compatibilit... | |
16,032 | [
-0.004680832382291555,
-0.010195722803473473,
-0.001656741718761623,
-0.036253705620765686,
-0.012576577253639698,
0.028934216126799583,
0.03732534125447273,
-0.03382735326886177,
-0.03952927514910698,
0.03350384160876274,
-0.0022026703227311373,
-0.0391855426132679,
0.014608644880354404,
... | 12 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "filename", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs"... | def parse_dictionary(filename):
dict_anagrams = defaultdict(set)
with open(filename) as dictionary:
for word in dictionary:
word = word.rstrip()
dict_anagrams[''.join(sorted(word))].add(word)
return dict_anagrams | |
16,033 | [
0.03735193610191345,
0.01415904238820076,
-0.010070154443383217,
-0.019205383956432343,
0.0011031831381842494,
0.012401835061609745,
0.013742269016802311,
0.01366342045366764,
-0.017718516290187836,
0.044470883905887604,
-0.0015755736967548728,
-0.008369266986846924,
0.023789895698428154,
... | 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 index:
def GET(self):
form_word = input_word()
return render.formtemplate(form_word)
def POST(self):
form_word = input_word()
if not form_word.validates():
return render.formtemplate(form_word)
else:
anagram_list=set()
sor... | |
16,034 | [
0.04565016180276871,
0.03578650578856468,
-0.014929682947695255,
0.013073258101940155,
-0.0066596451215445995,
0.0043810512870550156,
0.02677278034389019,
0.011099408380687237,
0.010366903617978096,
0.04929591342806816,
-0.02619124948978424,
0.0015656596515327692,
0.0024141911417245865,
-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 POST(self):
form_word = input_word()
if not form_word.validates():
return render.formtemplate(form_word)
else:
anagram_list=set()
sorted_word = ''.join(sorted(form_word.d.Word))
if word_anagrams[sorted_word]:
for word in w... | |
16,035 | [
0.028112225234508514,
-0.014168862253427505,
0.023777632042765617,
-0.0594816617667675,
0.018703900277614594,
0.002496150089427829,
-0.004243768285959959,
-0.028463002294301987,
0.03490225598216057,
0.042819779366254807,
0.0190922599285841,
-0.07025551050901413,
-0.0401388481259346,
-0.014... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "FunctionDef", "_fields": ... | def sa_version():
if hasattr(sa, '__version__'):
def tryint(s):
try:
return int(s)
except (ValueError, TypeError):
return -1
return tuple(map(tryint, sa.__version__.split('.')))
return (0, 0, 0) | |
16,036 | [
-0.01900513842701912,
-0.04881319776177406,
-0.02716290019452572,
-0.0022533871233463287,
0.03363131731748581,
-0.011869876645505428,
-0.022350488230586052,
-0.01624883897602558,
0.04083326458930969,
0.002813260769471526,
0.008341144770383835,
-0.03676549717783928,
0.04254483804106712,
-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 UserTest(TestCase):
@fixture
def event(self):
return mock.Mock(spec=Event())
@fixture
def interface(self):
return User.to_python(dict(
id=1,
email='lol@example.com',
favorite_color='brown',
))
def test_path(self):
assert sel... | |
16,037 | [
0.06056048721075058,
0.023504244163632393,
0.052725739777088165,
-0.04285819083452225,
0.005314923822879791,
0.021937295794487,
0.022932520136237144,
-0.028819169849157333,
-0.04309111461043358,
-0.00623603630810976,
0.014970721676945686,
-0.025621743872761726,
0.07106328755617142,
0.05319... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "engine", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "connection", "annotation": null, "type_comment": null}}], "kwar... | def withoutSqliteForeignKeys(engine, connection=None):
conn = connection
if engine.dialect.name == 'sqlite':
if conn is None:
conn = engine.connect()
# This context is not re-entrant. Ensure it.
assert not getattr(engine, 'fk_disabled', False)
engine.fk_disabled = Tru... | |
16,038 | [
-0.0073004369623959064,
0.014646860770881176,
0.021648382768034935,
0.0034346545580774546,
0.020970074459910393,
0.015658576041460037,
-0.008484601974487305,
0.006811825092881918,
0.003440402913838625,
0.05311499163508415,
-0.006599135231226683,
0.011807163245975971,
0.027707170695066452,
... | 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 MatrixDiagTest(test.TestCase):
def testVector(self):
with self.test_session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
mat = np.diag(v)
v_diag = array_ops.matrix_diag(v)
self.assertEqual((3, 3), v_diag.get_shape())
self.assertAllEqual(v_diag.eval(), mat)
def _testBatchVec... | |
16,039 | [
-0.020651161670684814,
-0.01988345943391323,
0.03338403254747391,
-0.025750890374183655,
-0.002580024302005768,
-0.0298526082187891,
0.0012625942472368479,
0.005680988542735577,
0.01272190548479557,
0.03676191717386246,
0.008066345937550068,
0.012425791472196579,
0.006306116934865713,
0.03... | 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": "dtype", "annotation": null, "type_comment": null}}], "kwarg": nul... | def _testBatchVector(self, dtype):
with self.test_session(use_gpu=True):
v_batch = np.array([[1.0, 0.0, 3.0], [4.0, 5.0, 6.0]]).astype(dtype)
mat_batch = np.array([[[1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 3.0]],
[[4.0, 0.0, 0.0], [0.0, 5.0, 0.0],
... | |
16,040 | [
-0.010850721038877964,
-0.011441946029663086,
0.04537363722920418,
0.006961386650800705,
0.04326377436518669,
-0.02060014009475708,
0.003614008892327547,
0.017504902556538582,
0.014931334182620049,
0.028332438319921494,
-0.008758247829973698,
0.02793828956782818,
0.00732655543833971,
0.021... | 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 testGrad(self):
shapes = ((3,), (7, 4))
with self.test_session(use_gpu=True):
for shape in shapes:
x = constant_op.constant(np.random.rand(*shape), np.float32)
y = array_ops.matrix_diag(x)
error = gradient_checker.compute_gradient_error(x,
... | |
16,041 | [
-0.02283736877143383,
-0.04880950599908829,
0.04959900304675102,
-0.01735732890665531,
0.02103777974843979,
-0.015580959618091583,
-0.00157464062795043,
-0.0007626485312357545,
0.04518710449337959,
0.032578371465206146,
0.0269590076059103,
0.015522908419370651,
0.003674645209684968,
0.0335... | 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 testSquare(self):
with self.test_session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
mat = np.array([[0.0, 1.0, 0.0], [1.0, 0.0, 1.0], [1.0, 1.0, 1.0]])
mat_set_diag = np.array([[1.0, 1.0, 0.0], [1.0, 2.0, 1.0],
[1.0, 1.0, 3.0]])
output = array_ops.matrix_... | |
16,042 | [
-0.008776679635047913,
-0.020730381831526756,
0.037977077066898346,
0.01119317952543497,
0.02713349461555481,
0.01873094215989113,
0.010457189753651619,
-0.016314443200826645,
0.00178017548751086,
0.04254021495580673,
0.018951740115880966,
0.004391406197100878,
0.020411452278494835,
0.0521... | 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 MatrixSetDiagTest(test.TestCase):
def testSquare(self):
with self.test_session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
mat = np.array([[0.0, 1.0, 0.0], [1.0, 0.0, 1.0], [1.0, 1.0, 1.0]])
mat_set_diag = np.array([[1.0, 1.0, 0.0], [1.0, 2.0, 1.0],
[1.0, 1... | |
16,043 | [
-0.036608509719371796,
-0.028678201138973236,
0.06348855793476105,
-0.003881585318595171,
0.02971559576690197,
-0.0075038219802081585,
-0.012806061655282974,
-0.00777469715103507,
0.022730471566319466,
0.04419301450252533,
0.02489747479557991,
0.016045039519667625,
0.02711058221757412,
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 testRectangular(self):
with self.test_session(use_gpu=True):
v = np.array([3.0, 4.0])
mat = np.array([[0.0, 1.0, 0.0], [1.0, 0.0, 1.0]])
expected = np.array([[3.0, 1.0, 0.0], [1.0, 4.0, 1.0]])
output = array_ops.matrix_set_diag(mat, v)
self.assertEqual((2, 3), output.get_shape())
... | |
16,044 | [
-0.022915655747056007,
-0.05622725188732147,
0.052894920110702515,
-0.02178923413157463,
0.0019301717402413487,
-0.02550877444446087,
0.007063607219606638,
-0.01254318282008171,
0.024663956835865974,
0.015852048993110657,
0.02041640505194664,
0.011733566410839558,
-0.0019037711899727583,
0... | 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": "dtype", "annotation": null, "type_comment": null}}], "kwarg": nul... | def _testSquareBatch(self, dtype):
with self.test_session(use_gpu=True):
v_batch = np.array([[-1.0, 0.0, -3.0], [-4.0, -5.0, -6.0]]).astype(dtype)
mat_batch = np.array([[[1.0, 0.0, 3.0], [0.0, 2.0, 0.0], [1.0, 0.0, 3.0]],
[[4.0, 0.0, 4.0], [0.0, 5.0, 0.0],
... | |
16,045 | [
0.006400887854397297,
-0.040070027112960815,
0.04023415222764015,
0.016975248232483864,
0.03477112576365471,
0.017971724271774292,
-0.00998819898813963,
0.010339896194636822,
-0.0028531430289149284,
0.021383186802268028,
0.0232120119035244,
0.007473564241081476,
0.043680787086486816,
0.029... | 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 testInvalidShapeAtEval(self):
with self.test_session(use_gpu=True):
v = array_ops.placeholder(dtype=dtypes_lib.float32)
with self.assertRaisesOpError("input must be at least 2-dim"):
array_ops.matrix_set_diag(v, [v]).eval(feed_dict={v: 0.0})
with self.assertRaisesOpError(
r"b... | |
16,046 | [
-0.035686906427145004,
-0.04553474113345146,
0.06704812496900558,
0.008358006365597248,
0.01312661450356245,
-0.026759427040815353,
-0.0011828045826405287,
-0.007121274713426828,
-0.0042595346458256245,
0.02795589342713356,
0.00958898663520813,
0.010750939138233662,
0.020132845267653465,
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 testRectangularBatch(self):
with self.test_session(use_gpu=True):
v_batch = np.array([[-1.0, -2.0], [-4.0, -5.0]])
mat_batch = np.array([[[1.0, 0.0, 3.0], [0.0, 2.0, 0.0]],
[[4.0, 0.0, 4.0], [0.0, 5.0, 0.0]]])
mat_set_diag_batch = np.array([[[-1.0, 0.0, 3.0], [0.0,... | |
16,047 | [
0.0008085062145255506,
-0.02241867035627365,
0.0357528030872345,
0.006409515161067247,
0.033481668680906296,
-0.0164949893951416,
0.01760714314877987,
-0.00436666514724493,
-0.01717398874461651,
0.02898622862994671,
-0.0056895422749221325,
0.026855576783418655,
0.016307679936289787,
0.0460... | 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 testGradWithNoShapeInformation(self):
with self.test_session(use_gpu=True) as sess:
v = array_ops.placeholder(dtype=dtypes_lib.float32)
mat = array_ops.placeholder(dtype=dtypes_lib.float32)
grad_input = array_ops.placeholder(dtype=dtypes_lib.float32)
output = array_ops.matrix_set_diag(ma... | |
16,048 | [
-0.0003110604884568602,
-0.02228725142776966,
0.049165867269039154,
0.0032850978896021843,
0.040030963718891144,
0.0007618647068738937,
0.000153194967424497,
0.015376290306448936,
-0.00436418829485774,
0.027500363066792488,
0.0020012492313981056,
0.029772132635116577,
0.009451755322515965,
... | 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 testGrad(self):
shapes = ((3, 4, 4), (3, 3, 4), (3, 4, 3), (7, 4, 8, 8))
with self.test_session(use_gpu=True):
for shape in shapes:
x = constant_op.constant(
np.random.rand(*shape), dtype=dtypes_lib.float32)
diag_shape = shape[:-2] + (min(shape[-2:]),)
x_diag = cons... | |
16,049 | [
-0.019052261486649513,
-0.01363857090473175,
0.052197303622961044,
0.01878219097852707,
0.01997295580804348,
0.019285503774881363,
-0.019481919705867767,
-0.01617969013750553,
0.005935417488217354,
0.04416883736848831,
0.005336965434253216,
-0.009145576506853104,
0.032604899257421494,
0.04... | 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 MatrixDiagPartTest(test.TestCase):
def testSquare(self):
with self.test_session(use_gpu=True):
v = np.array([1.0, 2.0, 3.0])
mat = np.diag(v)
mat_diag = array_ops.matrix_diag_part(mat)
self.assertEqual((3,), mat_diag.get_shape())
self.assertAllEqual(mat_diag.eval(), v)
def ... | |
16,050 | [
-0.02423921227455139,
-0.02437759004533291,
0.07670753449201584,
0.016490044072270393,
0.029705142602324486,
-0.010193845257163048,
-0.022382639348506927,
-0.006365387700498104,
0.01504860632121563,
0.05083084851503372,
0.021241022273898125,
0.0016605359269306064,
0.04008349031209946,
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}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []... | def testRectangular(self):
with self.test_session(use_gpu=True):
mat = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
mat_diag = array_ops.matrix_diag_part(mat)
self.assertAllEqual(mat_diag.eval(), np.array([1.0, 5.0]))
mat = np.array([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
mat_diag = arra... | |
16,051 | [
-0.02708503045141697,
-0.0566723570227623,
0.05333596467971802,
-0.022462734952569008,
0.0008196175913326442,
-0.02727038599550724,
0.00301491841673851,
-0.008792787790298462,
0.01634601317346096,
0.01759716123342514,
0.018153226003050804,
0.004465902224183083,
-0.0025761479046195745,
0.04... | 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": "dtype", "annotation": null, "type_comment": null}}], "kwarg": nul... | def _testSquareBatch(self, dtype):
with self.test_session(use_gpu=True):
v_batch = np.array([[1.0, 0.0, 3.0], [4.0, 5.0, 6.0]]).astype(dtype)
mat_batch = np.array([[[1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 3.0]],
[[4.0, 0.0, 0.0], [0.0, 5.0, 0.0],
... | |
16,052 | [
-0.041276972740888596,
-0.047483187168836594,
0.06156565248966217,
0.005650476552546024,
0.011780524626374245,
-0.026314351707696915,
-0.009794535115361214,
-0.0033457139506936073,
-0.008688700385391712,
0.03125675395131111,
0.008637922815978527,
0.00475339638069272,
0.02066105417907238,
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 testRectangularBatch(self):
with self.test_session(use_gpu=True):
v_batch = np.array([[1.0, 2.0], [4.0, 5.0]])
mat_batch = np.array([[[1.0, 0.0, 0.0], [0.0, 2.0, 0.0]],
[[4.0, 0.0, 0.0], [0.0, 5.0, 0.0]]])
self.assertEqual(mat_batch.shape, (2, 2, 3))
mat_batch... | |
16,053 | [
-0.017568698152899742,
-0.03278809413313866,
0.04389621317386627,
-0.00524124363437295,
0.00999092124402523,
0.011695441789925098,
-0.031741123646497726,
0.022343913093209267,
0.0005346579127945006,
0.03666955232620239,
0.011867809109389782,
-0.011625218205153942,
0.03485650196671486,
0.00... | 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 DiagPartOpTest(test.TestCase):
def setUp(self):
np.random.seed(0)
def _diagPartOp(self, tensor, dtype, expected_ans, use_gpu):
with self.test_session(use_gpu=use_gpu):
tensor = ops.convert_to_tensor(tensor.astype(dtype))
tf_ans_inv = array_ops.diag_part(tensor)
inv_out = tf_ans_inv... | |
16,054 | [
-0.006237959489226341,
-0.010164069011807442,
0.05350117012858391,
0.006261020433157682,
0.04522232338786125,
-0.015589133836328983,
0.0020106176380068064,
0.009039852768182755,
0.010861659422516823,
0.03454514965415001,
-0.008371087722480297,
0.03242355212569237,
0.0010881838388741016,
0.... | 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 testGrad(self):
shapes = ((3, 3), (2, 3), (3, 2), (5, 3, 3))
with self.test_session(use_gpu=True):
for shape in shapes:
x = constant_op.constant(np.random.rand(*shape), dtype=np.float32)
y = array_ops.matrix_diag_part(x)
error = gradient_checker.compute_gradient_error(x,
... | |
16,055 | [
-0.017984384670853615,
-0.027896035462617874,
0.033655665814876556,
0.008448612876236439,
0.03825874254107475,
-0.038119956851005554,
-0.00923506822437048,
0.039022065699100494,
0.025837372988462448,
0.04189031571149826,
0.007719985209405422,
0.03490474075078964,
0.011235903017222881,
0.00... | 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 testRankFourFloatTensorUnknownShape(self):
x = np.random.rand(3, 3)
i = np.arange(3)
expected_ans = x[i, i]
for shape in None, (None, 3), (3, None):
with self.test_session(use_gpu=False):
t = ops.convert_to_tensor(x.astype(np.float32))
t.set_shape(shape)
tf_ans = array_... | |
16,056 | [
0.006583188660442829,
-0.01670021004974842,
0.028886234387755394,
-0.018011149019002914,
0.0053206984885036945,
-0.03618188947439194,
-0.017121991142630577,
0.028133869171142578,
0.00425769854336977,
0.01919669285416603,
-0.01220882311463356,
0.0014413193566724658,
-0.019971854984760284,
-... | 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 testRankSixFloatTensor(self):
x = np.random.rand(2, 2, 2, 2, 2, 2)
i = np.arange(2)[:, None, None]
j = np.arange(2)[:, None]
k = np.arange(2)
expected_ans = x[i, j, k, i, j, k]
self.diagPartOp(x, np.float32, expected_ans)
self.diagPartOp(x, np.float64, expected_ans) | |
16,057 | [
-0.00663908151909709,
-0.006260043941438198,
0.024708516895771027,
-0.006935204844921827,
0.0040124692022800446,
-0.017068538814783096,
-0.016772417351603508,
0.02295546792447567,
0.015410250052809715,
0.027361780405044556,
-0.005981687922030687,
0.0049363733269274235,
0.007870953530073166,
... | 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 testRankEightComplexTensor(self):
x = np.random.rand(2, 2, 2, 3, 2, 2, 2, 3)
i = np.arange(2)[:, None, None, None]
j = np.arange(2)[:, None, None]
k = np.arange(2)[:, None]
l = np.arange(3)
expected_ans = x[i, j, k, l, i, j, k, l]
self.diagPartOp(x, np.complex64, expected_ans)
self.d... | |
16,058 | [
-0.002741847187280655,
-0.025483399629592896,
0.03374764323234558,
-0.0031705398578196764,
0.02857951447367668,
-0.00006447136547649279,
0.0017445412231609225,
0.015361488796770573,
-0.015802089124917984,
-0.007650974206626415,
-0.0055610970593988895,
0.004400054458528757,
0.0196484159678220... | 14 | {"_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 DiagGradOpTest(test.TestCase):
def testDiagGrad(self):
np.random.seed(0)
shapes = ((3,), (3, 3), (3, 3, 3))
dtypes = (dtypes_lib.float32, dtypes_lib.float64)
with self.test_session(use_gpu=False):
errors = []
for shape in shapes:
for dtype in dtypes:
x1 = constant_... | |
16,059 | [
-0.01231295894831419,
-0.030926739796996117,
0.06240574270486832,
0.00397252943366766,
0.03125307708978653,
-0.019981887191534042,
-0.004405554383993149,
0.03022385947406292,
-0.01788579672574997,
0.021638676524162292,
0.003319854848086834,
0.02565513551235199,
0.006966046988964081,
0.0249... | 13 | {"_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 testDiagGrad(self):
np.random.seed(0)
shapes = ((3,), (3, 3), (3, 3, 3))
dtypes = (dtypes_lib.float32, dtypes_lib.float64)
with self.test_session(use_gpu=False):
errors = []
for shape in shapes:
for dtype in dtypes:
x1 = constant_op.constant(np.random.rand(*shape), dtyp... | |
16,060 | [
-0.008631809614598751,
-0.021350806578993797,
0.041584767401218414,
0.012380379252135754,
0.02394094318151474,
0.004131743684411049,
-0.012819989584386349,
0.017928974702954292,
-0.014257634058594704,
-0.006600096356123686,
-0.01669331267476082,
-0.00006595083686988801,
0.027921199798583984,... | 14 | {"_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 DiagGradPartOpTest(test.TestCase):
def testDiagPartGrad(self):
np.random.seed(0)
shapes = ((3, 3), (3, 3, 3, 3))
dtypes = (dtypes_lib.float32, dtypes_lib.float64)
with self.test_session(use_gpu=False):
errors = []
for shape in shapes:
for dtype in dtypes:
x1 = cons... | |
16,061 | [
-0.01852310821413994,
-0.03277648240327835,
0.0660552829504013,
0.012432458810508251,
0.02206447534263134,
-0.010096663609147072,
-0.012501528486609459,
0.029837900772690773,
-0.013889191672205925,
0.017254745587706566,
-0.004451824817806482,
0.02020588517189026,
0.015119879506528378,
0.02... | 13 | {"_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 testDiagPartGrad(self):
np.random.seed(0)
shapes = ((3, 3), (3, 3, 3, 3))
dtypes = (dtypes_lib.float32, dtypes_lib.float64)
with self.test_session(use_gpu=False):
errors = []
for shape in shapes:
for dtype in dtypes:
x1 = constant_op.constant(np.random.rand(*shape), dty... | |
16,062 | [
-0.013124694116413593,
-0.04873891547322273,
0.008918060921132565,
-0.0029707530047744513,
0.021654004231095314,
0.009010897018015385,
0.009614331647753716,
-0.029382603242993355,
0.008007107302546501,
0.028709542006254196,
-0.04632518067955971,
-0.012985439971089363,
0.008889050222933292,
... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "ClassDef", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Constant", "_fields": {"... | class Laplacian(Benchmark):
params = [
[30, 300, 900],
['dense', 'coo', 'csc', 'csr', 'dia'],
[True, False]
]
param_names = ['n', 'format', 'normed']
def setup(self, n, format, normed):
data = scipy.sparse.rand(9, n, density=0.5, random_state=42).toarray()
data =... | |
16,063 | [
-0.010676240548491478,
-0.05050443857908249,
0.02184983901679516,
0.010382347740232944,
0.040873780846595764,
-0.0015189199475571513,
0.00807641539722681,
-0.013959934003651142,
-0.01817617192864418,
0.01618674024939537,
-0.05018794164061546,
0.0004705119354184717,
0.01832311972975731,
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}}, {"_type": "arg", "_fields": {"arg": "n", "annotation": null, "type_comment": null}}, {"_type": "arg", ... | def setup(self, n, format, normed):
data = scipy.sparse.rand(9, n, density=0.5, random_state=42).toarray()
data = np.vstack((data, data))
diags = list(range(-9, 0)) + list(range(1, 10))
A = scipy.sparse.spdiags(data, diags, n, n)
if format == 'dense':
self.A = A.toarr... | |
16,064 | [
0.018783533945679665,
0.035732582211494446,
0.011080024763941765,
-0.03844442963600159,
-0.005819173529744148,
0.009890268556773663,
0.000978724448941648,
-0.005367198958992958,
0.0059554302133619785,
0.0012686861446127295,
0.049956489354372025,
-0.05551312118768692,
-0.01855754666030407,
... | 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_fix_not_found(self):
course = CourseFactory.create(default_store=ModuleStoreEnum.Type.split)
ItemFactory.create(category='chapter', parent_location=course.location)
# get course again in order to update its children list
course = self.store.get_course(course.id)
# crea... | |
16,065 | [
0.02865595556795597,
0.028515255078673363,
-0.02298104576766491,
0.020424989983439445,
-0.04406263679265976,
-0.024458397179841995,
0.028843555599451065,
0.01231127418577671,
0.004349983297288418,
0.015805330127477646,
0.03533921763300896,
-0.0052176350727677345,
-0.0051824599504470825,
-0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "_step", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": [... | def clear_fields(_step):
# Clear the input fields and trigger an 'input' event
script = """
$('{selector}')
.prop('disabled', false)
.removeClass('is-disabled')
.val('')
.trigger('input');
""".format(selector=SELECTORS['url_inputs'])
world.browser... | |
16,066 | [
0.01412787102162838,
-0.028021838515996933,
0.006923592649400234,
0.0075434413738548756,
0.01645522750914097,
0.014431947842240334,
0.03796280547976494,
0.010835655964910984,
0.04790377616882324,
0.015355873852968216,
-0.010514036752283573,
-0.03157719597220421,
0.005704361945390701,
0.008... | 7 | {"_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 test_multiplication():
a=Matrix((
(1, 2),
(3, 1),
(0, 6),
))
b = Matrix ((
(1, 2),
(3, 0),
))
c= a*b
assert c[0,0]==7
assert c[0,1]==2
assert c[1,0]==6
assert c[1,1]==6
assert c[2,0]==18
assert c[2,1]==0
x = Symbol("x... | |
16,067 | [
0.046457767486572266,
0.001316610723733902,
-0.01740322820842266,
-0.02024231292307377,
0.019947342574596405,
0.01319990586489439,
0.014207719825208187,
-0.03586342930793762,
0.049038756638765335,
0.01319990586489439,
-0.0014241518219932914,
-0.027972985059022903,
0.04114830866456032,
0.02... | 7 | {"_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 test_creation():
x = Symbol("x")
a = Matrix([x, 0], [0, 0])
m = a
assert m.cols == m.lines
assert m.cols == 2
assert m[:] == [x,0,0,0]
b = Matrix(2,2, [x, 0, 0, 0])
m = b
assert m.cols == m.lines
assert m.cols == 2
assert m[:] == [x,0,0,0]
assert a == b | |
16,068 | [
0.02286829613149166,
-0.01833084039390087,
-0.02121502161026001,
0.03784431517124176,
0.025535259395837784,
0.03154497593641281,
-0.0029173672664910555,
0.008857693523168564,
0.04421606287360191,
0.02325446344912052,
0.016231060028076172,
-0.031182944774627686,
0.008157767355442047,
0.0211... | 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 test_power():
A = Matrix([[2,3],[4,5]])
assert (A**5)[:] == [6140, 8097, 10796, 14237]
A = Matrix([[2, 1, 3],[4,2, 4], [6,12, 1]])
assert (A**3)[:] == [290, 262, 251, 448, 440, 368, 702, 954, 433]
assert A**0 == eye(3)
assert A**1 == A
assert (Matrix([[2]]) ** 100)[0,0] == 2**100
ass... | |
16,069 | [
0.031051721423864365,
0.009249698370695114,
-0.027361243963241577,
0.054487425833940506,
-0.0001163374399766326,
0.04247574508190155,
0.013751140795648098,
-0.02675008215010166,
0.005471073556691408,
0.026044895872473717,
0.010918640531599522,
-0.02325940690934658,
0.016618900001049042,
0.... | 12 | {"_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": "Tuple", "_fields": {"... | def test_determinant():
x, y, z = Symbol('x'), Symbol('y'), Symbol('z')
assert Matrix([ [1] ]).det() == 1
assert Matrix(( (-3, 2),
( 8, -5) )).det() == -1
assert Matrix(( (x, 1),
(y, 2*y) )).det() == 2*x*y-y
assert Matrix(( (1, 1, 1),
... | |
16,070 | [
0.007854371331632137,
-0.012176532298326492,
-0.009422988630831242,
0.008537114597856998,
0.006708941888064146,
-0.010686909779906273,
0.05755358189344406,
-0.01188312191516161,
0.030627533793449402,
0.05299443379044533,
0.008853094652295113,
-0.024375634267926216,
0.04861585050821304,
0.0... | 9 | {"_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 test_submatrix():
m0 = eye(4)
assert m0[0:3, 0:3] == eye(3)
assert m0[2:4, 0:2] == zero(2)
m1 = Matrix(3,3, lambda i,j: i+j)
assert m1[0,:] == Matrix(1,3,(0,1,2))
assert m1[1:3, 1] == Matrix(2,1,(2,3))
m2 = Matrix([0,1,2,3],[4,5,6,7],[8,9,10,11],[12,13,14,15])
assert m2[:,-1] == Ma... | |
16,071 | [
-0.03909263014793396,
-0.03827435150742531,
-0.03560834378004074,
0.011792459525167942,
0.021539220586419106,
0.022146331146359444,
-0.009509196504950523,
0.010545243509113789,
0.037403278052806854,
0.03785201162099838,
0.02336055226624012,
-0.01763259805738926,
0.0002181802992708981,
0.01... | 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 test_LUdecomp():
testmat = Matrix([[0,2,5,3],
[3,3,7,4],
[8,4,0,2],
[-2,6,3,4]])
L,U,p = testmat.LUdecomposition()
assert L.is_lower()
assert U.is_upper()
assert (L*U).permuteBkwd(p)-testmat == zero(4)
testmat = Matrix([[6,-2... | |
16,072 | [
0.005926491692662239,
-0.005681689362972975,
-0.018456950783729553,
0.00855099968612194,
0.012114864774048328,
-0.014027738012373447,
0.0507366880774498,
-0.026711909100413322,
0.023091113194823265,
0.05019015446305275,
0.024890126660466194,
-0.005260401871055365,
0.04773074388504028,
0.03... | 8 | {"_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 test_submatrix_assignment():
m = zero(4)
m[2:4, 2:4] = eye(2)
assert m == Matrix((0,0,0,0),
(0,0,0,0),
(0,0,1,0),
(0,0,0,1))
m[0:2, 0:2] = eye(2)
assert m == eye(4)
m[:,0] = Matrix(4,1,(1,2,3,4))
assert m == Matrix((... | |
16,073 | [
0.001378268818370998,
-0.04948892444372177,
-0.03389780595898628,
0.01865783892571926,
0.026617268100380898,
-0.013624670915305614,
0.008380810730159283,
0.0018596388399600983,
0.028068695217370987,
0.01981663890182972,
0.010996888391673565,
-0.01899728551506996,
0.03523218259215355,
0.027... | 8 | {"_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 test_inverse():
A = eye(4)
assert A.inv() == eye(4)
A = Matrix([[2,3,5],
[3,6,2],
[8,3,6]])
Ainv = A.inv()
assert A*Ainv == eye(3)
Ainv2 = A.inv("LU")
assert Ainv == Ainv2 | |
16,074 | [
-0.02524997666478157,
-0.0416923351585865,
-0.013985964469611645,
-0.0004287627525627613,
0.001284905127249658,
-0.020403575152158737,
-0.028303874656558037,
-0.006417610216885805,
0.0457199402153492,
0.024630345404148102,
-0.01782546564936638,
-0.043551232665777206,
-0.03308388590812683,
... | 8 | {"_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 test_LUsolve():
A = Matrix([[2,3,5],
[3,6,2],
[8,3,6]])
x = Matrix(3,1,[3,7,5])
b = A*x
soln = A.LUsolve(b)
assert soln == x
A = Matrix([[0,-1,2],
[5,10,7],
[8,3,4]])
x = Matrix(3,1,[-1,2,5])
b = A*x
soln = A.LUsolve... | |
16,075 | [
-0.03187275305390358,
-0.025183409452438354,
-0.012904182076454163,
0.01579749770462513,
0.005448111332952976,
0.017695510759949684,
0.020473092794418335,
-0.023100223392248154,
0.04356174170970917,
0.05522758513689041,
0.008818822912871838,
-0.024836210533976555,
0.026780517771840096,
0.0... | 9 | {"_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 test_util():
v1 = Matrix(1,3,[1,2,3])
v2 = Matrix(1,3,[3,4,5])
assert v1.cross(v2) == Matrix(1,3,[-2,4,-2])
assert v1.norm() == sqrt(14)
# cofactor
assert eye(3) == eye(3).cofactorMatrix()
test = Matrix([[1,3,2],[2,6,3],[2,3,6]])
assert test.cofactorMatrix() == Matrix([[27,-6,-6],[-1... | |
16,076 | [
0.009644871577620506,
-0.04700963571667671,
-0.0004004777583759278,
0.017078952863812447,
0.01615576632320881,
0.00948695745319128,
-0.0004779161245096475,
-0.01860949955880642,
0.0401100292801857,
0.009274382144212723,
-0.0163622684776783,
-0.07302892208099365,
-0.029882093891501427,
0.00... | 12 | {"_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 test_jacobian_hessian():
x = Symbol('x')
y = Symbol('y')
L = Matrix(1,2,[x**2*y, 2*y**2 + x*y])
syms = [x,y]
assert L.jacobian(syms) == Matrix([[2*x*y, x**2],[y, 4*y+x]])
L = Matrix(1,2,[x, x**2*y**3])
assert L.jacobian(syms) == Matrix([[1, 0], [2*x*y**3, x**2*3*y**2]])
f = x**2*y
... | |
16,077 | [
-0.013205192051827908,
0.03545675799250603,
0.03910043463110924,
-0.0026432371232658625,
0.013745461590588093,
-0.014260602183640003,
0.015466785058379173,
0.005666547920554876,
0.01540396362543106,
0.06468156725168228,
-0.013845976442098618,
-0.0299284178763628,
0.004947235342115164,
0.06... | 12 | {"_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": "Name", "_fields": {"i... | def test_nullspace():
# first test reduced row-ech form
R = Rational
M = Matrix([[5,7,2,1],
[1,6,2,-1]])
out, tmp = M.rref()
assert out == Matrix([[1,0,-R(2)/23,R(13)/23],
[0,1,R(8)/23, R(-6)/23]])
M = Matrix([[1,3,0,2,6,3,1],
[-2,-6... | |
16,078 | [
0.008508093655109406,
-0.0038536658976227045,
-0.025874612852931023,
0.039562635123729706,
0.02016918547451496,
0.021357817575335503,
-0.027951588854193687,
0.014739020727574825,
-0.015877604484558105,
0.04321610927581787,
0.007907521910965443,
-0.03933741897344589,
-0.0011370191350579262,
... | 13 | {"_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 test_QR():
A = Matrix([[1,2],[2,3]])
Q, S = A.QRdecomposition()
R = Rational
assert Q == Matrix([[5**R(-1,2), (R(2)/5)*(R(1)/5)**R(-1,2)], [2*5**R(-1,2), (-R(1)/5)*(R(1)/5)**R(-1,2)]])
assert S == Matrix([[5**R(1,2), 8*5**R(-1,2)], [0, (R(1)/5)**R(1,2)]])
assert Q*S == A
assert Q.T * Q =... | |
16,079 | [
0.03773465007543564,
-0.0219059307128191,
-0.019986141473054886,
0.015752436593174934,
0.022465338930487633,
0.008639047853648663,
-0.0028447196818888187,
0.01699839159846306,
0.03694639354944229,
0.05878875404596329,
0.034149348735809326,
-0.0489228218793869,
0.0320897102355957,
0.0010075... | 13 | {"_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 test_eigen():
# test charpoly
x = Symbol('x')
y = Symbol('y')
eye3 = eye(3)
assert eye3.charpoly(x) == ((1-x)**3).expand()
assert eye3.charpoly(y) == ((1-y)**3).expand()
# test values
M = Matrix([(0,1,-1),
(1,1,0),
(-1,0,1) ])
vals = M.eigenvals()
... | |
16,080 | [
0.020829614251852036,
-0.014237514697015285,
0.0050269197672605515,
-0.002806376200169325,
-0.012923828326165676,
0.0025371296796947718,
-0.019882813096046448,
-0.024806177243590355,
0.046014510095119476,
0.039339564740657806,
0.0024202591739594936,
-0.02067575789988041,
-0.01146220508962869... | 14 | {"_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 test_wronskian():
x = Symbol('x')
assert wronskian([cos(x), sin(x)], x) == cos(x)**2 + sin(x)**2
assert wronskian([exp(x), exp(2*x)], x) == exp(3*x)
assert wronskian([exp(x), x], x) == exp(x) - x*exp(x)
assert wronskian([1, x, x**2], x) == 2
assert wronskian([exp(x), cos(x), x**3], x).expand... | |
16,081 | [
-0.010389522649347782,
-0.0063217030838131905,
0.01453856285661459,
0.020630139857530594,
0.017205320298671722,
0.0045889876782894135,
-0.01918169856071472,
-0.013171342201530933,
0.010585806332528591,
0.04578158259391785,
0.011262648738920689,
-0.05019459128379822,
0.016135910525918007,
0... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Return", "_fields": {"value": null}}, {"_type": "FunctionDef",... | def test_sparse_matrix():
return
def eye(n):
tmp = SMatrix(n,n,lambda i,j:0)
for i in range(tmp.lines):
tmp[i,i] = 1
return tmp
def zero(n):
return SMatrix(n,n,lambda i,j:0)
# test_multiplication
a=SMatrix((
(1, 2),
(3, 1),
(0, 6),... | |
16,082 | [
0.012659992091357708,
-0.018978044390678406,
-0.014857576228678226,
0.0014406712725758553,
0.010766965337097645,
0.02871190756559372,
0.020339591428637505,
-0.01503672730177641,
0.03098115138709545,
0.023946495726704597,
-0.010319088585674763,
-0.00468479422852397,
0.051643215119838715,
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 test_conjugate():
M = Matrix([ [0,I,5],
[1,2,0]])
assert M.T == Matrix([ [0,1],
[I,2],
[5,0]])
assert M.C == Matrix([ [0,-I,5],
[1,2,0]])
assert M.H == M.T.C
assert M.H == Matrix([ [0,1],
... | |
16,083 | [
0.0008063300629146397,
-0.024583347141742706,
0.04110495001077652,
0.028216108679771423,
0.040681954473257065,
0.03130146861076355,
0.017255619168281555,
0.004500519018620253,
-0.025951853021979332,
0.027345240116119385,
-0.03458588197827339,
-0.007601429708302021,
0.06125931069254875,
0.0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"arg... | def test_conj_dirac():
py.test.raises(ShapeError, "eye(3).D")
M = Matrix([ [1,I,I,I],
[0,1,I,I],
[0,0,1,I],
[0,0,0,1] ])
assert M.D == Matrix([
[1,0,0,0],
[-I,1,0,0],
[-I,-I,-1,0],
[-I,-I... | |
16,084 | [
0.053865354508161545,
0.016762467101216316,
0.00016848239465616643,
-0.02030366100370884,
0.016382616013288498,
0.03533841669559479,
0.014324067160487175,
-0.0419306755065918,
-0.011407789774239063,
0.015794459730386734,
-0.023060645908117294,
-0.04803280159831047,
0.00009687738202046603,
... | 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 test_col_row():
x, y = symbols("xy")
M = Matrix([[x,0,0],
[0,y,0]])
M.row(1,lambda x,i: x+i+1)
assert M == Matrix([[x,0,0],
[1,y+2,3]])
M.col(0,lambda x,i: x+y**i)
assert M == Matrix([[x+1,0,0],
[1+y,y+2,3]]) | |
16,085 | [
-0.006067828740924597,
0.021904194727540016,
0.04394174739718437,
-0.01165778748691082,
-0.08179344236850739,
-0.016569839790463448,
0.003561793128028512,
-0.006973557639867067,
0.024871429428458214,
0.010985436849296093,
-0.003428434254601598,
0.0030811454635113478,
-0.012102317065000534,
... | 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}}, {"_type": "arg", "_fields": {"arg": "ui", "annotation": nul... | class debugformatter(baseformatter):
def __init__(self, ui, topic, opts):
baseformatter.__init__(self, ui, topic, opts)
self._ui.write("%s = {\n" % self._topic)
def _showitem(self):
self._ui.write(" " + repr(self._item) + ",\n")
def end(self):
baseformatter.end(self)
... | |
16,086 | [
-0.010186957195401192,
0.026926778256893158,
0.06964173913002014,
-0.02253265492618084,
-0.06100677698850632,
-0.03408000245690346,
0.005738545674830675,
-0.029966898262500763,
-0.031142069026827812,
0.008960690349340439,
-0.0033945878967642784,
0.02188120037317276,
-0.013744408264756203,
... | 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 __ConfigureWidgets(self):
# configures widgets in base class:
Viewer._ConfigureWidgets(self)
self.connect(self._btnLoad, SIGNAL('clicked()'), self.LoadImage)
B = self._border
Wi, Wb, Wt = self._imageWidth , self._btnWidth , self._textWidth
Hi, Hb, Ht = ... | |
16,087 | [
0.05879731476306915,
0.0384443961083889,
0.008042684756219387,
-0.012644583359360695,
-0.030322683975100517,
-0.0061125620268285275,
0.016462275758385658,
0.0006778226234018803,
0.0053587500005960464,
0.048389848321676254,
0.00462317606434226,
0.03331361338496208,
-0.00251675839535892,
0.0... | 8 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "autoreset", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "convert", "annotation": null, "type_comment": null}}, {"_typ... | def init(autoreset=False, convert=None, strip=None, wrap=True):
if wrap==False and (autoreset==True or convert==True or strip==True):
raise ValueError('wrap=False conflicts with any other arg=True')
sys.stdout = wrap_stream(orig_stdout, convert, strip, autoreset, wrap)
sys.stderr = wrap_stream(ori... | |
16,088 | [
0.002987769665196538,
0.016137681901454926,
0.06097286194562912,
0.010168354958295822,
-0.009870199486613274,
-0.007193008903414011,
0.03779124841094017,
0.0007877058815211058,
0.013330048881471157,
0.008068840950727463,
0.029144730418920517,
-0.040300726890563965,
0.021169062703847885,
0.... | 11 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "app", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "db", "annotation": null, "type_comment": null}}, {"_type": "arg", ... | def test_delete_some_group(app, db, check_ui):
if len (db.get_group_list()) == 0:
app.group.create(Group(name="test"))
old_groups = db.get_group_list()
group = random.choice(old_groups)
app.group.delete_group_by_id(group.id)
new_groups = db.get_group_list()
assert len(old_groups) - 1 == ... | |
16,089 | [
0.011136071756482124,
-0.011073541827499866,
0.04734109714627266,
-0.0443623811006546,
0.010630144737660885,
0.02101016975939274,
0.015825841575860977,
0.0012903972528874874,
-0.00411562854424119,
-0.025034844875335693,
0.060029055923223495,
-0.05116112530231476,
0.031083226203918457,
-0.0... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "session", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "sector", "annotation": null, "type_comment": null}}], "kwarg":... | def create_from_object(session, sector):
data = Sector.get_schema_query(session, sector.uid).first()
if not data: data = Sector()
data.copy_from_object(sector)
for location in sector.locations:
location_data = Location.create_from_object(session, location)
if loc... | |
16,090 | [
0.010036803781986237,
0.015846407040953636,
0.008599779568612576,
-0.021739885210990906,
-0.017535051330924034,
-0.014135397970676422,
-0.009807550348341465,
0.04674522578716278,
-0.023350246250629425,
0.008348160423338413,
-0.018877018243074417,
-0.027398517355322838,
0.002556728897616267,
... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": {"_type": "arg", "_fields": {"arg": "kwargs", "annotation": null, "type_comment": null}}, "v... | def run(self, **kwargs):
self.prompt.render_title(_('Repositories'))
# Limit to only repositories of a specific type
if kwargs.get('str-eq', None) is None:
kwargs['str-eq'] = []
kwargs['str-eq'].append(['notes.%s' % constants.REPO_NOTE_TYPE_KEY, self.repo_type])
# S... | |
16,091 | [
-0.006454683840274811,
0.006282038986682892,
0.009551149792969227,
-0.02414797991514206,
-0.011427965015172958,
-0.04392972216010094,
0.016740966588258743,
0.0015844327863305807,
-0.03034091182053089,
0.023813828825950623,
-0.010291851125657558,
-0.00324683403596282,
-0.0031159583013504744,
... | 10 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "image_file_path", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "number", "annotation": null, "type_comment": null}}], ... | def write_number(image_file_path, number=1):
img = Image.open(image_file_path)
font_size = img.size[0] if img.size[0] < img.size[1] else img.size[1]
font_size = font_size / 4
number_txt = str(number) + ' ' if number < 100 else '99+'
font = ImageFont.truetype("arial.ttf", size=font_size)
if font.... | |
16,092 | [
0.034941092133522034,
0.007060249801725149,
0.07738262414932251,
-0.03752508759498596,
0.027097640559077263,
-0.034072138369083405,
0.003695912193506956,
-0.050445057451725006,
-0.04916449263691902,
0.008506600745022297,
-0.012096752412617207,
-0.04186985641717911,
0.0696992427110672,
0.04... | 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": "tblName", "annotation": null, "type_comment": null}}], "kwarg": n... | def _confirm(self,tblName):
conn = DbConnect(self.dbName,tblName)
res = conn.GetColumnNamesAndTypes()
assert len(res)==len(self.colHeads),'bad number of columns'
names = [x[0] for x in res]
for i in range(len(names)):
assert names[i].upper()==self.colHeads[i].upper(),'bad column head'
if R... | |
16,093 | [
0.0011392309097573161,
0.035224370658397675,
-0.001363972551189363,
-0.028939705342054367,
0.05554695427417755,
0.02210431918501854,
0.0048997728154063225,
0.0014672322431579232,
0.07856913655996323,
0.041811395436525345,
0.02148880995810032,
-0.03662816435098648,
-0.016564741730690002,
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": "For", "_fields": {"body": [{"_type": "Assign", "_fields": {"va... | def test_kernel_gradient():
# Compare analytic and numeric gradient of kernels.
for kernel in kernels:
K, K_gradient = kernel(X, eval_gradient=True)
assert_equal(K_gradient.shape[0], X.shape[0])
assert_equal(K_gradient.shape[1], X.shape[0])
assert_equal(K_gradient.shape[2], kern... | |
16,094 | [
0.008343435823917389,
-0.029519440606236458,
0.019520919770002365,
0.006688352674245834,
0.0028496349696069956,
-0.00292757130227983,
0.03446201980113983,
-0.021584106609225273,
0.010616342537105083,
0.040175460278987885,
-0.028793923556804657,
0.009448714554309845,
0.004500467795878649,
0... | 7 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body":... | def test_auto_vs_cross():
# Auto-correlation and cross-correlation should be consistent.
for kernel in kernels:
if kernel == kernel_white:
continue # Identity is not satisfied on diagonal
K_auto = kernel(X)
K_cross = kernel(X, X)
assert_almost_equal(K_auto, K_cross, ... | |
16,095 | [
-0.011898458003997803,
-0.007863528095185757,
0.010614616796374321,
0.0044533247128129005,
0.029046909883618355,
-0.014546380378305912,
0.02943664789199829,
0.022146262228488922,
0.04096829518675804,
0.02840498834848404,
-0.010694856755435467,
0.020220501348376274,
-0.007250264752656221,
0... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"arg... | def test_kernel_operator_commutative():
# Adding kernels and multiplying kernels should be commutative.
# Check addition
assert_almost_equal((RBF(2.0) + 1.0)(X),
(1.0 + RBF(2.0))(X))
# Check multiplication
assert_almost_equal((3.0 * RBF(2.0))(X),
(RBF... | |
16,096 | [
-0.0035770798567682505,
-0.0063514974899590015,
0.012691362760961056,
-0.00899213831871748,
0.012784425169229507,
-0.006101393140852451,
0.009678472764790058,
-0.036294274032115936,
0.04553069919347763,
0.04713602364063263,
-0.014715466648340225,
0.01047531794756651,
0.020136341452598572,
... | 8 | {"_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": "BinOp", "_fields": {"... | def test_kernel_anisotropic():
# Anisotropic kernel should be consistent with isotropic kernels.
kernel = 3.0 * RBF([0.5, 2.0])
K = kernel(X)
X1 = np.array(X)
X1[:, 0] *= 4
K1 = 3.0 * RBF(2.0)(X1)
assert_almost_equal(K, K1)
X2 = np.array(X)
X2[:, 1] /= 4
K2 = 3.0 * RBF(0.5)(X2)... | |
16,097 | [
-0.002487081103026867,
0.003515111980959773,
0.008101495914161205,
0.0023950187023729086,
-0.005177815444767475,
-0.0045389579609036446,
0.03385666385293007,
-0.00889379158616066,
0.034682437777519226,
0.05566151812672615,
0.018613355234265327,
0.009234143421053886,
0.0016459651524201035,
... | 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 test_matern_kernel():
# Test consistency of Matern kernel for special values of nu.
K = Matern(nu=1.5, length_scale=1.0)(X)
# the diagonal elements of a matern kernel are 1
assert_array_almost_equal(np.diag(K), np.ones(X.shape[0]))
# matern kernel for coef0==0.5 is equal to absolute exponential ... | |
16,098 | [
0.016772059723734856,
0.026461360976099968,
0.008737968280911446,
-0.010668129660189152,
-0.0029364849906414747,
0.007533678784966469,
-0.016178162768483162,
-0.002607917645946145,
-0.0014352482976391912,
0.060709353536367416,
0.03215835988521576,
-0.04364034906029701,
-0.030222700908780098,... | 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": "Tuple", "_fields": {"... | def test_kernel_clone():
# Test that sklearn's clone works correctly on kernels.
bounds = (1e-5, 1e5)
for kernel in kernels:
kernel_cloned = clone(kernel)
# XXX: Should this be fixed?
# This differs from the sklearn's estimators equality check.
assert_equal(kernel, kernel_cl... | |
16,099 | [
-0.03191469982266426,
-0.021625326946377754,
0.021366622298955917,
-0.034172482788562775,
-0.004489107057452202,
-0.018967727199196815,
0.0047213532961905,
-0.0027693116571754217,
0.04249805957078934,
0.03283192589879036,
0.013464381918311119,
-0.010642153210937977,
-0.011041969060897827,
... | 9 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body":... | def test_kernel_versus_pairwise():
# Check that GP kernels can also be used as pairwise kernels.
for kernel in kernels:
# Test auto-kernel
if kernel != kernel_white:
# For WhiteKernel: k(X) != k(X,X). This is assumed by
# pairwise_kernels
K1 = kernel(X)
... | |
16,100 | [
-0.020132284611463547,
0.003534158691763878,
-0.02316962741315365,
-0.062282487750053406,
-0.007271559443324804,
0.026466671377420425,
0.001236391020938754,
0.0037910344544798136,
0.04936530813574791,
0.020403273403644562,
0.003133319551125169,
-0.004047910217195749,
-0.0034805252216756344,
... | 13 | {"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "For", "_fields": {"body": [{"_type": "Assign", "_fields": {"va... | def test_set_get_params():
# Check that set_params()/get_params() is consistent with kernel.theta.
for kernel in kernels:
# Test get_params()
index = 0
params = kernel.get_params()
for hyperparameter in kernel.hyperparameters:
if hyperparameter.bounds == "fixed":
... |