uid stringlengths 24 24 | split stringclasses 1
value | category stringclasses 2
values | content stringlengths 5 482k | signature stringlengths 1 14k | suffix stringlengths 1 482k | prefix stringlengths 9 14k | prefix_token_count int64 3 5.01k | prefix_token_budget int64 64 256 | element_token_count int64 1 292k | signature_token_count int64 1 5.01k | prefix_context_token_count int64 0 255 | repo stringlengths 7 112 | path stringlengths 4 208 | language stringclasses 1
value | name stringlengths 1 218 | qualname stringlengths 1 218 | start_line int64 1 26.7k | end_line int64 1 26.7k | signature_start_line int64 1 26.7k | signature_end_line int64 1 26.7k | source_hash stringlengths 40 40 | source_dataset stringclasses 1
value | source_split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6ba63b2ff5c4000cfc89aee8 | train | class | class TestItemfreq(object):
a = [5, 7, 1, 2, 1, 5, 7] * 10
b = [1, 2, 5, 7]
def test_numeric_types(self):
# Check itemfreq works for all dtypes (adapted from np.unique tests)
def _check_itemfreq(dt):
a = np.array(self.a, dt)
v = stats.itemfreq(a)
assert_a... | class TestItemfreq(object):
| a = [5, 7, 1, 2, 1, 5, 7] * 10
b = [1, 2, 5, 7]
def test_numeric_types(self):
# Check itemfreq works for all dtypes (adapted from np.unique tests)
def _check_itemfreq(dt):
a = np.array(self.a, dt)
v = stats.itemfreq(a)
assert_array_equal(v[:, 0], [1, 2, 5... | _method='foobar')
assert_raises(ValueError, stats.scoreatpercentile, [1], 101)
assert_raises(ValueError, stats.scoreatpercentile, [1], -1)
def test_empty(self):
assert_equal(stats.scoreatpercentile([], 50), np.nan)
assert_equal(stats.scoreatpercentile(np.array([[], []]), 50), np.nan... | 111 | 111 | 370 | 6 | 105 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestItemfreq | TestItemfreq | 1,161 | 1,195 | 1,161 | 1,161 | a259568607b8495ab6b7d60ba4917c1b36f988c3 | bigcode/the-stack | train |
f09dc6c94af6599bce24e4b7 | train | class | 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 returne... | 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 repeats.
... | , stats.kendalltau, x, x, nan_policy='foobar')
# test unequal length inputs
x = np.arange(10.)
y = np.arange(20.)
assert_raises(ValueError, stats.kendalltau, x, y)
class TestFindRepeats(TestCase):
| 64 | 64 | 168 | 8 | 56 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestFindRepeats | TestFindRepeats | 623 | 636 | 623 | 624 | c88dc0e58ce08762b5b5c55568344b0a4b9dea3e | bigcode/the-stack | train |
130a1df7abfa1860efaaeaed | train | class | class TestHistogram(TestCase):
# Tests that histogram works as it should, and keeps old behaviour
#
# what is untested:
# - multidimensional arrays (since 'a' is ravel'd as the first line in the method)
# - very large arrays
# - Nans, Infs, empty and otherwise bad inputs
# sample arrays to ... | class TestHistogram(TestCase):
# Tests that histogram works as it should, and keeps old behaviour
#
# what is untested:
# - multidimensional arrays (since 'a' is ravel'd as the first line in the method)
# - very large arrays
# - Nans, Infs, empty and otherwise bad inputs
# sample arrays to ... | low_values = np.array([0.2, 0.3, 0.4, 0.5, 0.5, 0.6, 0.7, 0.8, 0.9, 1.1, 1.2],
dtype=float) # 11 values
high_range = np.array([2, 3, 4, 2, 21, 32, 78, 95, 65, 66, 66, 66, 66, 4],
dtype=float) # 14 values
low_range = np.array([2, 3, 3, 2, 3, 2.4, 2.1, 3.1... | test.
slope, intercept, lower, upper = stats.theilslopes([0,1,1])
assert_almost_equal(slope, 0.5)
assert_almost_equal(intercept, 0.5)
# Test of confidence intervals.
x = [1, 2, 3, 4, 10, 12, 18]
y = [9, 15, 19, 20, 45, 55, 78]
slope, intercept, lower, upper = stats.theilslopes(y, x, 0.07)
... | 256 | 256 | 1,827 | 85 | 171 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestHistogram | TestHistogram | 791 | 923 | 791 | 799 | 68d8614b4243901d886c49a880330a3651739cbf | bigcode/the-stack | train |
c9bde9a17f5b0006f7a78be5 | train | class | class TestJarqueBera(TestCase):
def test_jarque_bera_stats(self):
np.random.seed(987654321)
x = np.random.normal(0, 1, 100000)
y = np.random.chisquare(10000, 100000)
z = np.random.rayleigh(1, 100000)
assert_(stats.jarque_bera(x)[1] > stats.jarque_bera(y)[1])
assert_(... | class TestJarqueBera(TestCase):
| def test_jarque_bera_stats(self):
np.random.seed(987654321)
x = np.random.normal(0, 1, 100000)
y = np.random.chisquare(10000, 100000)
z = np.random.rayleigh(1, 100000)
assert_(stats.jarque_bera(x)[1] > stats.jarque_bera(y)[1])
assert_(stats.jarque_bera(x)[1] > stats.... | raise')
assert_raises(ValueError, stats.normaltest, x, nan_policy='foobar')
class TestRankSums(TestCase):
def test_ranksums_result_attributes(self):
res = stats.ranksums(np.arange(5), np.arange(25))
attributes = ('statistic', 'pvalue')
check_named_results(res, attributes)
class TestJar... | 83 | 83 | 279 | 9 | 74 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestJarqueBera | TestJarqueBera | 2,677 | 2,700 | 2,677 | 2,677 | 77707b1696ead0e1cffe4dad01490d3558e7a216 | bigcode/the-stack | train |
531a8c59a79881e6e7b09e33 | train | function | def _desc_stats(x1, x2, axis=0):
def _stats(x, axis=0):
x = np.asarray(x)
mu = np.mean(x, axis=axis)
std = np.std(x, axis=axis, ddof=1)
nobs = x.shape[axis]
return mu, std, nobs
return _stats(x1, axis) + _stats(x2, axis)
| def _desc_stats(x1, x2, axis=0):
| def _stats(x, axis=0):
x = np.asarray(x)
mu = np.mean(x, axis=axis)
std = np.std(x, axis=axis, ddof=1)
nobs = x.shape[axis]
return mu, std, nobs
return _stats(x1, axis) + _stats(x2, axis)
| # test incorrect input shape raise an error
x = np.arange(24)
assert_raises(ValueError, stats.ttest_rel, x.reshape((8, 3)),
x.reshape((2, 3, 4)))
def _desc_stats(x1, x2, axis=0):
| 63 | 64 | 93 | 14 | 49 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | _desc_stats | _desc_stats | 2,264 | 2,271 | 2,264 | 2,264 | 8c84d62e36877a7b2567121dc1a8152e2c8f87a0 | bigcode/the-stack | train |
a6b556f622eb14893f4888a9 | train | function | def test_obrientransform():
# A couple tests calculated by hand.
x1 = np.array([0, 2, 4])
t1 = stats.obrientransform(x1)
expected = [7, -2, 7]
assert_allclose(t1[0], expected)
x2 = np.array([0, 3, 6, 9])
t2 = stats.obrientransform(x2)
expected = np.array([30, 0, 0, 30])
assert_allcl... | def test_obrientransform():
# A couple tests calculated by hand.
| x1 = np.array([0, 2, 4])
t1 = stats.obrientransform(x1)
expected = [7, -2, 7]
assert_allclose(t1[0], expected)
x2 = np.array([0, 3, 6, 9])
t2 = stats.obrientransform(x2)
expected = np.array([30, 0, 0, 30])
assert_allclose(t2[0], expected)
# Test two arguments.
a, b = stats.obri... | .3,2.1,1.7,1.7,1.5,1.3,1.3,1.2,1.2,1.1,
0.8,0.7,0.6,0.5,0.2,0.2,0.1]
assert_almost_equal(stats.pointbiserialr(x, y)[0], 0.36149, 5)
# test for namedtuple attribute results
attributes = ('correlation', 'pvalue')
res = stats.pointbiserialr(x, y)
check_named_results(res, attributes)
def test_... | 153 | 153 | 513 | 17 | 136 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_obrientransform | test_obrientransform | 2,858 | 2,898 | 2,858 | 2,859 | aba2d5941131b8091c632f30ca8a22906253dfe8 | bigcode/the-stack | train |
78a3ded05497bff5b4cf4d88 | train | function | def test_ttest_rel():
# regression test
tr,pr = 0.81248591389165692, 0.41846234511362157
tpr = ([tr,-tr],[pr,pr])
rvs1 = np.linspace(1,100,100)
rvs2 = np.linspace(1.01,99.989,100)
rvs1_2D = np.array([np.linspace(1,100,100), np.linspace(1.01,99.989,100)])
rvs2_2D = np.array([np.linspace(1.01... | def test_ttest_rel():
# regression test
| tr,pr = 0.81248591389165692, 0.41846234511362157
tpr = ([tr,-tr],[pr,pr])
rvs1 = np.linspace(1,100,100)
rvs2 = np.linspace(1.01,99.989,100)
rvs1_2D = np.array([np.linspace(1,100,100), np.linspace(1.01,99.989,100)])
rvs2_2D = np.array([np.linspace(1.01,99.989,100), np.linspace(1,100,100)])
... | 62)))
assert_almost_equal(
np.array(stats.ks_2samp(np.linspace(1,100,100),
np.linspace(1,100,100)+2-0.1)),
np.array((0.020000000000000018, 0.99999999999999933)))
# these are just regression tests
assert_almost_equal(
np.array(stats.ks_2samp(np.linspace(1... | 256 | 256 | 995 | 11 | 245 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_ttest_rel | test_ttest_rel | 2,186 | 2,261 | 2,186 | 2,187 | 3755e676b3544278500eecd490a0fdba3cf86e84 | bigcode/the-stack | train |
91199db698146e93025be921 | train | function | def test_power_divergence_against_cressie_read_data():
# Test stats.power_divergence against tables 4 and 5 from
# Cressie and Read, "Multimonial Goodness-of-Fit Tests",
# J. R. Statist. Soc. B (1984), Vol 46, No. 3, pp. 440-464.
# This tests the calculation for several values of lambda.
# `table4`... | def test_power_divergence_against_cressie_read_data():
# Test stats.power_divergence against tables 4 and 5 from
# Cressie and Read, "Multimonial Goodness-of-Fit Tests",
# J. R. Statist. Soc. B (1984), Vol 46, No. 3, pp. 440-464.
# This tests the calculation for several values of lambda.
# `table4`... | table4 = np.array([
# observed, expected,
15, 15.171,
11, 13.952,
14, 12.831,
17, 11.800,
5, 10.852,
11, 9.9796,
10, 9.1777,
4, 8.4402,
8, 7.7620,
10, 7.1383,
7, 6.5647,
9, 6.0371,
11, 5.5520,
3, ... | ():
warnings.filterwarnings('ignore')
chisq, p = stats.chisquare(empty3.T)
assert_(isinstance(chisq, np.ma.MaskedArray))
assert_equal(chisq.shape, (3,))
assert_(np.all(chisq.mask))
def test_power_divergence_against_cressie_read_data():
# Test stats.power_divergence against table... | 169 | 169 | 566 | 111 | 58 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_power_divergence_against_cressie_read_data | test_power_divergence_against_cressie_read_data | 2,010 | 2,061 | 2,010 | 2,016 | 447daa32f02aaecbc14e7abae1bc386c8076bc15 | bigcode/the-stack | train |
d777ba60c71ad9de901f385b | train | class | class TestCombinePvalues(TestCase):
def test_fisher(self):
# Example taken from http://en.wikipedia.org/wiki/Fisher's_exact_test#Example
xsq, p = stats.combine_pvalues([.01, .2, .3], method='fisher')
assert_approx_equal(p, 0.02156, significant=4)
def test_stouffer(self):
Z, p =... | class TestCombinePvalues(TestCase):
| def test_fisher(self):
# Example taken from http://en.wikipedia.org/wiki/Fisher's_exact_test#Example
xsq, p = stats.combine_pvalues([.01, .2, .3], method='fisher')
assert_approx_equal(p, 0.02156, significant=4)
def test_stouffer(self):
Z, p = stats.combine_pvalues([.01, .2, .3],... | kal(x, x), (np.nan, np.nan))
assert_almost_equal(stats.kruskal(x, x, nan_policy='omit'), (0.0, 1.0))
assert_raises(ValueError, stats.kruskal, x, x, nan_policy='raise')
assert_raises(ValueError, stats.kruskal, x, x, nan_policy='foobar')
class TestCombinePvalues(TestCase):
| 90 | 90 | 301 | 8 | 82 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestCombinePvalues | TestCombinePvalues | 3,473 | 3,496 | 3,473 | 3,474 | c3ab2f37bc9495478448f1753845446729ee6a97 | bigcode/the-stack | train |
5f9826945da85fc4df46486d | train | function | def test_chisquare_masked_arrays():
# Test masked arrays.
obs = np.array([[8, 8, 16, 32, -1], [-1, -1, 3, 4, 5]]).T
mask = np.array([[0, 0, 0, 0, 1], [1, 1, 0, 0, 0]]).T
mobs = np.ma.masked_array(obs, mask)
expected_chisq = np.array([24.0, 0.5])
expected_g = np.array([2*(2*8*np.log(0.5) + 32*np.... | def test_chisquare_masked_arrays():
# Test masked arrays.
| obs = np.array([[8, 8, 16, 32, -1], [-1, -1, 3, 4, 5]]).T
mask = np.array([[0, 0, 0, 0, 1], [1, 1, 0, 0, 0]]).T
mobs = np.ma.masked_array(obs, mask)
expected_chisq = np.array([24.0, 0.5])
expected_g = np.array([2*(2*8*np.log(0.5) + 32*np.log(2.0)),
2*(3*np.log(0.75) + 5*np... | ", case.chi2)
yield (self.check_power_divergence,
case.f_obs, case.f_exp, case.ddof, case.axis,
"log-likelihood", case.log)
yield (self.check_power_divergence,
case.f_obs, case.f_exp, case.ddof, case.axis,
... | 256 | 256 | 977 | 15 | 241 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_chisquare_masked_arrays | test_chisquare_masked_arrays | 1,935 | 2,007 | 1,935 | 1,936 | f09ddefdf40647fbc9c4da9ffa9d10d931f3a2d3 | bigcode/the-stack | train |
e9580a7d231748eb74dd75b9 | train | class | class TestPowerDivergence(object):
def check_power_divergence(self, f_obs, f_exp, ddof, axis, lambda_,
expected_stat):
f_obs = np.asarray(f_obs)
if axis is None:
num_obs = f_obs.size
else:
b = np.broadcast(f_obs, f_exp)
num_... | class TestPowerDivergence(object):
| def check_power_divergence(self, f_obs, f_exp, ddof, axis, lambda_,
expected_stat):
f_obs = np.asarray(f_obs)
if axis is None:
num_obs = f_obs.size
else:
b = np.broadcast(f_obs, f_exp)
num_obs = b.shape[axis]
stat, p ... | _obs=[],
f_exp=None, ddof=0, axis=0,
chi2=0, log=0, mod_log=0, cr=0),
# Shape is (0, 3). This is 3 data sets, but each data set has
# length 0, so the computed test statistic should be [0, 0, 0].
PowerDivCase(f_obs=np.array([[],[],[]]).T,
f_exp=None, ddof=... | 256 | 256 | 1,723 | 8 | 248 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestPowerDivergence | TestPowerDivergence | 1,778 | 1,932 | 1,778 | 1,779 | fbf11c30697254cc3277acb6ae2d43035654d12d | bigcode/the-stack | train |
62a8816d884977501120aa2a | train | class | class TestKruskal(TestCase):
def test_simple(self):
x = [1]
y = [2]
h, p = stats.kruskal(x, y)
assert_equal(h, 1.0)
assert_approx_equal(p, stats.distributions.chi2.sf(h, 1))
h, p = stats.kruskal(np.array(x), np.array(y))
assert_equal(h, 1.0)
assert_app... | class TestKruskal(TestCase):
| def test_simple(self):
x = [1]
y = [2]
h, p = stats.kruskal(x, y)
assert_equal(h, 1.0)
assert_approx_equal(p, stats.distributions.chi2.sf(h, 1))
h, p = stats.kruskal(np.array(x), np.array(y))
assert_equal(h, 1.0)
assert_approx_equal(p, stats.distributi... | ']
for test_case in filenames:
rtol = 1e-7
fname = os.path.abspath(os.path.join(os.path.dirname(__file__),
'data/nist_anova', test_case))
with open(fname, 'r') as f:
content = f.read().split('\n')
c... | 256 | 256 | 976 | 8 | 248 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestKruskal | TestKruskal | 3,397 | 3,470 | 3,397 | 3,397 | 640ef4a22f0228bd9437e68a0eb1d6d52ecb3527 | bigcode/the-stack | train |
894c3233ffa53ce89db9071b | train | function | def test_percentileofscore():
pcos = stats.percentileofscore
assert_equal(pcos([1,2,3,4,5,6,7,8,9,10],4), 40.0)
for (kind, result) in [('mean', 35.0),
('strict', 30.0),
('weak', 40.0)]:
yield assert_equal, pcos(np.arange(10) + 1,
... | def test_percentileofscore():
| pcos = stats.percentileofscore
assert_equal(pcos([1,2,3,4,5,6,7,8,9,10],4), 40.0)
for (kind, result) in [('mean', 35.0),
('strict', 30.0),
('weak', 40.0)]:
yield assert_equal, pcos(np.arange(10) + 1,
... | assert_array_almost_equal(p, self.P1_1)
t, p = stats.ttest_1samp(self.X1, 2)
assert_array_almost_equal(t, self.T1_2)
assert_array_almost_equal(p, self.P1_2)
# check nan policy
np.random.seed(7654567)
x = stats.norm.rvs(loc=5, scale=10, size=51)
x[50] = ... | 256 | 256 | 954 | 7 | 249 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_percentileofscore | test_percentileofscore | 1,630 | 1,713 | 1,630 | 1,630 | f971b14eb36d9ff7571b0b4d9eae48f6c59028b1 | bigcode/the-stack | train |
f135f68013c1189fea7b9e80 | train | function | def test_binomtest2():
# test added for issue #2384
res2 = [
[1.0, 1.0],
[0.5,1.0,0.5],
[0.25,1.00,1.00,0.25],
[0.125,0.625,1.000,0.625,0.125],
[0.0625,0.3750,1.0000,1.0000,0.3750,0.0625],
[0.03125,0.21875,0.68750,1.00000,0.68750,0.21875,0.03125],
[0.015625,0.125000,0.453125,1.000000... | def test_binomtest2():
# test added for issue #2384
| res2 = [
[1.0, 1.0],
[0.5,1.0,0.5],
[0.25,1.00,1.00,0.25],
[0.125,0.625,1.000,0.625,0.125],
[0.0625,0.3750,1.0000,1.0000,0.3750,0.0625],
[0.03125,0.21875,0.68750,1.00000,0.68750,0.21875,0.03125],
[0.015625,0.125000,0.453125,1.000000,1.000000,0.453125,0.125000,0.015625],
[0.0078125,0.... | 0.027120993063129286,
2.6102587134694721e-006]
for p, res in zip(pp,results):
assert_approx_equal(stats.binom_test(x, n, p), res,
significant=12, err_msg='fail forp=%f' % p)
assert_approx_equal(stats.binom_test(50,100,0.1), 5.8320387857343647e-024,
... | 134 | 134 | 448 | 17 | 117 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_binomtest2 | test_binomtest2 | 3,117 | 3,137 | 3,117 | 3,118 | ec1ef41163f0351e0c0035a801b70e0d0342d6b6 | bigcode/the-stack | train |
74db1c196a056bb62957b047 | train | function | def test_pointbiserial():
# same as mstats test except for the nan
# Test data: http://support.sas.com/ctx/samples/index.jsp?sid=490&tab=output
x = [1,0,1,1,1,1,0,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,
0,0,0,0,1]
y = [14.8,13.8,12.4,10.1,7.1,6.1,5.8,4.6,4.3,3.5,3.3,3.2,3.0,
2.8,2... | def test_pointbiserial():
# same as mstats test except for the nan
# Test data: http://support.sas.com/ctx/samples/index.jsp?sid=490&tab=output
| x = [1,0,1,1,1,1,0,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,
0,0,0,0,1]
y = [14.8,13.8,12.4,10.1,7.1,6.1,5.8,4.6,4.3,3.5,3.3,3.2,3.0,
2.8,2.8,2.5,2.4,2.3,2.1,1.7,1.7,1.5,1.3,1.3,1.2,1.2,1.1,
0.8,0.7,0.6,0.5,0.2,0.2,0.1]
assert_almost_equal(stats.pointbiserialr(x, y)[0], 0.36149... | itneyu_result_attribuets(self):
# test for namedtuple attribute results
attributes = ('statistic', 'pvalue')
res = stats.mannwhitneyu(self.X, self.Y)
check_named_results(res, attributes)
def test_pointbiserial():
# same as mstats test except for the nan
# Test data: http://suppor... | 99 | 99 | 330 | 45 | 54 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_pointbiserial | test_pointbiserial | 2,842 | 2,855 | 2,842 | 2,844 | cd1a129326c79b878cbff2ad944fec5cfd02bcb9 | bigcode/the-stack | train |
9154823008404d6070f69807 | train | class | class TestFisherExact(TestCase):
"""Some tests to show that fisher_exact() works correctly.
Note that in SciPy 0.9.0 this was not working well for large numbers due to
inaccuracy of the hypergeom distribution (see #1218). Fixed now.
Also note that R and Scipy have different argument formats for their
... | class TestFisherExact(TestCase):
| """Some tests to show that fisher_exact() works correctly.
Note that in SciPy 0.9.0 this was not working well for large numbers due to
inaccuracy of the hypergeom distribution (see #1218). Fixed now.
Also note that R and Scipy have different argument formats for their
hypergeometric distribution f... | ROUNDROUND(self):
y = stats.pearsonr(ROUND,ROUND)
r = y[0]
assert_approx_equal(r,1.0)
def test_r_exactly_pos1(self):
a = arange(3.0)
b = a
r, prob = stats.pearsonr(a,b)
assert_equal(r, 1.0)
assert_equal(prob, 0.0)
def test_r_exactly_neg1(self):
... | 256 | 256 | 1,823 | 8 | 248 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestFisherExact | TestFisherExact | 272 | 399 | 272 | 272 | f790f90c25d60069558d277b79d6fa2b5cc85020 | bigcode/the-stack | train |
b932626949c3d8daf48416ce | train | class | class TestTrimmedStats(TestCase):
# TODO: write these tests to handle missing values properly
dprec = np.finfo(np.float64).precision
def test_tmean(self):
y = stats.tmean(X, (2, 8), (True, True))
assert_approx_equal(y, 5.0, significant=self.dprec)
y1 = stats.tmean(X, limits=(2, 8),... | class TestTrimmedStats(TestCase):
# TODO: write these tests to handle missing values properly
| dprec = np.finfo(np.float64).precision
def test_tmean(self):
y = stats.tmean(X, (2, 8), (True, True))
assert_approx_equal(y, 5.0, significant=self.dprec)
y1 = stats.tmean(X, limits=(2, 8), inclusive=(False, False))
y2 = stats.tmean(X, limits=None)
assert_approx_equal(y1... | 94,99999995,99999996,99999997,
99999998,99999999], float)
LITTLE = array([0.99999991,0.99999992,0.99999993,0.99999994,0.99999995,0.99999996,
0.99999997,0.99999998,0.99999999], float)
HUGE = array([1e+12,2e+12,3e+12,4e+12,5e+12,6e+12,7e+12,8e+12,9e+12], float)
TINY = array([1e-12,2e-12,3e-12... | 256 | 256 | 881 | 21 | 235 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestTrimmedStats | TestTrimmedStats | 54 | 132 | 54 | 55 | 61222862fc18c98f17c9abc8eaca9cfdb5c9f849 | bigcode/the-stack | train |
830778baf7f514deafe4e3bc | train | function | def test_gh5686():
mean1, mean2 = np.array([1, 2]), np.array([3, 4])
std1, std2 = np.array([5, 3]), np.array([4, 5])
nobs1, nobs2 = np.array([130, 140]), np.array([100, 150])
# This will raise a TypeError unless gh-5686 is fixed.
stats.ttest_ind_from_stats(mean1, std1, nobs1, mean2, std2, nobs2)
| def test_gh5686():
| mean1, mean2 = np.array([1, 2]), np.array([3, 4])
std1, std2 = np.array([5, 3]), np.array([4, 5])
nobs1, nobs2 = np.array([130, 140]), np.array([100, 150])
# This will raise a TypeError unless gh-5686 is fixed.
stats.ttest_ind_from_stats(mean1, std1, nobs1, mean2, std2, nobs2)
| 1, np.nan], [-1, 1]])
assert_equal(stats.ttest_ind(anan, np.zeros((2, 2)), equal_var=False),
([0, np.nan], [1, np.nan]))
finally:
np.seterr(**olderr)
def test_gh5686():
| 64 | 64 | 121 | 7 | 57 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_gh5686 | test_gh5686 | 2,463 | 2,468 | 2,463 | 2,463 | 574a2733171c5aa209912b5fa96a64f6a6b9f31f | bigcode/the-stack | train |
ff6cc60df59485fe2c1e9d8a | train | function | def test_ttest_1samp_new():
n1, n2, n3 = (10,15,20)
rvn1 = stats.norm.rvs(loc=5,scale=10,size=(n1,n2,n3))
# check multidimensional array and correct axis handling
# deterministic rvn1 and rvn2 would be better as in test_ttest_rel
t1,p1 = stats.ttest_1samp(rvn1[:,:,:], np.ones((n2,n3)),axis=0)
t... | def test_ttest_1samp_new():
| n1, n2, n3 = (10,15,20)
rvn1 = stats.norm.rvs(loc=5,scale=10,size=(n1,n2,n3))
# check multidimensional array and correct axis handling
# deterministic rvn1 and rvn2 would be better as in test_ttest_rel
t1,p1 = stats.ttest_1samp(rvn1[:,:,:], np.ones((n2,n3)),axis=0)
t2,p2 = stats.ttest_1samp(rvn... | anan = np.array([[1, np.nan], [-1, 1]])
assert_equal(stats.ttest_ind(anan, np.zeros((2, 2)), equal_var=False),
([0, np.nan], [1, np.nan]))
finally:
np.seterr(**olderr)
def test_gh5686():
mean1, mean2 = np.array([1, 2]), np.array([3, 4])
std1, std2 = np.array([5, 3]), ... | 194 | 194 | 648 | 10 | 184 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_ttest_1samp_new | test_ttest_1samp_new | 2,471 | 2,511 | 2,471 | 2,471 | 9415eb03ca9b72448c8fd42964dab7785f26b142 | bigcode/the-stack | train |
4c611d4fa11048b0bdcf9950 | train | class | class TestHMean(TestCase):
def test_1D_list(self):
a = (1,2,3,4)
actual = stats.hmean(a)
desired = 4. / (1./1 + 1./2 + 1./3 + 1./4)
assert_almost_equal(actual, desired, decimal=14)
desired1 = stats.hmean(array(a),axis=-1)
assert_almost_equal(actual, desired1, decimal... | class TestHMean(TestCase):
| def test_1D_list(self):
a = (1,2,3,4)
actual = stats.hmean(a)
desired = 4. / (1./1 + 1./2 + 1./3 + 1./4)
assert_almost_equal(actual, desired, decimal=14)
desired1 = stats.hmean(array(a),axis=-1)
assert_almost_equal(actual, desired1, decimal=14)
def test_1D_array... | ,2,3,4),
(1,2,3,4)))
actual = stats.gmean(a, axis=1)
v = power(1*2*3*4,1./4.)
desired = array((v,v,v))
assert_array_almost_equal(actual, desired, decimal=14)
def test_large_values(self):
a = array([1e100, 1e200, 1e300])
actual = stats.gmean(a)
... | 126 | 126 | 421 | 7 | 119 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestHMean | TestHMean | 1,003 | 1,041 | 1,003 | 1,003 | 98e14b1d9b64a96304489ce81ba01ee1e38aa3f0 | bigcode/the-stack | train |
55bdb8443528ff9eff6be275 | train | class | class TestMode(TestCase):
def test_empty(self):
vals, counts = stats.mode([])
assert_equal(vals, np.array([]))
assert_equal(counts, np.array([]))
def test_scalar(self):
vals, counts = stats.mode(4.)
assert_equal(vals, np.array([4.]))
assert_equal(counts, np.array... | class TestMode(TestCase):
| def test_empty(self):
vals, counts = stats.mode([])
assert_equal(vals, np.array([]))
assert_equal(counts, np.array([]))
def test_scalar(self):
vals, counts = stats.mode(4.)
assert_equal(vals, np.array([4.]))
assert_equal(counts, np.array([1]))
def test_basic... | assert_array_equal(v[:, 1], np.array([20, 10, 20, 20], dtype=dt))
dtypes = [np.int32, np.int64, np.float32, np.float64,
np.complex64, np.complex128]
for dt in dtypes:
yield _check_itemfreq, dt
def test_object_arrays(self):
a, b = self.a, self.b
... | 255 | 256 | 1,043 | 6 | 249 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestMode | TestMode | 1,198 | 1,299 | 1,198 | 1,198 | 22879713282f2d4a7f06371f4997b28fda5f053b | bigcode/the-stack | train |
0dd8ea145b8c88d61254cf41 | train | class | class TestRankSums(TestCase):
def test_ranksums_result_attributes(self):
res = stats.ranksums(np.arange(5), np.arange(25))
attributes = ('statistic', 'pvalue')
check_named_results(res, attributes)
| class TestRankSums(TestCase):
| def test_ranksums_result_attributes(self):
res = stats.ranksums(np.arange(5), np.arange(25))
attributes = ('statistic', 'pvalue')
check_named_results(res, attributes)
| 91)
assert_array_almost_equal(stats.normaltest(x, nan_policy='omit'), expected)
assert_raises(ValueError, stats.normaltest, x, nan_policy='raise')
assert_raises(ValueError, stats.normaltest, x, nan_policy='foobar')
class TestRankSums(TestCase):
| 64 | 64 | 54 | 8 | 56 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestRankSums | TestRankSums | 2,670 | 2,674 | 2,670 | 2,670 | d910d3a2708c3e13c68fa96d03bc171464c03acf | bigcode/the-stack | train |
8300206062831d07ee6269b6 | train | function | def test_ks_2samp():
# exact small sample solution
data1 = np.array([1.0,2.0])
data2 = np.array([1.0,2.0,3.0])
assert_almost_equal(np.array(stats.ks_2samp(data1+0.01,data2)),
np.array((0.33333333333333337, 0.99062316386915694)))
assert_almost_equal(np.array(stats.ks_2samp(data1-0.01,... | def test_ks_2samp():
# exact small sample solution
| data1 = np.array([1.0,2.0])
data2 = np.array([1.0,2.0,3.0])
assert_almost_equal(np.array(stats.ks_2samp(data1+0.01,data2)),
np.array((0.33333333333333337, 0.99062316386915694)))
assert_almost_equal(np.array(stats.ks_2samp(data1-0.01,data2)),
np.array((0.66666666666666674,... | 769)), 15)
assert_almost_equal(np.array(stats.kstest(x,'norm', alternative='less')),
np.array((0.12464329735846891, 0.040989164077641749)), 15)
# this 'greater' test fails with precision of decimal=14
assert_almost_equal(np.array(stats.kstest(x,'norm', alternative='greater')),
... | 136 | 136 | 456 | 16 | 119 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_ks_2samp | test_ks_2samp | 2,153 | 2,183 | 2,153 | 2,154 | af1d38ab9573d6f2a816e570a0f4a32958b51466 | bigcode/the-stack | train |
f09e8b6e83201b870d75c810 | train | class | class TestSigamClip(object):
def test_sigmaclip1(self):
a = np.concatenate((np.linspace(9.5,10.5,31),np.linspace(0,20,5)))
fact = 4 # default
c, low, upp = stats.sigmaclip(a)
assert_(c.min() > low)
assert_(c.max() < upp)
assert_equal(low, c.mean() - fact*c.std())
... | class TestSigamClip(object):
| def test_sigmaclip1(self):
a = np.concatenate((np.linspace(9.5,10.5,31),np.linspace(0,20,5)))
fact = 4 # default
c, low, upp = stats.sigmaclip(a)
assert_(c.min() > low)
assert_(c.max() < upp)
assert_equal(low, c.mean() - fact*c.std())
assert_equal(upp, c.mean... | 2/6., axis=axis)
res2 = stats.trim_mean(np.rollaxis(a, axis), 2/6.)
assert_equal(res1, res2)
res1 = stats.trim_mean(a, 2/6., axis=None)
res2 = stats.trim_mean(a.ravel(), 2/6.)
assert_equal(res1, res2)
assert_raises(ValueError, stats.trim_mean, a, 0.6)
#... | 138 | 138 | 462 | 7 | 131 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestSigamClip | TestSigamClip | 3,299 | 3,337 | 3,299 | 3,299 | 02038a7c138c64462845238d96a7264d648b40de | bigcode/the-stack | train |
e65e393be4feaf6c5c9c00b9 | train | function | def test_kstest():
# from numpy.testing import assert_almost_equal
# comparing with values from R
x = np.linspace(-1,1,9)
D,p = stats.kstest(x,'norm')
assert_almost_equal(D, 0.15865525393145705, 12)
assert_almost_equal(p, 0.95164069201518386, 1)
x = np.linspace(-15,15,9)
D,p = stats.ks... | def test_kstest():
# from numpy.testing import assert_almost_equal
# comparing with values from R
| x = np.linspace(-1,1,9)
D,p = stats.kstest(x,'norm')
assert_almost_equal(D, 0.15865525393145705, 12)
assert_almost_equal(p, 0.95164069201518386, 1)
x = np.linspace(-15,15,9)
D,p = stats.kstest(x,'norm')
assert_almost_equal(D, 0.44435602715924361, 15)
assert_almost_equal(p, 0.03885014008... | 2[2],x2[3]),
# (18.9428571428571, 0.000280938375189499))
assert_array_almost_equal(mstats.friedmanchisquare(x3[0], x3[1],
x3[2], x3[3]),
(10.68, 0.0135882729582176))
np.testing.assert_raises(ValueE... | 131 | 131 | 438 | 24 | 107 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_kstest | test_kstest | 2,117 | 2,148 | 2,117 | 2,120 | 3a85fc0c45139b9e53806553dfed1df78772f1ae | bigcode/the-stack | train |
4171a7d64c4ebe8d4634cc34 | train | function | def test_theilslopes():
# Basic slope test.
slope, intercept, lower, upper = stats.theilslopes([0,1,1])
assert_almost_equal(slope, 0.5)
assert_almost_equal(intercept, 0.5)
# Test of confidence intervals.
x = [1, 2, 3, 4, 10, 12, 18]
y = [9, 15, 19, 20, 45, 55, 78]
slope, intercept, lowe... | def test_theilslopes():
# Basic slope test.
| slope, intercept, lower, upper = stats.theilslopes([0,1,1])
assert_almost_equal(slope, 0.5)
assert_almost_equal(intercept, 0.5)
# Test of confidence intervals.
x = [1, 2, 3, 4, 10, 12, 18]
y = [9, 15, 19, 20, 45, 55, 78]
slope, intercept, lower, upper = stats.theilslopes(y, x, 0.07)
ass... | ] = np.nan
with warnings.catch_warnings():
warnings.simplefilter("ignore", RuntimeWarning)
assert_array_equal(stats.linregress(x, x),
(np.nan, np.nan, np.nan, np.nan, np.nan))
def test_theilslopes():
# Basic slope test.
| 64 | 64 | 182 | 13 | 51 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_theilslopes | test_theilslopes | 776 | 788 | 776 | 777 | 22564fad84af6333a41cc4581bcdd1c77ee0c868 | bigcode/the-stack | train |
d4d84e7e765fe46e2ad2a5a4 | train | function | def test_relfreq():
a = np.array([1, 4, 2, 1, 3, 1])
relfreqs, lowlim, binsize, extrapoints = stats.relfreq(a, numbins=4)
assert_array_almost_equal(relfreqs,
array([0.5, 0.16666667, 0.16666667, 0.16666667]))
# test for namedtuple attribute results
attributes = ('freque... | def test_relfreq():
| a = np.array([1, 4, 2, 1, 3, 1])
relfreqs, lowlim, binsize, extrapoints = stats.relfreq(a, numbins=4)
assert_array_almost_equal(relfreqs,
array([0.5, 0.16666667, 0.16666667, 0.16666667]))
# test for namedtuple attribute results
attributes = ('frequency', 'lowerlimit', ... | tuple attribute results
attributes = ('cumcount', 'lowerlimit', 'binsize', 'extrapoints')
res = stats.cumfreq(x, numbins=4, defaultreallimits=(1.5, 5))
check_named_results(res, attributes)
def test_relfreq():
| 64 | 64 | 209 | 6 | 58 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_relfreq | test_relfreq | 940 | 954 | 940 | 940 | 948487502e2c7ffeb61942603d7674d603904d15 | bigcode/the-stack | train |
034db0ec1fa58c9f7de4aec5 | train | class | class TestHarMean(HarMeanTestCase, TestCase):
def do(self, a, b, axis=None, dtype=None):
x = stats.hmean(a, axis=axis, dtype=dtype)
assert_almost_equal(b, x)
assert_equal(x.dtype, dtype)
| class TestHarMean(HarMeanTestCase, TestCase):
| def do(self, a, b, axis=None, dtype=None):
x = stats.hmean(a, axis=axis, dtype=dtype)
assert_almost_equal(b, x)
assert_equal(x.dtype, dtype)
| 90, 100, 110, 120]]
b = np.matrix([[19.2, 63.03939962, 103.80078637]]).T
self.do(np.matrix(a), b, axis=1)
class TestHarMean(HarMeanTestCase, TestCase):
| 64 | 64 | 61 | 13 | 51 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestHarMean | TestHarMean | 2,971 | 2,975 | 2,971 | 2,971 | 747308a404dea2060ce385dbfa18a5a454ebef12 | bigcode/the-stack | train |
cd4e1be8b3ed4dd2d8142e42 | train | function | def test_ttest_ind():
# regression test
tr = 1.0912746897927283
pr = 0.27647818616351882
tpr = ([tr,-tr],[pr,pr])
rvs2 = np.linspace(1,100,100)
rvs1 = np.linspace(5,105,100)
rvs1_2D = np.array([rvs1, rvs2])
rvs2_2D = np.array([rvs2, rvs1])
t,p = stats.ttest_ind(rvs1, rvs2, axis=0)
... | def test_ttest_ind():
# regression test
| tr = 1.0912746897927283
pr = 0.27647818616351882
tpr = ([tr,-tr],[pr,pr])
rvs2 = np.linspace(1,100,100)
rvs1 = np.linspace(5,105,100)
rvs1_2D = np.array([rvs1, rvs2])
rvs2_2D = np.array([rvs2, rvs1])
t,p = stats.ttest_ind(rvs1, rvs2, axis=0)
assert_array_almost_equal([t,p],(tr,pr))... | , 0, 0]), (np.nan, np.nan))
olderr = np.seterr(all='ignore')
try:
# check that nan in input array result in nan output
anan = np.array([[1, np.nan], [-1, 1]])
assert_equal(stats.ttest_rel(anan, np.zeros((2, 2))),
([0, np.nan], [1, np.nan]))
finally:
np.s... | 256 | 256 | 970 | 11 | 245 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_ttest_ind | test_ttest_ind | 2,274 | 2,349 | 2,274 | 2,275 | 74ca2a8cd8490fdfdea993155413688dbcb06be4 | bigcode/the-stack | train |
970280929c936c022ffe9dd9 | train | class | class TestGeoMean(GeoMeanTestCase, TestCase):
def do(self, a, b, axis=None, dtype=None):
# Note this doesn't test when axis is not specified
x = stats.gmean(a, axis=axis, dtype=dtype)
assert_almost_equal(b, x)
assert_equal(x.dtype, dtype)
| class TestGeoMean(GeoMeanTestCase, TestCase):
| def do(self, a, b, axis=None, dtype=None):
# Note this doesn't test when axis is not specified
x = stats.gmean(a, axis=axis, dtype=dtype)
assert_almost_equal(b, x)
assert_equal(x.dtype, dtype)
| 80, 90, -1])
b = 41.4716627439
olderr = np.seterr(all='ignore')
try:
self.do(a, b)
finally:
np.seterr(**olderr)
class TestGeoMean(GeoMeanTestCase, TestCase):
| 64 | 64 | 73 | 13 | 51 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestGeoMean | TestGeoMean | 3,087 | 3,092 | 3,087 | 3,087 | 4e7894d9adf2e507e9f2faa1ba962ccb63b6d2aa | bigcode/the-stack | train |
a4d46a461454cb310677c4ef | train | function | def test_kurtosistest_too_few_samples():
# Regression test for ticket #1425.
# kurtosistest requires at least 5 samples; 4 should raise a ValueError.
x = np.arange(4.0)
assert_raises(ValueError, stats.kurtosistest, x)
| def test_kurtosistest_too_few_samples():
# Regression test for ticket #1425.
# kurtosistest requires at least 5 samples; 4 should raise a ValueError.
| x = np.arange(4.0)
assert_raises(ValueError, stats.kurtosistest, x)
| .arange(7.0)
assert_raises(ValueError, stats.skewtest, x)
def test_kurtosistest_too_few_samples():
# Regression test for ticket #1425.
# kurtosistest requires at least 5 samples; 4 should raise a ValueError.
| 64 | 64 | 70 | 44 | 20 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_kurtosistest_too_few_samples | test_kurtosistest_too_few_samples | 2,710 | 2,714 | 2,710 | 2,712 | d1128ab728359cb5e1defb63598efc079c5fafbe | bigcode/the-stack | train |
14c524fde5665693e1a19ffc | train | class | class TestTrim(object):
# test trim functions
def test_trim1(self):
a = np.arange(11)
assert_equal(np.sort(stats.trim1(a, 0.1)), np.arange(10))
assert_equal(np.sort(stats.trim1(a, 0.2)), np.arange(9))
assert_equal(np.sort(stats.trim1(a, 0.2, tail='left')),
np... | class TestTrim(object):
# test trim functions
| def test_trim1(self):
a = np.arange(11)
assert_equal(np.sort(stats.trim1(a, 0.1)), np.arange(10))
assert_equal(np.sort(stats.trim1(a, 0.2)), np.arange(9))
assert_equal(np.sort(stats.trim1(a, 0.2, tail='left')),
np.arange(2, 11))
assert_equal(np.sort(stats... | 0.7205416252126137,
0.722454130389843, 0.723956813292035, 0.823802947998047,
0.701255953767043, 0.715928221686075, 0.723772209289768,
0.7286603031173616, 0.7319999279787631, 0.7344267920995765,
0.736270323773157, 0.737718376096348
])
res4_p1 = [stats.binom_test(v+1, v*k,... | 256 | 256 | 1,056 | 11 | 245 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestTrim | TestTrim | 3,224 | 3,296 | 3,224 | 3,225 | b7563b02ea3b23001d91852e4c7271f2ff6b2442 | bigcode/the-stack | train |
7ea6bfeae15feb9631c0e4c0 | train | class | class TestCorrSpearmanr(TestCase):
""" W.II.D. Compute a correlation matrix on all the variables.
All the correlations, except for ZERO and MISS, shoud be exactly 1.
ZERO and MISS should have undefined or missing correlations with the
other variables. The same should go for SPEARMAN corela... | class TestCorrSpearmanr(TestCase):
| """ W.II.D. Compute a correlation matrix on all the variables.
All the correlations, except for ZERO and MISS, shoud be exactly 1.
ZERO and MISS should have undefined or missing correlations with the
other variables. The same should go for SPEARMAN corelations, if
your program has ... | 0149169715733],
[1.0, 2.0056578803889148e-122],
[1.0, 5.7284374608319831e-44],
[0.7416227, 0.2959826],
# Exact:
[0.1, 1.0],
[0.7, 0.9],
[1.0, 0.3],
[2./3, 1.0],
[1.0, 1./3],
)
for table, pval ... | 255 | 256 | 1,204 | 9 | 246 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestCorrSpearmanr | TestCorrSpearmanr | 402 | 537 | 402 | 402 | 403340806b3a43acf4d476a5fc3de8f4467229cf | bigcode/the-stack | train |
bcabc82419b61cebd645c1ba | train | class | class TestRegression(TestCase):
def test_linregressBIGX(self):
# W.II.F. Regress BIG on X.
# The constant should be 99999990 and the regression coefficient should be 1.
y = stats.linregress(X,BIG)
intercept = y[1]
r = y[2]
assert_almost_equal(intercept,99999990)
... | class TestRegression(TestCase):
| def test_linregressBIGX(self):
# W.II.F. Regress BIG on X.
# The constant should be 99999990 and the regression coefficient should be 1.
y = stats.linregress(X,BIG)
intercept = y[1]
r = y[2]
assert_almost_equal(intercept,99999990)
assert_almost_equal(r,1.0)
... | raises(ValueError, stats.kendalltau, x, x, nan_policy='raise')
assert_raises(ValueError, stats.kendalltau, x, x, nan_policy='foobar')
# test unequal length inputs
x = np.arange(10.)
y = np.arange(20.)
assert_raises(ValueError, stats.kendalltau, x, y)
class TestFindRepeats(TestCase):
def test... | 255 | 256 | 1,786 | 6 | 249 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestRegression | TestRegression | 639 | 773 | 639 | 639 | 72829d2bc65765e6bc5ec2b283028cedf887c411 | bigcode/the-stack | train |
f56235ac8d81d5bac91a6c4f | train | function | def test_cumfreq():
x = [1, 4, 2, 1, 3, 1]
cumfreqs, lowlim, binsize, extrapoints = stats.cumfreq(x, numbins=4)
assert_array_almost_equal(cumfreqs, np.array([3., 4., 5., 6.]))
cumfreqs, lowlim, binsize, extrapoints = stats.cumfreq(x, numbins=4,
defau... | def test_cumfreq():
| x = [1, 4, 2, 1, 3, 1]
cumfreqs, lowlim, binsize, extrapoints = stats.cumfreq(x, numbins=4)
assert_array_almost_equal(cumfreqs, np.array([3., 4., 5., 6.]))
cumfreqs, lowlim, binsize, extrapoints = stats.cumfreq(x, numbins=4,
defaultreallimits=(1.5, 5... | .catch_warnings():
warnings.simplefilter("ignore", DeprecationWarning)
res = stats.histogram(self.low_range, numbins=20)
attributes = ('count', 'lowerlimit', 'binsize', 'extrapoints')
check_named_results(res, attributes)
def test_cumfreq():
| 64 | 64 | 189 | 6 | 58 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | test_cumfreq | test_cumfreq | 926 | 937 | 926 | 926 | 73fe683e755080db36a82ed1d5357deb9ba7f35c | bigcode/the-stack | train |
007c607cd39bd273d3483c62 | train | class | class TestStudentTest(TestCase):
X1 = np.array([-1, 0, 1])
X2 = np.array([0, 1, 2])
T1_0 = 0
P1_0 = 1
T1_1 = -1.732051
P1_1 = 0.2254033
T1_2 = -3.464102
P1_2 = 0.0741799
T2_0 = 1.732051
P2_0 = 0.2254033
def test_onesample(self):
with warnings.catch_warnings():
... | class TestStudentTest(TestCase):
| X1 = np.array([-1, 0, 1])
X2 = np.array([0, 1, 2])
T1_0 = 0
P1_0 = 1
T1_1 = -1.732051
P1_1 = 0.2254033
T1_2 = -3.464102
P1_2 = 0.0741799
T2_0 = 1.732051
P2_0 = 0.2254033
def test_onesample(self):
with warnings.catch_warnings():
warnings.filterwarnings('ig... | _basic(self):
a = [-1, 2, 3, 4, 5, -1, -2]
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=DeprecationWarning)
assert_array_equal(stats.threshold(a), a)
assert_array_equal(stats.threshold(a, 3, None, 0),
[0, 0,... | 180 | 180 | 601 | 7 | 173 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestStudentTest | TestStudentTest | 1,572 | 1,627 | 1,572 | 1,572 | 053e3865608cdc5dee4dd395756a7f45abd731f1 | bigcode/the-stack | train |
ff96c0214f383ce91a3dc1c9 | train | class | class TestScoreatpercentile(TestCase):
def setUp(self):
self.a1 = [3, 4, 5, 10, -3, -5, 6]
self.a2 = [3, -6, -2, 8, 7, 4, 2, 1]
self.a3 = [3., 4, 5, 10, -3, -5, -6, 7.0]
def test_basic(self):
x = arange(8) * 0.5
assert_equal(stats.scoreatpercentile(x, 0), 0.)
ass... | class TestScoreatpercentile(TestCase):
| def setUp(self):
self.a1 = [3, 4, 5, 10, -3, -5, 6]
self.a2 = [3, -6, -2, 8, 7, 4, 2, 1]
self.a3 = [3., 4, 5, 10, -3, -5, -6, 7.0]
def test_basic(self):
x = arange(8) * 0.5
assert_equal(stats.scoreatpercentile(x, 0), 0.)
assert_equal(stats.scoreatpercentile(x, 10... | =14)
desired1 = stats.hmean(a,axis=-1)
assert_almost_equal(actual, desired1, decimal=14)
def test_2D_array_default(self):
a = array(((1,2,3,4),
(1,2,3,4),
(1,2,3,4)))
actual = stats.hmean(a)
desired = array((1.,2.,3.,4.))
assert... | 256 | 256 | 1,513 | 9 | 247 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | TestScoreatpercentile | TestScoreatpercentile | 1,044 | 1,158 | 1,044 | 1,044 | a168474cbd6e24dccac4b34b21a5b5606afab0e4 | bigcode/the-stack | train |
0ee6fc81e1fdfc18c468b95b | train | class | class GeoMeanTestCase:
def test_1dlist(self):
# Test a 1d list
a = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
b = 45.2872868812
self.do(a, b)
def test_1darray(self):
# Test a 1d array
a = np.array([10, 20, 30, 40, 50, 60, 70, 80, 90, 100])
b = 45.2872868... | class GeoMeanTestCase:
| def test_1dlist(self):
# Test a 1d list
a = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
b = 45.2872868812
self.do(a, b)
def test_1darray(self):
# Test a 1d array
a = np.array([10, 20, 30, 40, 50, 60, 70, 80, 90, 100])
b = 45.2872868812
self.do(a, ... | a = [[10, 20, 30, 40], [50, 60, 70, 80], [90, 100, 110, 120]]
b = np.matrix([[22.88135593, 39.13043478, 52.90076336, 65.45454545]])
self.do(np.matrix(a), b, axis=0)
def test_2dmatrixaxis1(self):
# Test a 2d list with axis=1
a = [[10, 20, 30, 40], [50, 60, 70, 80], [90, 100,... | 256 | 256 | 1,410 | 6 | 250 | zeehio/scipy | scipy/stats/tests/test_stats.py | Python | GeoMeanTestCase | GeoMeanTestCase | 2,978 | 3,084 | 2,978 | 2,978 | 3087cd39ef5e6187e7a2e2b851a5f97287819bd8 | bigcode/the-stack | train |
30e7ac0534fa8b978c82ea04 | train | class | class TestPoloidalFieldCoilCaseSetFC(unittest.TestCase):
def setUp(self):
self.pf_coils_set = paramak.PoloidalFieldCoilSet(
heights=[10, 10, 20, 20],
widths=[10, 10, 20, 40],
center_points=[(100, 100), (100, 150), (50, 200), (50, 50)],
)
self.test_shape ... | class TestPoloidalFieldCoilCaseSetFC(unittest.TestCase):
| def setUp(self):
self.pf_coils_set = paramak.PoloidalFieldCoilSet(
heights=[10, 10, 20, 20],
widths=[10, 10, 20, 40],
center_points=[(100, 100), (100, 150), (50, 200), (50, 50)],
)
self.test_shape = paramak.PoloidalFieldCoilCaseSetFC(
pf_coils... |
import math
import unittest
import paramak
import pytest
class TestPoloidalFieldCoilCaseSetFC(unittest.TestCase):
| 29 | 256 | 2,668 | 15 | 13 | moatazharb/paramak | tests/test_parametric_components/test_PoloidalFieldCoilCaseSetFC.py | Python | TestPoloidalFieldCoilCaseSetFC | TestPoloidalFieldCoilCaseSetFC | 9 | 215 | 9 | 10 | 499a251a72865adfe6ade1d269eeb9bbe9e19945 | bigcode/the-stack | train |
39cffedde75638e214465f44 | train | function | def osascript(*args):
subprocess.check_call(["osascript"] + list(args))
| def osascript(*args):
| subprocess.check_call(["osascript"] + list(args))
| import subprocess
def osascript(*args):
| 10 | 64 | 19 | 7 | 2 | fredcallaway/SendCode | code_sender/applescript.py | Python | osascript | osascript | 4 | 5 | 4 | 4 | d47c5376f2115b4ce39629095b06351301467509 | bigcode/the-stack | train |
876d95666b8c8dd5e22b126d | train | class | class V1ReplicaSetSpec(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.... | class V1ReplicaSetSpec(object):
| """NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The... | # coding: utf-8
"""
Kubernetes
No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501
OpenAPI spec version: v1.15.7
Generated by: https://openapi-generator.tech
"""
import pprint
import re # noqa: F401
import six
class V1ReplicaSet... | 87 | 256 | 1,405 | 8 | 78 | itholic/python | kubernetes/client/models/v1_replica_set_spec.py | Python | V1ReplicaSetSpec | V1ReplicaSetSpec | 19 | 195 | 19 | 19 | 71e756a00514bea34f08bb8575a9c430e581018a | bigcode/the-stack | train |
101db2af9cae675751dac402 | train | class | class TransformerDecoderLayer(TransformerDecoderLayerBase):
def __init__(
self, args, no_encoder_attn=False, add_bias_kv=False, add_zero_attn=False
):
super().__init__(
TransformerConfig.from_namespace(args),
no_encoder_attn=no_encoder_attn,
add_bias_kv=add_bi... | class TransformerDecoderLayer(TransformerDecoderLayerBase):
| def __init__(
self, args, no_encoder_attn=False, add_bias_kv=False, add_zero_attn=False
):
super().__init__(
TransformerConfig.from_namespace(args),
no_encoder_attn=no_encoder_attn,
add_bias_kv=add_bias_kv,
add_zero_attn=add_zero_attn,
)
... | n, self_attn_state
return x, attn, None
def make_generation_fast_(self, need_attn: bool = False, **kwargs):
self.need_attn = need_attn
# backward compatible with the legacy argparse format
class TransformerDecoderLayer(TransformerDecoderLayerBase):
| 64 | 64 | 196 | 10 | 53 | marcinkusz/fairseq | fairseq/modules/transformer_layer.py | Python | TransformerDecoderLayer | TransformerDecoderLayer | 430 | 456 | 430 | 430 | deafbb3d835760537b66c067d868c7cc4c69b948 | bigcode/the-stack | train |
c49b85f47b351683406356b0 | train | class | class TransformerEncoderLayer(TransformerEncoderLayerBase):
def __init__(self, args):
super().__init__(TransformerConfig.from_namespace(args))
self.args = args
def build_self_attention(self, embed_dim, args):
return super().build_self_attention(
embed_dim, TransformerConfig.... | class TransformerEncoderLayer(TransformerEncoderLayerBase):
| def __init__(self, args):
super().__init__(TransformerConfig.from_namespace(args))
self.args = args
def build_self_attention(self, embed_dim, args):
return super().build_self_attention(
embed_dim, TransformerConfig.from_namespace(args)
)
| = self.fc2(x)
x = self.dropout_module(x)
x = self.residual_connection(x, residual)
if not self.normalize_before:
x = self.final_layer_norm(x)
return x
# backward compatible with the legacy argparse format
class TransformerEncoderLayer(TransformerEncoderLayerBase):
| 64 | 64 | 68 | 10 | 53 | marcinkusz/fairseq | fairseq/modules/transformer_layer.py | Python | TransformerEncoderLayer | TransformerEncoderLayer | 166 | 174 | 166 | 166 | cf35833b874737e7bb0dd9e66ea199f88dcf6b09 | bigcode/the-stack | train |
e9816c50e1c0db6ec6a797d7 | train | class | class TransformerEncoderLayerBase(nn.Module):
"""Encoder layer block.
In the original paper each operation (multi-head attention or FFN) is
postprocessed with: `dropout -> add residual -> layernorm`. In the
tensor2tensor code they suggest that learning is more robust when
preprocessing each layer w... | class TransformerEncoderLayerBase(nn.Module):
| """Encoder layer block.
In the original paper each operation (multi-head attention or FFN) is
postprocessed with: `dropout -> add residual -> layernorm`. In the
tensor2tensor code they suggest that learning is more robust when
preprocessing each layer with layernorm and postprocessing with:
`dr... | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Dict, List, Optional
import torch
import torch.nn as nn
from fairseq import utils
from fairseq.modules import LayerNorm, M... | 126 | 256 | 1,294 | 8 | 118 | marcinkusz/fairseq | fairseq/modules/transformer_layer.py | Python | TransformerEncoderLayerBase | TransformerEncoderLayerBase | 20 | 162 | 20 | 20 | e94e02d2a7ffb078e691c36e2594d5c73965ba94 | bigcode/the-stack | train |
d52705bdedf007957f7c50ba | train | class | class TransformerDecoderLayerBase(nn.Module):
"""Decoder layer block.
In the original paper each operation (multi-head attention, encoder
attention or FFN) is postprocessed with: `dropout -> add residual ->
layernorm`. In the tensor2tensor code they suggest that learning is more
robust when preproc... | class TransformerDecoderLayerBase(nn.Module):
| """Decoder layer block.
In the original paper each operation (multi-head attention, encoder
attention or FFN) is postprocessed with: `dropout -> add residual ->
layernorm`. In the tensor2tensor code they suggest that learning is more
robust when preprocessing each layer with layernorm and postproce... | x, _ = self.self_attn(
query=x,
key=x,
value=x,
key_padding_mask=encoder_padding_mask,
need_weights=False,
attn_mask=attn_mask,
)
x = self.dropout_module(x)
x = self.residual_connection(x, residual)
if not se... | 256 | 256 | 2,126 | 8 | 248 | marcinkusz/fairseq | fairseq/modules/transformer_layer.py | Python | TransformerDecoderLayerBase | TransformerDecoderLayerBase | 177 | 426 | 177 | 177 | 05842247ee6adba02b1c5685c33587e0d32cadd2 | bigcode/the-stack | train |
188dded7ecdd3eb24855be60 | train | function | def reserva():
py.click(x=1919, y=1076)
try:
py.leftClick(py.locateOnScreen(Imagens.Imagens.mais))
sleep(2)
py.doubleClick(py.locateOnScreen(Imagens.Imagens.razer2, confidence=0.9))
sleep(2)
aaaaa = py.locateOnScreen(Imagens.Imagens.teste)
py.moveTo(aaaaa[0] + 20... | def reserva():
| py.click(x=1919, y=1076)
try:
py.leftClick(py.locateOnScreen(Imagens.Imagens.mais))
sleep(2)
py.doubleClick(py.locateOnScreen(Imagens.Imagens.razer2, confidence=0.9))
sleep(2)
aaaaa = py.locateOnScreen(Imagens.Imagens.teste)
py.moveTo(aaaaa[0] + 200, aaaaa[1] + 1... | "))
sleep(0.5)
webbrowser.get('chrome').open('https://mail.google.com/mail/u/0/?zx=7quikovz9bly#inbox')
sleep(1)
sleep(0.5)
if f != 0:
reserva()
def reserva():
| 64 | 64 | 165 | 3 | 61 | GabrielCoutz/Automa--es | Auto.py | Python | reserva | reserva | 239 | 255 | 239 | 239 | 26f82eebeb0ea8105c581c156521e947445318c9 | bigcode/the-stack | train |
2dda410c8a3e87baffaa073a | train | function | def google():
sites = ['https://www.youtube.com', 'https://www.imissmybar.com/',
'https://mail.google.com/mail/u/0/?zx=7quikovz9bly#inbox']
webbrowser.register('chrome',
None,
webbrowser.BackgroundBrowser(r"C:\Program Files\Google\Chrome\Application\c... | def google():
| sites = ['https://www.youtube.com', 'https://www.imissmybar.com/',
'https://mail.google.com/mail/u/0/?zx=7quikovz9bly#inbox']
webbrowser.register('chrome',
None,
webbrowser.BackgroundBrowser(r"C:\Program Files\Google\Chrome\Application\chrome.exe"))
... | 0.2)
sleep(1)
try:
py.leftClick(Imagens.Imagens.conf2)
except:
py.leftClick(Imagens.Imagens.conf)
pos1 = py.position()
py.doubleClick(pos1[0] - 34, pos1[1] + 82)
py.doubleClick(pos1[0] - 34, pos1[1] + 82)
py.doubleClick(pos1[0] - 34, pos1[1] + 82)
sleep(1.5)
pos = ... | 201 | 201 | 673 | 3 | 198 | GabrielCoutz/Automa--es | Auto.py | Python | google | google | 145 | 224 | 145 | 145 | 8e2293fb0cbfa68f129150ffc89f1a7dfc0b55cb | bigcode/the-stack | train |
dd1eabbacd5dd37f8c762514 | train | function | def verificar(imagem, left=None, top=None, width=None, height=None):
if left:
if py.locateOnScreen(imagem, region=(left, top, width, height)):
return True
return False
else:
if py.locateCenterOnScreen(imagem, confidence=0.9):
return True
else:
... | def verificar(imagem, left=None, top=None, width=None, height=None):
| if left:
if py.locateOnScreen(imagem, region=(left, top, width, height)):
return True
return False
else:
if py.locateCenterOnScreen(imagem, confidence=0.9):
return True
else:
return False
| a += 1
log3 = py.locateCenterOnScreen(r'E:\Backup\backup PC\Imagens\log33.png')
if log3:
py.click(log3)
sleep(4)
def verificar(imagem, left=None, top=None, width=None, height=None):
| 64 | 64 | 80 | 17 | 47 | GabrielCoutz/Automa--es | Auto.py | Python | verificar | verificar | 57 | 66 | 57 | 57 | 02ea29b1292c94e26e1c35d943f0194f1be5b29b | bigcode/the-stack | train |
5ad32380e1ddf891d9c46f43 | train | function | def login(x, y):
py.click(x, y)
while verificar(Imagens.Imagens.conta1) is False:
sleep(0.1)
py.press('tab', 5)
sleep(1)
py.press('enter')
sleep(1.5)
a = 0
while verificar(Imagens.Imagens.log33) is False and a != 5:
sleep(1)
a += 1
log3 = py.locateCenterOnScre... | def login(x, y):
| py.click(x, y)
while verificar(Imagens.Imagens.conta1) is False:
sleep(0.1)
py.press('tab', 5)
sleep(1)
py.press('enter')
sleep(1.5)
a = 0
while verificar(Imagens.Imagens.log33) is False and a != 5:
sleep(1)
a += 1
log3 = py.locateCenterOnScreen(r'E:\Backup\ba... | # Biblioteca de Imagens
spec = importlib.util.spec_from_file_location(
"name", "C:\\Users\\Gabri\\PycharmProjects\\pythonProject\\Imagens.py")
Imagens = importlib.util.module_from_spec(spec)
spec.loader.exec_module(Imagens)
def login(x, y):
| 64 | 64 | 137 | 6 | 58 | GabrielCoutz/Automa--es | Auto.py | Python | login | login | 39 | 54 | 39 | 39 | a2c8f1a9601989311f81bd37ef126447abaacc07 | bigcode/the-stack | train |
9150b5ccc6298b82b736c321 | train | function | def inicio():
r = randint(1, 5)
winsound.PlaySound(f'E:\\Backup\\Musicas\\intro{r}.wav', winsound.SND_ASYNC)
| def inicio():
| r = randint(1, 5)
winsound.PlaySound(f'E:\\Backup\\Musicas\\intro{r}.wav', winsound.SND_ASYNC)
| )):
return True
return False
else:
if py.locateCenterOnScreen(imagem, confidence=0.9):
return True
else:
return False
def esperar(imagem):
while verificar(imagem) is False:
sleep(0.2)
def inicio():
| 64 | 64 | 39 | 3 | 61 | GabrielCoutz/Automa--es | Auto.py | Python | inicio | inicio | 74 | 76 | 74 | 74 | 0a5972a2eb4f9feeb0f6819e7a8caa54523981e7 | bigcode/the-stack | train |
e8c3ad32fb179ce4bd3965a0 | train | function | def googlefds():
webbrowser.register('chrome',
None,
webbrowser.BackgroundBrowser(r"C:\Program Files\Google\Chrome\Application\chrome.exe"))
sleep(0.5)
webbrowser.get('chrome').open('https://mail.google.com/mail/u/0/?zx=7quikovz9bly#inbox')
sleep(1)
sl... | def googlefds():
| webbrowser.register('chrome',
None,
webbrowser.BackgroundBrowser(r"C:\Program Files\Google\Chrome\Application\chrome.exe"))
sleep(0.5)
webbrowser.get('chrome').open('https://mail.google.com/mail/u/0/?zx=7quikovz9bly#inbox')
sleep(1)
sleep(0.5)
if f... | ra, barras[a])
sleep(0.5)
for b, c in enumerate(plays):
py.leftClick(play, plays[b])
sleep(0.5)
py.leftClick(x=25, y=14)
if f != 0:
reserva()
def googlefds():
| 64 | 64 | 93 | 4 | 60 | GabrielCoutz/Automa--es | Auto.py | Python | googlefds | googlefds | 227 | 236 | 227 | 227 | 8c224cecbd087aa618542e67e24d501c51e6855c | bigcode/the-stack | train |
d53ee2bb232401907085db44 | train | function | def powersheel(comando):
os.system(f'powershell /c {comando}')
| def powersheel(comando):
| os.system(f'powershell /c {comando}')
| (imagem):
while verificar(imagem) is False:
sleep(0.2)
def inicio():
r = randint(1, 5)
winsound.PlaySound(f'E:\\Backup\\Musicas\\intro{r}.wav', winsound.SND_ASYNC)
def powersheel(comando):
| 64 | 64 | 19 | 6 | 58 | GabrielCoutz/Automa--es | Auto.py | Python | powersheel | powersheel | 79 | 80 | 79 | 79 | 3d15be2acd6a6926a2f3e654ecd4933b4022cdfd | bigcode/the-stack | train |
7df47aca61745a94b3f3b0ce | train | function | def resolver():
global c
powersheel(r'Start-Process -WindowStyle hidden -FilePath C:\Users\Gabri\Documents\dpclat.exe')
while not window.getWindowsWithTitle("Error"):
sleep(0.2)
c += 1
if c == 5:
break
if window.getWindowsWithTitle("Error"):
window.getWindowsW... | def resolver():
| global c
powersheel(r'Start-Process -WindowStyle hidden -FilePath C:\Users\Gabri\Documents\dpclat.exe')
while not window.getWindowsWithTitle("Error"):
sleep(0.2)
c += 1
if c == 5:
break
if window.getWindowsWithTitle("Error"):
window.getWindowsWithTitle("Error"... | 2)
def inicio():
r = randint(1, 5)
winsound.PlaySound(f'E:\\Backup\\Musicas\\intro{r}.wav', winsound.SND_ASYNC)
def powersheel(comando):
os.system(f'powershell /c {comando}')
def resolver():
| 63 | 64 | 124 | 3 | 60 | GabrielCoutz/Automa--es | Auto.py | Python | resolver | resolver | 83 | 93 | 83 | 83 | c473664f849df80d23e2e630bd7bb17e36292913 | bigcode/the-stack | train |
175ed07e53f293ad45db0bbb | train | function | def esperar(imagem):
while verificar(imagem) is False:
sleep(0.2)
| def esperar(imagem):
| while verificar(imagem) is False:
sleep(0.2)
| if py.locateOnScreen(imagem, region=(left, top, width, height)):
return True
return False
else:
if py.locateCenterOnScreen(imagem, confidence=0.9):
return True
else:
return False
def esperar(imagem):
| 64 | 64 | 21 | 5 | 58 | GabrielCoutz/Automa--es | Auto.py | Python | esperar | esperar | 69 | 71 | 69 | 69 | 917c7676802f6acd1ac5f9bd00ac82804b0288f7 | bigcode/the-stack | train |
7838c74fd9e13afa0dbb9c49 | train | function | def som():
global f
py.click(Imagens.Imagens.mais)
if verificar(Imagens.Imagens.razeratt) is False:
try:
esperar(Imagens.Imagens.razer2)
py.doubleClick(py.locateOnScreen(Imagens.Imagens.razer2, confidence=0.9))
esperar(Imagens.Imagens.teste)
if verifi... | def som():
| global f
py.click(Imagens.Imagens.mais)
if verificar(Imagens.Imagens.razeratt) is False:
try:
esperar(Imagens.Imagens.razer2)
py.doubleClick(py.locateOnScreen(Imagens.Imagens.razer2, confidence=0.9))
esperar(Imagens.Imagens.teste)
if verificar(Imagens... | def resolver():
global c
powersheel(r'Start-Process -WindowStyle hidden -FilePath C:\Users\Gabri\Documents\dpclat.exe')
while not window.getWindowsWithTitle("Error"):
sleep(0.2)
c += 1
if c == 5:
break
if window.getWindowsWithTitle("Error"):
window.getWindowsW... | 127 | 127 | 426 | 3 | 124 | GabrielCoutz/Automa--es | Auto.py | Python | som | som | 96 | 142 | 96 | 96 | e7fe583f6bf43a739c538ffe53ca70d1251b8cb4 | bigcode/the-stack | train |
bf762b167249a025f1c2853c | train | function | def test_attri2vec_constructor():
attri2vec = Attri2Vec(
layer_sizes=[4], input_dim=2, node_num=4, multiplicity=2, normalize="l2"
)
assert attri2vec.dims == [2, 4]
assert attri2vec.input_node_num == 4
assert attri2vec.n_layers == 1
assert attri2vec.bias == False
# Check incorrect ac... | def test_attri2vec_constructor():
| attri2vec = Attri2Vec(
layer_sizes=[4], input_dim=2, node_num=4, multiplicity=2, normalize="l2"
)
assert attri2vec.dims == [2, 4]
assert attri2vec.input_node_num == 4
assert attri2vec.n_layers == 1
assert attri2vec.bias == False
# Check incorrect activation flag
with pytest.rais... | implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Attri2Vec tests
"""
from stellargraph.core.graph import StellarGraph
from stellargraph.mapper import Attri2VecNodeGenerator
from stellargraph.layer.attri2vec import *
from tensorflow import keras
imp... | 115 | 115 | 386 | 8 | 106 | timpitman/stellargraph | tests/layer/test_attri2vec.py | Python | test_attri2vec_constructor | test_attri2vec_constructor | 37 | 87 | 37 | 37 | 52c498407d0d7607926a6fae8ef64f601d3586ca | bigcode/the-stack | train |
802335c2b3f16993d503e752 | train | function | def test_attri2vec_serialize():
attri2vec = Attri2Vec(
layer_sizes=[4],
bias=False,
input_dim=2,
node_num=4,
multiplicity=2,
activation="linear",
normalize=None,
)
inp = keras.Input(shape=(2,))
out = attri2vec(inp)
model = keras.Model(inputs=i... | def test_attri2vec_serialize():
| attri2vec = Attri2Vec(
layer_sizes=[4],
bias=False,
input_dim=2,
node_num=4,
multiplicity=2,
activation="linear",
normalize=None,
)
inp = keras.Input(shape=(2,))
out = attri2vec(inp)
model = keras.Model(inputs=inp, outputs=out)
# Save mod... | w in model4.get_weights()]
model4.set_weights(model_weights4)
actual = model4.predict([x1, x2])
assert pytest.approx(y1) == actual[0]
assert pytest.approx(y2) == actual[1]
def test_attri2vec_serialize():
| 64 | 64 | 211 | 9 | 55 | timpitman/stellargraph | tests/layer/test_attri2vec.py | Python | test_attri2vec_serialize | test_attri2vec_serialize | 143 | 173 | 143 | 143 | 48e34a5aae6e2e1c9060f9607be3d8c84db3276a | bigcode/the-stack | train |
3e709b7e9d833f6b007b9520 | train | function | def test_attri2vec_apply():
attri2vec = Attri2Vec(
layer_sizes=[2, 2, 2],
bias=False,
input_dim=2,
node_num=4,
multiplicity=2,
activation="linear",
normalize=None,
)
x = np.array([[1, 2]])
expected = np.array([[12, 12]])
inp = keras.Input(sha... | def test_attri2vec_apply():
| attri2vec = Attri2Vec(
layer_sizes=[2, 2, 2],
bias=False,
input_dim=2,
node_num=4,
multiplicity=2,
activation="linear",
normalize=None,
)
x = np.array([[1, 2]])
expected = np.array([[12, 12]])
inp = keras.Input(shape=(2,))
out = attri2vec... | requirement for generator or input_dim and node_num & multiplicity
with pytest.raises(KeyError):
Attri2Vec(layer_sizes=[4])
# Construction from generator
G = example_graph(feature_size=3)
gen = Attri2VecNodeGenerator(G, batch_size=2)
attri2vec = Attri2Vec(layer_sizes=[4, 8], generator=gen,... | 146 | 146 | 487 | 8 | 137 | timpitman/stellargraph | tests/layer/test_attri2vec.py | Python | test_attri2vec_apply | test_attri2vec_apply | 90 | 140 | 90 | 90 | 962de08b6e4c7dc6e6be29bf96c5851239424cff | bigcode/the-stack | train |
cc58d053ca868301626623c3 | train | function | def main() -> typing.NoReturn:
n = int(input())
edges = set()
for i in range(n - 1):
for j in range(i + 1, n):
edges.add((i, j))
if n & 1:
for i in range(n // 2):
edges.remove((i, n - 2 - i))
else:
for i in range(n // 2):
edg... | def main() -> typing.NoReturn:
| n = int(input())
edges = set()
for i in range(n - 1):
for j in range(i + 1, n):
edges.add((i, j))
if n & 1:
for i in range(n // 2):
edges.remove((i, n - 2 - i))
else:
for i in range(n // 2):
edges.remove((i, n - 1 - i))
... | import typing
def main() -> typing.NoReturn:
| 11 | 64 | 131 | 8 | 2 | kagemeka/atcoder-submissions | jp.atcoder/agc032/agc032_b/27917968.py | Python | main | main | 4 | 21 | 4 | 4 | cb0747145702962f4132673acfe05717656afd07 | bigcode/the-stack | train |
fdde0c20f2ad02c71136bcf8 | train | function | def get_one_process(proc_name):
try:
global processDataList
# print(proc_name)
# proclist = process_list()
oneProcData = {}
current_process = psutil.pids()
if int(proc_name) in current_process:
dtime = datetime.now().strftime("%H:%M:%S") # 只有时分秒
... | def get_one_process(proc_name):
| try:
global processDataList
# print(proc_name)
# proclist = process_list()
oneProcData = {}
current_process = psutil.pids()
if int(proc_name) in current_process:
dtime = datetime.now().strftime("%H:%M:%S") # 只有时分秒
oneProcData["datetime"] = dt... | ():
procs = psutil.pids()
proclist = []
for aPid in procs:
# print(a)
aProcName = psutil.Process(aPid).name()
proc_data = (aPid, aProcName)
proclist.append(proc_data)
return proclist
def get_one_process(proc_name):
| 73 | 73 | 246 | 7 | 65 | re0phimes/FlaskTest | FlaskApp/test.py | Python | get_one_process | get_one_process | 22 | 45 | 22 | 22 | d23ad27fec1dac468448b4d2d9b47b69d7400175 | bigcode/the-stack | train |
72b62a851b5ae0b4ba1e5187 | train | function | def process_list():
procs = psutil.pids()
proclist = []
for aPid in procs:
# print(a)
aProcName = psutil.Process(aPid).name()
proc_data = (aPid, aProcName)
proclist.append(proc_data)
return proclist
| def process_list():
| procs = psutil.pids()
proclist = []
for aPid in procs:
# print(a)
aProcName = psutil.Process(aPid).name()
proc_data = (aPid, aProcName)
proclist.append(proc_data)
return proclist
| from threading import Timer
import time, schedule
import psutil
from datetime import datetime
from forms import ProcessForm
from getPCmemory import get_one_process
processDataList = []
def process_list():
| 43 | 64 | 69 | 4 | 39 | re0phimes/FlaskTest | FlaskApp/test.py | Python | process_list | process_list | 11 | 19 | 11 | 11 | 493f36df2affcbdb86c353685388151289ac30f3 | bigcode/the-stack | train |
77b3b51fb7fec104b9560405 | train | function | def test_func():
schedule.every(1).seconds.do(get_one_process,6700)
while True:
schedule.run_pending()
| def test_func():
| schedule.every(1).seconds.do(get_one_process,6700)
while True:
schedule.run_pending()
| else:
processDataList = processDataList[1:]
processDataList.append(oneProcData)
print(processDataList)
else:
print("no such process")
except Exception as e:
print(e)
print("eror in get_one_process")
def test_func():
| 63 | 64 | 28 | 4 | 59 | re0phimes/FlaskTest | FlaskApp/test.py | Python | test_func | test_func | 49 | 52 | 49 | 49 | 39c7f343d7fb1b76b1a4ba17a450267abaa6b302 | bigcode/the-stack | train |
3dcada7f4f9d96eb842832d4 | train | class | class Migration(migrations.Migration):
dependencies = [
('sources_main', '0018_migrate_sourcetypes'),
]
operations = [
migrations.AlterField(
model_name='source',
name='doctype',
field=models.CharField(choices=[('DOC', 'Document'), ('PDF', 'Pdf'), ('IMG'... | class Migration(migrations.Migration):
| dependencies = [
('sources_main', '0018_migrate_sourcetypes'),
]
operations = [
migrations.AlterField(
model_name='source',
name='doctype',
field=models.CharField(choices=[('DOC', 'Document'), ('PDF', 'Pdf'), ('IMG', 'Image'), ('LINK', 'Weblink'), ('VIDEO... | # Generated by Django 2.1 on 2018-11-22 18:22
from django.db import migrations, models
class Migration(migrations.Migration):
| 36 | 64 | 122 | 7 | 28 | DOSSIER-dev/DOSSIER-Sources | app/sources_main/migrations/0019_auto_20181122_1822.py | Python | Migration | Migration | 6 | 18 | 6 | 7 | 367aedcc77f54efbdfc02868ee98c884e78de86c | bigcode/the-stack | train |
d25e6805bdf979eaf1e5fc5c | train | class | class TestLinearRegression(unittest.TestCase):
def test_basic_linear_regression(self):
import numpy as np
from mlp.regression.linear import BasicLinearRegression
X = np.array([[x] for x in range(6)])
y = np.array([x for x in range(6)])
model = BasicLinearRegression()
... | class TestLinearRegression(unittest.TestCase):
| def test_basic_linear_regression(self):
import numpy as np
from mlp.regression.linear import BasicLinearRegression
X = np.array([[x] for x in range(6)])
y = np.array([x for x in range(6)])
model = BasicLinearRegression()
model.fit(X, y)
self.assertEqual(2,... | import unittest
class TestLinearRegression(unittest.TestCase):
| 11 | 64 | 143 | 8 | 2 | guidj/mlp | tests/linear.py | Python | TestLinearRegression | TestLinearRegression | 4 | 23 | 4 | 4 | 2e5fc4475566d7ca7e6dfce82f302aa4fefca60e | bigcode/the-stack | train |
2c973d5364a5bb95153b0872 | train | class | class PowerSeo2016(PowerSpectrumFit):
""" P(k) model inspired from Seo 2016.
See https://ui.adsabs.harvard.edu/abs/2016MNRAS.460.2453S for details.
"""
def __init__(
self, name="Pk Seo 2016", fix_params=("om", "f"), smooth_type="hinton2017", recon=False, postprocess=None, smooth=False, correct... | class PowerSeo2016(PowerSpectrumFit):
| """ P(k) model inspired from Seo 2016.
See https://ui.adsabs.harvard.edu/abs/2016MNRAS.460.2453S for details.
"""
def __init__(
self, name="Pk Seo 2016", fix_params=("om", "f"), smooth_type="hinton2017", recon=False, postprocess=None, smooth=False, correction=None, isotropic=True
):
... | import logging
from functools import lru_cache
import numpy as np
from scipy import integrate
from barry.models.bao_power import PowerSpectrumFit
from scipy.interpolate import splev, splrep
class PowerSeo2016(PowerSpectrumFit):
| 52 | 256 | 4,532 | 10 | 41 | nam8/Barry | barry/models/bao_power_Seo2016.py | Python | PowerSeo2016 | PowerSeo2016 | 10 | 298 | 10 | 10 | 8d3a6a96d6465d4c69ec08cb3404440cc59ad250 | bigcode/the-stack | train |
0e79a012375ea927993c88ab | train | class | @skipIf(NO_MOCK, NO_MOCK_REASON)
class MysqlGrantsTestCase(TestCase):
'''
Test cases for salt.states.mysql_grants
'''
# 'present' function tests: 1
def test_present(self):
'''
Test to ensure that the grant is present with the specified properties.
'''
name = 'frank_e... | @skipIf(NO_MOCK, NO_MOCK_REASON)
class MysqlGrantsTestCase(TestCase):
| '''
Test cases for salt.states.mysql_grants
'''
# 'present' function tests: 1
def test_present(self):
'''
Test to ensure that the grant is present with the specified properties.
'''
name = 'frank_exampledb'
ret = {'name': name,
'result': True,... | # -*- coding: utf-8 -*-
'''
:codeauthor: :email:`Jayesh Kariya <jayeshk@saltstack.com>`
'''
# Import Python libs
from __future__ import absolute_import
# Import Salt Testing Libs
from salttesting import skipIf, TestCase
from salttesting.mock import (
NO_MOCK,
NO_MOCK_REASON,
MagicMock,
patch)
from... | 155 | 256 | 886 | 21 | 134 | preoctopus/salt | tests/unit/states/mysql_grants_test.py | Python | MysqlGrantsTestCase | MysqlGrantsTestCase | 27 | 119 | 27 | 28 | 2396b2a98fe010233eef8a45323929b5c4de39f9 | bigcode/the-stack | train |
0277a83f36de5100fac15950 | train | class | class ProjectView(BumfViewSet):
queryset = Project.objects.all()
serializer_class = ProjectSerializer
user_relation = 'user'
| class ProjectView(BumfViewSet):
| queryset = Project.objects.all()
serializer_class = ProjectSerializer
user_relation = 'user'
| from bumf.api.serializers import ProjectSerializer
from bumf.api.views.base import BumfViewSet
from bumf.core.models import Project
class ProjectView(BumfViewSet):
| 39 | 64 | 30 | 9 | 29 | bumfiness/bumf | server/bumf/api/views/project.py | Python | ProjectView | ProjectView | 6 | 9 | 6 | 6 | 01be3ff2e60f95cc366576a478999d1ad8f0cd08 | bigcode/the-stack | train |
7b9c0c6de20e08e83e5e43c5 | train | function | async def watch_statefulsets(queue):
v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_stateful_set_for_all_namespaces):
await queue.put(event)
| async def watch_statefulsets(queue):
| v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_stateful_set_for_all_namespaces):
await queue.put(event)
| _all_namespaces):
await queue.put(event)
async def watch_daemonsets(queue):
v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_daemon_set_for_all_namespaces):
await queue.put(event)
async def watch_statefulsets(queue):
| 64 | 64 | 46 | 8 | 56 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | watch_statefulsets | watch_statefulsets | 23 | 26 | 23 | 23 | f4364073f031d0d940d740bd5f1a0f5ad76d23d4 | bigcode/the-stack | train |
f86f35184beb0fb1c765de12 | train | function | async def sync_up(has_synced):
# The naive approach is to just use a timer...
start_time = time()
while time() - start_time < 5:
await asyncio.sleep(0.5)
# Simple types assigment is an atomic operation
has_synced.done = True
print('sync-up')
| async def sync_up(has_synced):
# The naive approach is to just use a timer...
| start_time = time()
while time() - start_time < 5:
await asyncio.sleep(0.5)
# Simple types assigment is an atomic operation
has_synced.done = True
print('sync-up')
| _cronjobs(queue):
v1 = client.BatchV1beta1Api()
async for event in watch.Watch().stream(v1.list_cron_job_for_all_namespaces):
await queue.put(event)
async def sync_up(has_synced):
# The naive approach is to just use a timer...
| 64 | 64 | 72 | 20 | 44 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | sync_up | sync_up | 34 | 42 | 34 | 35 | 1b6215641fb035c29e5e87cc96cfbb3fb7d6c85f | bigcode/the-stack | train |
f98f441f567fc60dcb953fa5 | train | function | async def watch_cronjobs(queue):
v1 = client.BatchV1beta1Api()
async for event in watch.Watch().stream(v1.list_cron_job_for_all_namespaces):
await queue.put(event)
| async def watch_cronjobs(queue):
| v1 = client.BatchV1beta1Api()
async for event in watch.Watch().stream(v1.list_cron_job_for_all_namespaces):
await queue.put(event)
| _all_namespaces):
await queue.put(event)
async def watch_statefulsets(queue):
v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_stateful_set_for_all_namespaces):
await queue.put(event)
async def watch_cronjobs(queue):
| 64 | 64 | 47 | 8 | 56 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | watch_cronjobs | watch_cronjobs | 28 | 31 | 28 | 28 | 138082753fcfff076d8400258d1ec26711ba2cc5 | bigcode/the-stack | train |
27cb132507eae8c4c816f2c5 | train | function | async def consume_events(queue, has_synced, func):
storage = {}
count = 0
while True:
event = await queue.get()
count += 1
func(event, storage, has_synced, count)
| async def consume_events(queue, has_synced, func):
| storage = {}
count = 0
while True:
event = await queue.get()
count += 1
func(event, storage, has_synced, count)
| start_time = time()
while time() - start_time < 5:
await asyncio.sleep(0.5)
# Simple types assigment is an atomic operation
has_synced.done = True
print('sync-up')
async def consume_events(queue, has_synced, func):
| 64 | 64 | 51 | 12 | 52 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | consume_events | consume_events | 44 | 50 | 44 | 44 | b7be2b4b9f9b8f02bb88418ef7ffa6ca6aa31298 | bigcode/the-stack | train |
62d1f3eefbfd83321228c7e8 | train | class | class StatefulSet(WorkloadsResource):
pass
| class StatefulSet(WorkloadsResource):
| pass
| resource_version'] = None
meta['generation'] = None
spec = str(self.obj.spec)
return '{}\n{}'.format(str(meta), spec)
class Deployment(WorkloadsResource):
pass
class DaemonSet(WorkloadsResource):
pass
class StatefulSet(WorkloadsResource):
| 64 | 64 | 11 | 8 | 55 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | StatefulSet | StatefulSet | 87 | 88 | 87 | 87 | 25bacb18f71aeff758fda43b2cc6d2b28ccd4c40 | bigcode/the-stack | train |
b90cf15595a3a69b6f1c8f7d | train | function | def _notify_event(action, kind, name, event_count, diff):
print(action, kind, name, event_count)
print(diff)
webhook_url = os.environ['SLACK_WEBHOOK_URL']
short_message = "{} {}/{}".format(action, kind, name)
if action == 'ADDED': color = "#7CD197"
if action == 'DELETED': color = "#ff0000"
... | def _notify_event(action, kind, name, event_count, diff):
| print(action, kind, name, event_count)
print(diff)
webhook_url = os.environ['SLACK_WEBHOOK_URL']
short_message = "{} {}/{}".format(action, kind, name)
if action == 'ADDED': color = "#7CD197"
if action == 'DELETED': color = "#ff0000"
if action == 'MODIFIED': color = "#ff9900"
slack_dat... | (str(meta), spec)
class Deployment(WorkloadsResource):
pass
class DaemonSet(WorkloadsResource):
pass
class StatefulSet(WorkloadsResource):
pass
class CronJob(WorkloadsResource):
pass
def _notify_event(action, kind, name, event_count, diff):
| 64 | 64 | 207 | 15 | 48 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | _notify_event | _notify_event | 93 | 120 | 93 | 93 | de56f7bb4dda891355f600f2248db40afd112045 | bigcode/the-stack | train |
19bf25c52e949fbef6463cae | train | class | class HasSynced(object):
def __init__(self):
self.done = False
| class HasSynced(object):
| def __init__(self):
self.done = False
|
print('sync-up')
async def consume_events(queue, has_synced, func):
storage = {}
count = 0
while True:
event = await queue.get()
count += 1
func(event, storage, has_synced, count)
class HasSynced(object):
| 64 | 64 | 19 | 6 | 58 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | HasSynced | HasSynced | 52 | 54 | 52 | 52 | 2b9f89c59a8c156c2a70b30d19c89bfa74118882 | bigcode/the-stack | train |
e2e04e9c58ba6300b769dc92 | train | function | def _compare_manifests(a, b):
diff = '\n'.join(
filter(
lambda x: not x.startswith('@@') and not x.startswith('---') and not x.startswith('+++'),
difflib.unified_diff(
str(a).split('\n'),
str(b).split('\n'),
n=0,
linet... | def _compare_manifests(a, b):
| diff = '\n'.join(
filter(
lambda x: not x.startswith('@@') and not x.startswith('---') and not x.startswith('+++'),
difflib.unified_diff(
str(a).split('\n'),
str(b).split('\n'),
n=0,
lineterm=''
)
)... | }
response = requests.post(
webhook_url, data=json.dumps(slack_data),
headers={'Content-Type': 'application/json'}
)
if response.status_code != 200:
print('ERROR: slack webhook status code {}'.format(response.status_code))
def _compare_manifests(a, b):
| 64 | 64 | 91 | 10 | 54 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | _compare_manifests | _compare_manifests | 123 | 135 | 123 | 123 | 61561929bdcf53e86651cd9408fb99f69121af03 | bigcode/the-stack | train |
652a555d2c3cbedaa476448a | train | function | def _handle_event(event, storage, has_synced, count):
try:
kind = event['object'].kind
action = event['type']
klasses = {
'Deployment': Deployment,
'DaemonSet': DaemonSet,
'StatefulSet': StatefulSet,
'CronJob': CronJob
}
... | def _handle_event(event, storage, has_synced, count):
| try:
kind = event['object'].kind
action = event['type']
klasses = {
'Deployment': Deployment,
'DaemonSet': DaemonSet,
'StatefulSet': StatefulSet,
'CronJob': CronJob
}
if kind in klasses:
obj = klasses[ki... | : not x.startswith('@@') and not x.startswith('---') and not x.startswith('+++'),
difflib.unified_diff(
str(a).split('\n'),
str(b).split('\n'),
n=0,
lineterm=''
)
)
)
return diff
def _handle_event(event, storage, h... | 81 | 81 | 270 | 14 | 66 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | _handle_event | _handle_event | 137 | 176 | 137 | 137 | 050f0bf6708c109244461772c60df3ff071517b7 | bigcode/the-stack | train |
56f67a18e00deb7fff62dbd3 | train | class | class Deployment(WorkloadsResource):
pass
| class Deployment(WorkloadsResource):
| pass
| annotations' in meta and meta['annotations'] != None:
meta['annotations'] = None
meta['resource_version'] = None
meta['generation'] = None
spec = str(self.obj.spec)
return '{}\n{}'.format(str(meta), spec)
class Deployment(WorkloadsResource):
| 64 | 64 | 10 | 7 | 57 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | Deployment | Deployment | 81 | 82 | 81 | 81 | 1e227a269d3ca9a70fc56cef2ba4c43ea02befc6 | bigcode/the-stack | train |
a5816fcb1fcb0b053d975491 | train | class | class CronJob(WorkloadsResource):
pass
| class CronJob(WorkloadsResource):
| pass
| = None
spec = str(self.obj.spec)
return '{}\n{}'.format(str(meta), spec)
class Deployment(WorkloadsResource):
pass
class DaemonSet(WorkloadsResource):
pass
class StatefulSet(WorkloadsResource):
pass
class CronJob(WorkloadsResource):
| 64 | 64 | 11 | 8 | 55 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | CronJob | CronJob | 90 | 91 | 90 | 90 | 4cce2ab83f1167d4aed920ebfebd81e846be1b16 | bigcode/the-stack | train |
24d7a6d7b4b8ce74a6a0c4d4 | train | function | async def watch_daemonsets(queue):
v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_daemon_set_for_all_namespaces):
await queue.put(event)
| async def watch_daemonsets(queue):
| v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_daemon_set_for_all_namespaces):
await queue.put(event)
| ernetes_asyncio import client, config, watch
async def watch_deployments(queue):
v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_deployment_for_all_namespaces):
await queue.put(event)
async def watch_daemonsets(queue):
| 64 | 64 | 46 | 8 | 56 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | watch_daemonsets | watch_daemonsets | 18 | 21 | 18 | 18 | 64e0ad589e215175afe94a3d1506415d7369657c | bigcode/the-stack | train |
a9038edc74dab3a183e6ef3d | train | function | async def watch_deployments(queue):
v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_deployment_for_all_namespaces):
await queue.put(event)
| async def watch_deployments(queue):
| v1 = client.AppsV1Api()
async for event in watch.Watch().stream(v1.list_deployment_for_all_namespaces):
await queue.put(event)
| s event streams without threads."""
import asyncio
import json
import copy
import difflib
import os, sys, traceback
import requests
from time import time
from abc import ABC, abstractmethod
from kubernetes_asyncio import client, config, watch
async def watch_deployments(queue):
| 64 | 64 | 45 | 8 | 55 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | watch_deployments | watch_deployments | 13 | 16 | 13 | 13 | cf08252ff67b413cf2dba790c66feda27fc3741f | bigcode/the-stack | train |
f1adb34f0256a44b2eff3ad6 | train | class | class WorkloadsResource(ABC):
def __init__(self, event):
self.obj = event['object']
self.kind = event['object'].kind
self.name = event['object'].metadata.name
self.namespace = event['object'].metadata.namespace
self.version = event['object'].metadata.resourc... | class WorkloadsResource(ABC):
| def __init__(self, event):
self.obj = event['object']
self.kind = event['object'].kind
self.name = event['object'].metadata.name
self.namespace = event['object'].metadata.namespace
self.version = event['object'].metadata.resource_version
@property
d... | storage = {}
count = 0
while True:
event = await queue.get()
count += 1
func(event, storage, has_synced, count)
class HasSynced(object):
def __init__(self):
self.done = False
class WorkloadsResource(ABC):
| 64 | 64 | 191 | 7 | 56 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | WorkloadsResource | WorkloadsResource | 56 | 79 | 56 | 56 | 1bf63ecd53036b0a0a9368b90b3f1824516e6686 | bigcode/the-stack | train |
495016d6c85ebac26faedc59 | train | class | class DaemonSet(WorkloadsResource):
pass
| class DaemonSet(WorkloadsResource):
| pass
| meta['annotations'] = None
meta['resource_version'] = None
meta['generation'] = None
spec = str(self.obj.spec)
return '{}\n{}'.format(str(meta), spec)
class Deployment(WorkloadsResource):
pass
class DaemonSet(WorkloadsResource):
| 64 | 64 | 12 | 9 | 54 | snebel29/kwatchman | prototype/async_kwatchman.py | Python | DaemonSet | DaemonSet | 84 | 85 | 84 | 84 | fe97e3c0d5ae8d69889e8d6ecd9b4e2442e7ffec | bigcode/the-stack | train |
d5e6c47a7a26a1d10059d0f9 | train | function | def get_nlp_credentials():
config = ConfigObj("users" + os.sep + "config.ini")
return config["nlp_user"], config["nlp_password"]
| def get_nlp_credentials():
| config = ConfigObj("users" + os.sep + "config.ini")
return config["nlp_user"], config["nlp_password"]
| # Web resource
resp = requests.get(banner)
return resp.text
else: # File name in templates/ dir
banner = config["banner"]
banner = open(prefix + "templates" + os.sep + banner).read()
return banner
def get_nlp_credentials():
| 64 | 64 | 34 | 6 | 57 | CopticScriptorium/gitdox | paths.py | Python | get_nlp_credentials | get_nlp_credentials | 36 | 38 | 36 | 36 | f6fca33d96103c0e63aa712816c1d96fd470ef42 | bigcode/the-stack | train |
774a06ae4707c398dbd66e4d | train | function | def get_menu():
config = ConfigObj(prefix + "users" + os.sep + "config.ini")
if "banner" not in config:
return ""
banner = config["banner"]
if banner.startswith("http"): # Web resource
resp = requests.get(banner)
return resp.text
else: # File name in templates/ dir
banner = config["banner"]
banner = ... | def get_menu():
| config = ConfigObj(prefix + "users" + os.sep + "config.ini")
if "banner" not in config:
return ""
banner = config["banner"]
if banner.startswith("http"): # Web resource
resp = requests.get(banner)
return resp.text
else: # File name in templates/ dir
banner = config["banner"]
banner = open(prefix + "t... | project root
try:
ether_url = ConfigObj(gitdox_root + os.sep + "users" + os.sep + "config.ini")["ether_url"]
if not ether_url.endswith(os.sep):
ether_url += os.sep
except KeyError:
ether_url = ""
def get_menu():
| 64 | 64 | 104 | 4 | 60 | CopticScriptorium/gitdox | paths.py | Python | get_menu | get_menu | 20 | 33 | 20 | 20 | 9cdc3caa575657cc3293df4e7f0d8285817b27c2 | bigcode/the-stack | train |
71045fdad32f7cd726256ab0 | train | function | @pytest.fixture
def root():
return ProjectPackage("root", "1.2.3")
| @pytest.fixture
def root():
| return ProjectPackage("root", "1.2.3")
| import MockEnv as BaseMockEnv
from tests.helpers import get_dependency
from subprocess import CalledProcessError
class MockEnv(BaseMockEnv):
def run(self, bin, *args):
raise EnvCommandError(CalledProcessError(1, "python", output=""))
@pytest.fixture
def root():
| 63 | 64 | 20 | 6 | 57 | mgasner/poetry | tests/puzzle/test_provider.py | Python | root | root | 27 | 29 | 27 | 28 | 92645f879a90fec175039532f2112c5eb7f5a728 | bigcode/the-stack | train |
f1f83c4cead9f49c950fbca4 | train | function | @pytest.mark.skipif(not PY35, reason="AST parsing does not work for Python <3.4")
def test_search_for_directory_setup_read_setup(provider, mocker):
mocker.patch("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = DirectoryDependency(
"demo",
Path(__file__).parent.parent
... | @pytest.mark.skipif(not PY35, reason="AST parsing does not work for Python <3.4")
def test_search_for_directory_setup_read_setup(provider, mocker):
| mocker.patch("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = DirectoryDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "git"
/ "github.com"
/ "demo"
/ "demo",
)
package = provider.search_for_directory(depend... | tras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
@pytest.mark.skipif(not PY35, reason="AST parsing does not work for Python <3.4")
def test_search_for_directory_setup_read_setup(provider, mocker):
| 64 | 64 | 186 | 35 | 29 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_directory_setup_read_setup | test_search_for_directory_setup_read_setup | 177 | 199 | 177 | 178 | a1b8046964b1c14e865a7ff6d92351c826e60779 | bigcode/the-stack | train |
e5f38c4dca44b0d44743d9e1 | train | function | def test_search_for_directory_setup_egg_info(provider):
dependency = DirectoryDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "git"
/ "github.com"
/ "demo"
/ "demo",
)
package = provider.search_for_directory(dependency)[0]
assert ... | def test_search_for_directory_setup_egg_info(provider):
| dependency = DirectoryDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "git"
/ "github.com"
/ "demo"
/ "demo",
)
package = provider.search_for_directory(dependency)[0]
assert package.name == "demo"
assert package.version.text =... | ("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = VCSDependency("demo", "git", "https://github.com/demo/no-version.git")
with pytest.raises(RuntimeError):
provider.search_for_vcs(dependency)
def test_search_for_directory_setup_egg_info(provider):
| 64 | 64 | 143 | 11 | 53 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_directory_setup_egg_info | test_search_for_directory_setup_egg_info | 129 | 148 | 129 | 129 | 381bba147e684b94646bb6ec5460c3321457e356 | bigcode/the-stack | train |
9b131e78f55fc2f96d0fed27 | train | function | def test_search_for_vcs_setup_egg_info_with_extras(provider):
dependency = VCSDependency("demo", "git", "https://github.com/demo/demo.git")
dependency.extras.append("foo")
package = provider.search_for_vcs(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.2"
asse... | def test_search_for_vcs_setup_egg_info_with_extras(provider):
| dependency = VCSDependency("demo", "git", "https://github.com/demo/demo.git")
dependency.extras.append("foo")
package = provider.search_for_vcs(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.2"
assert package.requires == [
get_dependency("pendulum", ">... | == [get_dependency("pendulum", ">=1.4.4")]
assert package.extras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
def test_search_for_vcs_setup_egg_info_with_extras(provider):
| 64 | 64 | 143 | 15 | 49 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_vcs_setup_egg_info_with_extras | test_search_for_vcs_setup_egg_info_with_extras | 64 | 79 | 64 | 64 | 6e94750be20e11b45ae85b5ae7015f63488a340d | bigcode/the-stack | train |
4db6a5d8420f18df8603d5a8 | train | function | def test_search_for_vcs_read_setup_raises_error_if_no_version(provider, mocker):
mocker.patch("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = VCSDependency("demo", "git", "https://github.com/demo/no-version.git")
with pytest.raises(RuntimeError):
provider.search_for_vcs(dep... | def test_search_for_vcs_read_setup_raises_error_if_no_version(provider, mocker):
| mocker.patch("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = VCSDependency("demo", "git", "https://github.com/demo/no-version.git")
with pytest.raises(RuntimeError):
provider.search_for_vcs(dependency)
| "),
get_dependency("cleo", optional=True),
]
assert package.extras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
def test_search_for_vcs_read_setup_raises_error_if_no_version(provider, mocker):
| 64 | 64 | 76 | 19 | 45 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_vcs_read_setup_raises_error_if_no_version | test_search_for_vcs_read_setup_raises_error_if_no_version | 120 | 126 | 120 | 120 | 23ad95f5a18d2d1d444f0abdd17eb162dcaf7cb3 | bigcode/the-stack | train |
d6a0e4f7ddc6a28375defa81 | train | function | @pytest.fixture
def repository():
return Repository()
| @pytest.fixture
def repository():
| return Repository()
| Error
class MockEnv(BaseMockEnv):
def run(self, bin, *args):
raise EnvCommandError(CalledProcessError(1, "python", output=""))
@pytest.fixture
def root():
return ProjectPackage("root", "1.2.3")
@pytest.fixture
def repository():
| 64 | 64 | 10 | 6 | 58 | mgasner/poetry | tests/puzzle/test_provider.py | Python | repository | repository | 32 | 34 | 32 | 33 | 3ceed9fd5e871d50002fb4422b452d74920d63d8 | bigcode/the-stack | train |
183e0f7392e527f825abd445 | train | function | def test_search_for_directory_setup_egg_info_with_extras(provider):
dependency = DirectoryDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "git"
/ "github.com"
/ "demo"
/ "demo",
)
dependency.extras.append("foo")
package = provider.... | def test_search_for_directory_setup_egg_info_with_extras(provider):
| dependency = DirectoryDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "git"
/ "github.com"
/ "demo"
/ "demo",
)
dependency.extras.append("foo")
package = provider.search_for_directory(dependency)[0]
assert package.name == "dem... | .requires == [get_dependency("pendulum", ">=1.4.4")]
assert package.extras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
def test_search_for_directory_setup_egg_info_with_extras(provider):
| 64 | 64 | 166 | 14 | 50 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_directory_setup_egg_info_with_extras | test_search_for_directory_setup_egg_info_with_extras | 151 | 174 | 151 | 151 | 42227209d5428e72b08f2b53982f765f2f0fa4be | bigcode/the-stack | train |
6c08d7bc621d984ccae0fd07 | train | function | @pytest.fixture
def provider(root, pool):
return Provider(root, pool, NullIO())
| @pytest.fixture
def provider(root, pool):
| return Provider(root, pool, NullIO())
| =""))
@pytest.fixture
def root():
return ProjectPackage("root", "1.2.3")
@pytest.fixture
def repository():
return Repository()
@pytest.fixture
def pool(repository):
pool = Pool()
pool.add_repository(repository)
return pool
@pytest.fixture
def provider(root, pool):
| 64 | 64 | 19 | 9 | 54 | mgasner/poetry | tests/puzzle/test_provider.py | Python | provider | provider | 45 | 47 | 45 | 46 | 4aef81b2c9384caab560aafc5a846d808f410d92 | bigcode/the-stack | train |
3ca694bd86f6495c900dc405 | train | function | def test_search_for_file_wheel_with_extras(provider):
dependency = FileDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "distributions"
/ "demo-0.1.0-py2.py3-none-any.whl",
)
dependency.extras.append("foo")
package = provider.search_for_file(depend... | def test_search_for_file_wheel_with_extras(provider):
| dependency = FileDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "distributions"
/ "demo-0.1.0-py2.py3-none-any.whl",
)
dependency.extras.append("foo")
package = provider.search_for_file(dependency)[0]
assert package.name == "demo"
assert... | assert package.requires == [get_dependency("pendulum", ">=1.4.4")]
assert package.extras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
def test_search_for_file_wheel_with_extras(provider):
| 64 | 64 | 169 | 12 | 52 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_file_wheel_with_extras | test_search_for_file_wheel_with_extras | 350 | 371 | 350 | 350 | fbb7a0698139925ad1329efaac4f2f2ddd36f947 | bigcode/the-stack | train |
dc59ae631695617030dd40a9 | train | function | def test_search_for_directory_poetry(provider):
dependency = DirectoryDependency(
"demo", Path(__file__).parent.parent / "fixtures" / "project_with_extras"
)
package = provider.search_for_directory(dependency)[0]
assert package.name == "project-with-extras"
assert package.version.text == "... | def test_search_for_directory_poetry(provider):
| dependency = DirectoryDependency(
"demo", Path(__file__).parent.parent / "fixtures" / "project_with_extras"
)
package = provider.search_for_directory(dependency)[0]
assert package.name == "project-with-extras"
assert package.version.text == "1.2.3"
assert package.requires == []
ass... | / "no-dependencies",
)
package = provider.search_for_directory(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.2"
assert package.requires == []
assert package.extras == {}
def test_search_for_directory_poetry(provider):
| 63 | 64 | 132 | 9 | 54 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_directory_poetry | test_search_for_directory_poetry | 253 | 266 | 253 | 253 | db5bec9cfb86b8ff16a9c0b7bd2615dd82f9e9f7 | bigcode/the-stack | train |
afda4f511030d9215dcb9d9a | train | function | @pytest.mark.skipif(not PY35, reason="AST parsing does not work for Python <3.4")
def test_search_for_vcs_read_setup(provider, mocker):
mocker.patch("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = VCSDependency("demo", "git", "https://github.com/demo/demo.git")
package = provider.s... | @pytest.mark.skipif(not PY35, reason="AST parsing does not work for Python <3.4")
def test_search_for_vcs_read_setup(provider, mocker):
| mocker.patch("poetry.utils.env.EnvManager.get", return_value=MockEnv())
dependency = VCSDependency("demo", "git", "https://github.com/demo/demo.git")
package = provider.search_for_vcs(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.2"
assert package.requires =... | tras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
@pytest.mark.skipif(not PY35, reason="AST parsing does not work for Python <3.4")
def test_search_for_vcs_read_setup(provider, mocker):
| 64 | 64 | 162 | 35 | 29 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_vcs_read_setup | test_search_for_vcs_read_setup | 82 | 96 | 82 | 83 | 29f619553ac1b58433370206bc897cbc2eb9d5df | bigcode/the-stack | train |
2229c134f1b3875d6ff5c97e | train | function | def test_search_for_vcs_setup_egg_info(provider):
dependency = VCSDependency("demo", "git", "https://github.com/demo/demo.git")
package = provider.search_for_vcs(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.2"
assert package.requires == [get_dependency("pendulum... | def test_search_for_vcs_setup_egg_info(provider):
| dependency = VCSDependency("demo", "git", "https://github.com/demo/demo.git")
package = provider.search_for_vcs(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.2"
assert package.requires == [get_dependency("pendulum", ">=1.4.4")]
assert package.extras == {
... | ")
@pytest.fixture
def repository():
return Repository()
@pytest.fixture
def pool(repository):
pool = Pool()
pool.add_repository(repository)
return pool
@pytest.fixture
def provider(root, pool):
return Provider(root, pool, NullIO())
def test_search_for_vcs_setup_egg_info(provider):
| 64 | 64 | 120 | 12 | 52 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_vcs_setup_egg_info | test_search_for_vcs_setup_egg_info | 50 | 61 | 50 | 50 | 2e341e918fcf0d554c6eccebaed2f306b22c4cae | bigcode/the-stack | train |
4dbab70ee7ea7a8b73776f21 | train | function | def test_search_for_directory_poetry_with_extras(provider):
dependency = DirectoryDependency(
"demo", Path(__file__).parent.parent / "fixtures" / "project_with_extras"
)
dependency.extras.append("extras_a")
package = provider.search_for_directory(dependency)[0]
assert package.name == "proj... | def test_search_for_directory_poetry_with_extras(provider):
| dependency = DirectoryDependency(
"demo", Path(__file__).parent.parent / "fixtures" / "project_with_extras"
)
dependency.extras.append("extras_a")
package = provider.search_for_directory(dependency)[0]
assert package.name == "project-with-extras"
assert package.version.text == "1.2.3"
... | assert package.extras == {
"extras_a": [get_dependency("pendulum", ">=1.4.4")],
"extras_b": [get_dependency("cachy", ">=0.2.0")],
}
def test_search_for_directory_poetry_with_extras(provider):
| 64 | 64 | 158 | 12 | 52 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_directory_poetry_with_extras | test_search_for_directory_poetry_with_extras | 269 | 283 | 269 | 269 | 0dc6d563864d809a005cd2367a5452919811ab96 | bigcode/the-stack | train |
16e4cf2d238662541ec7b41a | train | function | def test_search_for_file_sdist_with_extras(provider):
dependency = FileDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "distributions"
/ "demo-0.1.0.tar.gz",
)
dependency.extras.append("foo")
package = provider.search_for_file(dependency)[0]
... | def test_search_for_file_sdist_with_extras(provider):
| dependency = FileDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "distributions"
/ "demo-0.1.0.tar.gz",
)
dependency.extras.append("foo")
package = provider.search_for_file(dependency)[0]
assert package.name == "demo"
assert package.versi... | assert package.requires == [get_dependency("pendulum", ">=1.4.4")]
assert package.extras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
def test_search_for_file_sdist_with_extras(provider):
| 64 | 64 | 162 | 12 | 52 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_file_sdist_with_extras | test_search_for_file_sdist_with_extras | 306 | 327 | 306 | 306 | e87d019f04b3b6a6729b04e5c216a50d7e82bc7a | bigcode/the-stack | train |
32171e767f71893ccadc0a24 | train | function | def test_search_for_file_wheel(provider):
dependency = FileDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "distributions"
/ "demo-0.1.0-py2.py3-none-any.whl",
)
package = provider.search_for_file(dependency)[0]
assert package.name == "demo"
... | def test_search_for_file_wheel(provider):
| dependency = FileDependency(
"demo",
Path(__file__).parent.parent
/ "fixtures"
/ "distributions"
/ "demo-0.1.0-py2.py3-none-any.whl",
)
package = provider.search_for_file(dependency)[0]
assert package.name == "demo"
assert package.version.text == "0.1.0"
... | pendulum", ">=1.4.4"),
get_dependency("cleo", optional=True),
]
assert package.extras == {
"foo": [get_dependency("cleo")],
"bar": [get_dependency("tomlkit")],
}
def test_search_for_file_wheel(provider):
| 64 | 64 | 146 | 9 | 55 | mgasner/poetry | tests/puzzle/test_provider.py | Python | test_search_for_file_wheel | test_search_for_file_wheel | 330 | 347 | 330 | 330 | 4e27b4a05a54fdf6e2686c981099fb9a3a5cd819 | bigcode/the-stack | train |
9324800af06629fc80ea35cc | train | class | class MockEnv(BaseMockEnv):
def run(self, bin, *args):
raise EnvCommandError(CalledProcessError(1, "python", output=""))
| class MockEnv(BaseMockEnv):
| def run(self, bin, *args):
raise EnvCommandError(CalledProcessError(1, "python", output=""))
| .repositories.repository import Repository
from poetry.utils._compat import PY35
from poetry.utils._compat import Path
from poetry.utils.env import EnvCommandError
from poetry.utils.env import MockEnv as BaseMockEnv
from tests.helpers import get_dependency
from subprocess import CalledProcessError
class MockEnv(BaseM... | 64 | 64 | 35 | 7 | 56 | mgasner/poetry | tests/puzzle/test_provider.py | Python | MockEnv | MockEnv | 22 | 24 | 22 | 22 | 1e8cf77ce3ec26cc5d78bb37b6983df5261c2ddd | bigcode/the-stack | train |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.