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November 24, 2016 15:41
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· Running 32 total benchmarks (1 commits * 1 environments * 32 benchmarks) | |
[ 0.00%] ·· Building for existing-py_home_sourav_miniconda2_bin_python | |
[ 0.00%] ·· Benchmarking existing-py_home_sourav_miniconda2_bin_python | |
[ 3.12%] ··· Running sparse.Arithmetic.time_arithmetic ok | |
[ 3.12%] ···· | |
======== ==== ========= ========= ========== ========= | |
-- op | |
------------- ---------------------------------------- | |
format XY __add__ __sub__ multiply __mul__ | |
======== ==== ========= ========= ========== ========= | |
csr AA 2.93ms 2.74ms 2.98ms 10.96ms | |
csr AB 5.54ms 5.52ms 6.37ms 22.66ms | |
csr BA 6.39ms 5.72ms 6.41ms 24.70ms | |
csr BB 6.75ms 6.00ms 6.86ms 56.07ms | |
======== ==== ========= ========= ========== ========= | |
[ 6.25%] ··· Running sparse.Construction.time_construction ok | |
[ 6.25%] ···· | |
============ ========== ========== | |
-- format | |
------------ --------------------- | |
matrix lil dok | |
============ ========== ========== | |
Empty 5.52ms 25.64μs | |
Identity 86.33ms 365.98ms | |
Poisson5pt 412.62ms 1.92s | |
============ ========== ========== | |
[ 9.38%] ··· Running sparse.Conversion.time_conversion ok | |
[ 9.38%] ···· | |
============= ========== ========== ========== ========== ========== ========== | |
-- to_format | |
------------- ----------------------------------------------------------------- | |
from_format csr csc coo dia lil dok | |
============= ========== ========== ========== ========== ========== ========== | |
csr 530.77ns 346.32μs 469.19μs 9.72ms 20.94ms 37.88ms | |
csc 329.55μs 518.22ns 501.47μs 10.28ms 21.20ms 39.18ms | |
coo 486.90μs 493.18μs 514.17ns 1.96ms 22.72ms 31.26ms | |
dia 2.13ms 1.31ms 1.57ms 514.13ns 23.76ms 32.21ms | |
lil 12.02ms 11.19ms 12.67ms 22.02ms 513.02ns 49.22ms | |
dok 54.31ms 52.92ms 51.46ms 55.73ms 71.79ms 517.31ns | |
============= ========== ========== ========== ========== ========== ========== | |
[ 12.50%] ··· Running sparse.Diagonal.time_diagonal ok | |
[ 12.50%] ···· | |
========= ========== ========== ========== ========= ========== ======== | |
-- format | |
--------- -------------------------------------------------------------- | |
density csr csc coo lil dok dia | |
========= ========== ========== ========== ========= ========== ======== | |
0.01 24.31μs 24.63μs 61.26μs 1.53ms 6.41ms 9.18μs | |
0.1 108.18μs 97.14μs 222.05μs 14.29ms 104.92ms 9.59μs | |
0.5 420.26μs 423.36μs 1.03ms 64.06ms n/a 9.79μs | |
========= ========== ========== ========== ========= ========== ======== | |
[ 12.50%] ····· | |
For parameters: 0.01, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1801 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1810 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1792 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.1, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1982 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1980 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1981 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.5, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1998 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1997 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
[ 15.62%] ··· Running sparse.Getset.time_fancy_getitem ok | |
[ 15.62%] ···· | |
======= ================== ========== ========== ========== ========== | |
-- format | |
-------------------------- ------------------------------------------- | |
N sparsity pattern csr csc lil dok | |
======= ================== ========== ========== ========== ========== | |
1 different 36.22μs 123.95μs 5.56μs 16.46μs | |
1 same 37.36μs 123.40μs 5.86μs 16.38μs | |
10 different 93.99μs 185.18μs 101.75μs 110.73μs | |
10 same 95.12μs 182.48μs 98.49μs 108.57μs | |
100 different 97.03μs 183.73μs 101.81μs 185.72μs | |
100 same 95.45μs 182.98μs 100.37μs 187.69μs | |
1000 different 109.26μs 198.06μs 125.97μs n/a | |
1000 same 109.13μs 193.32μs 127.36μs n/a | |
10000 different 191.02μs 281.38μs 347.88μs n/a | |
10000 same 193.88μs 284.41μs 376.56μs n/a | |
======= ================== ========== ========== ========== ========== | |
[ 18.75%] ··· Running sparse.Getset.track_fancy_setitem ok | |
[ 18.75%] ···· | |
======= ================== ========== ========== ========== ========== | |
-- format | |
-------------------------- ------------------------------------------- | |
N sparsity pattern csr csc lil dok | |
======= ================== ========== ========== ========== ========== | |
1 different 380.04μs 367.88μs 19.07μs 17.88μs | |
1 same 123.02μs 115.87μs 6.39μs 16.93μs | |
10 different 553.85μs 539.78μs 116.11μs 113.01μs | |
10 same 118.02μs 120.88μs 85.83μs 113.01μs | |
100 different 2.15ms 2.22ms 128.03μs 136.85μs | |
100 same 120.88μs 120.88μs 92.03μs 141.86μs | |
1000 different 12.80ms 12.87ms 248.19μs n/a | |
1000 same 146.87μs 150.20μs 171.90μs n/a | |
10000 different 23.40ms 23.00ms 1.87ms n/a | |
10000 same 564.10μs 581.98μs 1.37ms n/a | |
======= ================== ========== ========== ========== ========== | |
[ 21.88%] ··· Running sparse.Matmul.time_large failed | |
[ 21.88%] ····· Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 231, in setup | |
matrix2 = lil_matrix(zeros((H2, W2))) | |
MemoryError | |
[ 25.00%] ··· Running sparse.Matvec.time_matvec ok | |
[ 25.00%] ···· | |
============ ========== ========== ========== ========== ========= ========= ========= | |
-- format | |
------------ ------------------------------------------------------------------------- | |
matrix dia csr csc dok lil coo bsr | |
============ ========== ========== ========== ========== ========= ========= ========= | |
Identity 25.77μs 41.00μs 38.44μs n/a n/a 33.80μs 42.95μs | |
Poisson5pt 674.60μs 896.62μs 989.46μs 359.54ms 91.60ms 1.12ms 1.20ms | |
Block2x2 n/a 1.01ms n/a n/a n/a n/a 1.09ms | |
Block3x3 n/a 723.26μs n/a n/a n/a n/a 1.02ms | |
============ ========== ========== ========== ========== ========= ========= ========= | |
[ 28.12%] ··· Running sparse.Matvec.time_matvec_inplace_1_0 ok | |
[ 28.12%] ···· | |
============ ========== ========== ========== ======== ======= ========= ========== | |
-- format | |
------------ ---------------------------------------------------------------------- | |
matrix dia csr csc dok lil coo bsr | |
============ ========== ========== ========== ======== ======= ========= ========== | |
Identity 18.10μs 43.09μs 33.71μs n/a n/a 26.34μs 27.76μs | |
Poisson5pt 615.61μs 823.72μs 967.02μs 16.77s 2.54s 1.05ms 815.20μs | |
Block2x2 n/a 646.27μs n/a n/a n/a n/a 979.13μs | |
Block3x3 n/a 597.64μs n/a n/a n/a n/a 701.90μs | |
============ ========== ========== ========== ======== ======= ========= ========== | |
[ 31.25%] ··· Running sparse.Matvec.time_matvec_inplace_1_1 ok | |
[ 31.25%] ···· | |
============ ========== ========== ========== ======== ======= ========= ========== | |
-- format | |
------------ ---------------------------------------------------------------------- | |
matrix dia csr csc dok lil coo bsr | |
============ ========== ========== ========== ======== ======= ========= ========== | |
Identity 14.17μs 30.56μs 28.34μs n/a n/a 23.63μs 31.78μs | |
Poisson5pt 605.70μs 848.28μs 952.88μs 17.11s 2.85s 1.10ms 963.01μs | |
Block2x2 n/a 735.96μs n/a n/a n/a n/a 971.03μs | |
Block3x3 n/a 714.06μs n/a n/a n/a n/a 723.88μs | |
============ ========== ========== ========== ======== ======= ========= ========== | |
[ 34.38%] ··· Running sparse.Matvec.time_matvec_inplace_2_3 ok | |
[ 34.38%] ···· | |
============ ========== ========== ========= ======== ======= ========= ========== | |
-- format | |
------------ --------------------------------------------------------------------- | |
matrix dia csr csc dok lil coo bsr | |
============ ========== ========== ========= ======== ======= ========= ========== | |
Identity 14.58μs 31.12μs 32.77μs n/a n/a 28.70μs 32.28μs | |
Poisson5pt 639.34μs 848.85μs 1.02ms 16.42s 2.57s 1.03ms 836.54μs | |
Block2x2 n/a 660.61μs n/a n/a n/a n/a 983.76μs | |
Block3x3 n/a 631.31μs n/a n/a n/a n/a 706.08μs | |
============ ========== ========== ========= ======== ======= ========= ========== | |
[ 37.50%] ··· Running sparse.Matvecs.time_matvecs ok | |
[ 37.50%] ···· | |
======== ======== | |
format | |
-------- -------- | |
csr 6.15ms | |
csc 8.32ms | |
bsr 7.56ms | |
======== ======== | |
[ 40.62%] ··· Running sparse.Matvecs.time_matvecs_inplace_1_0 failed | |
[ 40.62%] ···· | |
======== ======== | |
format | |
-------- -------- | |
csr failed | |
csc failed | |
bsr failed | |
======== ======== | |
[ 40.62%] ····· | |
For parameters: 'csr' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 209, in time_matvecs_inplace_1_0 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
For parameters: 'csc' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 209, in time_matvecs_inplace_1_0 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
For parameters: 'bsr' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 209, in time_matvecs_inplace_1_0 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
[ 43.75%] ··· Running sparse.Matvecs.time_matvecs_inplace_1_1 failed | |
[ 43.75%] ···· | |
======== ======== | |
format | |
-------- -------- | |
csr failed | |
csc failed | |
bsr failed | |
======== ======== | |
[ 43.75%] ····· | |
For parameters: 'csr' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 213, in time_matvecs_inplace_1_1 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
For parameters: 'csc' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 213, in time_matvecs_inplace_1_1 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
For parameters: 'bsr' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 213, in time_matvecs_inplace_1_1 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
[ 46.88%] ··· Running sparse.Matvecs.time_matvecs_inplace_2_3 failed | |
[ 46.88%] ···· | |
======== ======== | |
format | |
-------- -------- | |
csr failed | |
csc failed | |
bsr failed | |
======== ======== | |
[ 46.88%] ····· | |
For parameters: 'csr' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 217, in time_matvecs_inplace_2_3 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
For parameters: 'csc' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 217, in time_matvecs_inplace_2_3 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
For parameters: 'bsr' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 772, in main_run | |
result = benchmark.do_run() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 456, in do_run | |
return self.run(*self._current_params) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 531, in run | |
timing = timer.timeit(number) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 202, in timeit | |
timing = self.inner(it, self.timer) | |
File "/home/sourav/miniconda2/lib/python2.7/timeit.py", line 100, in inner | |
_func() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 512, in <lambda> | |
func = lambda: self.func(*param) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 217, in time_matvecs_inplace_2_3 | |
A = self.matrices[fmt] | |
AttributeError: 'Matvecs' object has no attribute 'matrices' | |
[ 50.00%] ··· Running sparse.NullSlice.time_10000_rows 3/6 failed | |
[ 50.00%] ···· | |
========= ======== ======== ========= | |
-- format | |
--------- --------------------------- | |
density csr csc lil | |
========= ======== ======== ========= | |
0.05 failed failed failed | |
0.01 1.39ms 8.24ms 19.16ms | |
========= ======== ======== ========= | |
[ 50.00%] ····· | |
For parameters: 0.05, 'csr' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'csc' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'lil' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 370, in setup | |
self.X = sparse.rand(n, k, format=format, density=density) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 795, in rand | |
return random(m, n, density, format, dtype, random_state) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 768, in random | |
return coo_matrix((vals, (i, j)), shape=(m, n)).asformat(format) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 254, in asformat | |
return getattr(self, 'to' + format)() | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 758, in tolil | |
return self.tocsr(copy=False).tolil(copy=copy) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/csr.py", line 157, in tolil | |
data[n] = dat[start:end].tolist() | |
MemoryError | |
[ 53.12%] ··· Running sparse.NullSlice.time_100_cols 3/6 failed | |
[ 53.12%] ···· | |
========= ======== ======== ========== | |
-- format | |
--------- ---------------------------- | |
density csr csc lil | |
========= ======== ======== ========== | |
0.05 failed failed failed | |
0.01 8.88ms 2.58ms 582.52ms | |
========= ======== ======== ========== | |
[ 53.12%] ····· | |
For parameters: 0.05, 'csr' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'csc' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'lil' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 370, in setup | |
self.X = sparse.rand(n, k, format=format, density=density) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 795, in rand | |
return random(m, n, density, format, dtype, random_state) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 768, in random | |
return coo_matrix((vals, (i, j)), shape=(m, n)).asformat(format) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 254, in asformat | |
return getattr(self, 'to' + format)() | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 758, in tolil | |
return self.tocsr(copy=False).tolil(copy=copy) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/csr.py", line 157, in tolil | |
data[n] = dat[start:end].tolist() | |
MemoryError | |
[ 56.25%] ··· Running sparse.NullSlice.time_3_cols 3/6 failed | |
[ 56.25%] ···· | |
========= ======== ========== ========== | |
-- format | |
--------- ------------------------------ | |
density csr csc lil | |
========= ======== ========== ========== | |
0.05 failed failed failed | |
0.01 6.82ms 676.19μs 112.40ms | |
========= ======== ========== ========== | |
[ 56.25%] ····· | |
For parameters: 0.05, 'csr' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'csc' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'lil' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 370, in setup | |
self.X = sparse.rand(n, k, format=format, density=density) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 795, in rand | |
return random(m, n, density, format, dtype, random_state) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 768, in random | |
return coo_matrix((vals, (i, j)), shape=(m, n)).asformat(format) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 254, in asformat | |
return getattr(self, 'to' + format)() | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 758, in tolil | |
return self.tocsr(copy=False).tolil(copy=copy) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/csr.py", line 157, in tolil | |
data[n] = dat[start:end].tolist() | |
MemoryError | |
[ 59.38%] ··· Running sparse.NullSlice.time_3_rows 3/6 failed | |
[ 59.38%] ···· | |
========= ========== ======== ========= | |
-- format | |
--------- ----------------------------- | |
density csr csc lil | |
========= ========== ======== ========= | |
0.05 failed failed failed | |
0.01 351.20μs 6.01ms 84.90μs | |
========= ========== ======== ========= | |
[ 59.38%] ····· | |
For parameters: 0.05, 'csr' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'csc' | |
asv: benchmark timed out (timeout 60.0s) | |
For parameters: 0.05, 'lil' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse.py", line 370, in setup | |
self.X = sparse.rand(n, k, format=format, density=density) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 795, in rand | |
return random(m, n, density, format, dtype, random_state) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/construct.py", line 768, in random | |
return coo_matrix((vals, (i, j)), shape=(m, n)).asformat(format) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 254, in asformat | |
return getattr(self, 'to' + format)() | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/base.py", line 758, in tolil | |
return self.tocsr(copy=False).tolil(copy=copy) | |
File "/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/csr.py", line 157, in tolil | |
data[n] = dat[start:end].tolist() | |
MemoryError | |
[ 62.50%] ··· Running sparse.Sort.time_sort ok | |
[ 62.50%] ···· | |
========= ========= | |
matrix | |
--------- --------- | |
Rand10 1.11μs | |
Rand25 1.07μs | |
Rand50 1.07μs | |
Rand100 1.07μs | |
Rand200 33.72ms | |
========= ========= | |
[ 65.62%] ··· Running sparse.Sum.time_sum ok | |
[ 65.62%] ···· | |
========= ========== ========== ========== ========= ========= ======== | |
-- format | |
--------- ------------------------------------------------------------- | |
density csr csc coo lil dok dia | |
========= ========== ========== ========== ========= ========= ======== | |
0.01 107.57μs 103.74μs 84.05μs 1.59ms 6.79ms 1.21ms | |
0.1 201.88μs 246.78μs 237.08μs 14.71ms 73.77ms 1.27ms | |
0.5 816.41μs 1.01ms 1.08ms 64.26ms n/a 1.53ms | |
========= ========== ========== ========== ========= ========= ======== | |
[ 65.62%] ····· | |
For parameters: 0.01, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1801 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1810 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1792 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.1, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1982 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1980 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1981 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.5, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1998 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1997 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
[ 68.75%] ··· Running sparse.Sum.time_sum_axis0 ok | |
[ 68.75%] ···· | |
========= ========== ========== ========== ========== ========== ========= | |
-- format | |
--------- ---------------------------------------------------------------- | |
density csr csc coo lil dok dia | |
========= ========== ========== ========== ========== ========== ========= | |
0.01 278.10μs 96.58μs 242.52μs 6.52ms 406.71ms 26.47ms | |
0.1 396.74μs 141.65μs 872.40μs 37.84ms 3.75s 18.73ms | |
0.5 1.16ms 475.39μs 3.69ms 175.02ms n/a 19.45ms | |
========= ========== ========== ========== ========== ========== ========= | |
[ 68.75%] ····· | |
For parameters: 0.01, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1801 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1810 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1792 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.1, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1982 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1980 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1981 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.5, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1998 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1997 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
[ 71.88%] ··· Running sparse.Sum.time_sum_axis1 ok | |
[ 71.88%] ···· | |
========= ========== ========== ========== ========= ========= ======== | |
-- format | |
--------- ------------------------------------------------------------- | |
density csr csc coo lil dok dia | |
========= ========== ========== ========== ========= ========= ======== | |
0.01 99.23μs 99.23μs 87.11μs 1.82ms 6.88ms 1.23ms | |
0.1 135.73μs 237.64μs 235.32μs 13.73ms 73.42ms 1.26ms | |
0.5 459.19μs 919.20μs 950.93μs 60.79ms n/a 1.16ms | |
========= ========== ========== ========== ========= ========= ======== | |
[ 71.88%] ····· | |
For parameters: 0.01, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1801 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1810 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1792 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.1, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1982 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1980 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1981 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
For parameters: 0.5, 'dia' | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1998 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
/home/sourav/scipy/build/testenv/lib/python2.7/site-packages/scipy/sparse/coo.py:359: SparseEfficiencyWarning: Constructing a DIA matrix with 1997 diagonals is inefficient | |
"is inefficient" % len(diags), SparseEfficiencyWarning) | |
[ 75.00%] ··· Running sparse_csgraph.Laplacian.time_laplacian ok | |
[ 75.00%] ···· | |
===== ======== ========== ========== | |
-- normed | |
-------------- --------------------- | |
n format True False | |
===== ======== ========== ========== | |
30 dense 56.09μs 21.79μs | |
30 coo 350.83μs 313.56μs | |
30 csc 248.58μs 213.56μs | |
30 csr 350.05μs 308.34μs | |
30 dia 325.36μs 177.90μs | |
300 dense 563.47μs 177.60μs | |
300 coo 463.76μs 366.49μs | |
300 csc 341.95μs 282.80μs | |
300 csr 468.02μs 378.14μs | |
300 dia 588.34μs 221.08μs | |
900 dense 6.29ms 3.28ms | |
900 coo 614.70μs 456.11μs | |
900 csc 535.55μs 382.68μs | |
900 csr 622.84μs 468.63μs | |
900 dia 1.10ms 308.10μs | |
===== ======== ========== ========== | |
[ 78.12%] ··· Running sparse_linalg_expm.Expm.time_expm ok | |
[ 78.12%] ···· | |
===== ========== ========== | |
-- format | |
----- --------------------- | |
n sparse dense | |
===== ========== ========== | |
30 21.03ms 737.10μs | |
100 66.85ms 8.90ms | |
300 481.77ms 198.12ms | |
===== ========== ========== | |
[ 81.25%] ··· Running sparse_linalg_expm.ExpmMultiply.time_expm_multiply ok | |
[ 81.25%] ···· | |
============ ========= | |
run format | |
------------ --------- | |
sparse 13.36ms | |
full 59.51s | |
============ ========= | |
[ 84.38%] ··· Running sparse_linalg_lobpcg.Bench.time_mikota ok | |
[ 84.38%] ···· | |
====== ========== ========== | |
-- solver | |
------ --------------------- | |
n lobpcg eigh | |
====== ========== ========== | |
128 26.37ms 5.61ms | |
256 60.80ms 36.11ms | |
512 204.74ms 251.08ms | |
1024 1.04s 1.94s | |
2048 6.33s 15.10s | |
====== ========== ========== | |
[ 87.50%] ··· Running sparse_linalg_lobpcg.Bench.time_sakurai ok | |
[ 87.50%] ···· | |
====== ========== ========== | |
-- solver | |
------ --------------------- | |
n lobpcg eigh | |
====== ========== ========== | |
50 53.04ms 623.91μs | |
400 565.80ms 222.01ms | |
2400 1.63s 45.62s | |
====== ========== ========== | |
[ 90.62%] ··· Running sparse_linalg_onenormest.BenchmarkOneNormEst.time_onenormest 2/24 failed | |
[ 90.62%] ···· | |
=========== ========== ============ | |
-- solver | |
----------- ----------------------- | |
n exact onenormest | |
=========== ========== ============ | |
2 2.19ms 4.61ms | |
3 2.27ms 46.33ms | |
5 2.18ms 45.71ms | |
10 2.27ms 46.89ms | |
30 3.18ms 47.05ms | |
100 19.97ms 57.92ms | |
300 332.06ms 127.15ms | |
500 1.84s 283.93ms | |
1000 failed failed | |
10000.0 n/a 2.60ms | |
100000.0 n/a 50.70ms | |
1000000.0 n/a 328.50ms | |
=========== ========== ============ | |
[ 90.62%] ····· | |
For parameters: 1000, 'exact' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse_linalg_onenormest.py", line 32, in setup | |
M = np.random.randn(*shape) | |
File "mtrand.pyx", line 1680, in mtrand.RandomState.randn (numpy/random/mtrand/mtrand.c:17791) | |
File "mtrand.pyx", line 1810, in mtrand.RandomState.standard_normal (numpy/random/mtrand/mtrand.c:18258) | |
File "mtrand.pyx", line 163, in mtrand.cont0_array (numpy/random/mtrand/mtrand.c:2204) | |
MemoryError | |
For parameters: 1000, 'onenormest' | |
Traceback (most recent call last): | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 795, in <module> | |
commands[mode](args) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 766, in main_run | |
skip = benchmark.do_setup() | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 499, in do_setup | |
result = Benchmark.do_setup(self) | |
File "/home/sourav/miniconda2/lib/python2.7/site-packages/asv/benchmark.py", line 434, in do_setup | |
setup(*self._current_params) | |
File "/home/sourav/scipy/benchmarks/benchmarks/sparse_linalg_onenormest.py", line 32, in setup | |
M = np.random.randn(*shape) | |
File "mtrand.pyx", line 1680, in mtrand.RandomState.randn (numpy/random/mtrand/mtrand.c:17791) | |
File "mtrand.pyx", line 1810, in mtrand.RandomState.standard_normal (numpy/random/mtrand/mtrand.c:18258) | |
File "mtrand.pyx", line 163, in mtrand.cont0_array (numpy/random/mtrand/mtrand.c:2204) | |
MemoryError | |
[ 93.75%] ··· Running sparse_linalg_solve.Bench.time_solve ok | |
[ 93.75%] ···· | |
======= ========== ========== ========== ========== ========== | |
-- solver | |
------- ------------------------------------------------------ | |
(n,n) dense spsolve cg minres lgmres | |
======= ========== ========== ========== ========== ========== | |
4 79.21μs 81.83μs 263.02μs 358.88μs 502.23μs | |
6 141.36μs 104.33μs 432.53μs 660.30μs 760.73μs | |
10 1.33ms 331.23μs 770.26μs 1.18ms 1.55ms | |
16 21.59ms 808.02μs 1.36ms 2.02ms 2.87ms | |
25 n/a 2.51ms 2.55ms 3.29ms 9.58ms | |
40 n/a 8.60ms 5.69ms 5.51ms 21.69ms | |
64 n/a 34.19ms 15.00ms 11.66ms 56.64ms | |
100 n/a 118.94ms 48.90ms 28.46ms 196.65ms | |
======= ========== ========== ========== ========== ========== | |
[ 96.88%] ··· Running sparse_linalg_solve.Lgmres.time_inner ok | |
[ 96.88%] ···· | |
======= ========== ========== ========== ========== ========== | |
-- m | |
------- ------------------------------------------------------ | |
n 10 30 60 90 180 | |
======= ========== ========== ========== ========== ========== | |
10 451.13μs 435.68μs 380.48μs 366.35μs 368.92μs | |
50 894.45μs 881.95μs 988.17μs 904.44μs 895.64μs | |
100 1.11ms 1.29ms 1.28ms 1.29ms 1.31ms | |
1000 1.98ms 6.37ms 17.31ms 42.94ms 125.95ms | |
10000 23.23ms 78.07ms 194.35ms 371.28ms 1.04s | |
======= ========== ========== ========== ========== ========== | |
[100.00%] ··· Running spatial.Neighbors.time_sparse_distance_matrix ok | |
[100.00%] ···· | |
================== ===== ============== ========== ============ ========== =========== | |
-- boxsize / leafsize | |
--------------------------------------- ---------------------------------------------- | |
(m, n1, n2) p probe radius None / 8 None / 128 1.0 / 8 1.0 / 128 | |
================== ===== ============== ========== ============ ========== =========== | |
(3, 1000, 1000) 1 0.2 9.16ms 14.65ms 13.76ms 20.82ms | |
(3, 1000, 1000) 1 0.5 108.27ms 109.20ms 177.91ms 172.97ms | |
(3, 1000, 1000) 2 0.2 20.93ms 25.02ms 35.48ms 41.48ms | |
(3, 1000, 1000) 2 0.5 276.69ms 276.98ms 570.13ms 553.05ms | |
(3, 1000, 1000) inf 0.2 40.42ms 45.65ms 62.87ms 67.38ms | |
(3, 1000, 1000) inf 0.5 450.27ms 448.20ms 1.22s 1.21s | |
(8, 1000, 1000) 1 0.2 12.44ms 11.51ms 23.92ms 20.24ms | |
(8, 1000, 1000) 1 0.5 21.13ms 18.55ms 36.89ms 32.31ms | |
(8, 1000, 1000) 2 0.2 11.61ms 11.94ms 26.29ms 22.52ms | |
(8, 1000, 1000) 2 0.5 16.10ms 14.97ms 63.91ms 58.98ms | |
(8, 1000, 1000) inf 0.2 16.71ms 13.25ms 30.56ms 23.47ms | |
(8, 1000, 1000) inf 0.5 130.63ms 121.14ms 1.31s 1.31s | |
(16, 1000, 1000) 1 0.2 15.54ms 14.26ms 25.01ms 24.04ms | |
(16, 1000, 1000) 1 0.5 26.48ms 24.11ms 38.89ms 34.98ms | |
(16, 1000, 1000) 2 0.2 20.66ms 20.21ms 27.34ms 24.18ms | |
(16, 1000, 1000) 2 0.5 21.90ms 20.33ms 53.81ms 49.22ms | |
(16, 1000, 1000) inf 0.2 20.09ms 15.68ms 32.13ms 25.19ms | |
(16, 1000, 1000) inf 0.5 46.87ms 40.80ms 1.36s 1.32s | |
================== ===== ============== ========== ============ ========== =========== |
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