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/// <reference path="../ext/jquery-1.12.4.js" /> | |
/// <reference path="../ext/jquery-ui-1.12.1.js" /> | |
"use strict"; | |
function BlobLine(element, options) { | |
element = $(element); | |
this.numBlobs = options.numBlobs; | |
this.blobWidth = options.blobWidth; | |
this.blobHeight = options.blobHeight; |
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2 | |
view 227 ns ± 8.56 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) | |
array_copy_view 582 ns ± 37.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) | |
array_int_index 1.38 µs ± 33.9 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) | |
array_bool_index 1.85 µs ± 111 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) | |
array_delete 5.45 µs ± 43.9 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) | |
array_resize 7.8 µs ± 179 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) | |
8 | |
view 226 ns ± 8.13 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) | |
array_copy_view 558 ns ± 17.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each) |
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Names: | |
MSeifert | |
MSeifert2 | |
original1 | |
original2 | |
Coldspeed1 | |
Coldspeed2 | |
Chris_Rands | |
EvKounis | |
schumich |
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import timeit | |
timeit.timeit( | |
"""print('numpy' in sys.modules) | |
import numpy""", "import sys", number=3) | |
# False | |
# True | |
# True | |
# 0.3159413684456874 |
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a = 99 | |
if a == 1: | |
pass | |
elif a == 1: | |
pass | |
elif a == 2: | |
pass | |
elif a == 3: | |
pass |
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import line_profiler | |
def foo(): | |
for i in range(10000): | |
a = i**i | |
if i % 1000 == 0: | |
print(i) | |
lp = line_profiler.LineProfiler() | |
lp.add_function(foo) |
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from collections import Mapping | |
cls = Mapping | |
subclass = dict | |
for scls in cls.__subclasses__(): | |
if issubclass(subclass, scls): | |
cls._abc_cache.add(subclass) | |
print('found', scls) | |
break |
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from astropy.io import fits | |
import numpy as np | |
hdul = fits.HDUList(fits.PrimaryHDU(np.random.random((10, 10)))) | |
hdul.writeto('tmp1.fits', overwrite=True) | |
from __future__ import division | |
import numpy as np | |
obj1 = fits.open('tmp1.fits') | |
data_obj1 = obj1[0].data |
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def double_evens1(inp): | |
for item in inp: | |
if not item % 2: | |
yield item | |
yield item | |
def double_evens2(inp): | |
for item in inp: | |
if not item % 2: | |
yield item |
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import timeit | |
def f_range(n): | |
for i in range(n): | |
pass | |
def f_xrange(n): | |
for i in xrange(n): | |
pass | |
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