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Subject: Re: Bottleneck 0.6 release candidate 1
From: chrisspalm <chrissp...@gmail.com>
To: bottle-neck <bottle-neck@googlegroups.com>
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Here's the bench too on the same machine.

In [4]: bn.bench()
Bottleneck performance benchmark
    Bottleneck  0.6.0rc1
    Numpy (np)  1.6.1
    Scipy (sp)  0.9.0
    Speed is NumPy or SciPy time divided by Bottleneck time
    NaN means one-third NaNs; float64 and axis=1 are used
    High-level functions used (mode='fast')

                 no NaN     no NaN     no NaN      NaN
NaN        NaN
                (10,10)   (100,100) (1000,1000)  (10,10)   (100,100)
(1000,1000)
median            3.57       1.71       2.34       3.37
2.97       5.74
nanmedian        89.44      22.43       5.21      55.33
10.95       1.87
nansum            7.41       4.07       5.63       4.06
0.40       0.68
nanmax            1.64       1.16       1.01       1.43
1.09       1.07
nanmean          17.50       8.69       9.38       9.92
1.70       1.83
nanstd           24.90       6.43       9.11      10.66
1.02       1.31
nanargmax         5.94       3.86       6.58       3.51
0.44       0.69
ss                3.84       2.82       5.51       1.91
1.40       1.41
rankdata         23.56      17.00      13.55      12.55
8.63       5.36
partsort          1.16       1.81       2.40       2.60
3.49       6.68
argpartsort       0.62       1.78       2.01       2.10
3.41       6.30
replace           2.88       2.21       2.22       2.88
2.21       2.00
anynan            2.47       3.07       2.84       1.96
3.84      46.74
move_sum          8.58     100.22     623.85       5.32      48.87
495.47
move_nansum      20.11     112.98     683.94       9.58      12.79
118.75
move_mean         8.46      71.84     531.29       5.27      48.54
487.48
move_nanmean     21.71      81.16     563.07      10.88      12.03
108.60
move_std         10.49      24.87     222.32      13.43      88.00
818.85
move_nanstd      26.43      38.19     328.89      15.69      16.64
146.23
move_max          3.64      17.67     147.75       2.21      16.34
161.52
move_nanmax      14.47      20.61     163.93       7.34
6.91      62.78

Reference functions:
median         np.median
nanmedian      local copy of sp.stats.nanmedian
nansum         np.nansum
nanmax         np.nanmax
nanmean        local copy of sp.stats.nanmean
nanstd         local copy of sp.stats.nanstd
nanargmax      np.nanargmax
ss             scipy.stats.ss
rankdata       scipy.stats.rankdata based (axis support added)
partsort       np.sort, n=max(a.shape[1]/2,1)
argpartsort    np.argsort, n=max(a.shape[1]/2,1)
replace        np.putmask based (see bn.slow.replace)
anynan         np.isnan(arr).any(axis)
move_sum       sp.ndimage.convolve1d based, window=a.shape[1] // 5
move_nansum    sp.ndimage.convolve1d based, window=a.shape[1] // 5
move_mean      sp.ndimage.convolve1d based, window=a.shape[1] // 5
move_nanmean   sp.ndimage.convolve1d based, window=a.shape[1] // 5
move_std       sp.ndimage.convolve1d based, window=a.shape[1] // 5
move_nanstd    sp.ndimage.convolve1d based, window=a.shape[1] // 5
move_max       sp.ndimage.maximum_filter1d based, window=a.shape[1] //
5
move_nanmax    sp.ndimage.maximum_filter1d based, window=a.shape[1] //