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Mass COM calculation #686

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1206092
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richardjgowers Jan 31, 2016
62fdf99
Using memory views instead
richardjgowers Jan 31, 2016
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29 changes: 29 additions & 0 deletions package/MDAnalysis/lib/trans.pyx
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Original file line number Diff line number Diff line change
@@ -0,0 +1,29 @@
import numpy as np
cimport cython
cimport numpy as np


@cython.boundscheck(False)
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@hainm hainm Jan 31, 2016

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you can turn this off globally in setup.py file. check my pytraj's one

https://github.com/Amber-MD/pytraj/blob/master/setup.py#L327-L347

@cython.wraparound(False)
def residue_positions(
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@kain88-de kain88-de Jan 31, 2016

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a doc string would be nice.

float[:, :] coords not None,
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@kain88-de kain88-de Jan 31, 2016

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You can tell the compiler how the array is stored (Row or Column Major). That can be done by giving it the strides directly float[:, ::1 is row major for example the C/Python standard. That should give a small boost but requires that the given arrays follow that memory layout.

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@kain88-de kain88-de Jan 31, 2016

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I would keep your current version as this is less pain for someone who uses the function.

long[:] indices not None):
cdef Py_ssize_t i, j, k
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@kain88-de kain88-de Jan 31, 2016

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I usually use just int here as type.


cdef int n_items = indices.shape[0]
cdef int n_res = np.unique(indices).shape[0]

cdef long[:] counter = np.zeros(n_res, dtype=np.int64)
cdef float[:, :] output = np.zeros((n_res, 3), dtype=np.float32)

for i in range(n_items):
j = indices[i]
for k in range(3):
output[j, k] += coords[i, k]
counter[j] += 1

for i in range(n_res):
for k in range(3):
output[i, k] /= counter[i]

return np.asarray(output)
5 changes: 4 additions & 1 deletion package/setup.py
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Expand Up @@ -310,9 +310,12 @@ def extensions(config):
util = MDAExtension('lib.formats.cython_util',
sources=['MDAnalysis/lib/formats/cython_util.pyx'],
include_dirs=include_dirs)
trans = MDAExtension('lib.trans',
sources=['MDAnalysis/lib/trans.pyx'],
include_dirs=include_dirs)

extensions = [dcd, dcd_time, distances, distances_omp, qcprot,
transformation, xdrlib, util]
transformation, xdrlib, util, trans]
if use_cython:
extensions = cythonize(extensions)
return extensions
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