Here is the output of the same function rewritten using an iterator on the
a MultiPoint object rather than creating each Point object:
Tue Sep 3 14:51:46 2013 restats
148634517 function calls (148605205 primitive calls) in 273.772
seconds
Ordered by: internal time
List reduced from 1869 to 40 due to restriction <40>
ncalls tottime percall cumtime percall filename:lineno(function)
7518198 137.685 0.000 187.778 0.000 predicates.py:8(__call__)
7518198 17.106 0.000 17.106 0.000 base.py:24(geometry_type_name)
1253033 15.604 0.000 18.043 0.000
point.py:170(geos_point_from_py)
7518198 14.405 0.000 204.416 0.000 base.py:447(intersects)
8011 12.041 0.002 268.612 0.034
shapely_intersects.py:28(shape_function)
15042841 11.606 0.000 45.573 0.000 topology.py:14(_validate)
8771251 7.613 0.000 10.888 0.000 collections.py:119(itervalues)
1253033 6.750 0.000 11.462 0.000 base.py:588(_get_geom_item)
37623215 5.981 0.000 5.981 0.000 base.py:162(_get_geom)
8778104 5.789 0.000 33.026 0.000 {hasattr}
7518198 5.584 0.000 23.819 0.000 base.py:242(geometryType)
6445 4.689 0.001 25.740 0.004
multipoint.py:131(geos_multipoint_from_py)
7518198 3.416 0.000 27.235 0.000 base.py:245(type)
8771313 3.275 0.000 3.275 0.000 collections.py:72(__iter__)
1259478 2.822 0.000 2.822 0.000 __init__.py:501(cast)
7524643 2.313 0.000 2.313 0.000
geos.py:185(errcheck_predicate)
7524643 2.237 0.000 2.237 0.000 impl.py:43(__getitem__)
2518960 1.739 0.000 1.756 0.000 base.py:131(empty)
1253033 1.615 0.000 1.831 0.000 point.py:38(__init__)
1253033 1.357 0.000 3.187 0.000
multipoint.py:55(shape_factory)
16038 1.267 0.000 2.065 0.000
oilmdl_reader.py:218(stream_record_blocks)
1259484 1.013 0.000 1.552 0.000 base.py:164(_set_geom)
1259478 1.012 0.000 12.509 0.000 base.py:596(__iter__)
1259476/1253032 0.885 0.000 2.103 0.000 base.py:141(__del__)
43347 0.881 0.000 0.881 0.000 {method 'reduce' of
'numpy.ufunc' objects}
6445 0.733 0.000 0.733 0.000 {sum}
1259478 0.636 0.000 2.432 0.000 coords.py:17(required)
16040 0.609 0.000 0.609 0.000 {method 'read' of 'file'
objects}
8028 0.428 0.000 1.224 0.000 util.py:113(extents_coroutine)
2577031/2576733 0.415 0.000 0.415 0.000 {len}
8010 0.309 0.000 0.309 0.000 grids.py:79(indexof)
6445 0.244 0.000 0.244 0.000 {method 'dot' of
'numpy.ndarray' objects}
1 0.218 0.218 0.218 0.218 parallel.py:1(<module>)
6446 0.120 0.000 0.343 0.000
polygon_counter_op.py:17(polygon_counter_op)
6446 0.110 0.000 0.353 0.000
polygon_mass_op.py:17(polygon_mass_op)
8011 0.103 0.000 1.230 0.000
bin_grid_mapper.py:20(grid_function)
32040 0.077 0.000 0.077 0.000
{numpy.core.multiarray.frombuffer}
28886 0.073 0.000 0.073 0.000 {abs}
6445 0.062 0.000 25.829 0.004 multipoint.py:28(__init__)
8011 0.060 0.000 0.795 0.000
shore_oil_stats_op.py:27(shore_oil_stats_op)
On Fri, Aug 30, 2013 at 4:10 PM, David Stuebe <[email protected]> wrote:
>
>
> Hi GisPython
>
> I am new to using shapley.
>
> I have a few polygons and I am interested in finding out about which of
> some millions of points intersect those polygons.
>
> I only need to create the polygons once - there are dozens at most, but
> creating millions of point objects is killing my performance big time!
>
> Here is some cprofile output from a test run:
>
> 159616551 function calls (159601695 primitive calls) in 307.189
> seconds
>
> Ordered by: internal time
> List reduced from 1844 to 20 due to restriction <20>
>
> ncalls tottime percall cumtime percall filename:lineno(function)
> 7518198 135.451 0.000 185.103 0.000 predicates.py:8(__call__)
> 1253033 22.242 0.000 51.047 0.000
> point.py:170(geos_point_from_py)
> 7518198 16.698 0.000 16.698 0.000
> base.py:24(geometry_type_name)
> 8011 16.586 0.002 302.903 0.038
> shapely_intersects.py:26(shape_function)
> 7518198 14.399 0.000 201.687 0.000 base.py:447(intersects)
> 8771627 11.716 0.000 38.436 0.000 {hasattr}
> 15036396 11.607 0.000 45.146 0.000 topology.py:14(_validate)
> 8771241 7.834 0.000 11.235 0.000
> collections.py:119(itervalues)
> 3759104 7.515 0.000 10.693 0.000 base.py:131(empty)
> 1253033 7.092 0.000 12.961 0.000 numeric.py:446(require)
> 1253033 5.791 0.000 63.158 0.000 point.py:105(_set_coords)
> 37590990 5.679 0.000 5.679 0.000 base.py:162(_get_geom)
> 7518198 5.659 0.000 23.459 0.000 base.py:242(geometryType)
> 1253033 4.999 0.000 4.999 0.000 __init__.py:501(cast)
> 8771283 3.401 0.000 3.401 0.000 collections.py:72(__iter__)
> 7518198 3.260 0.000 26.719 0.000 base.py:245(type)
> 3759104 3.178 0.000 3.178 0.000 base.py:124(_is_empty)
> 1253033 2.874 0.000 66.251 0.000 point.py:38(__init__)
> 1253033 2.835 0.000 23.231 0.000 coords.py:17(required)
> 1253036 2.689 0.000 2.689 0.000 {method 'copy' of
> 'numpy.ndarray' objects}
>
> Would it be possible to pool the point objects and just change out the
> lat/lon location of the point object before every call to intersects?
>
> Here is a code except -
>
> blen = len(block)
>
> particle_position = block['loc'] # a (n,2) array of lat/lon
>
> spillets_in_shapes = numpy.zeros((blen, slen),dtype='bool')
>
> for i, pos in enumerate(particle_position):
> p = Point(pos)
> for j,shape in enumerate(shapes.itervalues()):
> if shape.intersects(p):
> spillets_in_shapes[i,j] = True
>
>
> This code is called many times for each block of particles that I have to
> process.
>
> It seems most of my time is spent in initializing point objects and in
> something called predicates.py?
>
> Any suggestions for optimization?
>
> David
>
>
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