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- Run on a LiDAR subset of 100000 points; eps=4.5, min_samples=100
- # OPTICS #
- 4000099 function calls in 329.232 seconds
- Ordered by: internal time
- ncalls tottime percall cumtime percall filename:lineno(function)
- 100001 271.306 0.003 279.411 0.003 {method 'query' of 'sklearn.neighbors.ball_tree.BinaryTree' objects}
- 100000 44.965 0.000 321.988 0.003 <ipython-input-2-16e5fd29397b>:144(_set_reach_dist)
- 1 1.951 1.951 1.951 1.951 {method 'query_radius' of 'sklearn.neighbors.ball_tree.BinaryTree' objects}
- 100002 1.420 0.000 8.105 0.000 validation.py:267(check_array)
- 9 1.104 0.123 323.132 35.904 <ipython-input-2-16e5fd29397b>:131(_expandClusterOrder)
- 100002 0.987 0.000 0.987 0.000 {method 'reduce' of 'numpy.ufunc' objects}
- 99991 0.869 0.000 0.869 0.000 {method 'argmin' of 'numpy.ndarray' objects}
- 300010 0.865 0.000 0.865 0.000 {numpy.core.multiarray.array}
- 100002 0.769 0.000 2.154 0.000 validation.py:45(_assert_all_finite)
- 100002 0.618 0.000 1.335 0.000 shape_base.py:60(atleast_2d)
- 300006 0.583 0.000 0.583 0.000 validation.py:155(<genexpr>)
- 100002 0.509 0.000 1.092 0.000 {method 'join' of 'str' objects}
- 400008 0.399 0.000 0.399 0.000 {hasattr}
- 100002 0.376 0.000 1.496 0.000 validation.py:128(_shape_repr)
- 300006 0.301 0.000 0.301 0.000 {isinstance}
- 100002 0.293 0.000 0.293 0.000 {getattr}
- 200005 0.275 0.000 0.791 0.000 numeric.py:464(asanyarray)
- 1 0.273 0.273 0.282 0.282 <ipython-input-2-16e5fd29397b>:30(__init__)
- 100002 0.255 0.000 0.525 0.000 validation.py:107(_num_samples)
- 100000 0.205 0.000 0.286 0.000 function_base.py:47(iterable)
- 99991 0.168 0.000 1.037 0.000 fromnumeric.py:946(argmin)
- 100002 0.129 0.000 1.223 0.000 {method 'sum' of 'numpy.ndarray' objects}
- 100002 0.107 0.000 1.094 0.000 _methods.py:31(_sum)
- 100002 0.100 0.000 0.143 0.000 base.py:865(isspmatrix)
- 1 0.094 0.094 0.094 0.094 <ipython-input-2-16e5fd29397b>:294(_ExtractDBSCAN)
- 600016 0.091 0.000 0.091 0.000 {len}
- 100000 0.081 0.000 0.081 0.000 {iter}
- 200003 0.074 0.000 0.074 0.000 {method 'append' of 'list' objects}
- 1 0.032 0.032 323.163 323.163 <ipython-input-2-16e5fd29397b>:103(_build_optics)
- 1 0.013 0.013 5.676 5.676 <ipython-input-2-16e5fd29397b>:56(_prep_optics)
- 1 0.010 0.010 329.232 329.232 <ipython-input-2-16e5fd29397b>:227(fit)
- 1 0.006 0.006 0.006 0.006 {max}
- 1 0.002 0.002 0.002 0.002 {range}
- 5 0.000 0.000 0.000 0.000 {numpy.core.multiarray.copyto}
- 1 0.000 0.000 329.232 329.232 <string>:1(<module>)
- 1 0.000 0.000 0.000 0.000 {numpy.core.multiarray.zeros}
- 5 0.000 0.000 0.000 0.000 {numpy.core.multiarray.empty}
- 5 0.000 0.000 0.000 0.000 numeric.py:141(ones)
- 2 0.000 0.000 0.001 0.000 numeric.py:394(asarray)
- 1 0.000 0.000 0.000 0.000 shape_base.py:8(atleast_1d)
- 1 0.000 0.000 0.000 0.000 {method 'reshape' of 'numpy.ndarray' objects}
- 1 0.000 0.000 0.000 0.000 {method 'get_arrays' of 'sklearn.neighbors.ball_tree.BinaryTree' objects}
- 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
- # DBSCAN Comparison #
- 100296 function calls in 131.351 seconds
- Ordered by: internal time
- ncalls tottime percall cumtime percall filename:lineno(function)
- 1 67.604 67.604 67.604 67.604 {sklearn.cluster._dbscan_inner.dbscan_inner}
- 1 59.786 59.786 59.787 59.787 {method 'query_radius' of 'sklearn.neighbors.kd_tree.BinaryTree' objects}
- 1 3.643 3.643 131.351 131.351 dbscan_.py:221(fit)
- 1 0.267 0.267 0.268 0.268 base.py:171(_fit)
- 1 0.027 0.027 127.706 127.706 dbscan_.py:24(dbscan)
- 100040 0.010 0.000 0.010 0.000 {len}
- 20 0.008 0.000 0.008 0.000 {numpy.core.multiarray.array}
- 1 0.003 0.003 0.003 0.003 {numpy.core.multiarray.where}
- 1 0.001 0.001 0.001 0.001 {method 'copy' of 'numpy.ndarray' objects}
- 5 0.001 0.000 0.001 0.000 {method 'reduce' of 'numpy.ufunc' objects}
- 1 0.000 0.000 0.000 0.000 {numpy.core.multiarray.copyto}
- 5 0.000 0.000 0.003 0.001 validation.py:267(check_array)
- 5 0.000 0.000 0.002 0.000 validation.py:45(_assert_all_finite)
- 1 0.000 0.000 0.000 0.000 base.py:198(get_params)
- 5 0.000 0.000 0.000 0.000 validation.py:128(_shape_repr)
- 5 0.000 0.000 0.000 0.000 {method 'join' of 'str' objects}
- 15 0.000 0.000 0.000 0.000 validation.py:155(<genexpr>)
- 27 0.000 0.000 0.000 0.000 {hasattr}
- 5 0.000 0.000 0.000 0.000 shape_base.py:60(atleast_2d)
- 11 0.000 0.000 0.000 0.000 numeric.py:464(asanyarray)
- 5 0.000 0.000 0.000 0.000 validation.py:107(_num_samples)
- 30 0.000 0.000 0.000 0.000 {isinstance}
- 1 0.000 0.000 59.787 59.787 base.py:490(radius_neighbors)
- 1 0.000 0.000 0.000 0.000 base.py:116(_init_params)
- 14 0.000 0.000 0.000 0.000 {getattr}
- 1 0.000 0.000 131.351 131.351 <string>:1(<module>)
- 7 0.000 0.000 0.000 0.000 warnings.py:339(__enter__)
- 1 0.000 0.000 0.001 0.001 numeric.py:141(ones)
- 7 0.000 0.000 0.000 0.000 warnings.py:74(simplefilter)
- 1 0.000 0.000 0.000 0.000 inspect.py:744(getargs)
- 1 0.000 0.000 0.000 0.000 {numpy.core.multiarray.empty}
- 1 0.000 0.000 0.000 0.000 inspect.py:804(getargspec)
- 3 0.000 0.000 0.001 0.000 numeric.py:394(asarray)
- 5 0.000 0.000 0.001 0.000 _methods.py:31(_sum)
- 1 0.000 0.000 0.000 0.000 abc.py:128(__instancecheck__)
- 5 0.000 0.000 0.001 0.000 {method 'sum' of 'numpy.ndarray' objects}
- 7 0.000 0.000 0.000 0.000 warnings.py:318(__init__)
- 7 0.000 0.000 0.000 0.000 base.py:865(isspmatrix)
- 1 0.000 0.000 0.000 0.000 base.py:172(_get_param_names)
- 7 0.000 0.000 0.000 0.000 warnings.py:355(__exit__)
- 1 0.000 0.000 0.000 0.000 unsupervised.py:111(__init__)
- 1 0.000 0.000 0.000 0.000 shape_base.py:8(atleast_1d)
- 2 0.000 0.000 0.000 0.000 _weakrefset.py:70(__contains__)
- 6 0.000 0.000 0.000 0.000 {method 'append' of 'list' objects}
- 8 0.000 0.000 0.000 0.000 {method 'pop' of 'list' objects}
- 1 0.000 0.000 0.000 0.000 inspect.py:67(ismethod)
- 2 0.000 0.000 0.000 0.000 {built-in method __new__ of type object at 0x1024eb7c8}
- 1 0.000 0.000 0.000 0.000 {range}
- 1 0.000 0.000 0.000 0.000 {method 'reshape' of 'numpy.ndarray' objects}
- 1 0.000 0.000 0.000 0.000 {method 'sort' of 'list' objects}
- 1 0.000 0.000 0.268 0.268 base.py:774(fit)
- 1 0.000 0.000 0.000 0.000 <string>:8(__new__)
- 7 0.000 0.000 0.000 0.000 {method 'insert' of 'list' objects}
- 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
- 1 0.000 0.000 0.000 0.000 inspect.py:142(isfunction)
- 1 0.000 0.000 0.000 0.000 inspect.py:209(iscode)
- 1 0.000 0.000 0.000 0.000 {method 'get' of 'dict' objects}
- 1 0.000 0.000 0.000 0.000 {callable}
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