Hey,
I cooked up an initial implementation for one-dimensional
histogram_discrete().
Example:
>> import numpy
>> numpy.histogram_discrete([-1, 9, 9, 0, 3, 5, 3])
array([1, 1, 0, 0, 2, 0, 1, 0, 0, 0, 2])
>> numpy.histogram_discrete([-99999, 99999])
array([1, 0, 0, ..., 0, 0, 1])
Suggestions, criticism? :)
Priit :)
From f322bfb9bb2d18a93eac37ba0947743b93f94a5b Mon Sep 17 00:00:00 2001
From: Priit Laes <pl...@plaes.org>
Date: Fri, 13 Nov 2009 00:45:42 +0200
Subject: [PATCH] Initial implementation of histogram_discrete().
Signed-off-by: Priit Laes <pl...@plaes.org>
---
numpy/lib/function_base.py | 4 ++-
numpy/lib/src/_compiled_base.c | 46 ++++++++++++++++++++++++++++++++++++++++
2 files changed, 49 insertions(+), 1 deletions(-)
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 76ea08d..0516d42 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -4,7 +4,8 @@ __all__ = ['select', 'piecewise', 'trim_zeros',
'diff', 'gradient', 'angle', 'unwrap', 'sort_complex', 'disp',
'extract', 'place', 'nansum', 'nanmax', 'nanargmax',
'nanargmin', 'nanmin', 'vectorize', 'asarray_chkfinite', 'average',
- 'histogram', 'histogramdd', 'bincount', 'digitize', 'cov',
+ 'histogram', 'histogram_discrete', 'histogramdd', 'bincount',
+ 'digitize', 'cov',
'corrcoef', 'msort', 'median', 'sinc', 'hamming', 'hanning',
'bartlett', 'blackman', 'kaiser', 'trapz', 'i0', 'add_newdoc',
'add_docstring', 'meshgrid', 'delete', 'insert', 'append',
@@ -27,6 +28,7 @@ from numpy.core import atleast_1d, atleast_2d
from numpy.lib.twodim_base import diag
from _compiled_base import _insert, add_docstring
from _compiled_base import digitize, bincount, interp as compiled_interp
+from _compiled_base import histogram_discrete
from arraysetops import setdiff1d
from utils import deprecate
import numpy as np
diff --git a/numpy/lib/src/_compiled_base.c b/numpy/lib/src/_compiled_base.c
index 3a8193f..7076d1f 100644
--- a/numpy/lib/src/_compiled_base.c
+++ b/numpy/lib/src/_compiled_base.c
@@ -85,6 +85,50 @@ mnx (intp *i , intp len)
return mn;
}
+/*
+ * arr_histogram_discrete is registered as histogram_discrete.
+ *
+ * histogram_discrete accepts one arguments containing a 1-d array of
+ * integers called as list. This function returns an array with a length
+ * of max(list) - min(list) containing counts of each integer in list.
+ * Self is not used.
+ */
+static PyObject *
+arr_histogram_discrete(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwds)
+{
+ PyArray_Descr *type;
+ PyObject *list = NULL;
+ PyObject *lst=NULL, *ans=NULL;
+ intp *numbers, *ians, len , mxi, mni, ans_size;
+ int i;
+ static char *kwlist[] = {"list", NULL};
+
+ if (!PyArg_ParseTupleAndKeywords(args, kwds, "O",
+ kwlist, &list)) {
+ goto fail;
+ }
+ if (!(lst = PyArray_ContiguousFromAny(list, PyArray_INTP, 1, 1))) {
+ goto fail;
+ }
+ len = PyArray_SIZE(lst);
+ numbers = (intp *) PyArray_DATA(lst);
+ mxi = mxx(numbers, len);
+ mni = mnx(numbers, len);
+ ans_size = (numbers[mxi] + 1) - numbers[mni];
+ type = PyArray_DescrFromType(PyArray_INTP);
+ if (!(ans = PyArray_Zeros(1, &ans_size, type, 0))) {
+ goto fail;
+ }
+ ians = (intp *)(PyArray_DATA(ans));
+ for (i = 0; i < len; i++)
+ ians[numbers[i] - numbers[mni]] += 1;
+ Py_DECREF(lst);
+ return ans;
+
+fail:
+ Py_XDECREF(lst);
+ return NULL;
+}
/*
* arr_bincount is registered as bincount.
@@ -889,6 +933,8 @@ static struct PyMethodDef methods[] = {
METH_VARARGS | METH_KEYWORDS, NULL},
{"unpackbits", (PyCFunction)io_unpack,
METH_VARARGS | METH_KEYWORDS, NULL},
+ {"histogram_discrete", (PyCFunction)arr_histogram_discrete,
+ METH_VARARGS | METH_KEYWORDS, NULL},
{NULL, NULL, 0, NULL} /* sentinel */
};
--
1.6.5.2
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