diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/_methods.py | 105 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/methods.c | 61 |
2 files changed, 147 insertions, 19 deletions
diff --git a/numpy/core/_methods.py b/numpy/core/_methods.py new file mode 100644 index 000000000..3c05cf71d --- /dev/null +++ b/numpy/core/_methods.py @@ -0,0 +1,105 @@ +# Array methods which are called by the both the C-code for the method +# and the Python code for the NumPy-namespace function + +import multiarray as mu +import umath as um +from numeric import asanyarray + +def _amax(a, axis=None, out=None, skipna=False, keepdims=False): + return um.maximum.reduce(a, axis=axis, + out=out, skipna=skipna, keepdims=keepdims) + +def _amin(a, axis=None, out=None, skipna=False, keepdims=False): + return um.minimum.reduce(a, axis=axis, + out=out, skipna=skipna, keepdims=keepdims) + +def _sum(a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): + return um.add.reduce(a, axis=axis, dtype=dtype, + out=out, skipna=skipna, keepdims=keepdims) + +def _prod(a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): + return um.multiply.reduce(a, axis=axis, dtype=dtype, + out=out, skipna=skipna, keepdims=keepdims) + +def _any(a, axis=None, out=None, skipna=False, keepdims=False): + return um.logical_or.reduce(a, axis=axis, + out=out, skipna=skipna, keepdims=keepdims) + +def _all(a, axis=None, out=None, skipna=False, keepdims=False): + return um.logical_and.reduce(a, axis=axis, + out=out, skipna=skipna, keepdims=keepdims) + +def _mean(a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): + arr = asanyarray(a) + + # Upgrade bool, unsigned int, and int to float64 + if dtype is None and arr.dtype.kind in ['b','u','i']: + ret = um.add.reduce(arr, axis=axis, dtype='f8', + out=out, skipna=skipna, keepdims=keepdims) + else: + ret = um.add.reduce(arr, axis=axis, dtype=dtype, + out=out, skipna=skipna, keepdims=keepdims) + rcount = mu.count_reduce_items(arr, axis=axis, + skipna=skipna, keepdims=keepdims) + if isinstance(ret, mu.ndarray): + ret = um.true_divide(ret, rcount, + out=ret, casting='unsafe', subok=False) + else: + ret = ret / float(rcount) + return ret + +def _var(a, axis=None, dtype=None, out=None, ddof=0, + skipna=False, keepdims=False): + arr = asanyarray(a) + + # First compute the mean, saving 'rcount' for reuse later + if dtype is None and arr.dtype.kind in ['b','u','i']: + arrmean = um.add.reduce(arr, axis=axis, dtype='f8', + skipna=skipna, keepdims=True) + else: + arrmean = um.add.reduce(arr, axis=axis, dtype=dtype, + skipna=skipna, keepdims=True) + rcount = mu.count_reduce_items(arr, axis=axis, + skipna=skipna, keepdims=True) + if isinstance(arrmean, mu.ndarray): + arrmean = um.true_divide(arrmean, rcount, + out=arrmean, casting='unsafe', subok=False) + else: + arrmean = arrmean / float(rcount) + + # arr - arrmean + x = arr - arrmean + + # (arr - arrmean) ** 2 + if arr.dtype.kind == 'c': + x = um.multiply(x, um.conjugate(x), out=x).real + else: + x = um.multiply(x, x, out=x) + + # add.reduce((arr - arrmean) ** 2, axis) + ret = um.add.reduce(x, axis=axis, dtype=dtype, out=out, + skipna=skipna, keepdims=keepdims) + + # add.reduce((arr - arrmean) ** 2, axis) / (n - ddof) + if not keepdims and isinstance(rcount, mu.ndarray): + rcount = rcount.squeeze(axis=axis) + rcount -= ddof + if isinstance(ret, mu.ndarray): + ret = um.true_divide(ret, rcount, + out=ret, casting='unsafe', subok=False) + else: + ret = ret / float(rcount) + + return ret + +def _std(a, axis=None, dtype=None, out=None, ddof=0, + skipna=False, keepdims=False): + ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, + skipna=skipna, keepdims=keepdims) + + if isinstance(ret, mu.ndarray): + um.sqrt(ret, out=ret) + else: + ret = um.sqrt(ret) + + return ret diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c index afeae9a30..6af1ca984 100644 --- a/numpy/core/src/multiarray/methods.c +++ b/numpy/core/src/multiarray/methods.c @@ -49,17 +49,10 @@ NpyArg_ParseKeywords(PyObject *keys, const char *format, char **kwlist, ...) return ret; } -/* - * Forwards an ndarray method to a the Python function - * numpy.core._methods.<name>(...) - */ static PyObject * -forward_ndarray_method(PyArrayObject *self, PyObject *args, PyObject *kwds, - const char *name) +get_forwarding_ndarray_method(const char *name) { - PyObject *sargs, *ret; PyObject *module_methods, *callable; - int i, n; /* Get a reference to the function we're calling */ module_methods = PyImport_ImportModule("numpy.core._methods"); @@ -72,14 +65,28 @@ forward_ndarray_method(PyArrayObject *self, PyObject *args, PyObject *kwds, PyErr_Format(PyExc_RuntimeError, "NumPy internal error: could not find function " "numpy.core._methods.%s", name); - return NULL; } + Py_INCREF(callable); + Py_DECREF(module_methods); + return callable; +} + +/* + * Forwards an ndarray method to a the Python function + * numpy.core._methods.<name>(...) + */ +static PyObject * +forward_ndarray_method(PyArrayObject *self, PyObject *args, PyObject *kwds, + PyObject *forwarding_callable) +{ + PyObject *sargs, *ret; + int i, n; + /* Combine 'self' and 'args' together into one tuple */ n = PyTuple_GET_SIZE(args); sargs = PyTuple_New(n + 1); if (sargs == NULL) { - Py_DECREF(module_methods); return NULL; } Py_INCREF(self); @@ -91,12 +98,28 @@ forward_ndarray_method(PyArrayObject *self, PyObject *args, PyObject *kwds, } /* Call the function and return */ - ret = PyObject_Call(callable, sargs, kwds); + ret = PyObject_Call(forwarding_callable, sargs, kwds); Py_DECREF(sargs); - Py_DECREF(module_methods); return ret; } +/* + * Forwards an ndarray method to the function numpy.core._methods.<name>(...), + * caching the callable in a local static variable. Note that the + * initialization is not thread-safe, but relies on the CPython GIL to + * be correct. + */ +#define NPY_FORWARD_NDARRAY_METHOD(name) \ + static PyObject *callable = NULL; \ + if (callable == NULL) { \ + callable = get_forwarding_ndarray_method(name); \ + if (callable == NULL) { \ + return NULL; \ + } \ + } \ + return forward_ndarray_method(self, args, kwds, callable) + + static PyObject * array_take(PyArrayObject *self, PyObject *args, PyObject *kwds) { @@ -340,13 +363,13 @@ array_argmin(PyArrayObject *self, PyObject *args, PyObject *kwds) static PyObject * array_max(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_amax"); + NPY_FORWARD_NDARRAY_METHOD("_amax"); } static PyObject * array_min(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_amin"); + NPY_FORWARD_NDARRAY_METHOD("_amin"); } static PyObject * @@ -1885,13 +1908,13 @@ _get_type_num_double(PyArray_Descr *dtype1, PyArray_Descr *dtype2) static PyObject * array_mean(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_mean"); + NPY_FORWARD_NDARRAY_METHOD("_mean"); } static PyObject * array_sum(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_sum"); + NPY_FORWARD_NDARRAY_METHOD("_sum"); } @@ -1920,7 +1943,7 @@ array_cumsum(PyArrayObject *self, PyObject *args, PyObject *kwds) static PyObject * array_prod(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_prod"); + NPY_FORWARD_NDARRAY_METHOD("_prod"); } static PyObject * @@ -2004,14 +2027,14 @@ array_all(PyArrayObject *self, PyObject *args, PyObject *kwds) static PyObject * array_stddev(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_std"); + NPY_FORWARD_NDARRAY_METHOD("_std"); } static PyObject * array_variance(PyArrayObject *self, PyObject *args, PyObject *kwds) { - return forward_ndarray_method(self, args, kwds, "_var"); + NPY_FORWARD_NDARRAY_METHOD("_var"); } |