matplotlib/src/_image_wrapper.cpp at main · mathstuf/matplotlib · GitHub

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#include "mplutils.h"

#include "_image_resample.h"

#include "numpy_cpp.h"

#include "py_converters.h"

/**********************************************************************

* Free functions

* */

const char* image_resample__doc__ =

"resample(input_array, output_array, transform, interpolation=NEAREST, resample=False, alpha=1.0, norm=False, radius=1.0)\n"

"--\n\n"

"Resample input_array, blending it in-place into output_array, using an\n"

"affine transformation.\n\n"

"Parameters\n"

"----------\n"

"input_array : 2-d or 3-d NumPy array of float, double or `numpy.uint8`\n"

" If 2-d, the image is grayscale. If 3-d, the image must be of size\n"

" 4 in the last dimension and represents RGBA data.\n\n"

"output_array : 2-d or 3-d NumPy array of float, double or `numpy.uint8`\n"

" The dtype and number of dimensions must match `input_array`.\n\n"

"transform : matplotlib.transforms.Transform instance\n"

" The transformation from the input array to the output array.\n\n"

"interpolation : int, default: NEAREST\n"

" The interpolation method. Must be one of the following constants\n"

" defined in this module:\n\n"

" NEAREST, BILINEAR, BICUBIC, SPLINE16, SPLINE36,\n"

" HANNING, HAMMING, HERMITE, KAISER, QUADRIC, CATROM, GAUSSIAN,\n"

" BESSEL, MITCHELL, SINC, LANCZOS, BLACKMAN\n\n"

"resample : bool, optional\n"

" When `True`, use a full resampling method. When `False`, only\n"

" resample when the output image is larger than the input image.\n\n"

"alpha : float, default: 1\n"

" The transparency level, from 0 (transparent) to 1 (opaque).\n\n"

"norm : bool, default: False\n"

" Whether to norm the interpolation function.\n\n"

"radius: float, default: 1\n"

" The radius of the kernel, if method is SINC, LANCZOS or BLACKMAN.\n";

static PyArrayObject *

_get_transform_mesh(PyObject *py_affine, npy_intp *dims)

{

/* TODO: Could we get away with float, rather than double, arrays here? */

/* Given a non-affine transform object, create a mesh that maps

every pixel in the output image to the input image. This is used

as a lookup table during the actual resampling. */

PyObject *py_inverse = NULL;

npy_intp out_dims[3];

out_dims[0] = dims[0] * dims[1];

out_dims[1] = 2;

py_inverse = PyObject_CallMethod(py_affine, "inverted", NULL);

if (py_inverse == NULL) {

return NULL;

}

numpy::array_view<double, 2> input_mesh(out_dims);

double *p = (double *)input_mesh.data();

for (npy_intp y = 0; y < dims[0]; ++y) {

for (npy_intp x = 0; x < dims[1]; ++x) {

*p++ = (double)x;

*p++ = (double)y;

}

PyObject *output_mesh = PyObject_CallMethod(

py_inverse, "transform", "O", input_mesh.pyobj_steal());

Py_DECREF(py_inverse);

if (output_mesh == NULL) {

return NULL;

}

PyArrayObject *output_mesh_array =

(PyArrayObject *)PyArray_ContiguousFromAny(

output_mesh, NPY_DOUBLE, 2, 2);

Py_DECREF(output_mesh);

if (output_mesh_array == NULL) {

return NULL;

}

return output_mesh_array;

}

static PyObject *

image_resample(PyObject *self, PyObject* args, PyObject *kwargs)

{

PyObject *py_input = NULL;

PyObject *py_output = NULL;

PyObject *py_transform = NULL;

resample_params_t params;

PyArrayObject *input = NULL;

PyArrayObject *output = NULL;

PyArrayObject *transform_mesh = NULL;

int ndim;

int type;

params.interpolation = NEAREST;

params.transform_mesh = NULL;

params.resample = false;

params.norm = false;

params.radius = 1.0;

params.alpha = 1.0;

const char *kwlist[] = {

"input_array", "output_array", "transform", "interpolation",

"resample", "alpha", "norm", "radius", NULL };

if (!PyArg_ParseTupleAndKeywords(

args, kwargs, "OOO|iO&dO&d:resample", (char **)kwlist,

&py_input, &py_output, &py_transform,

&params.interpolation, &convert_bool, &params.resample,

&params.alpha, &convert_bool, &params.norm, &params.radius)) {

return NULL;

}

if (params.interpolation < 0 || params.interpolation >= _n_interpolation) {

PyErr_Format(PyExc_ValueError, "Invalid interpolation value %d",

params.interpolation);

goto error;

}

input = (PyArrayObject *)PyArray_FromAny(

py_input, NULL, 2, 3, NPY_ARRAY_C_CONTIGUOUS, NULL);

if (!input) {

goto error;

}

ndim = PyArray_NDIM(input);

type = PyArray_TYPE(input);

if (!PyArray_Check(py_output)) {

PyErr_SetString(PyExc_ValueError, "Output array must be a NumPy array");

goto error;

}

output = (PyArrayObject *)py_output;

if (PyArray_NDIM(output) != ndim) {

PyErr_Format(

PyExc_ValueError,

"Input (%dD) and output (%dD) have different dimensionalities.",

ndim, PyArray_NDIM(output));

goto error;

}

// PyArray_FromAny above checks that input is 2D or 3D.

if (ndim == 3 && (PyArray_DIM(input, 2) != 4 || PyArray_DIM(output, 2) != 4)) {

PyErr_Format(

PyExc_ValueError,

"If 3D, input and output arrays must be RGBA with shape (M, N, 4); "

"got trailing dimensions of %" NPY_INTP_FMT " and %" NPY_INTP_FMT

" respectively", PyArray_DIM(input, 2), PyArray_DIM(output, 2));

goto error;

}

if (PyArray_TYPE(output) != type) {

PyErr_SetString(PyExc_ValueError, "Mismatched types");

goto error;

}

if (!PyArray_IS_C_CONTIGUOUS(output)) {

PyErr_SetString(PyExc_ValueError, "Output array must be C-contiguous");

goto error;

}

if (py_transform == NULL || py_transform == Py_None) {

params.is_affine = true;

} else {

PyObject *py_is_affine;

int py_is_affine2;

py_is_affine = PyObject_GetAttrString(py_transform, "is_affine");

if (!py_is_affine) {

goto error;

}

py_is_affine2 = PyObject_IsTrue(py_is_affine);

Py_DECREF(py_is_affine);

if (py_is_affine2 == -1) {

goto error;

} else if (py_is_affine2) {

if (!convert_trans_affine(py_transform, &params.affine)) {

goto error;

}

params.is_affine = true;

} else {

transform_mesh = _get_transform_mesh(

py_transform, PyArray_DIMS(output));

if (!transform_mesh) {

goto error;

}

params.transform_mesh = (double *)PyArray_DATA(transform_mesh);

params.is_affine = false;

}

if (auto resampler =

(ndim == 2) ? (

(type == NPY_UINT8) ? resample<agg::gray8> :

(type == NPY_INT8) ? resample<agg::gray8> :

(type == NPY_UINT16) ? resample<agg::gray16> :

(type == NPY_INT16) ? resample<agg::gray16> :

(type == NPY_FLOAT32) ? resample<agg::gray32> :

(type == NPY_FLOAT64) ? resample<agg::gray64> :

nullptr) : (

// ndim == 3

(type == NPY_UINT8) ? resample<agg::rgba8> :

(type == NPY_INT8) ? resample<agg::rgba8> :

(type == NPY_UINT16) ? resample<agg::rgba16> :

(type == NPY_INT16) ? resample<agg::rgba16> :

(type == NPY_FLOAT32) ? resample<agg::rgba32> :

(type == NPY_FLOAT64) ? resample<agg::rgba64> :

nullptr)) {

Py_BEGIN_ALLOW_THREADS

resampler(

PyArray_DATA(input), PyArray_DIM(input, 1), PyArray_DIM(input, 0),

PyArray_DATA(output), PyArray_DIM(output, 1), PyArray_DIM(output, 0),

params);

Py_END_ALLOW_THREADS

} else {

PyErr_SetString(

PyExc_ValueError,

"arrays must be of dtype byte, short, float32 or float64");

goto error;

}

Py_DECREF(input);

Py_XDECREF(transform_mesh);

Py_RETURN_NONE;

error:

Py_XDECREF(input);

Py_XDECREF(transform_mesh);

return NULL;

}

static PyMethodDef module_functions[] = {

{"resample", (PyCFunction)image_resample, METH_VARARGS|METH_KEYWORDS, image_resample__doc__},

{NULL}

};

static struct PyModuleDef moduledef = {

PyModuleDef_HEAD_INIT, "_image", NULL, 0, module_functions,

};

PyMODINIT_FUNC PyInit__image(void)

{

PyObject *m;

import_array();

m = PyModule_Create(&moduledef);

if (m == NULL) {

return NULL;

}

if (PyModule_AddIntConstant(m, "NEAREST", NEAREST) ||

PyModule_AddIntConstant(m, "BILINEAR", BILINEAR) ||

PyModule_AddIntConstant(m, "BICUBIC", BICUBIC) ||

PyModule_AddIntConstant(m, "SPLINE16", SPLINE16) ||

PyModule_AddIntConstant(m, "SPLINE36", SPLINE36) ||

PyModule_AddIntConstant(m, "HANNING", HANNING) ||

PyModule_AddIntConstant(m, "HAMMING", HAMMING) ||

PyModule_AddIntConstant(m, "HERMITE", HERMITE) ||

PyModule_AddIntConstant(m, "KAISER", KAISER) ||

PyModule_AddIntConstant(m, "QUADRIC", QUADRIC) ||

PyModule_AddIntConstant(m, "CATROM", CATROM) ||

PyModule_AddIntConstant(m, "GAUSSIAN", GAUSSIAN) ||

PyModule_AddIntConstant(m, "BESSEL", BESSEL) ||

PyModule_AddIntConstant(m, "MITCHELL", MITCHELL) ||

PyModule_AddIntConstant(m, "SINC", SINC) ||

PyModule_AddIntConstant(m, "LANCZOS", LANCZOS) ||

PyModule_AddIntConstant(m, "BLACKMAN", BLACKMAN) ||

PyModule_AddIntConstant(m, "_n_interpolation", _n_interpolation)) {

Py_DECREF(m);

return NULL;

}

return m;

}

matplotlib/src/_image_wrapper.cpp at main · mathstuf/matplotlib · GitHub

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