{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "2fbfeced", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pyclesperanto_prototype as cle\n", "import numpy as np\n", "\n", "cle.get_device()" ] }, { "cell_type": "code", "execution_count": 2, "id": "8cf5fc5c", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "img = np.zeros((100,100))\n", "img[25:75, 25:75] = 1\n", "\n", "image = cle.push(img)\n", "\n", "cle.imshow(image)" ] }, { "cell_type": "code", "execution_count": 3, "id": "61711ccb", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "binary_image = (image == 1)\n", "\n", "cle.imshow(binary_image)" ] }, { "cell_type": "code", "execution_count": 4, "id": "6a99098f", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "another_binary_image = cle.equal_constant(binary_image)\n", "cle.imshow(another_binary_image)" ] }, { "cell_type": "code", "execution_count": 5, "id": "d2f8b067", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on function equal_constant in module pyclesperanto_prototype._tier1._equal_constant:\n", "\n", "equal_constant(source: Union[numpy.ndarray, pyclesperanto_prototype._tier0._pycl.OCLArray, pyopencl._cl.Image, pyclesperanto_prototype._tier0._pycl._OCLImage], destination: Union[numpy.ndarray, pyclesperanto_prototype._tier0._pycl.OCLArray, pyopencl._cl.Image, pyclesperanto_prototype._tier0._pycl._OCLImage] = None, constant: float = 0)\n", " Determines if an image A and a constant b are equal.\n", " \n", " 
f(a, b) = 1 if a == b; 0 otherwise.
\n", " \n", " Parameters\n", " ----------\n", " source : Image\n", " The image where every pixel is compared to the constant.\n", " destination : Image\n", " The resulting binary image where pixels will be 1 only if source1 \n", " and source2 equal in the given pixel.\n", " constant : float\n", " The constant where every pixel is compared to.\n", " \n", " \n", " Returns\n", " -------\n", " destination\n", " \n", " Examples\n", " --------\n", " >>> import pyclesperanto_prototype as cle\n", " >>> cle.equal_constant(source, destination, constant)\n", " \n", " References\n", " ----------\n", " .. [1] https://clij.github.io/clij2-docs/reference_equalConstant\n", "\n" ] } ], "source": [ "# The reason why this image is the inverted version of `binary_image` is that `constant` \n", "# in `equal_constant` has a default value: 0. Thus, you're checking if `binary_image` \n", "# is _equal to the constant 0_. See also documentation:\n", "help(cle.equal_constant)" ] }, { "cell_type": "code", "execution_count": null, "id": "5aac8559", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 5 }