{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Work in progress\n", "\n", "import k3d\n", "import math\n", "import numpy as np\n", "import nibabel as nib\n", "from k3d.helpers import download\n", "\n", "filename = download('https://github.com/FNNDSC/data/raw/master/nifti/adi_brain/adi_brain.nii.gz')\n", "\n", "nii_source = nib.load(filename)\n", "img = nii_source.get_fdata()\n", "dx, dy, dz = nii_source.header.get_zooms()\n", "img = np.swapaxes(img,0,2).astype(np.float32)\n", "nz, ny, nx = img.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "volume = k3d.volume(img, color_range=[50,1000], color_map=np.array(k3d.basic_color_maps.Jet, dtype=np.float32))\n", "\n", "plot = k3d.plot()\n", "plot += volume\n", "plot.display()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "volume.samples = 1024.0" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "volume.color_range = [650,1500]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }