Define M_PI_2 on Windows

include/viennaray/rayUtil.hpp

@@ -30,6 +30,10 @@
 #define M_PI 3.14159265358979323846
 #endif
 
+#ifndef M_PI_2
+#define M_PI_2 1.57079632679489661923
+#endif
+
 namespace viennaray {
 
 using namespace viennacore;

tests/reflection/visualize.ipynb

@@ -0,0 +1,208 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 194,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 195,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path = '../../build/tests/reflection/'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 196,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "diffuse = np.genfromtxt(path + 'diffuse_reflection.txt')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# arrow plot in 3D\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111, projection='3d')\n",
+    "\n",
+    "# draw arrow\n",
+    "for ref in diffuse[:100]:\n",
+    "    ax.quiver(0, 0, 0, ref[0], ref[1], ref[2], color='blue', alpha=0.5)\n",
+    "\n",
+    "ax.set_xlim([-1, 1])\n",
+    "ax.set_ylim([-1, 1])\n",
+    "ax.set_zlim([0, 1])\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# theta and phi\n",
+    "theta = np.arccos(diffuse[:, 2])\n",
+    "phi = np.arctan2(diffuse[:, 1], diffuse[:, 0])\n",
+    "\n",
+    "plt.hist(theta, bins=100, histtype='step', color='blue', label='theta', density=True)\n",
+    "plt.hist(phi, bins=100, histtype='step', color='red', label='phi', density=True)\n",
+    "\n",
+    "# expected distribution\n",
+    "theta = np.linspace(0, np.pi / 2, 100)\n",
+    "plt.plot(theta, np.sin(theta * 2), '--', color='blue', label='sin(theta)')\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 199,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conedSpecularOld = np.genfromtxt(path + 'coned_specular_reflection_old.txt')\n",
+    "conedSpecular = np.genfromtxt(path + 'coned_specular_reflection.txt')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# arrow plot in 3D\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111, projection='3d')\n",
+    "\n",
+    "# draw arrow\n",
+    "for ref in conedSpecular[:100]:\n",
+    "    ax.quiver(0, 0, 0, ref[0], ref[1], ref[2], color='blue', alpha=0.5)\n",
+    "\n",
+    "ax.set_xlim([-1, 1])\n",
+    "ax.set_ylim([-1, 1])\n",
+    "ax.set_zlim([0, 1])\n",
+    "plt.title(\"New\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))   \n",
+    "\n",
+    "# theta and phi\n",
+    "theta = np.arccos(conedSpecular[:, 2])\n",
+    "phi = np.arctan2(conedSpecular[:, 1], conedSpecular[:, 0])\n",
+    "\n",
+    "ax1.hist(theta, bins=80, histtype='step', color='blue', label='theta', density=True)\n",
+    "ax1.hist(phi, bins=80, histtype='step', color='red', label='phi', density=True)\n",
+    "ax1.set_xlim([-np.pi, np.pi])\n",
+    "ax1.set_title('New')\n",
+    "\n",
+    "theta = np.arccos(conedSpecularOld[:, 2])\n",
+    "phi = np.arctan2(conedSpecularOld[:, 1], conedSpecularOld[:, 0])\n",
+    "\n",
+    "ax2.hist(theta, bins=80, histtype='step', color='blue', label='theta', density=True)\n",
+    "ax2.hist(phi, bins=80, histtype='step', color='red', label='phi', density=True)\n",
+    "ax2.set_xlim([-np.pi, np.pi])\n",
+    "ax2.set_title('Old')\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, (ax1) = plt.subplots(1, 1, figsize=(6, 4))   \n",
+    "\n",
+    "# theta and phi\n",
+    "theta = np.arccos(conedSpecular[:, 2])\n",
+    "phi = np.arctan2(conedSpecular[:, 1], conedSpecular[:, 0])\n",
+    "\n",
+    "ax1.hist(theta, bins=80, histtype='step', color='blue', label='theta new', density=True)\n",
+    "ax1.hist(phi, bins=80, histtype='step', color='red', label='phi new', density=True)\n",
+    "ax1.set_xlim([-np.pi, np.pi])\n",
+    "ax1.set_title('New')\n",
+    "\n",
+    "theta = np.arccos(conedSpecularOld[:, 2])\n",
+    "phi = np.arctan2(conedSpecularOld[:, 1], conedSpecularOld[:, 0])\n",
+    "\n",
+    "ax1.hist(theta, bins=80, histtype='step', color='purple', label='theta old', density=True)\n",
+    "ax1.hist(phi, bins=80, histtype='step', color='orange', label='phi old', density=True)\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# arrow plot in 3D\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111, projection='3d')\n",
+    "\n",
+    "# draw arrow\n",
+    "for ref in conedSpecularOld[:100]:\n",
+    "    ax.quiver(0, 0, 0, ref[0], ref[1], ref[2], color='blue', alpha=0.5)\n",
+    "\n",
+    "ax.set_xlim([-1, 1])\n",
+    "ax.set_ylim([-1, 1])\n",
+    "ax.set_zlim([0, 1])\n",
+    "plt.title('Old')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}