examples/old/k3d_test_r2.1.0.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K3D - Release 2.1.0\n",
    "\n",
    "Final tests\n",
    "\n",
    "\n",
    "\n",
    "\n",
    " \n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import k3d\n",
    "k3d.version_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "plot = k3d.plot()\n",
    "plot.display()\n",
    "\n",
    "plot += k3d.vectors(\n",
    "   (0,0,0,0,0,0,0,0,0), \n",
    "   (1,0,0,0,1,0,0,0,1), \n",
    "    colors=(0xff0000, 0xff0000, 0xffff00, 0xffff00, 0x00ff00, 0x00ff00), \n",
    "   labels=('x', 'y', 'z')\n",
    ")\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## surface \n",
    "\n",
    " \n",
    " \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.randint(0, 0xFFFFFF, 1)[0].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plot.grid_auto_fit =  True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Nx = 50\n",
    "Ny = 50\n",
    "xmin,xmax = -3,3\n",
    "ymin,ymax = -0,3\n",
    "\n",
    "\n",
    "x = np.linspace(xmin,xmax,Nx)\n",
    "y = np.linspace(ymin,ymax,Ny)\n",
    "x,y = np.meshgrid(x,y)\n",
    "\n",
    "surface_plot =  k3d.surface(np.sin(x**2+y**2),xmin=xmin,xmax=xmax,\\\n",
    "                    ymin=ymin,ymax=ymax, color=int(np.random.randint(0, 0xFFFFFF, 1)[0]))\n",
    "plot += surface_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time \n",
    "\n",
    "\n",
    "Nx,Ny = 40,50\n",
    "dx,dy = 1.4,2.7\n",
    "x0,y0 = .2,1.3\n",
    "xmin,xmax = x0-dx, x0+dx\n",
    "ymin,ymax = y0-dy, y0+dy\n",
    "x = np.linspace(xmin,xmax,Nx)\n",
    "y = np.linspace(ymin,ymax,Ny)\n",
    "x,y = np.meshgrid(x,y)\n",
    "surface_plot2 = k3d.surface(np.sin(x**2+y**2),xmin=xmin,xmax=xmax,ymin=ymin,ymax=ymax, color=int(np.random.randint(0, 0xFFFFFF, 1)[0]))\n",
    "plot += surface_plot2\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## text\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "texture_text = k3d.texture_text(\"K3D.text(\\\"X max\\\", position=(3, 0, 0) )\", position=(0, 0, 1), size=10)\n",
    "plot += texture_text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "text = k3d.text(\"O\", position=(0, 0, 1) )\n",
    "plot += text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "text.text = \"\\int_0^1 dx \\sin x\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import time\n",
    "for i in range(26):\n",
    "    text.position = [0,0,1+np.sin(0.1*i)]\n",
    "    time.sleep(0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = x.flatten()[::4]\n",
    "y = y.flatten()[::4]\n",
    "z = np.sin(x**2+y**2) \n",
    "points = np.vstack([x,y,z]).T \n",
    "points_plt = k3d.points(points,colors=np.ones_like(x)*0xFF0F00 ,point_size=.1)\n",
    "plot += points_plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## line "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Nx,Ny = 10,65"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.linspace(-3,0,Nx)\n",
    "y = np.linspace(-3,0,Ny)\n",
    "x, y = np.meshgrid(x,y)\n",
    "\n",
    "for i in range(0,Nx):\n",
    "    x_ = x[:,i]\n",
    "    y_ = y[:,i]\n",
    "    z = np.sin(x_**2+y_**2)\n",
    "    points = np.vstack([x_,y_,z]).T\n",
    "    vars()['line_%d'%i]  = k3d.line(points,color=0xFF0000 ,width=1)\n",
    "    plot += vars()['line_%d'%i]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## vectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Nx,Ny = 100,100\n",
    "x = np.linspace(xmin,xmax,Nx)\n",
    "y = np.linspace(ymin,ymax,Ny)\n",
    "dx, dy  = x[1]-x[0],y[1]-y[0]\n",
    "\n",
    "x,y = np.meshgrid(x,y)\n",
    "z = np.sin(x**2+y**2)\n",
    "dx,dy \n",
    "if True:\n",
    "    dFy,dFx = np.gradient(z)\n",
    "    dFy,dFx = dFy/dy,dFx/dx \n",
    "else:\n",
    "    dFx,dFy = 2*x*np.cos(x**2+y**2),2*y*np.cos(x**2+y**2)\n",
    "\n",
    "origins = np.vstack([x.flatten(),y.flatten(),z.flatten()]).T\n",
    "vectors = 0.01*(np.vstack([dFx.flatten(),dFy.flatten(),-np.ones(Nx*Ny)] )).T\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def normalized(a, axis=-1, order=2):\n",
    "    l2 = np.atleast_1d(np.linalg.norm(a, order, axis))\n",
    "    l2[l2==0] = 1\n",
    "    return a / np.expand_dims(l2, axis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "vector_plot = k3d.vectors(-0.4*normalized(vectors[::10]), origins[::10], color=0xffff00)\n",
    "plot += vector_plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  marching cubes\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Nz = Nx\n",
    "zmin,zmax = -1,1\n",
    "ymin,ymax = 2,6\n",
    "\n",
    "x = np.linspace(xmin,xmax,Nx//2)\n",
    "y = np.linspace(ymin,ymax,Ny//2)\n",
    "z = np.linspace(zmin,zmax,Nz//2)\n",
    "x,y,z = np.meshgrid(x,y,z)\n",
    "F = np.sin(x**2+y**2)-z\n",
    "\n",
    "marching_cubes =k3d.marching_cubes(np.moveaxis(F,2,0),\\\n",
    "          xmin=xmin,xmax=xmax,ymin=ymin,ymax=ymax, \\\n",
    "          zmin=zmin, zmax=zmax, level=0.0,color=0xff0000)\n",
    "plot += marching_cubes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plot.camera_auto_fit = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import widgets\n",
    "\n",
    "class plot_ctrl(object):\n",
    "    plot = None\n",
    "    def __init__(self,id1,plot):\n",
    "        self.id = id1\n",
    "        ref_names = [ n for n,v in globals().items() if self.id==id(v)]  \n",
    "        if len(ref_names)==1:\n",
    "            desc = ref_names[0]\n",
    "        else:\n",
    "            desc = str(self.id)\n",
    "        self.w = widgets.Checkbox(description=desc,value=True)\n",
    "        self.w.observe(self.runme)\n",
    "        if type(self).plot == None:\n",
    "            type(self).plot = plot\n",
    "            type(self).objs = plot.objects.copy()\n",
    "\n",
    "    def runme(self,change):\n",
    "        if change['name']=='value':\n",
    "            for obj in type(self).objs:\n",
    "                if obj.id == self.id: #int(self.w.description):\n",
    "                    if self.w.value==True:\n",
    "                        type(self).plot += obj\n",
    "                        #print(\"Added obj\")\n",
    "                    else:\n",
    "                        type(self).plot -= obj  \n",
    "                        #print(\"Removed obj\")\n",
    "    \n",
    "    @classmethod\n",
    "    def VBox(cls,plot,ncol = 4):\n",
    "        names = {obj.id:obj.__class__.__name__ for obj in plot.objects}\n",
    "        cls.l = [cls(id1=key,plot=plot) for key in names.keys()]\n",
    "        \n",
    "        if ncol < len(cls.l):\n",
    "            checkboxes = widgets.VBox( [widgets.HBox([ el.w for el in cls.l[i:i+ncol]]) for i in range(0,len(cls.l),ncol)] ) \n",
    "        else:\n",
    "            checkboxes = widgets.VBox([el.w for el in cls.l])\n",
    "        return widgets.VBox([checkboxes,plot])\n",
    "    \n",
    "plot_ctrl.VBox(plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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