{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import laspy\n",
    "\n",
    "triskele_path = Path('../triskele/python/')\n",
    "sys.path.append(str(triskele_path.resolve()))\n",
    "import triskele\n",
    "\n",
    "figsize = (16, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read and Write"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "R = np.random.random((1000,4000))\n",
    "\n",
    "plt.figure(figsize=figsize)\n",
    "plt.imshow(R)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "R.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## F64 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "triskele.write('../Res/rw_test.tiff', R)\n",
    "R2 = triskele.read('../Res/rw_test.tiff')\n",
    "R2.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=figsize)\n",
    "plt.imshow(R2)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## F32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=figsize)\n",
    "plt.imshow(R.astype(np.float32))\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "triskele.write('../Res/rw_test.tiff', R.astype(np.float32))\n",
    "R2 = triskele.read('../Res/rw_test.tiff')\n",
    "R2.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=figsize)\n",
    "plt.imshow(R2)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Int32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "R = np.random.random_integers(0, 10000, (1000,4000)).astype(np.int32)\n",
    "\n",
    "plt.figure(figsize=figsize)\n",
    "plt.imshow(R)\n",
    "plt.colorbar()\n",
    "plt.show()\n",
    "\n",
    "R.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "triskele.write('../Res/rw_test.tiff', R)\n",
    "R2 = triskele.read('../Res/rw_test.tiff')\n",
    "R2.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=figsize)\n",
    "plt.imshow(R2)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  }
 ],
 "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"
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 "nbformat": 4,
 "nbformat_minor": 2
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