cpu_based_version.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Numba CUDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numba import cuda\n",
    "import numpy as np\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.load('example_data.npy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Original (CPU-based)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ridge_detection(f, thres):\n",
    "    count = np.zeros(f.shape)\n",
    "    for i in range(len(f)):\n",
    "        for j in range(len(f[i])):\n",
    "            if (\n",
    "                i > 0\n",
    "                and j > 0\n",
    "                and i < (len(f) - 1)\n",
    "                and j < (len(f[i]) - 1)\n",
    "                and f[i, j] > thres\n",
    "                and ~np.isnan(f[i, j])\n",
    "            ):\n",
    "                step_i = i\n",
    "                step_j = j\n",
    "                for k in range(1000):\n",
    "                    if (\n",
    "                        step_i == 0\n",
    "                        or step_j == 0\n",
    "                        or step_i == (len(f) - 1)\n",
    "                        or step_j == (len(f[i]) - 1)\n",
    "                    ):\n",
    "                        break\n",
    "                    index = np.nanargmax(\n",
    "                        f[step_i - 1 : step_i + 2, step_j - 1 : step_j + 2].data\n",
    "                    )\n",
    "                    vmax = np.nanmax(\n",
    "                        f[step_i - 1 : step_i + 2, step_j - 1 : step_j + 2].data\n",
    "                    )\n",
    "                    if index == 4 or vmax == f[step_i, step_j] or np.isnan(vmax):\n",
    "                        break\n",
    "                    row = int(index / 3)\n",
    "                    col = index % 3\n",
    "                    count[step_i - 1 + row, step_j - 1 + col] += 1\n",
    "                    step_i = step_i - 1 + row\n",
    "                    step_j = step_j - 1 + col\n",
    "    return count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 6min 14s, sys: 15.9 s, total: 6min 30s\n",
      "Wall time: 6min 6s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "results = ridge_detection(data, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %timeit -r 7 -n 1 ridge_detection(data, 0)"
   ]
  }
 ],
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