Fast_filter.ipynb

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      "4.01 ms ± 23.9 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
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   "source": [
    "np.random.seed(42)\n",
    "arr = np.random.randn(1000000)\n",
    "%timeit np.where(arr>0,1,0)"
   ]
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     "text": [
      "804 µs ± 6.73 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
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   "source": [
    "from numba import njit\n",
    "\n",
    "\n",
    "@njit\n",
    "def filt1(arr):\n",
    "    N = arr.shape[0]\n",
    "    out = np.empty(N)\n",
    "    for i in range(N):\n",
    "        if arr[i] > 0:\n",
    "            out[i] = arr[i]\n",
    "        else:\n",
    "            out[i] = 0\n",
    "    return out\n",
    "\n",
    "\n",
    "%timeit filt1(arr)"
   ]
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      "809 µs ± 6.14 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
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   "source": [
    "@njit(fastmath=True)\n",
    "def filt2(arr):\n",
    "    N = arr.shape[0]\n",
    "    out = np.empty(N)\n",
    "    for i in range(N):\n",
    "        if arr[i] > 0:\n",
    "            out[i] = arr[i]\n",
    "        else:\n",
    "            out[i] = 0\n",
    "    return out\n",
    "\n",
    "\n",
    "%timeit filt2(arr)"
   ]
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   "outputs": [
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     "text": [
      "306 µs ± 91.5 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "from numba import prange\n",
    "\n",
    "\n",
    "@njit(fastmath=True, parallel=True)\n",
    "def filt3(arr):\n",
    "    N = arr.shape[0]\n",
    "    out = np.empty(N)\n",
    "    for i in prange(N):\n",
    "        if arr[i] > 0:\n",
    "            out[i] = arr[i]\n",
    "        else:\n",
    "            out[i] = 0\n",
    "    return out\n",
    "\n",
    "\n",
    "%timeit filt3(arr)"
   ]
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