From cf7a7f32a3f6ab315db65d77b8b0648acc1bcf83 Mon Sep 17 00:00:00 2001 From: Francisco Barreto Date: Thu, 10 Mar 2022 17:20:17 +0000 Subject: [PATCH] numpy --- your-code/main.ipynb | 396 +++++++++++++++++++++++++++++++++++-------- 1 file changed, 323 insertions(+), 73 deletions(-) diff --git a/your-code/main.ipynb b/your-code/main.ipynb index e66d6ce..57edd97 100644 --- a/your-code/main.ipynb +++ b/your-code/main.ipynb @@ -12,11 +12,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "import numpy as np" ] }, { @@ -28,11 +29,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.20.3\n" + ] + } + ], "source": [ - "# your code here" + "# your code here\n", + "print(np.__version__)" ] }, { @@ -45,29 +55,86 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Method 1" + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.92329899, 0.2735768 , 0.81071175, 0.98780487, 0.71475797],\n", + " [0.16613524, 0.57792115, 0.65555143, 0.24400684, 0.62367727],\n", + " [0.75472776, 0.06756629, 0.06293682, 0.62289541, 0.74144022]],\n", + "\n", + " [[0.96883467, 0.34792269, 0.74718702, 0.69030318, 0.21635223],\n", + " [0.5203064 , 0.411508 , 0.46509676, 0.16966541, 0.07002832],\n", + " [0.43219317, 0.77250002, 0.56847303, 0.64554749, 0.50166846]]])" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Method 1\n", + "a = np.random.random((2,3,5))\n", + "a" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Method 2" + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[421, 957, 47, 778, 843],\n", + " [775, 409, 522, 257, 564],\n", + " [618, 556, 507, 709, 758]],\n", + "\n", + " [[893, 58, 125, 775, 338],\n", + " [ 88, 381, 529, 140, 942],\n", + " [392, 905, 148, 776, 716]]])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Method 3\n", + "import random\n", + "a = np.random.randint(0.1, 1000, size=(2, 3, 5))\n", + "a" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Method 3" + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.92329899, 0.2735768 , 0.81071175, 0.98780487, 0.71475797],\n", + " [0.16613524, 0.57792115, 0.65555143, 0.24400684, 0.62367727],\n", + " [0.75472776, 0.06756629, 0.06293682, 0.62289541, 0.74144022]],\n", + "\n", + " [[0.96883467, 0.34792269, 0.74718702, 0.69030318, 0.21635223],\n", + " [0.5203064 , 0.411508 , 0.46509676, 0.16966541, 0.07002832],\n", + " [0.43219317, 0.77250002, 0.56847303, 0.64554749, 0.50166846]]])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a= np.empty((2,3,5))\n", + "a" ] }, { @@ -79,11 +146,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[0.92329899 0.2735768 0.81071175 0.98780487 0.71475797]\n", + " [0.16613524 0.57792115 0.65555143 0.24400684 0.62367727]\n", + " [0.75472776 0.06756629 0.06293682 0.62289541 0.74144022]]\n", + "\n", + " [[0.96883467 0.34792269 0.74718702 0.69030318 0.21635223]\n", + " [0.5203064 0.411508 0.46509676 0.16966541 0.07002832]\n", + " [0.43219317 0.77250002 0.56847303 0.64554749 0.50166846]]]\n" + ] + } + ], "source": [ - "# your code here" + "# your code here\n", + "print(a)" ] }, { @@ -95,11 +177,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "b = np.ones(shape =(5,2,3))" ] }, { @@ -111,11 +194,33 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[1. 1. 1.]\n", + " [1. 1. 1.]]\n", + "\n", + " [[1. 1. 1.]\n", + " [1. 1. 1.]]\n", + "\n", + " [[1. 1. 1.]\n", + " [1. 1. 1.]]\n", + "\n", + " [[1. 1. 1.]\n", + " [1. 1. 1.]]\n", + "\n", + " [[1. 1. 1.]\n", + " [1. 1. 1.]]]\n" + ] + } + ], + "source": [ + "# your code here\n", + "print(b)" ] }, { @@ -127,11 +232,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# your code here" + "# your code here\n", + "len(a) == len(b)" ] }, { @@ -143,11 +260,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ - "# your answer here" + "# your answer here \n", + "# no becasuse they have diferent sizes/shapes" ] }, { @@ -159,11 +277,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1., 1., 1., 1., 1.],\n", + " [1., 1., 1., 1., 1.],\n", + " [1., 1., 1., 1., 1.]],\n", + "\n", + " [[1., 1., 1., 1., 1.],\n", + " [1., 1., 1., 1., 1.],\n", + " [1., 1., 1., 1., 1.]]])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code here\n", + "c = b.reshape(2,3,5)\n", + "c" ] }, { @@ -175,11 +312,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ - "# your code/answer here" + "# your code/answer here\n", + "d = a+c" ] }, { @@ -191,11 +329,35 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code/answer here" + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[0.92329899 0.2735768 0.81071175 0.98780487 0.71475797]\n", + " [0.16613524 0.57792115 0.65555143 0.24400684 0.62367727]\n", + " [0.75472776 0.06756629 0.06293682 0.62289541 0.74144022]]\n", + "\n", + " [[0.96883467 0.34792269 0.74718702 0.69030318 0.21635223]\n", + " [0.5203064 0.411508 0.46509676 0.16966541 0.07002832]\n", + " [0.43219317 0.77250002 0.56847303 0.64554749 0.50166846]]]\n", + "[[[1.92329899 1.2735768 1.81071175 1.98780487 1.71475797]\n", + " [1.16613524 1.57792115 1.65555143 1.24400684 1.62367727]\n", + " [1.75472776 1.06756629 1.06293682 1.62289541 1.74144022]]\n", + "\n", + " [[1.96883467 1.34792269 1.74718702 1.69030318 1.21635223]\n", + " [1.5203064 1.411508 1.46509676 1.16966541 1.07002832]\n", + " [1.43219317 1.77250002 1.56847303 1.64554749 1.50166846]]]\n" + ] + } + ], + "source": [ + "# your code/answer here\n", + "print(a)\n", + "\n", + "print(d)" ] }, { @@ -207,11 +369,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.92329899, 0.2735768 , 0.81071175, 0.98780487, 0.71475797],\n", + " [0.16613524, 0.57792115, 0.65555143, 0.24400684, 0.62367727],\n", + " [0.75472776, 0.06756629, 0.06293682, 0.62289541, 0.74144022]],\n", + "\n", + " [[0.96883467, 0.34792269, 0.74718702, 0.69030318, 0.21635223],\n", + " [0.5203064 , 0.411508 , 0.46509676, 0.16966541, 0.07002832],\n", + " [0.43219317, 0.77250002, 0.56847303, 0.64554749, 0.50166846]]])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code here\n", + "e = a*c\n", + "e" ] }, { @@ -223,11 +404,29 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code/answer here" + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[ True, True, True, True, True],\n", + " [ True, True, True, True, True],\n", + " [ True, True, True, True, True]],\n", + "\n", + " [[ True, True, True, True, True],\n", + " [ True, True, True, True, True],\n", + " [ True, True, True, True, True]]])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code/answer here\n", + "a == e" ] }, { @@ -239,11 +438,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "d_max = np.max(d)\n", + "d_min = np.min(d)\n", + "d_mean = np.mean(d)" ] }, { @@ -255,11 +457,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "f= np.empty((2,3,5))\n" ] }, { @@ -275,11 +478,11 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "f= 25 * (d > d_min) * (d < d_mean) + 75 * (d < d_max) * (d > d_mean) + 0 * (d == d_min) + 100 * (d == d_max)" ] }, { @@ -309,11 +512,34 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[1.92329899 1.2735768 1.81071175 1.98780487 1.71475797]\n", + " [1.16613524 1.57792115 1.65555143 1.24400684 1.62367727]\n", + " [1.75472776 1.06756629 1.06293682 1.62289541 1.74144022]]\n", + "\n", + " [[1.96883467 1.34792269 1.74718702 1.69030318 1.21635223]\n", + " [1.5203064 1.411508 1.46509676 1.16966541 1.07002832]\n", + " [1.43219317 1.77250002 1.56847303 1.64554749 1.50166846]]]\n", + "[[[ 75 25 75 100 75]\n", + " [ 25 75 75 25 75]\n", + " [ 75 25 0 75 75]]\n", + "\n", + " [[ 75 25 75 75 25]\n", + " [ 25 25 25 25 25]\n", + " [ 25 75 75 75 25]]]\n" + ] + } + ], + "source": [ + "# your code here\n", + "print(d)\n", + "print(f)" ] }, { @@ -333,19 +559,43 @@ "**Note**: you don't have to use Numpy in this question." ] }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[ 75 25 75 100 75]\n", + " [ 25 75 75 25 75]\n", + " [ 75 25 0 75 75]]\n", + "\n", + " [[ 75 25 75 75 25]\n", + " [ 25 25 25 25 25]\n", + " [ 25 75 75 75 25]]]\n" + ] + } + ], + "source": [ + "# your code here\n", + "\n", + "print(f)\n", + " " + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "# your code here" - ] + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -359,7 +609,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.9.7" } }, "nbformat": 4,