diff --git a/your-code/main.ipynb b/your-code/main.ipynb index e66d6ce..f00ede1 100644 --- a/your-code/main.ipynb +++ b/your-code/main.ipynb @@ -12,11 +12,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 76, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "import numpy as np\n" ] }, { @@ -28,11 +29,21 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.23.5\n" + ] + } + ], + "source": [ + "# your code here\n", + "\n", + "print(np.__version__)" ] }, { @@ -45,29 +56,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 78, "metadata": {}, "outputs": [], "source": [ - "# Method 1" + "# Method 1\n", + "myarraya = np.random.rand(2, 3, 5)\n", + "a = myarraya" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 79, "metadata": {}, "outputs": [], "source": [ - "# Method 2" + "# Method 2\n", + "#¿?" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 80, "metadata": {}, "outputs": [], "source": [ - "# Method 3" + "# Method 3\n", + "#¿?" ] }, { @@ -79,11 +94,29 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.9622012 , 0.68401175, 0.92129142, 0.21063041, 0.9531126 ],\n", + " [0.6448279 , 0.83191571, 0.57907917, 0.89587852, 0.41243569],\n", + " [0.98967683, 0.03546157, 0.25337469, 0.95921911, 0.15031784]],\n", + "\n", + " [[0.53010454, 0.13710341, 0.02179434, 0.21937253, 0.51261877],\n", + " [0.32979838, 0.57808173, 0.5667957 , 0.80159631, 0.96924552],\n", + " [0.28306735, 0.54886252, 0.45906404, 0.03135791, 0.49664123]]])" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code herea\n", + "a" ] }, { @@ -95,11 +128,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 82, "metadata": {}, "outputs": [], "source": [ - "# your code here" + "# your code here\n", + "myarrayb = np.ones((5, 2, 3))\n", + "\n", + "b = myarrayb" ] }, { @@ -111,11 +147,36 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[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.]]])" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code here\n", + "b" ] }, { @@ -127,11 +188,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 84, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "They are not equal\n" + ] + } + ], "source": [ - "# your code here" + "# your code here\n", + "if np.shape(a) == np.shape(b):\n", + " print(True)\n", + "else:\n", + " print(\"They are not equal\")" ] }, { @@ -143,11 +216,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 85, "metadata": {}, "outputs": [], "source": [ - "# your answer here" + "# your answer here\n", + "\n", + "# ab = a + b\n", + "# ab\n", + "\n", + "# Cannot add them because they don't have the same shape\n", + " # ValueError: operands could not be broadcast together with shapes (2,3,5) (5,2,3) " ] }, { @@ -159,11 +238,31 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.9622012 , 0.53010454, 0.68401175, 0.13710341, 0.92129142],\n", + " [0.02179434, 0.21063041, 0.21937253, 0.9531126 , 0.51261877],\n", + " [0.6448279 , 0.32979838, 0.83191571, 0.57808173, 0.57907917]],\n", + "\n", + " [[0.5667957 , 0.89587852, 0.80159631, 0.41243569, 0.96924552],\n", + " [0.98967683, 0.28306735, 0.03546157, 0.54886252, 0.25337469],\n", + " [0.45906404, 0.95921911, 0.03135791, 0.15031784, 0.49664123]]])" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code here\n", + "b = np.transpose(a, (1, 2, 0)).reshape(2, 3, 5)\n", + "c = b\n", + "c" ] }, { @@ -175,11 +274,32 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code/answer here" + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[1.9244024 , 1.21411629, 1.60530316, 0.34773382, 1.87440401],\n", + " [0.66662224, 1.04254612, 0.7984517 , 1.84899112, 0.92505446],\n", + " [1.63450473, 0.36525995, 1.0852904 , 1.53730085, 0.72939701]],\n", + "\n", + " [[1.09690025, 1.03298193, 0.82339065, 0.63180822, 1.48186428],\n", + " [1.31947521, 0.86114909, 0.60225727, 1.35045883, 1.22262021],\n", + " [0.74213139, 1.50808163, 0.49042195, 0.18167575, 0.99328245]]])" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code/answer here\n", + "d = a + c\n", + "d\n", + "\n", + "# It works now because they are the same shape" ] }, { @@ -191,11 +311,37 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code/answer here" + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[0.9622012 0.68401175 0.92129142 0.21063041 0.9531126 ]\n", + " [0.6448279 0.83191571 0.57907917 0.89587852 0.41243569]\n", + " [0.98967683 0.03546157 0.25337469 0.95921911 0.15031784]]\n", + "\n", + " [[0.53010454 0.13710341 0.02179434 0.21937253 0.51261877]\n", + " [0.32979838 0.57808173 0.5667957 0.80159631 0.96924552]\n", + " [0.28306735 0.54886252 0.45906404 0.03135791 0.49664123]]]\n", + " \n", + "[[[1.9244024 1.21411629 1.60530316 0.34773382 1.87440401]\n", + " [0.66662224 1.04254612 0.7984517 1.84899112 0.92505446]\n", + " [1.63450473 0.36525995 1.0852904 1.53730085 0.72939701]]\n", + "\n", + " [[1.09690025 1.03298193 0.82339065 0.63180822 1.48186428]\n", + " [1.31947521 0.86114909 0.60225727 1.35045883 1.22262021]\n", + " [0.74213139 1.50808163 0.49042195 0.18167575 0.99328245]]]\n" + ] + } + ], + "source": [ + "# your code/answer here\n", + "print(a)\n", + "print(\" \")\n", + "print(d)\n", + "# that they are both floats?" ] }, { @@ -207,11 +353,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.9622012 , 0.53010454, 0.68401175, 0.13710341, 0.92129142],\n", + " [0.02179434, 0.21063041, 0.21937253, 0.9531126 , 0.51261877],\n", + " [0.6448279 , 0.32979838, 0.83191571, 0.57808173, 0.57907917]],\n", + "\n", + " [[0.5667957 , 0.89587852, 0.80159631, 0.41243569, 0.96924552],\n", + " [0.98967683, 0.28306735, 0.03546157, 0.54886252, 0.25337469],\n", + " [0.45906404, 0.95921911, 0.03135791, 0.15031784, 0.49664123]]])" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code here\n", + "e = a * c\n", + "c" ] }, { @@ -223,11 +388,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code/answer here" + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[False, False, False, False, False],\n", + " [False, False, False, False, False],\n", + " [False, False, False, False, False]],\n", + "\n", + " [[False, False, False, False, False],\n", + " [False, False, False, False, False],\n", + " [False, False, False, False, False]]])" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code/answer here\n", + "e == a\n", + "#ttey don't have the same values" ] }, { @@ -239,11 +423,28 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.9244023966818753\n", + "0.181675752341653\n", + "1.0645959118302344\n" + ] + } + ], + "source": [ + "# your code here\n", + "d_max = np.max(d)\n", + "d_min = np.min(d)\n", + "d_mean = np.mean(d)\n", + "\n", + "print(d_max)\n", + "print(d_min)\n", + "print(d_mean)" ] }, { @@ -255,11 +456,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[0.9622012 , 0.53010454, 0.68401175, 0.13710341, 0.92129142],\n", + " [0.02179434, 0.21063041, 0.21937253, 0.9531126 , 0.51261877],\n", + " [0.6448279 , 0.32979838, 0.83191571, 0.57808173, 0.57907917]],\n", + "\n", + " [[0.5667957 , 0.89587852, 0.80159631, 0.41243569, 0.96924552],\n", + " [0.98967683, 0.28306735, 0.03546157, 0.54886252, 0.25337469],\n", + " [0.45906404, 0.95921911, 0.03135791, 0.15031784, 0.49664123]]])" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# your code here\n", + "f = np.empty((2,3,5))\n", + "f" ] }, { @@ -275,11 +495,43 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "# your code here" + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[[1.9244024 1.21411629 1.60530316 0.34773382 1.87440401]\n", + " [0.66662224 1.04254612 0.7984517 1.84899112 0.92505446]\n", + " [1.63450473 0.36525995 1.0852904 1.53730085 0.72939701]]\n", + "\n", + " [[1.09690025 1.03298193 0.82339065 0.63180822 1.48186428]\n", + " [1.31947521 0.86114909 0.60225727 1.35045883 1.22262021]\n", + " [0.74213139 1.50808163 0.49042195 0.18167575 0.99328245]]]\n", + " \n", + "[[[100. 75. 75. 25. 75.]\n", + " [ 25. 25. 25. 75. 25.]\n", + " [ 75. 25. 75. 75. 25.]]\n", + "\n", + " [[ 75. 25. 25. 25. 75.]\n", + " [ 75. 25. 25. 75. 75.]\n", + " [ 25. 75. 25. 0. 25.]]]\n" + ] + } + ], + "source": [ + "# your code here\n", + "\n", + "f[(d > d_min) & (d < d_mean)] = 25\n", + "f[(d > d_mean) & (d < d_max)] = 75\n", + "f[d == d_mean] = 50\n", + "f[d == d_min] = 0\n", + "f[d == d_max] = 100\n", + "\n", + "print(d)\n", + "print(\" \")\n", + "print(f)\n" ] }, { @@ -309,7 +561,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 94, "metadata": {}, "outputs": [], "source": [ @@ -335,7 +587,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 95, "metadata": {}, "outputs": [], "source": [ @@ -359,7 +611,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.10.9" } }, "nbformat": 4,