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aula_06.ipynb

Lines changed: 19 additions & 46 deletions
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@@ -18,7 +18,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 3,
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"id": "97fd8eb7",
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"metadata": {},
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"outputs": [],
@@ -68,13 +68,13 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 7,
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"id": "e603fd22",
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"metadata": {},
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"outputs": [],
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"source": [
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"a = np.array([1, 3, 4])\n",
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"b = np.array([2, 2, 2])"
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"a = np.array([2, 3, 1])\n",
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"b = np.array([4, 5, 7])"
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]
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},
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{
@@ -87,23 +87,21 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 8,
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"id": "4ffd2bd9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([-2, 6, -4])"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[ 16 -10 -2]\n"
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]
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}
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],
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"source": [
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"np.cross(a, b)"
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"v = np.cross(a, b)\n",
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"print(v)"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 14,
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"id": "5147948e",
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"metadata": {},
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"outputs": [],
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 15,
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"id": "781529c1",
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"metadata": {},
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"outputs": [
@@ -156,46 +154,21 @@
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" [-2, 6, -4]])"
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]
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},
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"execution_count": 7,
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.cross(a, b)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6d6d2944",
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"metadata": {},
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"source": [
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"- ##### Criando as matrizes 3D"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "88939389",
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"metadata": {},
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"outputs": [],
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"source": [
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"a = np.array([[[1, 3, 4], [1, 3, 4]]])\n",
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"b = np.array([[2, 2, 2], [2, 2, 2]])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "dfe04ce6",
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"metadata": {},
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"source": [
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"#### Encontrando o Produto Escalar com o Método np.dot() do NumPy"
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"v2 = np.cross(a, b)\n",
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"\n",
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"v2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c08ff8c4",
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"id": "eca48d45",
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"metadata": {},
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"outputs": [],
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"source": []

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