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import apoor |
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3
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import pytest |
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4
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5
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6
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def test_make_scale(): |
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7
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assert apoor.make_scale(0,1,0,10)(0.1) == 1 |
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8
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assert apoor.make_scale(10,0,0,1)(9) == 0.1 |
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9
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assert apoor.make_scale(0,1,0,1,True)(-1) == 0 |
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10
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assert apoor.make_scale(0,1,0,10,True)(11) == 10 |
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11
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12
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def test_set_seed(): |
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13
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np = apoor.np |
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14
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n = 0 |
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15
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apoor.set_seed(n) |
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16
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a = np.random.random() |
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assert a != np.random.random() or a != np.random.random() |
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apoor.set_seed(n) |
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19
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b = np.random.random() |
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20
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assert a == b |
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21
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22
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23
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def test_train_test_split(): |
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24
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# Getting started |
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25
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np = apoor.np |
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x = np.arange(10) |
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y = x[::-1] |
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z = np.arange(0,20,2) |
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29
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### Test 1 ### |
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30
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x_train = np.array([2,8,4,9,1,6,7,3,0]) |
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31
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x_test = np.array([5]) |
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32
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apoor.set_seed(0) |
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33
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result = apoor.train_test_split(x) |
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34
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assert ( |
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(result[0] == x_train).all() and |
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(result[1] == x_test).all() |
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) |
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38
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### Test 2 ### |
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39
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y_train = np.array([7,1,5,0,8,3,2,6,9]) |
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40
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y_test = np.array([4]) |
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41
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apoor.set_seed(0) |
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42
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result = apoor.train_test_split(x,y) |
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43
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assert ( |
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(result[0] == x_train).all() and |
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(result[1] == x_test ).all() and |
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46
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(result[2] == y_train).all() and |
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(result[3] == y_test ).all() |
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48
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) |
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### Test 3 ### |
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50
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z_train = np.array([4,16,8,18,2,12,14,6,0]) |
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z_test = np.array([10]) |
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apoor.set_seed(0) |
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result = apoor.train_test_split(x,y,z) |
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54
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assert ( |
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(result[0] == x_train).all() and |
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56
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(result[1] == x_test ).all() and |
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57
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(result[2] == y_train).all() and |
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58
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(result[3] == y_test ).all() and |
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59
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(result[4] == z_train).all() and |
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60
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(result[5] == z_test ).all() |
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61
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) |
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62
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63
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def test_ibuff(): |
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64
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assert list(apoor.ibuff(range(10))) == \ |
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[[i] for i in range(10)] |
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assert list(apoor.ibuff(range(10),2)) == \ |
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67
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[[i,i+1] for i in range(0,10,2)] |
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68
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with pytest.raises(TypeError) as e_info: |
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69
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apoor.ibuff(range(10),1.0) |
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70
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with pytest.raises(ValueError) as e_info: |
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71
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apoor.ibuff(range(10),0) |
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72
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73
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74
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75
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a-poor /
apoor
