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analysis.py v 1.2.1.001
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@ -7,10 +7,14 @@
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# current benchmark of optimization: 1.33 times faster
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# current benchmark of optimization: 1.33 times faster
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# setup:
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# setup:
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__version__ = "1.2.1.000"
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__version__ = "1.2.1.001"
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# changelog should be viewed using print(analysis.__changelog__)
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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__changelog__ = """changelog:
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1.2.1.001:
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- added add, mul, neg, and inv functions to ArrayTest class
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- added normalize function to ArrayTest class
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- added dot and cross functions to ArrayTest class
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1.2.1.000:
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1.2.1.000:
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- added ArrayTest class
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- added ArrayTest class
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- added elementwise mean, median, standard deviation, variance, min, max functions to ArrayTest class
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- added elementwise mean, median, standard deviation, variance, min, max functions to ArrayTest class
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@ -974,4 +978,44 @@ class ArrayTest(): # tests on nd arrays independent of basic_stats
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_min = self.elementwise_npmin(*args)
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_min = self.elementwise_npmin(*args)
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_max = self.elementwise_npmax(*args)
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_max = self.elementwise_npmax(*args)
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return _mean, _median, _stdev, _variance, _min, _max
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return _mean, _median, _stdev, _variance, _min, _max
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def normalize(self, array):
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a = np.atleast_1d(np.linalg.norm(array))
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a[a==0] = 1
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return array / np.expand_dims(a)
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def add(self, *args):
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temp = np.array([])
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for a in *args:
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temp += a
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return temp
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def mul(self, *args):
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temp = np.array([])
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for a in *args:
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temp *= a
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return temp
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def neg(self, array):
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return -array
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def inv(self, array):
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return 1/array
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def dot(self, a, b):
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return np.dot(a, b)
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def cross(self, a, b):
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return np.cross(a, b)
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