mirror of
https://github.com/titanscouting/tra-analysis.git
synced 2024-12-26 01:29:10 +00:00
analysis.py v 1.2.1.001
This commit is contained in:
parent
db8fbbf068
commit
24f8961500
@ -7,10 +7,14 @@
|
|||||||
# current benchmark of optimization: 1.33 times faster
|
# current benchmark of optimization: 1.33 times faster
|
||||||
# setup:
|
# setup:
|
||||||
|
|
||||||
__version__ = "1.2.1.000"
|
__version__ = "1.2.1.001"
|
||||||
|
|
||||||
# changelog should be viewed using print(analysis.__changelog__)
|
# changelog should be viewed using print(analysis.__changelog__)
|
||||||
__changelog__ = """changelog:
|
__changelog__ = """changelog:
|
||||||
|
1.2.1.001:
|
||||||
|
- added add, mul, neg, and inv functions to ArrayTest class
|
||||||
|
- added normalize function to ArrayTest class
|
||||||
|
- added dot and cross functions to ArrayTest class
|
||||||
1.2.1.000:
|
1.2.1.000:
|
||||||
- added ArrayTest class
|
- added ArrayTest class
|
||||||
- added elementwise mean, median, standard deviation, variance, min, max functions to ArrayTest class
|
- added elementwise mean, median, standard deviation, variance, min, max functions to ArrayTest class
|
||||||
@ -975,3 +979,43 @@ class ArrayTest(): # tests on nd arrays independent of basic_stats
|
|||||||
_max = self.elementwise_npmax(*args)
|
_max = self.elementwise_npmax(*args)
|
||||||
|
|
||||||
return _mean, _median, _stdev, _variance, _min, _max
|
return _mean, _median, _stdev, _variance, _min, _max
|
||||||
|
|
||||||
|
def normalize(self, array):
|
||||||
|
|
||||||
|
a = np.atleast_1d(np.linalg.norm(array))
|
||||||
|
a[a==0] = 1
|
||||||
|
return array / np.expand_dims(a)
|
||||||
|
|
||||||
|
def add(self, *args):
|
||||||
|
|
||||||
|
temp = np.array([])
|
||||||
|
|
||||||
|
for a in *args:
|
||||||
|
temp += a
|
||||||
|
|
||||||
|
return temp
|
||||||
|
|
||||||
|
def mul(self, *args):
|
||||||
|
|
||||||
|
temp = np.array([])
|
||||||
|
|
||||||
|
for a in *args:
|
||||||
|
temp *= a
|
||||||
|
|
||||||
|
return temp
|
||||||
|
|
||||||
|
def neg(self, array):
|
||||||
|
|
||||||
|
return -array
|
||||||
|
|
||||||
|
def inv(self, array):
|
||||||
|
|
||||||
|
return 1/array
|
||||||
|
|
||||||
|
def dot(self, a, b):
|
||||||
|
|
||||||
|
return np.dot(a, b)
|
||||||
|
|
||||||
|
def cross(self, a, b):
|
||||||
|
|
||||||
|
return np.cross(a, b)
|
Loading…
Reference in New Issue
Block a user