mirror of
https://github.com/titanscouting/tra-analysis.git
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Merge pull request #31 from titanscout2022/master
merge changes from master into tra-service
This commit is contained in:
Arthur Lu
GitHub
commit
5e52155fd0
@ -7,10 +7,28 @@
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# current benchmark of optimization: 1.33 times faster
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# setup:
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__version__ = "1.2.1.003"
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__version__ = "1.2.2.000"
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# changelog should be viewed using print(analysis.__changelog__)
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__changelog__ = """changelog:
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1.2.2.000:
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- added Sort class
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- added several array sorting functions to Sort class including:
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- quick sort
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- merge sort
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- intro(spective) sort
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- heap sort
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- insertion sort
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- tim sort
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- selection sort
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- bubble sort
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- cycle sort
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- cocktail sort
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- tested all sorting algorithms with both lists and numpy arrays
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- depreciated sort function from Array class
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- added warnings as an import
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1.2.1.004:
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- added sort and search functions to Array class
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1.2.1.003:
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- changed output of basic_stats and histo_analysis to libraries
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- fixed __all__
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@ -338,6 +356,7 @@ from scipy import optimize, stats
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import sklearn
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from sklearn import preprocessing, pipeline, linear_model, metrics, cluster, decomposition, tree, neighbors, naive_bayes, svm, model_selection, ensemble
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from analysis.metrics import trueskill as Trueskill
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import warnings
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class error(ValueError):
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pass
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@ -1031,4 +1050,438 @@ class Array(): # tests on nd arrays independent of basic_stats
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def cross(self, a, b):
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return np.cross(a, b)
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return np.cross(a, b)
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def sort(self, array): # depreciated
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warnings.warn("Array.sort has been depreciated in favor of Sort")
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array_length = len(array)
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if array_length <= 1:
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return array
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middle_index = int(array_length / 2)
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left = array[0:middle_index]
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right = array[middle_index:]
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left = self.sort(left)
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right = self.sort(right)
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return self.__merge(left, right)
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def __merge(self, left, right):
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sorted_list = []
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left = left[:]
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right = right[:]
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while len(left) > 0 or len(right) > 0:
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if len(left) > 0 and len(right) > 0:
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if left[0] <= right[0]:
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sorted_list.append(left.pop(0))
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else:
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sorted_list.append(right.pop(0))
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elif len(left) > 0:
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sorted_list.append(left.pop(0))
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elif len(right) > 0:
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sorted_list.append(right.pop(0))
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return sorted_list
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def search(self, arr, x):
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return self.__search(arr, 0, len(arr) - 1, x)
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def __search(self, arr, low, high, x):
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if high >= low:
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mid = (high + low) // 2
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if arr[mid] == x:
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return mid
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elif arr[mid] > x:
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return binary_search(arr, low, mid - 1, x)
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else:
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return binary_search(arr, mid + 1, high, x)
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else:
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return -1
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class Sort: # if you haven't used a sort, then you've never lived
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def quicksort(self, a):
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def sort(array):
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less = []
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equal = []
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greater = []
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if len(array) > 1:
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pivot = array[0]
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for x in array:
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if x < pivot:
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less.append(x)
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elif x == pivot:
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equal.append(x)
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elif x > pivot:
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greater.append(x)
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return sort(less)+equal+sort(greater)
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else:
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return array
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return np.array(sort(a))
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def mergesort(self, a):
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def sort(array):
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array = array
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if len(array) >1:
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middle = len(array) // 2
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L = array[:middle]
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R = array[middle:]
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sort(L)
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sort(R)
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i = j = k = 0
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while i < len(L) and j < len(R):
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if L[i] < R[j]:
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array[k] = L[i]
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i+= 1
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else:
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array[k] = R[j]
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j+= 1
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k+= 1
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while i < len(L):
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array[k] = L[i]
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i+= 1
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k+= 1
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while j < len(R):
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array[k] = R[j]
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j+= 1
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k+= 1
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return array
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return sort(a)
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def introsort(self, a):
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def sort(array, start, end, maxdepth):
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array = array
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if end - start <= 1:
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return
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elif maxdepth == 0:
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heapsort(array, start, end)
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else:
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p = partition(array, start, end)
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sort(array, start, p + 1, maxdepth - 1)
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sort(array, p + 1, end, maxdepth - 1)
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return array
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def partition(array, start, end):
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pivot = array[start]
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i = start - 1
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j = end
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while True:
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i = i + 1
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while array[i] < pivot:
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i = i + 1
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j = j - 1
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while array[j] > pivot:
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j = j - 1
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if i >= j:
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return j
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swap(array, i, j)
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def swap(array, i, j):
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array[i], array[j] = array[j], array[i]
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def heapsort(array, start, end):
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build_max_heap(array, start, end)
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for i in range(end - 1, start, -1):
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swap(array, start, i)
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max_heapify(array, index=0, start=start, end=i)
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def build_max_heap(array, start, end):
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def parent(i):
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return (i - 1)//2
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length = end - start
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index = parent(length - 1)
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while index >= 0:
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max_heapify(array, index, start, end)
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index = index - 1
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def max_heapify(array, index, start, end):
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def left(i):
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return 2*i + 1
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def right(i):
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return 2*i + 2
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size = end - start
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l = left(index)
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r = right(index)
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if (l < size and array[start + l] > array[start + index]):
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largest = l
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else:
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largest = index
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if (r < size and array[start + r] > array[start + largest]):
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largest = r
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if largest != index:
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swap(array, start + largest, start + index)
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max_heapify(array, largest, start, end)
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maxdepth = (len(a).bit_length() - 1)*2
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return sort(a, 0, len(a), maxdepth)
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def heapsort(self, a):
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def sort(array):
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array = array
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n = len(array)
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for i in range(n//2 - 1, -1, -1):
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heapify(array, n, i)
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for i in range(n-1, 0, -1):
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array[i], array[0] = array[0], array[i]
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heapify(array, i, 0)
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return array
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def heapify(array, n, i):
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array = array
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largest = i
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l = 2 * i + 1
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r = 2 * i + 2
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if l < n and array[i] < array[l]:
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largest = l
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if r < n and array[largest] < array[r]:
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largest = r
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if largest != i:
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array[i],array[largest] = array[largest],array[i]
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heapify(array, n, largest)
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return array
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return sort(a)
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def insertionsort(self, a):
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def sort(array):
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array = array
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for i in range(1, len(array)):
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key = array[i]
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j = i-1
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while j >=0 and key < array[j] :
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array[j+1] = array[j]
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j -= 1
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array[j+1] = key
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return array
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return sort(a)
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def timsort(self, a, block = 32):
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BLOCK = block
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def sort(array, n):
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array = array
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for i in range(0, n, BLOCK):
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insertionsort(array, i, min((i+31), (n-1)))
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size = BLOCK
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while size < n:
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for left in range(0, n, 2*size):
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mid = left + size - 1
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right = min((left + 2*size - 1), (n-1))
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merge(array, left, mid, right)
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size = 2*size
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return array
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def insertionsort(array, left, right):
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array = array
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for i in range(left + 1, right+1):
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temp = array[i]
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j = i - 1
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while j >= left and array[j] > temp :
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array[j+1] = array[j]
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j -= 1
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array[j+1] = temp
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return array
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def merge(array, l, m, r):
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len1, len2 = m - l + 1, r - m
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left, right = [], []
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for i in range(0, len1):
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left.append(array[l + i])
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for i in range(0, len2):
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right.append(array[m + 1 + i])
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i, j, k = 0, 0, l
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while i < len1 and j < len2:
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if left[i] <= right[j]:
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array[k] = left[i]
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i += 1
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else:
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array[k] = right[j]
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j += 1
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k += 1
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while i < len1:
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array[k] = left[i]
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k += 1
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i += 1
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while j < len2:
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array[k] = right[j]
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k += 1
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j += 1
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return sort(a, len(a))
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def selectionsort(self, a):
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array = a
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for i in range(len(array)):
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min_idx = i
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for j in range(i+1, len(array)):
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if array[min_idx] > array[j]:
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min_idx = j
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array[i], array[min_idx] = array[min_idx], array[i]
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return array
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def shellsort(self, a):
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array = a
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n = len(array)
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gap = n//2
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while gap > 0:
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for i in range(gap,n):
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temp = array[i]
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j = i
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while j >= gap and array[j-gap] >temp:
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array[j] = array[j-gap]
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j -= gap
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array[j] = temp
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gap //= 2
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return array
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def bubblesort(self, a):
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def sort(array):
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for i, num in enumerate(array):
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try:
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if array[i+1] < num:
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array[i] = array[i+1]
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array[i+1] = num
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sort(array)
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except IndexError:
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pass
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return array
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return sort(a)
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def cyclesort(self, a):
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def sort(array):
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array = array
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writes = 0
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for cycleStart in range(0, len(array) - 1):
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item = array[cycleStart]
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pos = cycleStart
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for i in range(cycleStart + 1, len(array)):
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if array[i] < item:
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pos += 1
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if pos == cycleStart:
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continue
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while item == array[pos]:
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pos += 1
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array[pos], item = item, array[pos]
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writes += 1
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while pos != cycleStart:
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pos = cycleStart
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for i in range(cycleStart + 1, len(array)):
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if array[i] < item:
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pos += 1
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while item == array[pos]:
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pos += 1
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array[pos], item = item, array[pos]
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writes += 1
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return array
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return sort(a)
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def cocktailsort(self, a):
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def sort(array):
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array = array
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n = len(array)
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swapped = True
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start = 0
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end = n-1
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while (swapped == True):
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swapped = False
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for i in range (start, end):
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if (array[i] > array[i + 1]) :
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array[i], array[i + 1]= array[i + 1], array[i]
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swapped = True
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if (swapped == False):
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break
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swapped = False
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end = end-1
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for i in range(end-1, start-1, -1):
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if (array[i] > array[i + 1]):
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array[i], array[i + 1] = array[i + 1], array[i]
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swapped = True
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start = start + 1
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return array
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return sort(a)
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@ -5,6 +5,8 @@ def test_():
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test_data_linear = [1, 3, 6, 7, 9]
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y_data_ccu = [1, 3, 7, 14, 21]
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y_data_ccd = [1, 5, 7, 8.5, 8.66]
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test_data_scrambled = [-32, 34, 19, 72, -65, -11, -43, 6, 85, -17, -98, -26, 12, 20, 9, -92, -40, 98, -78, 17, -20, 49, 93, -27, -24, -66, 40, 84, 1, -64, -68, -25, -42, -46, -76, 43, -3, 30, -14, -34, -55, -13, 41, -30, 0, -61, 48, 23, 60, 87, 80, 77, 53, 73, 79, 24, -52, 82, 8, -44, 65, 47, -77, 94, 7, 37, -79, 36, -94, 91, 59, 10, 97, -38, -67, 83, 54, 31, -95, -63, 16, -45, 21, -12, 66, -48, -18, -96, -90, -21, -83, -74, 39, 64, 69, -97, 13, 55, 27, -39]
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test_data_sorted = [-98, -97, -96, -95, -94, -92, -90, -83, -79, -78, -77, -76, -74, -68, -67, -66, -65, -64, -63, -61, -55, -52, -48, -46, -45, -44, -43, -42, -40, -39, -38, -34, -32, -30, -27, -26, -25, -24, -21, -20, -18, -17, -14, -13, -12, -11, -3, 0, 1, 6, 7, 8, 9, 10, 12, 13, 16, 17, 19, 20, 21, 23, 24, 27, 30, 31, 34, 36, 37, 39, 40, 41, 43, 47, 48, 49, 53, 54, 55, 59, 60, 64, 65, 66, 69, 72, 73, 77, 79, 80, 82, 83, 84, 85, 87, 91, 93, 94, 97, 98]
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assert an.basic_stats(test_data_linear) == {"mean": 5.2, "median": 6.0, "standard-deviation": 2.85657137141714, "variance": 8.16, "minimum": 1.0, "maximum": 9.0}
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assert an.z_score(3.2, 6, 1.5) == -1.8666666666666665
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assert an.z_normalize([test_data_linear], 1).tolist() == [[0.07537783614444091, 0.22613350843332272, 0.45226701686664544, 0.5276448530110863, 0.6784005252999682]]
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@ -15,4 +17,15 @@ def test_():
|
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#assert all(isinstance(item, str) for item in an.regression(test_data_linear, y_data_ccd, ["sig"])) == True
|
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assert an.Metric().elo(1500, 1500, [1, 0], 400, 24) == 1512.0
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assert an.Metric().glicko2(1500, 250, 0.06, [1500, 1400], [250, 240], [1, 0]) == (1478.864307445517, 195.99122679202452, 0.05999602937563585)
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#assert an.Metric().trueskill([[(25, 8.33), (24, 8.25), (32, 7.5)], [(25, 8.33), (25, 8.33), (21, 6.5)]], [1, 0]) == [(metrics.trueskill.Rating(mu=21.346, sigma=7.875), metrics.trueskill.Rating(mu=20.415, sigma=7.808), metrics.trueskill.Rating(mu=29.037, sigma=7.170)), (metrics.trueskill.Rating(mu=28.654, sigma=7.875), metrics.trueskill.Rating(mu=28.654, sigma=7.875), metrics.trueskill.Rating(mu=23.225, sigma=6.287))]
|
||||
#assert an.Metric().trueskill([[(25, 8.33), (24, 8.25), (32, 7.5)], [(25, 8.33), (25, 8.33), (21, 6.5)]], [1, 0]) == [(metrics.trueskill.Rating(mu=21.346, sigma=7.875), metrics.trueskill.Rating(mu=20.415, sigma=7.808), metrics.trueskill.Rating(mu=29.037, sigma=7.170)), (metrics.trueskill.Rating(mu=28.654, sigma=7.875), metrics.trueskill.Rating(mu=28.654, sigma=7.875), metrics.trueskill.Rating(mu=23.225, sigma=6.287))]
|
||||
assert all(a == b for a, b in zip(an.Sort().quicksort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().mergesort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().introsort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().heapsort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().insertionsort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().timsort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().selectionsort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().shellsort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().bubblesort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().cyclesort(test_data_scrambled), test_data_sorted))
|
||||
assert all(a == b for a, b in zip(an.Sort().cocktailsort(test_data_scrambled), test_data_sorted))
|
||||
55
data-analysis/test.py
Normal file
55
data-analysis/test.py
Normal file
@ -0,0 +1,55 @@
|
||||
import threading
|
||||
from multiprocessing import Process, Queue
|
||||
import time
|
||||
from os import system
|
||||
|
||||
class testcls():
|
||||
|
||||
i = 0
|
||||
j = 0
|
||||
|
||||
t1_en = True
|
||||
t2_en = True
|
||||
|
||||
def main(self):
|
||||
t1 = Process(name = "task1", target = self.task1)
|
||||
t2 = Process(name = "task2", target = self.task2)
|
||||
t1.start()
|
||||
t2.start()
|
||||
#print(self.i)
|
||||
#print(self.j)
|
||||
|
||||
def task1(self):
|
||||
self.i += 1
|
||||
time.sleep(1)
|
||||
if(self.i < 10):
|
||||
t1 = Process(name = "task1", target = self.task1)
|
||||
t1.start()
|
||||
|
||||
def task2(self):
|
||||
self.j -= 1
|
||||
time.sleep(1)
|
||||
if(self.j > -10):
|
||||
t2 = t2 = Process(name = "task2", target = self.task2)
|
||||
t2.start()
|
||||
"""
|
||||
if __name__ == "__main__":
|
||||
|
||||
tmain = threading.Thread(name = "main", target = main)
|
||||
tmain.start()
|
||||
|
||||
t = 0
|
||||
while(True):
|
||||
system("clear")
|
||||
for thread in threading.enumerate():
|
||||
if thread.getName() != "MainThread":
|
||||
print(thread.getName())
|
||||
print(str(len(threading.enumerate())))
|
||||
print(i)
|
||||
print(j)
|
||||
time.sleep(0.1)
|
||||
t += 1
|
||||
if(t == 100):
|
||||
t1_en = False
|
||||
t2_en = False
|
||||
"""
|
||||
Loading…
Reference in New Issue
Block a user