Merge pull request #31 from titanscout2022/master

merge changes from master into tra-service

analysis-master/analysis/analysis.py

@@ -7,10 +7,28 @@
 #    current benchmark of optimization: 1.33 times faster
 # setup:
 
-__version__ = "1.2.1.003"
+__version__ = "1.2.2.000"
 
 # changelog should be viewed using print(analysis.__changelog__)
 __changelog__ = """changelog:
+	1.2.2.000:
+		- added Sort class
+		- added several array sorting functions to Sort class including:
+			- quick sort
+			- merge sort
+			- intro(spective) sort
+			- heap sort
+			- insertion sort
+			- tim sort
+			- selection sort
+			- bubble sort
+			- cycle sort
+			- cocktail sort
+		- tested all sorting algorithms with both lists and numpy arrays
+		- depreciated sort function from Array class
+		- added warnings as an import
+	1.2.1.004:
+		- added sort and search functions to Array class
 	1.2.1.003:
 		- changed output of basic_stats and histo_analysis to libraries
 		- fixed __all__
@@ -338,6 +356,7 @@ from scipy import optimize, stats
 import sklearn
 from sklearn import preprocessing, pipeline, linear_model, metrics, cluster, decomposition, tree, neighbors, naive_bayes, svm, model_selection, ensemble
 from analysis.metrics import trueskill as Trueskill
+import warnings
 
 class error(ValueError):
 	pass
@@ -1032,3 +1051,437 @@ class Array(): # tests on nd arrays independent of basic_stats
 	def cross(self, a, b):
 
 		return np.cross(a, b)
+
+	def sort(self, array): # depreciated
+		warnings.warn("Array.sort has been depreciated in favor of Sort")
+		array_length = len(array)
+		if array_length <= 1:
+			return array
+		middle_index = int(array_length / 2)
+		left = array[0:middle_index]
+		right = array[middle_index:]
+		left = self.sort(left)
+		right = self.sort(right)
+		return self.__merge(left, right)
+
+
+	def __merge(self, left, right):
+		sorted_list = []
+		left = left[:]
+		right = right[:]
+		while len(left) > 0 or len(right) > 0:
+			if len(left) > 0 and len(right) > 0:
+				if left[0] <= right[0]:
+					sorted_list.append(left.pop(0))
+				else:
+					sorted_list.append(right.pop(0))
+			elif len(left) > 0:
+				sorted_list.append(left.pop(0))
+			elif len(right) > 0:
+				sorted_list.append(right.pop(0))
+		return sorted_list
+
+	def search(self, arr, x):
+		return self.__search(arr, 0, len(arr) - 1, x)
+
+	def __search(self, arr, low, high, x): 
+		if high >= low: 
+			mid = (high + low) // 2
+			if arr[mid] == x: 
+				return mid 
+			elif arr[mid] > x: 
+				return binary_search(arr, low, mid - 1, x) 
+			else: 
+				return binary_search(arr, mid + 1, high, x) 
+		else:
+			return -1
+
+class Sort: # if you haven't used a sort, then you've never lived
+
+	def quicksort(self, a):
+
+		def sort(array):
+
+			less = []
+			equal = []
+			greater = []
+
+			if len(array) > 1:
+				pivot = array[0]
+				for x in array:
+					if x < pivot:
+						less.append(x)
+					elif x == pivot:
+						equal.append(x)
+					elif x > pivot:
+						greater.append(x)
+				return sort(less)+equal+sort(greater) 
+			else:
+				return array
+
+		return np.array(sort(a))
+
+	def mergesort(self, a):
+
+		def sort(array):
+
+			array = array
+
+			if len(array) >1: 
+				middle = len(array) // 2
+				L = array[:middle]
+				R = array[middle:]
+		
+				sort(L)
+				sort(R)
+		
+				i = j = k = 0
+
+				while i < len(L) and j < len(R): 
+					if L[i] < R[j]: 
+						array[k] = L[i] 
+						i+= 1
+					else: 
+						array[k] = R[j] 
+						j+= 1
+					k+= 1
+
+				while i < len(L): 
+					array[k] = L[i] 
+					i+= 1
+					k+= 1
+				
+				while j < len(R): 
+					array[k] = R[j] 
+					j+= 1
+					k+= 1
+
+				return array
+
+		return sort(a)
+
+	def introsort(self, a):
+
+		def sort(array, start, end, maxdepth):
+
+			array = array
+
+			if end - start <= 1:
+				return
+			elif maxdepth == 0:
+				heapsort(array, start, end)
+			else:
+				p = partition(array, start, end)
+				sort(array, start, p + 1, maxdepth - 1)
+				sort(array, p + 1, end, maxdepth - 1)
+
+			return array
+
+		def partition(array, start, end):
+			pivot = array[start]
+			i = start - 1
+			j = end
+		
+			while True:
+				i = i + 1
+				while array[i] < pivot:
+					i = i + 1
+				j = j - 1
+				while array[j] > pivot:
+					j = j - 1
+		
+				if i >= j:
+					return j
+		
+				swap(array, i, j)
+
+		def swap(array, i, j):
+			array[i], array[j] = array[j], array[i]
+
+		def heapsort(array, start, end):
+			build_max_heap(array, start, end)
+			for i in range(end - 1, start, -1):
+				swap(array, start, i)
+				max_heapify(array, index=0, start=start, end=i)
+
+		def build_max_heap(array, start, end):
+			def parent(i):
+				return (i - 1)//2
+			length = end - start
+			index = parent(length - 1)
+			while index >= 0:
+				max_heapify(array, index, start, end)
+				index = index - 1
+
+		def max_heapify(array, index, start, end):
+			def left(i):
+				return 2*i + 1
+			def right(i):
+				return 2*i + 2
+		
+			size = end - start
+			l = left(index)
+			r = right(index)
+			if (l < size and array[start + l] > array[start + index]):
+				largest = l
+			else:
+				largest = index
+			if (r < size and array[start + r] > array[start + largest]):
+				largest = r
+			if largest != index:
+				swap(array, start + largest, start + index)
+				max_heapify(array, largest, start, end)
+
+		maxdepth = (len(a).bit_length() - 1)*2
+
+		return sort(a, 0, len(a), maxdepth)
+
+	def heapsort(self, a):
+
+		def sort(array):
+			
+			array = array
+
+			n = len(array) 
+ 
+			for i in range(n//2 - 1, -1, -1): 
+				heapify(array, n, i) 
+
+			for i in range(n-1, 0, -1): 
+				array[i], array[0] = array[0], array[i]
+				heapify(array, i, 0) 
+
+			return array
+
+		def heapify(array, n, i):
+
+			array = array
+
+			largest = i
+			l = 2 * i + 1
+			r = 2 * i + 2
+
+			if l < n and array[i] < array[l]: 
+				largest = l 
+
+			if r < n and array[largest] < array[r]: 
+				largest = r 
+
+			if largest != i: 
+				array[i],array[largest] = array[largest],array[i]
+				heapify(array, n, largest)
+			
+			return array
+
+		return sort(a)
+
+	def insertionsort(self, a):
+
+		def sort(array):
+
+			array = array
+
+			for i in range(1, len(array)): 
+		
+				key = array[i] 
+
+				j = i-1
+				while j >=0 and key < array[j] : 
+						array[j+1] = array[j] 
+						j -= 1
+				array[j+1] = key 
+
+			return array
+
+		return sort(a)
+
+	def timsort(self, a, block = 32):
+
+		BLOCK = block
+
+		def sort(array, n):
+
+			array = array
+
+			for i in range(0, n, BLOCK):  
+				insertionsort(array, i, min((i+31), (n-1)))
+
+			size = BLOCK 
+			while size < n:
+
+				for left in range(0, n, 2*size):  
+	 
+					mid = left + size - 1 
+					right = min((left + 2*size - 1), (n-1))  
+					merge(array, left, mid, right)  
+		  
+				size = 2*size
+
+			return array
+
+		def insertionsort(array, left, right):
+
+			array = array 
+   
+			for i in range(left + 1, right+1):  
+			
+				temp = array[i]  
+				j = i - 1 
+				while j >= left and array[j] > temp :  
+				
+					array[j+1] = array[j]  
+					j -= 1
+				
+				array[j+1] = temp
+
+			return array
+			
+ 
+		def merge(array, l, m, r): 
+		
+			len1, len2 =  m - l + 1, r - m  
+			left, right = [], []  
+			for i in range(0, len1):  
+				left.append(array[l + i])  
+			for i in range(0, len2):  
+				right.append(array[m + 1 + i])  
+			
+			i, j, k = 0, 0, l 
+
+			while i < len1 and j < len2:  
+			
+				if left[i] <= right[j]:  
+					array[k] = left[i]  
+					i += 1 
+				
+				else: 
+					array[k] = right[j]  
+					j += 1 
+				
+				k += 1
+
+			while i < len1:  
+			
+				array[k] = left[i]  
+				k += 1 
+				i += 1
+
+			while j < len2:  
+				array[k] = right[j]  
+				k += 1
+				j += 1
+
+		return sort(a, len(a))
+	
+	def selectionsort(self, a):
+		array = a
+		for i in range(len(array)): 
+			min_idx = i
+			for j in range(i+1, len(array)): 
+				if array[min_idx] > array[j]: 
+					min_idx = j         
+			array[i], array[min_idx] = array[min_idx], array[i]
+		return array
+
+	def shellsort(self, a):
+		array = a
+		n = len(array)
+		gap = n//2
+
+		while gap > 0: 
+	
+			for i in range(gap,n): 
+
+				temp = array[i] 
+				j = i 
+				while  j >= gap and array[j-gap] >temp: 
+					array[j] = array[j-gap] 
+					j -= gap 
+				array[j] = temp 
+			gap //= 2
+
+		return array
+
+	def bubblesort(self, a):
+
+		def sort(array):
+			for i, num in enumerate(array):
+				try:
+					if array[i+1] < num:
+						array[i] = array[i+1]
+						array[i+1] = num
+						sort(array)
+				except IndexError:
+					pass
+			return array
+
+		return sort(a)
+
+	def cyclesort(self, a):
+
+		def sort(array):
+
+			array = array
+			writes = 0
+
+			for cycleStart in range(0, len(array) - 1): 
+				item = array[cycleStart] 
+
+				pos = cycleStart 
+				for i in range(cycleStart + 1, len(array)): 
+					if array[i] < item: 
+						pos += 1
+
+				if pos == cycleStart: 
+					continue
+
+				while item == array[pos]: 
+					pos += 1
+					array[pos], item = item, array[pos] 
+					writes += 1
+
+				while pos != cycleStart: 
+
+					pos = cycleStart 
+					for i in range(cycleStart + 1, len(array)): 
+						if array[i] < item: 
+							pos += 1
+
+					while item == array[pos]: 
+						pos += 1
+					array[pos], item = item, array[pos] 
+					writes += 1
+				
+			return array
+		
+		return sort(a)
+
+	def cocktailsort(self, a):
+
+		def sort(array):
+
+			array = array
+
+			n = len(array) 
+			swapped = True
+			start = 0
+			end = n-1
+			while (swapped == True): 
+				swapped = False
+				for i in range (start, end): 
+					if (array[i] > array[i + 1]) : 
+						array[i], array[i + 1]= array[i + 1], array[i] 
+						swapped = True
+				if (swapped == False): 
+					break
+				swapped = False
+				end = end-1
+				for i in range(end-1, start-1, -1): 
+					if (array[i] > array[i + 1]): 
+						array[i], array[i + 1] = array[i + 1], array[i] 
+						swapped = True
+				start = start + 1
+
+			return array
+
+		return sort(a)

analysis-master/test_analysis.py

@@ -5,6 +5,8 @@ def test_():
 	test_data_linear = [1, 3, 6, 7, 9]
 	y_data_ccu = [1, 3, 7, 14, 21]
 	y_data_ccd = [1, 5, 7, 8.5, 8.66]
+	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]
+	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]
 	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}
 	assert an.z_score(3.2, 6, 1.5) == -1.8666666666666665
 	assert an.z_normalize([test_data_linear], 1).tolist() == [[0.07537783614444091, 0.22613350843332272, 0.45226701686664544, 0.5276448530110863, 0.6784005252999682]]
@@ -16,3 +18,14 @@ def test_():
 	assert an.Metric().elo(1500, 1500, [1, 0], 400, 24) == 1512.0
 	assert an.Metric().glicko2(1500, 250, 0.06, [1500, 1400], [250, 240], [1, 0]) == (1478.864307445517, 195.99122679202452, 0.05999602937563585)
 	#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))

data-analysis/test.py

@@ -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
+"""