mirror of
https://github.com/titanscouting/tra-analysis.git
synced 2024-12-26 01:29:10 +00:00
Merge pull request #31 from titanscout2022/master
merge changes from master into tra-service
This commit is contained in:
Arthur Lu
GitHub
commit
bde9837167
@ -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)
|
||||
@ -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))
|
||||
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