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Changed from dict to class #1

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Changed from dict to class #1

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0575747
Changed from dict to class
Jan 4, 2023
a9c57e6
unneccessary try statement removed
Jan 5, 2023
9d92ac3
Slots slots slots
Jan 5, 2023
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97 changes: 53 additions & 44 deletions Tech Calculator/tech_calc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,15 +20,23 @@
#
#
#

class swing:
__slots__ = 'time', 'angle', 'frequency', 'forehand', 'strain', 'reset'
def __init__(self, iTime, iAngle):
self.time = iTime
self.angle = iAngle
self.frequency = 0
self.forehand = NULL
self.strain = 0
self.reset = NULL

def average(lst): # Returns the averate of a list of integers
return sum(lst) / len(lst)
def margin(num, margin):
return
def bernstein_poly(i, n, t): # For later
"""
The Bernstein polynomial of n, i as a function of t
"""

return comb(n, i) * ( t**(n-i) ) * (1 - t)**i
def bezier_curve(points, nTimes=100): # For later
"""
Expand Down Expand Up @@ -159,27 +167,27 @@ def V2_to_V3(V2mapData: dict): # Convert V2 JSON to V3
newMapData['obstacles'][-1]['d'] = V2mapData['_obstacles'][i]['_duration']
newMapData['obstacles'][-1]['w'] = V2mapData['_obstacles'][i]['_width']
return newMapData
def splitMapData(mapData: dict, leftOrRight: int): # False or 0 = Left, True or 1 = Right, 2 = Bombs
if leftOrRight == 0:
def splitMapData(mapData: dict, type: int): # False or 0 = Left, True or 1 = Right, 2 = Bombs
if type == 0:
bloqList = [block for block in mapData['colorNotes'] if block['c'] == 0] #Right handed blocks
elif leftOrRight == 1:
elif type == 1:
bloqList = [block for block in mapData['colorNotes'] if block['c'] == 1] #Left handed blocks
else:
bloqList = [bomb for bomb in mapData['bombNotes']]
return bloqList
def swingProcesser(mapSplitData: list): # Returns a list of dictionaries for all swings returning swing angles and timestamps
swingData = []
swingData: list[swing] = []
for i in range(0, len(mapSplitData)):
isSlider = False
cBlockB = mapSplitData[i]['b'] # Current Block Position in Time in unit [Beats]
cBlockA = cut_direction_index[mapSplitData[i]['d']] + mapSplitData[i]['a'] # Current Block Angle in degrees
cBlockP = [mapSplitData[i]['x'], mapSplitData[i]['y']]
if i > 0:
pBlockB = mapSplitData[i-1]['b'] # Pre-cache data for neater code
pBlockA = swingData[-1]['angle'] # Previous Block Angle in degrees
pBlockA = swingData[-1].angle # Previous Block Angle in degrees
pBlockP = [mapSplitData[i-1]['x'], mapSplitData[i-1]['y']]
if mapSplitData[i]['d'] == 8: #Dot note? Just assume opposite angle. If it's a slider, the program will handle it
pBlockA = swingData[-1]['angle']
pBlockA = swingData[-1].angle
if cBlockB - pBlockB <= 0.03125:
cBlockA = pBlockA
else:
Expand All @@ -191,7 +199,7 @@ def swingProcesser(mapSplitData: list): # Returns a list of dictionaries for
if cBlockB - pBlockB >= 0.03125: # = 1/32 Just a check if notes are unreasonable close, just assume they're apart of the same swing
if cBlockB - pBlockB > 0.125: # = 1/8 The upper bound of normal slider precision commonly used
if cBlockB - pBlockB > 0.5: # = 1/2 About the limit of whats reasonable to expect from a slider
swingData.append({'time': cBlockB, 'angle': cBlockA})
swingData.append(swing(cBlockB, cBlockA))
else: # 1/2 Check (just to weed out obvious non-sliders) More complicated methods need to be used
if abs(cBlockA - pBlockA) < 112.5: # 90 + 22.5 JUST IN CASE. not the full 90 + 45 since that would be one hell of a slider or dot note
try:
Expand All @@ -206,15 +214,15 @@ def swingProcesser(mapSplitData: list): # Returns a list of dictionaries for
sliderTime = cBlockB - pBlockB
isSlider = True
else:
swingData.append({'time': cBlockB, 'angle': cBlockA})
swingData.append(swing(cBlockB, cBlockA))
else:
swingData.append({'time': cBlockB, 'angle': cBlockA})
swingData.append(swing(cBlockB, cBlockA))
else: # 1/8 Check
if mapSplitData[i]['d'] == 8 or abs(cBlockA - pBlockA) < 90: # 90 degree check since 90 degrees is what most would consider the maximum angle for a slider or dot note
sliderTime = 0.125
isSlider = True
else:
swingData.append({'time': cBlockB, 'angle': cBlockA})
swingData.append(swing(cBlockB, cBlockA))
else: # 1/32 Check
sliderTime = 0.03125
isSlider = True
Expand All @@ -227,12 +235,12 @@ def swingProcesser(mapSplitData: list): # Returns a list of dictionaries for
pBlockP = [mapSplitData[blockIndex]['x'], mapSplitData[blockIndex]['y']]
break
try:
swingData[-1]['angle'] = math.degrees(math.atan((pBlockP[1]-cBlockP[1])/(pBlockP[0]-cBlockP[0]))) % 360 # Replaces angle swing from block angle to slider angle
swingData[-1].angle = math.degrees(math.atan((pBlockP[1]-cBlockP[1])/(pBlockP[0]-cBlockP[0]))) % 360 # Replaces angle swing from block angle to slider angle
except ZeroDivisionError: # Often we get a divide by zero error which is actually 90 or 270 degrees. Try putting a super large number into atan in your calculator ;)
if cBlockP[1] > pBlockP[1]:
swingData[-1]['angle'] = 90
swingData[-1].angle = 90
else:
swingData[-1]['angle'] = 270
swingData[-1].angle = 270
guideAngle = 1150 # A random test value to check later
for f in range(1, len(mapSplitData)): # Checker that will try to find a guiding block (arrow block) for the slider angle prediction.
blockIndex = i - f
Expand All @@ -242,44 +250,44 @@ def swingProcesser(mapSplitData: list): # Returns a list of dictionaries for
guideAngle = cut_direction_index[mapSplitData[blockIndex]['d']]
break
if guideAngle != 1150: # A test to see if guideAngle was actually changed
if abs(swingData[-1]['angle'] - guideAngle) > 90: # If this is true, the predicted angle is wrong, likely by 180 degrees wrong
if swingData[-1]['angle'] >= 180:
swingData[-1]['angle'] -= 180 # Apply Fix
if abs(swingData[-1].angle - guideAngle) > 90: # If this is true, the predicted angle is wrong, likely by 180 degrees wrong
if swingData[-1].angle >= 180:
swingData[-1].angle -= 180 # Apply Fix
else:
swingData[-1]['angle'] += 180
swingData[-1].angle += 180
else:
swingData.append({'time': cBlockB, 'angle': cBlockA}) # First Note Exception. will never be a slider or need to undergo any test
swingData.append(swing(cBlockB, cBlockA)) # First Note Exception. will never be a slider or need to undergo any test
return swingData
def swingStrainCalc(swingData: list, leftOrRight): # False or 0 = Left, True or 1 = Right
def swingStrainCalc(swingData: list[swing], leftOrRight): # False or 0 = Left, True or 1 = Right
strainAmount = 0
#TODO calculate strain from angle based on left or right hand
for i in range(0, len(swingData)):
if swingData[i]['forehand']: #The Formula firse calculates by first normalizing the angle difference (/180) then using
if swingData[i].forehand: #The Formula firse calculates by first normalizing the angle difference (/180) then using
if leftOrRight:
strainAmount += 2 * (((180 - abs(abs(right_handed_angle_strain_forehand - swingData[i]['angle']) - 180)) / 180)**2) # Right Handed Forehand
strainAmount += 2 * (((180 - abs(abs(right_handed_angle_strain_forehand - swingData[i].angle) - 180)) / 180)**2) # Right Handed Forehand
else:
strainAmount += 2 * (((180 - abs(abs(left_handed_angle_strain_forehand - swingData[i]['angle']) - 180)) / 180)**2) # Left Handed Forehand
strainAmount += 2 * (((180 - abs(abs(left_handed_angle_strain_forehand - swingData[i].angle) - 180)) / 180)**2) # Left Handed Forehand
else:
if leftOrRight:
strainAmount += 2 * (((180 - abs(abs(right_handed_angle_strain_forehand - 180 - swingData[i]['angle']) - 180))/180)**2) # Right Handed Backhand
strainAmount += 2 * (((180 - abs(abs(right_handed_angle_strain_forehand - 180 - swingData[i].angle) - 180))/180)**2) # Right Handed Backhand
else:
strainAmount += 2 * (((180 - abs(abs(left_handed_angle_strain_forehand - 180 - swingData[i]['angle']) - 180))/180)**2) # Left Handed Backhand
strainAmount += 2 * (((180 - abs(abs(left_handed_angle_strain_forehand - 180 - swingData[i].angle) - 180))/180)**2) # Left Handed Backhand
return strainAmount
def patternSplitter(swingData: list): # Does swing speed analysis to split the long list of dictionaries into smaller lists of patterns containing lists of dictionaries
def patternSplitter(swingData: list[swing]): # Does swing speed analysis to split the long list of dictionaries into smaller lists of patterns containing lists of dictionaries
for i in range(0, len(swingData)): # Swing Frequency Analyzer
if i > 0 and i+1 < len(swingData): # Checks done so we don't try to access data that doesn't exist
SF = 2/(swingData[i+1]['time'] - swingData[i-1]['time']) # Swing Frequency
SF = 2/(swingData[i+1].time - swingData[i-1].time) # Swing Frequency
else:
SF = 0
swingData[i]['frequency'] = SF
swingData[i].frequency = SF
patternFound = False
SFList = [freq['frequency'] for freq in swingData]
SFList = [freq.frequency for freq in swingData]
SFmargin = average(SFList) / 32
patternList = [] # Pattern List
tempPlist = [] # Temp Pattern List
for i in range(0, len(swingData)):
if i > 0:
if (1 / (swingData[i]['time'] - swingData[i-1]['time'])) - swingData[i]['frequency'] <= SFmargin: # Tries to find Patterns within margin
if (1 / (swingData[i].time - swingData[i-1].time)) - swingData[i].frequency <= SFmargin: # Tries to find Patterns within margin
if not patternFound: # Found a pattern and it's the first one?
patternFound = True
del tempPlist[-1]
Expand All @@ -298,34 +306,34 @@ def patternSplitter(swingData: list): # Does swing speed analysis to split th
else:
tempPlist.append(swingData[0])
return patternList
def parityPredictor(patternData: list, bombData: list, leftOrRight): # Parses through a List of Lists of Dictionaries to calculate the most likely parity for each pattern
def parityPredictor(patternData: list[list[swing]], bombData: list, leftOrRight): # Parses through a List of Lists of Dictionaries to calculate the most likely parity for each pattern
newPatternData = []
for p in range(0, len(patternData)):
testData1 = patternData[p]
testData2 = copy.deepcopy(patternData[p])
for i in range(0, len(testData1)): # Build Forehand TestData Build
if i > 0:
testData1[i]['forehand'] = not testData1[i-1]['forehand']
testData1[i].forehand = not testData1[i-1].forehand
else:
testData1[0]['forehand'] = True
testData1[0].forehand = True
forehandTest = swingStrainCalc(testData1, leftOrRight) # Test data
for i in range(0, len(testData2)): # Build Banckhand Test Data
if i > 0:
testData2[i]['forehand'] = not testData2[i-1]['forehand']
testData2[i].forehand = not testData2[i-1].forehand
else:
testData2[0]['forehand'] = False
testData2[0].forehand = False
backhandTest = swingStrainCalc(testData2, leftOrRight) # Test data
if forehandTest <= backhandTest: #Prefer forehand starts over backhand if equal
newPatternData += testData1 # Forehand gave a lower stress value, therefore is the best option in terms of hand placement for the pattern
elif forehandTest > backhandTest:
newPatternData += testData2
for i in range(0, len(newPatternData)):
newPatternData[i]['strain'] = swingStrainCalc([newPatternData[i]], leftOrRight) # Assigns individual strain values to each swing. Done like this in square brackets because the function expects a list.
newPatternData[i].strain = swingStrainCalc([newPatternData[i]], leftOrRight) # Assigns individual strain values to each swing. Done like this in square brackets because the function expects a list.
if i > 0:
if newPatternData[i]['forehand'] == newPatternData[i-1]['forehand']:
newPatternData[i]['reset'] = True
if newPatternData[i].forehand == newPatternData[i-1].forehand:
newPatternData[i].reset = True
else:
newPatternData[i]['reset'] = False
newPatternData[i].reset = False
return newPatternData
def staminaCalc(swingData: list):
staminaList: list = []
Expand Down Expand Up @@ -355,8 +363,9 @@ def swingCurveCalc(swingData: list):
curveList[i] = 0
return curveList
def combineAndSortList(array1, array2, key):
combinedArray = array1 + array2
combinedArray = sorted(combinedArray, key=lambda x: x[f'{key}']) # once combined, sort by time
combinedArray: list[swing] = array1 + array2
# combinedArray = sorted(combinedArray, key=lambda x: x[f'{key}']) # once combined, sort by time # DEPRECIATED
combinedArray.sort(key=lambda x: x.time)
return combinedArray
def loadInfoData(mapID: str):
songPath = findSongPath(mapID)
Expand Down Expand Up @@ -388,7 +397,7 @@ def calculateTech(mapData):
RightSwingData = parityPredictor(RightPatternData, bombData, True)

SwingData = combineAndSortList(LeftSwingData, RightSwingData, 'time')
StrainList = [strain['strain'] for strain in SwingData]
StrainList = [strain.strain for strain in SwingData]
tech = average(StrainList)


Expand Down