chore: finalize file rename by removing old CoreTraidMath.py

Complete the file rename by removing the old file with typo.

This commit ensures the git history properly tracks the rename from
CoreTraidMath.py to CoreTradeMath.py.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

market_trade/core/CoreTraidMath.py

@@ -1,138 +0,0 @@
- 
-import pandas as pd
-import datetime
-import numpy as np
-import plotly as pl
-import plotly.graph_objs as go
-import matplotlib.pyplot as plt
-import math
-import scipy
-import random
-import statistics 
-
-
-import datetime 
-
-
-
-
-
-class CoreMath:
-    
-    def __init__(self, base_df, params={
-        'dataType':'ohcl',
-        'action': None,
-        'actionOptions':{}
-    }
-                ):
-    
-        self.base_df=base_df.reset_index(drop=True)
-        self.params=params
-        if self.params['dataType']=='ohcl':
-            self.col=self.base_df[self.params['actionOptions']['valueType']]
-        elif self.params['dataType']=='series':
-            self.col=self.base_df
-        self.ans=self.getAns()
-        
-    
-    def getAns(self):
-        ans=None
-        
-        if self.params['action']=='findExt':
-            ans = self.getExtremumValue()
-        elif self.params['action']=='findMean':
-            ans = self.getMeanValue()
-        elif self.params['action']=='findSTD':
-            ans=self.getSTD()
-        
-            
-        return ans
-    
-    
-    def getExtremumValue(self):
-        ans=None
-        '''
-        actionOptions:
-            'extremumtype':
-                'min'
-                'max'
-            'valueType':
-                'open'
-                'close'
-                'high'
-                'low'
-        '''
-        if self.params['actionOptions']['extremumtype']=='max':
-            ans=max(self.col)
-            
-        if self.params['actionOptions']['extremumtype']=='min':
-            ans=min(self.col)
-
-            
-        return ans
-     
-        
-    def getMeanValue(self):
-        '''
-        actionOptions:
-            'MeanType':
-                'MA'
-                'SMA'
-                'EMA'
-                'WMA'
-                --'SMMA'
-            'valueType':
-                'open'
-                'close'
-                'high'
-                'low'
-            'window'
-            'span'
-            'weights'
-        '''
-        ans=None
-        if self.params['actionOptions']['MeanType']=='MA':
-            ans = self.col.mean()
-        if self.params['actionOptions']['MeanType']=='SMA':
-            ans=np.convolve(self.col, np.ones(self.params['actionOptions']['window']), 'valid') / self.params['actionOptions']['window']
-            #ans=self.col.rolling(window=self.params['actionOptions']['window']).mean().to_list()
-            
-        if self.params['actionOptions']['MeanType']=='EMA':
-            ans=self.col.ewm(span=self.params['actionOptions']['span'], adjust=False).mean().to_list()
-        if self.params['actionOptions']['MeanType']=='WMA':
-            try:
-                weights=self.params['actionOptions']['weights']
-            except KeyError:
-                weights=np.arange(1,self.params['actionOptions']['window']+1)
-            ans=self.col.rolling(window=self.params['actionOptions']['window']).apply(lambda x: np.sum(weights*x) / weights.sum(), raw=False).to_list()
-
-        
-        
-        return(ans)
-    
-    def getSTD(self):
-        '''
-        actionOptions:
-            window
-        
-        
-        
-        
-        
-        '''
-        
-        ans=None
-
-
-        try:
-            window=self.params['actionOptions']['window']
-            ans=np.asarray([])
-            for i in range(len(self.col)-window+1):
-                ans=np.append(ans,np.std(self.col[i:i+window], ddof=1))
-            
-        except:
-            #window = len(self.col)
-            ans=np.std(self.col, ddof=1)
-
-        return ans
-