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Core/Ind_Alligator.py

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+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 
+import matplotlib.dates as mdates
+import matplotlib.pyplot as plt
+
+import mplfinance as mpf
+
+import plotly
+#import plotly.plotly as py
+import plotly.graph_objs as go
+# these two lines allow your code to show up in a notebook
+from plotly.offline import init_notebook_mode, iplot
+from plotly.subplots import make_subplots
+init_notebook_mode()
+
+import CoreTraidMath 
+import CoreDraw
+
+
+class Alligator:
+
+    def __init__(self, base_df,options={}, needFig=False,showOnlyIndex=True,drawFig=False):
+        self.base_df=base_df.reset_index(drop=True)
+        self.options=options
+        self.ans=self.getAns()
+        if needFig:
+            self.fig=self.pltShow(showOnlyIndex,drawFig)
+            
+            
+    def getMA(self,keyAns):
+        ans=None
+        op={'dataType':'ohcl',
+                'action':'findMean',
+                'actionOptions':{'MeanType':self.options[keyAns]['MeanType'],
+                                 'valueType':self.options['valueType'],
+                                 'window':self.options[keyAns]['window']}
+            }
+        ans=CoreTraidMath.CoreMath(self.base_df,op).ans
+        
+        return ans
+    
+    def getAns(self):
+        ans={'Jaw':{},
+             'Teeth':{},
+             'Lips':{}
+            }
+        
+        
+        for i in ans.keys():
+            ma=self.getMA(i)
+            ans[i]['y']=ma[:len(ma)-self.options[i]['shift']]
+            ans[i]['x']=self.base_df['date'][self.options[i]['window']+self.options[i]['shift']-1:]
+
+
+        return ans
+            
+            
+    def pltShow(self,showOnlyIndex,drawFig):
+        ans=None
+        req=[]
+        row=1
+        if not showOnlyIndex:
+            
+            #row=2
+            req.append({
+                'vtype':'OCHL',
+                'df':self.base_df,
+                'row':1,
+                'col':1,
+                'name':'OHCL'
+
+            })
+        req.append({
+            'vtype':'Scatter',
+            'df':pd.DataFrame(
+                {'value':self.ans['Jaw']['y'],'date':self.ans['Jaw']['x']}) ,
+            'row':row,
+            'col':1,
+            'name':'Jaw'
+            
+        })
+        req.append({
+            'vtype':'Scatter',
+            'df':pd.DataFrame(
+                {'value':self.ans['Teeth']['y'],'date':self.ans['Teeth']['x']}) ,
+            'row':row,
+            'col':1,
+            'name':'Teeth'
+            
+        })
+        req.append({
+            'vtype':'Scatter',
+            'df':pd.DataFrame(
+                {'value':self.ans['Lips']['y'],'date':self.ans['Lips']['x']}) ,
+            'row':row,
+            'col':1,
+            'name':'Lips'
+            
+        })
+        
+        self.figDict=req
+        ans = CoreDraw.coreDraw(req,drawFig)
+        return ans