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wat_correlation.py
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#!/usr/bin/env python
# coding: utf-8
# In[1]:
from pyspark.sql import SparkSession
import pandas as pd
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
# In[2]:
_sp = SparkSession.builder.master("local").appName("TSMC_WAT&YIELD").getOrCreate()
# In[3]:
Wat = _sp.read.format("csv"). option("header","true"). load("WAT.csv")
# In[4]:
Yield = _sp.read.format("csv"). option("header","true"). load("Yield.csv")
# In[5]:
import numpy as np
# In[6]:
w = Wat.toPandas()
# In[7]:
yy = Yield.toPandas()
# In[8]:
data = w.merge(yy,right_on=["_c0"],left_on=["wafer_id"],how="inner")
# In[9]:
data = data.drop(["_c0_x","wafer_id","_c0_y"],axis=1)
# In[10]:
data = data.convert_objects(convert_numeric=True)
# In[11]:
rate = data.corr("pearson")
print(rate)
# In[12]:
rank = rate.sort_values(by=["yield"],ascending=[False])
# In[13]:
print(rank["yield"][0:10])
# In[14]:
import matplotlib.pyplot as plt
f=plt.figure()
# In[15]:
f, (ax1) = plt.subplots(sharex=True, sharey=True)
ax1.scatter(data["yield"],data["WAT1036"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT1036"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][1])
f, (ax2) = plt.subplots(sharex=True, sharey=True)
ax2.scatter(data["yield"],data["WAT2985"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT2985"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][2])
f, (ax3) = plt.subplots(sharex=True, sharey=True)
ax3.scatter(data["yield"],data["WAT2848"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT2848"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][3])
f, (ax4) = plt.subplots(sharex=True, sharey=True)
ax4.scatter(data["yield"],data["WAT748"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT748"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][4])
f, (ax5) = plt.subplots(sharex=True, sharey=True)
ax5.scatter(data["yield"],data["WAT517"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT517"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][5])
f, (ax6) = plt.subplots(sharex=True, sharey=True)
ax6.scatter(data["yield"],data["WAT1477"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT1477"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][6])
f, (ax7) = plt.subplots(sharex=True, sharey=True)
ax7.scatter(data["yield"],data["WAT33"])
plt.ylim(max(data["WAT33"]), min(data["WAT33"]))
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT33"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= -%f'%rank["yield"][7])
f, (ax8) = plt.subplots(sharex=True, sharey=True)
ax8.scatter(data["yield"],data["WAT2064"])
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT2064"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= %f'%rank["yield"][8])
f,(ax9) = plt.subplots(sharex=True, sharey=True)
ax9.scatter(data["yield"],data["WAT2086"])
plt.ylim(max(data["WAT2086"]), min(data["WAT2086"]))
A = np.vstack([data["yield"],np.ones(len(data["yield"]))]).T
m,c = np.linalg.lstsq(A,np.array(data["WAT2086"]))[0]
plt.plot(data["yield"],data["yield"]*m+c,color="r")
plt.title('corr= -%f'%rank["yield"][9])
# In[ ]: