-
Notifications
You must be signed in to change notification settings - Fork 0
/
userclasser.py
53 lines (42 loc) · 1.83 KB
/
userclasser.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
import pandas as pd
import globalfile as gf
import function as fu
import csv
class user:
def __init__(self):
self.value = 0.1 # the value of external variable is stored here
self.meterno = 1 # thee meter value is stored here
self.rowno = 1 # the row no is stored
self.paramsfileno = 1 # the params file value is used here
self.outputfileno = 1 # the outfile details are used here
def element(self, paramsfileno, rowno):
'''
f = pd.read_csv(gf.paramsarray[paramsfileno], header=None, index_col=False)
c = f.iloc[meterno, 3]
f.to_csv(gf.paramsarray[paramsfileno], sep=',', header=None, index_col=False, )
return c
'''
with open(gf.paramsarray[paramsfileno-1], 'r') as f:
reader = csv.reader(f) # read parameter file
urlist = list(reader) # converting parameter file as a list
c = float(urlist[rowno-1][3]) # assigning valve bacck
new = pd.DataFrame(urlist) # rewriting the parameters back
new.to_csv(gf.paramsarray[paramsfileno-1], sep=',', header=False, index=False, )
return c
def avg(self, outputfileno, meterno):
return fu.avg(outputfileno-1, meterno-1) # the avg is computed
def rms(self, outputfileno, meterno):
return fu.rms(outputfileno-1, meterno-1)
def thd(self, outputfileno, meterno):
return fu.thd(outputfileno-1, meterno-1)
def peak(self, outputfileno, meterno):
return fu.peak(outputfileno-1, meterno-1)
def ripple(self, outputfileno, meterno):
return fu.ripple(outputfileno-1, meterno-1)
def mov_avg_final(self, outputfileno, meterno):
return fu.moving_avg(outputfileno-1, meterno-1)
def store(self, value):
self.value = value
return
def __str__(self):
return str(self.value)