Generates a Riemann of a CSV dataset

Integrator.py

import csv
import matplotlib.pyplot as plt

data = csv.reader(open('Lab25.csv'))

runNum = int(input("Enter run number: "))

minX = int(input("Enter x minimum: "))

delt = int(input("Enter x-axis domain: "))

run = runNum

runNum = (runNum - 1) * 3 + 1 # Edit to change the column

# Skip labels
null = next(data)

# Time base
time = 0.0001

# Create a global variable for the final summation
totalC = 0.0

rawData = []
avgData = []

# Yeet the raw data into a List
for row in data:
    if len(row[runNum]) < 1:
        break

    if float(row[runNum]) < 0.001:
        rawData.append(0)
        continue

    rawData.append(float(row[runNum]))
    
for x in range(len(rawData)):
    nums = 0
    tempSum = 0.0
    for y in range(x-30, x+30):
        if ( y < 0 ):
            continue

        if ( y >= len(rawData) ):
            break
        
        nums += 1
        tempSum += float(rawData[y])

    avgData.append(float(tempSum / nums))

maxX = minX + delt

plt.figure().suptitle("Figure "+str(run)+"b: Rolling Average for Run "+str(run))
plt.xlabel("Time (ten-thousandths of a second)")
plt.ylabel("Current (amperes)")
plt.axis([minX, maxX, 0, 0.014])
plt.plot(avgData)
plt.savefig('meanout'+str(run)+'.png', dpi=300)

plt.figure().suptitle("Figure "+str(run)+"a: Raw Data for Run "+str(run))
plt.xlabel("Time (ten-thousandths of a second)")
plt.ylabel("Current (amperes)")
plt.axis([minX, maxX, 0, 0.014])
plt.plot(rawData)
plt.savefig('rmeanout'+str(run)+'.png', dpi=300)

tSum = 0

for x in avgData:
    tSum += x * time

print(tSum)