Bootleg Dropview.py

import numpy
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path
import math
from math import pi
from math import sqrt
import shutil

# SETUP VARIABLES - USER INPUTS
BD = 3 #Bluedrop file is from 
fileNum = '0B32'
# write the bin file number for the earliest drop in the folder (do not include 'bLog' or '.bin')
numFiles = 25 #write the number of bin files in the folder of interest (if only looking at 1 drop, write 2)
offset = 0 # this value is subtracted from the accelerometer readings
# paste the filepath to the folder where the BD data is stored
binFilepath = Path("D:/BD3_11-6-2023")
#paste the filepath that you want the files containing drops copied to 
outputPath = Path("D:/BD3_11-6-2023/Drops_Only")
plotPath = Path("D:/BD3_11-6-2023/Drops_Only/File_Images")

def overviewplot(): #Plot showing all accelerometers and pore pressure readings
    fig, (ax1) = plt.subplots(1)
    fig.set_size_inches(4, 4)
    ax1.plot(time, g250g, label="250g")
    ax1.plot(time, g50g, label="50g")
    ax1.plot(time, g18g, label="18g")
    ax1.plot(time, g2g, label="2g")
    ax1.legend(loc = "upper right")
    ax1.set(ylabel="Deceleration (g)")
    ax1.set_title("BD file "+ newName)
    ax1.grid()

    plt.draw()
    print("Is there a drop? y/n")
    plt.waitforbuttonpress(2)
    drop_input=input()

    if drop_input=='y':   
        origFile = 'bLog'+newName+".bin"
        origFilePath = binFilepath / origFile
        newFilePath = outputPath / origFile
        plotFilePath = plotPath / newName
        shutil.copyfile(origFilePath, newFilePath)
        plt.savefig(plotPath / newName)

    plt.close(fig)

def newNamefun(): #find the next sequential bin name a=existing last variable, b=new last variable
    global newName
    a = name[3]
    c = name[2]
    e = name[1]
    g = name[0]
    if a == "A":
        b = "B"
    elif a == "B":
        b = "C"
    elif a == "C":
        b = "D"
    elif a == "D":
        b = "E"
    elif a == "E":
            b = "F"
    elif a == "F":
        b = "0"
        if c == "A":
            d = "B"
        elif c == "B":
            d = "C"
        elif c == "C":
            d = "D"
        elif c == "D":
            d = "E"
        elif c == "E":
            d = "F"
        elif c == "F":
            d = "0"
            if e == "A":
                f = "B"
            elif e == "B":
                f = "C"
            elif e == "C":
                f = "D"
            elif e == "D":
                f = "E"
            elif e == "E":
                f = "F"
            elif e == "F":
                f = "0"
                if g == "A":
                    h = "B"
                elif g == "B":
                    h = "C"
                elif g == "C":
                    h = "D"
                elif g == "D":
                    h = "E"
                elif g == "E":
                    h = "F"
                elif g == "F":
                    h = "0"
                    f = "0"
                    d = "0"
                    b = "0"
                elif g == "9":
                    h = "A"
                else: #a <=8:
                    g = int(name[0]) #the only other options are numbers
                    h = g + 1
                    h = str(b)    

            elif e == "9":
                f = "A"
            else: #a <=8:
                e = int(name[1]) #the only other options are numbers
                f = e + 1
                f = str(f)    


        elif c == "9":
            d = "A"
        else: #a <=8:
            c = int(name[2]) #the only other options are numbers
            d = c + 1
            d = str(d)    


    elif a == "9":
        b = "A"
    else: #a <=8:
        a = int(name[3]) #the only other options are numbers
        b = a + 1
        b = str(b)    


    newNameList = name
    newNameList[3] = b #b always will change
    if a == "F":
        newNameList[2] = d
        if c == "F":
            newNameList[1] = f
            if e == "F":
                newNameList[0] = h
                    
    else:
        newNameList[2] = c
        newNameList[1] = e
        newNameList[0] = g

    print(newNameList)
    newName = ""
    newName = newName.join(newNameList)
    print(newName)

newName = fileNum #for the first drop, select the earliest drop defined earlier

for i in range(1, numFiles):

    # READ BD DATA IN
    data_array = []  # creates an empty array for us to fill with bd data
    fileName = 'bLog'+newName+".bin"
    # print(fileName)
    newPath = binFilepath / fileName
    #print(newPath)
    file = open(newPath, 'rb')  # read file
    element = file.read(3)  # create a byte list with each element having 3 bytes

    while element:
        # Convert to signed integer before adding to data array
        iVAl = int.from_bytes(element, byteorder='big', signed=True)
        data_array.append(iVAl)  # adds the reshaped data from the bd file to the data frame
        element = file.read(3)

    np_array = np.array(data_array)  # create numpy array from the list
    np_array = np.reshape(np_array, (-1, 10))  # convert the 1d array to 2d array with 10 cols


    df = pd.DataFrame(np_array) # Creates a Dataframe in pandas from the bd data
    df.columns = ['Count', 'no clue', 'g2g', 'g18g', 'g50g', 'ppm', 'g200g', 'gX55g', 'gY55g', 'g250g'] # names columns

    # APPLY CALIBRATION FACTORS
    if BD == 3:  # calibration factors from March 2023
        g2g = (df['g2g']-33570.1)/1614577.9 - offset# accelerometers are in g
        g18g = (df['g18g']+13495)/163387.2 - offset
        g50g = (df['g50g']-238817.4)/63779.5 - offset
        ppm = ((df['ppm']-139040.1)/20705) * 6.89475729 # converts to kPa
        g200g = ((df['g200g'] -262332.4/38888.7)) - offset
        gX55g = (df['gX55g']-70406)/59754.3  
        gY55g = (df['gY55g']-69421.1)/141871.5
        g250g = (df['g250g']-39077.4)/13746.9 - offset

    if BD == 2: # calibration factors from Aug 26, 2021
    
        g2g = (df['g2g']+37242.2)/1639250.2 - offset# accelerometers are in g
        g18g = (df['g18g']-26867.0)/160460.5 - offset
        g50g = (df['g50g']-213923.3)/64080.7- offset
        ppm = ((df['ppm']+55518.9)/18981.7) * 6.89475729 # converts to kPa
        g200g = (df['g200g']-171448.6)/30334.2 - offset
        gX55g = (df['gX55g']-54242.6)/64767.7 
        gY55g = (df['gY55g']-40574.2)/66343.1 
        g250g = (df['g250g']-40614.9)/13654.6 - offset

    if BD == 1: # calibration factors from July 2020
        g2g = (df['g2g']-42590.9)/1626361.1 - offset # accelerometers are in g
        g18g = (df['g18g']-44492.9)/161125.5 - offset
        g50g = (df['g50g']-171656.1)/64020.3 - offset
        ppm = ((df['ppm']+31776.1)/20679.7) * 6.89475729 # this is kPa
        g200g = (df['g200g'] -723404.8)/32209.7  - offset
        gX55g = (df['gX55g'] -54881.1)/64858.6 
        gY55g = (df['gY55g']-28735.5)/63839.9 
        g250g = (df['g250g']+13299.7)/13697.1 - offset

    time = (df['Count']-df['Count'].iloc[0]+1)/2000 # gives time in s
    count = df["Count"]-df['Count'].iloc[0]

    # make a new dataframe of the calibrated values in units of g
    dfCalg = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])
    dfCalg = dfCalg.T
    dfCalg.columns = ['Count', 'Time (s)', '2g (g)', '18g (g)', '50g (g)', '200g (g)', '250g (g)', 'X55g (g)', 'Y55g (g)', 'Pore Pressure (kPa)']  # names columns
    #print(dfCalg)

    #make a new dataframe of the calibrated values in units of m/s^2
    dfCal = pd.DataFrame([count, time, g2g, g18g, g50g, g200g, g250g, gX55g, gY55g, ppm])
    dfCal = dfCal.T
    dfCal.columns = ['Count','Time (s)', '2g (m/s^2)', '18g (m/s^2)', '50g (m/s^2)', '200g (m/s^2)', '250g (m/s^2)', 'X55g (m/s^2)', 'Y55g (m/s^2)', 'Pore Pressure (kPa)']  # names columns
    dfCal['2g (m/s^2)'] = dfCal['2g (m/s^2)'] * 9.80665
    dfCal['18g (m/s^2)'] = dfCal['18g (m/s^2)'] * 9.80665
    dfCal['50g (m/s^2)'] = dfCal['50g (m/s^2)'] * 9.80665
    dfCal['200g (m/s^2)'] = dfCal['200g (m/s^2)'] * 9.80665
    dfCal['250g (m/s^2)'] = dfCal['250g (m/s^2)'] * 9.80665
    dfCal['X55g (m/s^2)'] = dfCal['X55g (m/s^2)'] * 9.80665
    dfCal['Y55g (m/s^2)'] = dfCal['Y55g (m/s^2)'] * 9.80665
    #print(dfCal)

    overviewplot()

    name = [*newName]

    newNamefun()

print("all files checked")