项目概述：

用户通过浏览器选择一个文件来导入数据。然后，我解包二进制文件。然后，我将新解包的数据保存为.csv文件，以便以后在excel中查看数据。用户当前通过键入新文件名来创建文件名。然后我继续用matplotlib库绘制所有数据。在

整个代码：#import Gnuplot

import struct

#import binascii

import csv

import matplotlib.pyplot as plt

import os.path

import pylab as pl

from Tkinter import Tk

from tkFileDialog import askopenfilename

#print "testing"

#data = '$'

#data2 = '7'

#out = ord(data)*256 + ord(data2)

#print out

'''

open_path = "/media/6265-D02D/"

fname = raw_input('Enter the file name you want to open (without the entire filepath)(include filetype ex. .txt): ')

#combines open_path with fname

entirepath = os.path.join(open_path, fname)

f = open(entirepath, 'r')

'''

#This opens the file browser inorder to the user to

#choose the file that they want to decipher

Tk().withdraw() '''we don't want a full GUI, so keep the root

window from appearing.

-This opens the filebrowser'''

filename1 = askopenfilename()

f = open(filename1 'r')

time = []

pitch = []

roll = []

yaw = []

p_rate = []

r_rate = []

y_rate = []

motor0 = []

motor1 = []

motor2 = []

motor3 = []

alt = []

thr_in = []

pitch_in = []

roll_in = []

yaw_in = []

byte_count = 50

s = struct.Struct('>3s I h h h h h h h h h h I h h h h s')

while True:

temp_data = []

unpacked_date = []

temp_data = f.read(40)

byte_count = len(temp_data)

if byte_count <40:

break

unpacked_data = s.unpack(temp_data)

if unpacked_data[0] == '$$$': #storing the unpacked data if a good packet is received

time.append(unpacked_data[1])

pitch.append(unpacked_data[2])

roll.append(unpacked_data[3])

yaw.append(unpacked_data[4])

p_rate.append(unpacked_data[5])

r_rate.append(unpacked_data[6])

y_rate.append(unpacked_data[7])

motor0.append(unpacked_data[8])

motor1.append(unpacked_data[9])

motor2.append(unpacked_data[10])

motor3.append(unpacked_data[11])

alt.append(unpacked_data[12])

thr_in.append(unpacked_data[13])

yaw_in.append(unpacked_data[14])

pitch_in.append(unpacked_data[15])

roll_in.append(unpacked_data[16])

#code not being used here

# Create plot from interpreted data

#pitch_plot = Gnuplot.Gnuplot()

#pitch_plot.title('Pitch vs. Time')

#pitch_plot('set style data linespoints')

#pitch_plot(time, pitch)

#creating a new csv file using the new parsed data

creatingcolumns = (time,pitch,roll,yaw, p_rate,

r_rate,y_rate,motor0,motor1,motor2,motor3,alt,

thr_in,yaw_in,pitch_in,roll_in)

creatingcolumns = zip(*creatingcolumns)

#creates headers

header = ["Time", "Pitch", "Roll", "Yaw", "P Rate",

"R Rate", "Y Rate", "Motor 0", "Motor 1", "Motor 2",

"Motor 3", "Altitude", "Thrust In", "Yaw In",

"Pitch in", "Roll in"]

#saves the file to the python, csv folder on the desktop

#determines the save path

save_path = "/home/pi/Desktop/Python CSV files"

#user inputs a file name

filename2 = raw_input("Give a name for the new CSV file (do not include the filetype such as .csv) ")

#combining everything into a variable for the save path

completeName = os.path.join(save_path, filename2+".csv")

#opens a new csvfile and writes the information to it

with open(completeName , "wb" ) as csvfile:

writingcsv = csv.writer(csvfile, dialect='excel')

writingcsv.writerow(header)

for row in creatingcolumns:

writingcsv.writerow(row)

#plots the data and creates the titles

#creates the first figure of Time vs Pitch

plt.figure(1)

plt.plot(time,pitch)

plt.xlabel('Time')

plt.ylabel('Pitch')

plt.title('Pitch vs Time')

fig = pl.gcf()

fig.canvas.set_window_title('Pitch vs Time')

#plt.show()

#creates second figure of Time vs Roll

plt.figure(2)

plt.plot(time, roll)

plt.title('Roll vs Time')

plt.xlabel('Time')

plt.ylabel('Roll')

fig2 = pl.gcf()

fig2.canvas.set_window_title('Roll vs Time')

#creates second figure of Time vs Yaw

plt.figure(3)

plt.plot(time, yaw)

plt.title('Yaw vs Time')

plt.xlabel('Time')

plt.ylabel('Yaw')

fig3 = pl.gcf()

fig3.canvas.set_window_title('Yaw vs Time')

#creates second figure of Time vs Pitch Rate

plt.figure(4)

plt.plot(time, p_rate)

plt.title('Pitch Rate vs Time')

plt.xlabel('Time')

plt.ylabel('Pitch Rate')

fig4 = pl.gcf()

fig4.canvas.set_window_title('Pitch Rate vs Time')

#creates second figure of Time vs Roll Rate

plt.figure(5)

plt.plot(time, r_rate)

plt.title('Roll Rate vs Time')

plt.xlabel('Time')

plt.ylabel('Roll Rate')

fig5 = pl.gcf()

fig5.canvas.set_window_title('Roll Rate vs Time')

#creates second figure of Time vs Yaw Rate

plt.figure(6)

plt.plot(time, y_rate)

plt.title('Yaw Rate vs Time')

plt.xlabel('Time')

plt.ylabel('Yaw Rate')

fig6 = pl.gcf()

fig6.canvas.set_window_title('Yaw Rate vs Time')

#creates second figure of Time vs Motor 0

plt.figure(7)

plt.plot(time, yaw)

plt.title('Motor 0 vs Time')

plt.xlabel('Time')

plt.ylabel('Motor 0')

fig7 = pl.gcf()

fig7.canvas.set_window_title('Motor 0 vs Time')

#creates second figure of Time vs Motor 1

plt.figure(8)

plt.plot(time, motor1)

plt.title('Motor 1 vs Time')

plt.xlabel('Time')

plt.ylabel('Motor 1')

fig8 = pl.gcf()

fig8.canvas.set_window_title('Motor 1 vs Time')

#creates second figure of Time vs Motor 2

plt.figure(9)

plt.plot(time, motor2)

plt.title('Motor 2 vs Time')

plt.xlabel('Time')

plt.ylabel('Motor 2')

fig9 = pl.gcf()

fig9.canvas.set_window_title('Motor 2 vs Time')

#creates second figure of Time vs Motor 3

plt.figure(10)

plt.plot(time, motor3)

plt.title('Motor 3 vs Time')

plt.xlabel('Time')

plt.ylabel('Motor 3')

fig10 = pl.gcf()

fig10.canvas.set_window_title('Motor 3 vs Time')

#creates second figure of Time vs Altitude

plt.figure(11)

plt.plot(time, alt)

plt.title('Altitude vs Time')

plt.xlabel('Time')

plt.ylabel('Altitude')

fig11 = pl.gcf()

fig11.canvas.set_window_title('Altitude vs Time')

#creates second figure of Time vs Thrust in

plt.figure(12)

plt.plot(time, thr_in)

plt.title('Thrust In vs Time')

plt.xlabel('Time')

plt.ylabel('Thrust In')

fig12 = pl.gcf()

fig12.canvas.set_window_title('Thrust In vs Time')

#creates second figure of Time vs Yaw Input

plt.figure(13)

plt.plot(time, yaw_in)

plt.title('Yaw Input vs Time')

plt.xlabel('Time')

plt.ylabel('Yaw Input')

fig13 = pl.gcf()

fig13.canvas.set_window_title('Yaw Input vs Time')

#creates second figure of Time vs Pitch Input

plt.figure(14)

plt.plot(time, pitch_in)

plt.title('Pitch Input vs Time')

plt.xlabel('Time')

plt.ylabel('Pitch Input')

fig14 = pl.gcf()

fig14.canvas.set_window_title('Pitch Input vs Time')

#creates second figure of Time vs Roll Input

plt.figure(15)

plt.plot(time, roll_in)

plt.title('Roll Input vs Time')

plt.xlabel('Time')

plt.ylabel('Roll Input')

fig15 = pl.gcf()

fig15.canvas.set_window_title('Roll Input vs Time')

plt.show()

我的问题：

我想在带有触摸屏的raspberry pi(Python2.7)上运行此代码。我想尽量避免打字。在

问题：

用户使用下面的代码选择要读取的文件。

这将创建一个类似于这样的变量：“C:/Users/Andrew/Desktop/Python/LOG1.txt”(注意：我意识到这是一个windows文件路径，在pi上它创建了一个linux文件路径)

^{pr2}$

以后我要在目录中输入一个新的文件名。在#saves the file to the python, csv folder on the desktop

#determines the save path

save_path = "/home/pi/Desktop/Python CSV files"

#user inputs a file name

filename2 = raw_input("Give a name for the new CSV file (do not include the filetype such as .csv) ")

#combining everything into a variable for the save path

completeName = os.path.join(save_path, filename2+".csv")

我想从变量filename1中去掉filepath的“LOG1”部分。所以基本上我删除了变量的“C:/Users/Andrew/Desktop/Python/”和“.txt”部分，但保留了文件名。然后，我希望使用这个文件名“LOG1”，并将其用于上面定义的completeName变量。我将使用以下代码：completeName = os.path.join(save_path,**INSERT VARIABLE HERE**, +".csv")

这将创建一个名为“LOG1.csv”的csv文件

如何删除文件路径的无关部分？？

谢谢您！！在