New to python, used Matlab previously.
I get an error message: "The debugger backend could not be started." when I try to run any script in Eric IDE editor for python. (I am using various simple code examples for importing and visualizing data. An example of borrowed code is below.)
I installed python 3.6, and Python 3.5 (should I uninstall one of these?) I downloaded Eric to use as an editor and debugger and installed as an administrator.
In the Eric Python documentation I did not find a solution. I did look in preferences for debugging and tried both the path for Python 3.5 as well as Python 3.6 I am not sure what I changed or broke as a script had worked from the "shell" tab in Eric previously. So I broke something and cannot fix it.
Should I try uninstalling Eric, and both versions of Python (3.5 and 3.6) and starting over from scratch?
I think my issue may have something to do with paths, file locations etc., installation directories, really not sure and cannot find anything helpful online after much searching.
I also am not certain know what paths (full directory filenames) should be in "Interpreter:" and "Working directory:" in the "Run Script" window.
Any help much appreciated! Thanks in advance.
Rebecca
# Numpy (data import, manipulation, export)
import numpy as np
# Matplotlib (create trends)
import matplotlib.pyplot as plt
# load the data file
data_file = np.genfromtxt('data_file.txt', delimiter=',')
# create time vector from imported data (starts from index 0)
time = data_file[:,0]
# parse good sensor data from imported data
sensors = data_file[:,1:5]
# display the first 6 sensor rows
print(sensors[0:6])
# adjust time to start at zero by subtracting the
# first element in the time vector (index = 0)
time = time - time[0]
# calculate the average of the sensor readings
avg = np.mean(sensors,1) # over the 2nd dimension
# export data
# stack time and avg as column vectors
my_data = np.vstack((time,sensors.T,avg))
# transpose data
my_data = my_data.T
# save text file with comma delimiter
np.savetxt('export_from_python.txt',my_data,delimiter=',')
# generate a figure
plt.figure(1)
plt.plot(time/60.0,sensors[:,1],'ro')
plt.plot(time/60.0,avg,'b.')
# add text labels to the plot
plt.legend(['Sensor 2','Average Sensors 1-4'])
plt.xlabel('Time (min)')
plt.ylabel('Sensor Values')
# save the figure as a PNG file
plt.savefig('my_Python_plot.png')
# show the figure on the screen (pauses execution until closed)
plt.show()
