def get_raw_data_mean(self, times=1):
backup_channel = self._current_channel # do backup of current channel befor reading for later use
backup_gain = self._gain_channel_A # backup of gain channel A
if times > 0 and times < 100: # check if times is in required range
data_list = [] # create empty list
for i in range(times): # for number of times read and add up all readings.
data_list.append(self._read()) # append every read value to the list
if times > 2 and self._pstdev_filter: # if times is > 2 filter the data
data_pstdev = stat.pstdev(data_list) # calculate population standard deviation from the data
data_mean = stat.mean(data_list) # calculate mean from the collected data
max_num = data_mean + data_pstdev # calculate max number which is within pstdev
min_num = data_mean - data_pstdev # calculate min number which is within pstdev
filtered_data = [] # create new list for filtered data
if data_pstdev <=100: # is pstdev is less than 100 it is ok
self._save_last_raw_data(backup_channel, backup_gain, data_mean) # save last data
return data_mean # just return the calculated mean
for index,num in enumerate(data_list): # now I know that pstdev is greater then iterate through the list
if (num > min_num and num < max_num): # check if the number is within pstdev
filtered_data.append(num) # then append to the filtered data list
if self._debug_mode:
print('data_list: ' + str(data_list))
print('filtered_data lsit: ' + str(filtered_data))
print('pstdev data: ' + str(data_pstdev))
print('pstdev filtered data: ' + str(stat.pstdev(filtered_data)))
print('mean data_list: ' + str(stat.mean(data_list)))
print('mean filtered_data: ' + str(stat.mean(filtered_data)))
f_data_mean = stat.mean(filtered_data) # calculate mean from filtered data
self._save_last_raw_data(backup_channel, backup_gain, f_data_mean) # save last data
return f_data_mean # return mean from filtered data
else:
data_mean = stat.mean(data_list) # calculate mean from the list
self._save_last_raw_data(backup_channel, backup_gain, data_mean) # save last data
return data_mean # times was 2 or less just return mean
else:
raise ValueError('function "get_raw_data_mean" parameter "times" has to be in range 1 up to 99.\n I have got: '\
+ str(times))
############################################################
# get_data_mean returns average value of readings minus #
# offset for the particular channel which was read. #
# If return False something is wrong. Try debug mode. #
# INPUTS: times # how many times to read data. Default 1 #
# OUTPUTS: INT | BOOL #
############################################################
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