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analyse.py
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analyse.py
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import serial
import os
import glob
import argparse
import re
import json
import random
import string
from time import sleep
import datetime, time
from timeit import default_timer as timer
from math import log10
import pandas as pd
import sys
import termios
import atexit
from select import select
from config import Config
from influxdb_client import InfluxDBClient
from influxdb_client.client.write_api import SYNCHRONOUS
import matplotlib.pyplot as plt
from pylab import title, figure, xlabel, ylabel, xticks, bar, legend, axis, savefig
from fpdf import FPDF
import seaborn as sns
db = None # InfluxDB device
write = None # InfluxDB write object
parser = argparse.ArgumentParser(description='VTX-Measurements')
parser.add_argument('-l',"--load", type=str, help='load an existing csv file for reporting, no measurements are done')
args = parser.parse_args()
line = Config.influx_line
row_list = []
df = None
print ("-------------------------------------------------------")
print ("Loading an existing data file to create an report")
print ("Import csv \t{}".format(args.load))
print ("")
print ("-------------------------------------------------------")
def mW2dBm(mW):
''' convert mW to dBm '''
mW = float(mW)
return 10.*log10(mW)
def dBm2mW(dBm):
''' convert dBm to mW '''
dBm = float(dBm)
return 10**((dBm)/10.)
def run():
global line, row_list, df
ms = datetime.datetime.now()
id = int(time.mktime(ms.timetuple()))
test_ts = ms.strftime("%Y%m%d") + "_" + str(id)
df = pd.read_csv(args.load, sep=Config.csv_sep, decimal=Config.csv_decimal, header=0, encoding="utf-8")
print ("Data size: \t{0}".format(df.shape))
print ("Data cols: \t{0}".format(df.columns))
# group data : model / target freq / target mw
group_mfw = df.groupby(['Model','Target Freq','Target mW']).agg({'mW':['count','mean', 'min','max','std']},{'dBm':['mean']})
group_mfw.colums = ['mw_count','dBm_mean','mw_mean', 'mw_min', 'mw_max','mw_std']
group_mfw = group_mfw.reset_index()
print ("\n\n")
print ("** Stastic 1 : grouping by model/freq/power **")
print (group_mfw)
#out = plt.figure()
#bp = df.boxplot(column=['mW'], by='Model')
#out.savefig("test.png", format="png")
if __name__ == "__main__":
# if args.load is None:
run()