export_csv_code.py

from google.colab import files
from datetime import datetime
from scipy.signal import find_peaks
import io
import pandas as pd
import matplotlib.pyplot as plt
import warnings

# choose file to upload
uploaded = files.upload()

"""##Functions"""

def import_file(uploaded, fonte):
  ### uploaded is the archive chosen and fonte is str type where it was measured from: mouth or nose
  warnings.filterwarnings('ignore')
  # import/read file and add column name:
  a = str(uploaded.keys())
  a = a[12:]
  for i in range(len(a)):
    if a[i]=='_':
      break
    else:
      b = a[:i+1]

  file_name = b+'_'+fonte+'.csv'
  df = pd.read_csv(io.BytesIO(uploaded[file_name]))
  df = df.set_axis(['Time','Temp'],axis='columns')
  df = df.drop_duplicates(subset='Time', keep ='last', ignore_index = True)
  df['Count']=df['Time']
  df['T(ms)']=df['Time']

  # Calculates the minutes and seconds:
  temp= []
  time_ms = []

  for index in df.index:
    # replace the date + time for just the time
    df['Time'] = df['Time'].replace(df['Time'][index],df['Time'][index][11:])
    time = df['Time'][index]
    if index == 0:
      # sets the first measurement as 00:00
      start = datetime.strptime(time,'%H:%M:%S.%f')
      df['Count'][index] = '00:00.000'
      df['T(ms)'][index] = '0'
    else:
      pt = datetime.strptime(time,'%H:%M:%S.%f')
      diff = pt-start # calculate the difference between the start and time of measurement
      df['Count'][index] = str(diff)[2:-3]
      df['T(ms)'][index] = str(diff.total_seconds()*1000) # calculates the ms 
    temp.append(df['Temp'][index])
    time_ms.append(df['T(ms)'][index])

  # 1st plot: 
  df.plot(x = 'T(ms)', y='Temp', kind = 'line', figsize = (20,10), title = 'Temperature (C) x time (Milliseconds)', legend = 'Temperature',xlabel = 'Time (milliseconds)', ylabel = 'Temperature (C)')
  plt.show()  

  return df

def cut_choice(cut):
  ### function to define if user wants to calculate the respiratory rate for a certain timeframe
  # chosing 'N' will result in default as -20 seconds, considered the time to calibrate the sensor
  while ((cut!='Y') & (cut!='N')):
    cut = str(input('Choose timeframe? [Y/N]'))
  return cut

def plot_peaks(df2,cut,mode):
  # this function cuts the time for the default (-20s) or for the chosen one and plots the peaks. Also returns the respiratory rate
  if cut=='Y':
    start = 10
    end = 4
    # defines start and end from users choices:
    while start>=end:
      start = float(input('Start from (s): '))*1000
      end = float(input('End at (s): '))*1000

    # cuts for the time frame chosen:
    for i in range(len(df2)):
      time = float(df2['T(ms)'][i])
      if start>time:
        df2 = df2.drop(i)
      elif end<time:
        df2 = df2.drop(i)

  elif cut=='N':
    start = 20000
    # cuts for default:
    for i in range(len(df2)):
      time = float(df2['T(ms)'][i])
      if start>time:
        df2 = df2.drop(i)
  df2 = df2.reset_index(drop=True)

  # if it was measured by nose, the prominence considered is 0.2, if it was for mouth, is 0.5
  # this is due to the difference between measurement type
  if mode=='nose':
    peaks, properties = find_peaks(df2['Temp'], prominence = 0.2)
  else:
    peaks, properties = find_peaks(df2['Temp'], prominence = 0.5)
  
  # calculates the respiratory rate by counting the peaks calculated above, multiplying by 60 (seconds) and dividing by the diference between the start and end time
  first = float(df2['T(ms)'][0])
  last = df2.iloc[-1]
  seconds =(float(last['T(ms)'])-first)/1000
  x = len(peaks)*60/seconds
  print('This round resulted in ', round(x),'breathes per minute')

  df2.plot(x = 'T(ms)', y='Temp', kind = 'line', figsize = (20,10), title = 'Temperature (C) x time (Milliseconds)', legend = 'Temperature',xlabel = 'Time (milliseconds)', ylabel = 'Temperature (C)')
  plt.plot(peaks, df2['Temp'][peaks], ".")
  plt.show()

"""## Plot and breath measurement:"""

a = import_file(uploaded, 'mouth')

cut_c = cut_choice('S')
plotar = plot_peaks(a,cut_c,'mouth')