windchillcomp.py

# Column names and column indices to read
columns = {'date': 0, 'time': 1, 'tempout': 2, 'windspeed': 7}

# Data types for each column (only if non-string)
types = {'tempout': float, 'windspeed': float}

# Initialize my data variable
data = {}
for column in columns:
   data[column] = []

# Read and parse the data file
filename = "data/wxobs20170821.txt"
with open(filename, 'r') as datafile:

   # Read the first three lines (header)
   for _ in range(3):
      datafile.readline()

   # Read and parse the rest of the file
   for line in datafile:
      split_line = line.split()
      for column in columns:
         i = columns[column]
         t = types.get(column, str)
         value = t(split_line[i])
         data[column].append(value)

# DEBUG
print(data['tempout'])

# Compute the wind chill temperature
def compute_windchill(t, v):
   a = 35.74
   b = 0.6215
   c = 35.75
   d = 0.4275

   v16 = v ** 0.16
   wci = a + (b * t) - (c * v16) + (d * t * v16)
   return wci

# Let's actually compute the wind chill factor
windchill = []
for temp, windspeed in zip(data['tempout'], data['windspeed']):
   windchill.append(compute_windchill(temp, windspeed))

# DEBUG
print(windchill)

# Output comparison of data
print('                ORIGINAL  COMPUTED')
print(' DATE    TIME  WINDCHILL WINDCHILL DIFFERENCE')
print('------- ------ --------- --------- ----------')
zip_data = zip(data['date'], data['time'], data['windchill'], windchill)
for date, time, wc_orig, wc_comp in zip_data:
   wc_diff = wc_orig - wc_comp
   print(f'{date} {time:>6} {wc_orig:9.6f} {wc_comp:9.6f} {wc_diff:10.6f}')