preprocess

preprocess.py

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+#!/usr/bin/env python
+import numpy as np
+from scipy.signal import butter, lfilter, freqz, medfilt
+#from optparse import OptionParser
+import argparse
+import sys
+import signal
+
+def butter_lowpass(cutoff, fs, order):
+  nyq = 0.5 * fs
+  normal_cutoff = cutoff / nyq
+  b, a = butter(order, normal_cutoff, btype='low', analog=False)
+  return b, a
+
+def butter_highpass(cutoff, fs, order):
+  nyq = 0.5 * fs
+  normal_cutoff = cutoff / nyq
+  b, a = butter(order, normal_cutoff, btype='high', analog=False)
+  return b, a
+
+def butter_lowpass_filter(data, cutoff, fs, order):
+  b, a = butter_lowpass(cutoff, fs, order=order)
+  y = lfilter(b, a, data)
+  return y
+
+def butter_highpass_filter(data, cutoff, fs, order):
+  b, a = butter_highpass(cutoff, fs, order=order)
+  y = lfilter(b, a, data)
+  return y
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("-c", "--cutoff", dest="cutoff",
+                  help="cutoff frequency", metavar="CUTOFF", type=float)
+parser.add_argument("-f", "--frequency", dest="fs",
+                  help="The rate of incoming data", metavar="RATE", type=float)
+#comment the next block for now and compute it straight from input
+#parser.add_argument("-n", "--size", dest="vectorSize",
+#                  help="The vector size of the incoming data", metavar="VECTOR_SIZE", type=int)
+parser.add_argument("-o", "--order", dest="order", default=5,
+                  help="The filter's order (optional)", metavar="ORDER", type=int)
+parser.add_argument("-t", "--type", dest="filterType", default="LPF",
+                  help="The type of filter to use, HPF (High-Pass Filter), or LPF (Low-Pass Filter). The default is set to LPF.", metavar="FILTER_TYPE")
+
+
+args = parser.parse_args()
+
+#this is a default value in case the user doesn't provide it.
+order=5
+try: 
+  order = int(args.order)
+except ValueError:
+  print("Wrong value for order entered.")
+  sys.exit(1)
+
+#comment the next block for now and compute it straight from input
+#try: 
+#  vectorSize = args.vectorSize
+#except ValueError:
+#  print("Wrong value for VECTOR_SIZE entered.")
+#  sys.exit()
+
+try: 
+  cutoff = args.cutoff
+except ValueError:
+  print("Wrong value for cutoff frequency entered.")
+  sys.exit()
+
+try: 
+  fs = args.fs
+except ValueError:
+  print("Wrong value for RATE entered.")
+  sys.exit(1)
+
+filterType = args.filterType
+filterType = filterType.upper()
+
+#if condition to check on the data entered, exit if soemthing is wrong or missing
+if filterType not in ["LPF","HPF"]:
+  print("Wrong type of filter selected.")
+  sys.exit(1)
+
+if order < 1:
+  print("Invalid value for filter's order.")
+  sys.exit(1) 
+
+if fs <= 0:
+  print("Invalid value for data frequency.")
+  sys.exit(1)
+
+if cutoff <= 0:
+  print("Invalid value for cutoff frequency.")
+  sys.exit(1)
+
+#load data from stdin as string
+try:
+#  data = np.loadtxt(sys.stdin, dtype=str)
+  data = np.loadtxt(sys.stdin, dtype=bytes).astype(str)
+ #loadtxt will throw an exception if the rows are not consistent.
+except ValueError:
+  print("Invalid input data.")
+  sys.exit(1)
+
+#take the label column and place it in the final array
+finalData = data[:,0]
+#take the remainder in a 2d float array
+floats = data[:,1:].astype(np.float)
+
+#compute the vector size from the first line
+vectorSize = len(floats[0])
+
+for i in range(0,vectorSize):
+
+  #filter a column
+  if filterType == "HPF":
+    filteredData = butter_highpass_filter(floats[:, i], cutoff, fs, order)
+  elif filterType == "LPF":
+    filteredData = butter_lowpass_filter(floats[:, i], cutoff, fs, order)
+
+  #stack each newly filtered array to the final array
+  finalData = np.column_stack((finalData, filteredData))
+
+#print to stdout
+print('\n'.join(['\t'.join([item for item in row]) for row in finalData]))