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python/envi.py 9.76 KB
18368aa9   David Mayerich   added a new set o...
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  # -*- coding: utf-8 -*-
  """
  Created on Fri Jul 21 20:18:01 2017
  
  @author: david
  """
  
  import os
  import numpy
  import scipy
  import matplotlib.pyplot as plt
  import progressbar
  
  class envi_header:
      def __init__(self, filename = ""):
          if filename != "":
              self.load(filename)
          else:
              self.initialize()
          
      #initialization function
      def initialize(self):
          self.samples = int(0)
          self.lines = int(0)
          self.bands = int(0)
          self.header_offset = int(0)
          self.data_type = int(4)
          self.interleave = "bsq"
          self.sensor_type = ""
          self.byte_order = int(0)
          self.x_start = int(0)
          self.y_start = int(0)
          self.z_plot_titles = ""
          self.pixel_size = [float(0), float(0)]
          self.pixel_size_units = "Meters"
          self.wavelength_units = "Wavenumber"
          self.description = ""
          self.band_names = []
          self.wavelength = []
          
      #convert an ENVI data_type value to a numpy data type        
      def get_numpy_type(self, val):
          if val == 1:
              return numpy.byte
          elif val == 2:
              return numpy.int16
          elif val == 3:
              return numpy.int32
          elif val == 4:
              return numpy.float32
          elif val == 5:
              return numpy.float64
          elif val == 6:
              return numpy.complex64
          elif val == 9:
              return numpy.complex128
          elif val == 12:
              return numpy.uint16
          elif val == 13:
              return numpy.uint32
          elif val == 14:
              return numpy.int64
          elif val == 15:
              return numpy.uint64
      
      def get_envi_type(self, val):
          if val == numpy.byte:
              return 1
          elif val == numpy.int16:
              return 2
          elif val == numpy.int32:
              return 3
          elif val == numpy.float32:
              return 4
          elif val == numpy.float64:
              return 5
          elif val == numpy.complex64:
              return 6
          elif val == numpy.complex128:
              return 9
          elif val == numpy.uint16:
              return 12
          elif val == numpy.uint32:
              return 13
          elif val == numpy.int64:
              return 14
          elif val == numpy.uint64:
              return 15
              
      def load(self, fname):
          f = open(fname)
          l = f.readlines()
          if l[0].strip() != "ENVI":
              print("ERROR: not an ENVI file")
              return
          li = 1
          while li < len(l):
              #t = l[li].split()               #split the line into tokens
              #t = map(str.strip, t)               #strip all of the tokens in the token list
              
              #handle the simple conditions
              if l[li].startswith("file type"):
                  if not l[li].strip().endswith("ENVI Standard"):
                      print("ERROR: unsupported ENVI file format: " + l[li].strip())
                      return
              elif l[li].startswith("samples"):
                  self.samples = int(l[li].split()[-1])
              elif l[li].startswith("lines"):
                  self.lines = int(l[li].split()[-1])
              elif l[li].startswith("bands"):
                  self.bands = int(l[li].split()[-1])
              elif l[li].startswith("header offset"):
                  self.header_offset = int(l[li].split()[-1])
              elif l[li].startswith("data type"):
                  self.data_type = self.get_numpy_type(int(l[li].split()[-1]))
              elif l[li].startswith("interleave"):
                  self.interleave = l[li].split()[-1].strip()
              elif l[li].startswith("sensor type"):
                  self.sensor_type = l[li].split()[-1].strip()
              elif l[li].startswith("byte order"):
                  self.byte_order = int(l[li].split()[-1])
              elif l[li].startswith("x start"):
                  self.x_start = int(l[li].split()[-1])
              elif l[li].startswith("y start"):
                  self.y_start = int(l[li].split()[-1])
              elif l[li].startswith("z plot titles"):
                  i0 = l[li].rindex('{')
                  i1 = l[li].rindex('}')
                  self.z_plot_titles = l[li][i0 + 1 : i1]
              elif l[li].startswith("pixel size"):
                  i0 = l[li].rindex('{')
                  i1 = l[li].rindex('}')
                  s = l[li][i0 + 1 : i1].split(',')
                  self.pixel_size = [float(s[0]), float(s[1])]
                  self.pixel_size_units = s[2][s[2].rindex('=') + 1:].strip()
              elif l[li].startswith("wavelength units"):
                  self.wavelength_units = l[li].split()[-1].strip()                
              
              #handle the complicated conditions
              elif l[li].startswith("description"):
                  desc = [l[li]]
                  while l[li].strip()[-1] != '}':
                      li += 1
                      desc.append(l[li])
                  desc = ''.join(list(map(str.strip, desc)))           #strip all white space from the string list
                  i0 = desc.rindex('{')
                  i1 = desc.rindex('}')
                  self.description = desc[i0 + 1 : i1]
                  
              elif l[li].startswith("band names"):
                  names = [l[li]]
                  while l[li].strip()[-1] != '}':
                      li += 1
                      names.append(l[li])
                  names = ''.join(list(map(str.strip, names)))           #strip all white space from the string list
                  i0 = names.rindex('{')
                  i1 = names.rindex('}')
                  names = names[i0 + 1 : i1]
                  self.band_names = list(map(str.strip, names.split(',')))
              elif l[li].startswith("wavelength"):
                  waves = [l[li]]
                  while l[li].strip()[-1] != '}':
                      li += 1
                      waves.append(l[li])
                  waves = ''.join(list(map(str.strip, waves)))           #strip all white space from the string list
                  i0 = waves.rindex('{')
                  i1 = waves.rindex('}')
                  waves = waves[i0 + 1 : i1]
                  self.wavelength = list(map(float, waves.split(',')))
  
              li += 1          
          
          f.close()
          
  class envi:
      def __init__(self, filename, headername = "", maskname = ""):
          self.open(filename, headername)
          if maskname == "":
              self.mask = numpy.ones((self.header.samples, self.header.lines), dtype=numpy.bool)
          else:
              self.mask = scipy.misc.imread(maskname, flatten=True).astype(numpy.bool)
          
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      def open(self, filename, headername = ""):
          if headername == "":
              headername = filename + ".hdr"
              
          if not os.path.isfile(filename):
              print("ERROR: " + filename + " not found")
              return
          if not os.path.isfile(headername):
              print("ERROR: " + headername + " not found")
              return
          
          #open the file
          self.header = envi_header(headername)
          self.file = open(filename, "rb")
          
      def loadall(self):
          X = self.header.samples
          Y = self.header.lines
          B = self.header.bands
          
          #load the data
          D = numpy.fromfile(self.file, dtype=self.header.data_type)
          
          if self.header.interleave == "bsq":
              return numpy.reshape(D, (B, Y, X))
              #return numpy.swapaxes(D, 0, 2)
          elif self.header.interleave == "bip":
              D = numpy.reshape(D, (Y, X, B))
              return numpy.rollaxis(D, 2)
          elif self.header.interleave == "bil":
              D = numpy.reshape(D, (Y, B, X))
              return numpy.rollaxis(D, 1)
          
      #loads all of the pixels where mask != 0 and returns them as a matrix
      def loadmask(self, mask):
          X = self.header.samples
          Y = self.header.lines
          B = self.header.bands
          
          P = numpy.count_nonzero(mask)           #count the number of zeros in the mask file
          M = numpy.zeros((B, P), dtype=self.header.data_type)
          type_bytes = numpy.dtype(self.header.data_type).itemsize
          
          self.file.seek(0)
          if self.header.interleave == "bip":
              spectrum = numpy.zeros(B, dtype=self.header.data_type)
              flatmask = numpy.reshape(mask, (X * Y))
              i = numpy.flatnonzero(flatmask)
              bar = progressbar.ProgressBar(max_value = P)
              for p in range(0, P):
                  self.file.seek(i[p] * B * type_bytes)
                  self.file.readinto(spectrum)
                  M[:, p] = spectrum
                  bar.update(p+1)
          if self.header.interleave == "bsq":
              band = numpy.zeros(mask.shape, dtype=self.header.data_type)
              i = numpy.nonzero(mask)
              bar = progressbar.ProgressBar(max_value=B)
              for b in range(0, B):
                  self.file.seek(b * X * Y * type_bytes)
                  self.file.readinto(band)
                  M[b, :] = band[i]
                  bar.update(b+1)
          if self.header.interleave == "bil":
              plane = numpy.zeros((B, X), dtype=self.header.data_type)
              p = 0
              bar = progressbar.ProgressBar(max_value=Y)
              for l in range(0, Y):
                  i = numpy.flatnonzero(mask[l, :])
                  self.file.readinto(plane)
                  M[:, p:p+i.shape[0]] = plane[:, i]
                  p = p + i.shape[0]
                  bar.update(l+1)
          return M
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      def loadband(self, n):
          X = self.header.samples
          Y = self.header.lines
          B = self.header.bands
  
          band = numpy.zeros((Y, X), dtype=self.header.data_type)
          type_bytes = numpy.dtype(self.header.data_type).itemsize
  
          if self.header.interleave == "bsq":
              self.file.seek(n * X * Y * type_bytes)
              self.file.readinto(band)
  
          return band
  
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      def __del__(self):
          self.file.close()