Changeset 2544 for TI02-CSML

Timestamp:

31/05/07 15:04:34 (13 years ago)

Author:

domlowe

Message:

adding Mark's optimisation to RawFileInterface?

File:

• TI02-CSML/trunk/csml/csmllibs/csmldataiface.py (modified) (2 diffs)

TI02-CSML/trunk/csml/csmllibs/csmldataiface.py

@@ -597 +597 @@
    # Read the data from the raw file into a multidimensional Numeric array
    def readFile(self, **kwargs):
-      # Valid values for numericType and their associated struct format
-      # character:
-      numericLookup = {
-         'uint8':'B', 'uint16':'H', 'uint32':'I', 'uint64':'Q',
-          'int8':'b',  'int16':'h',  'int32':'i',  'int64':'q',
-         'float':'f', 'double':'d'
-      }
-
-      # Valid values for endianness and their associated struct format
-      # character:
-      endiannessLookup = {
-         'big':'>',  'little':'<',  'host':'='
-      }
-
-      # Build the desired format string:
-      try:
-         format_str  = endiannessLookup[kwargs['endianness']]
-         format_str += str(reduce(lambda a,b:a*b, kwargs['dimensions']))
-         format_str += numericLookup[kwargs['numericType']]
-      except KeyError, TypeError:
-         raise TypeError("Missing or invalid parameters. Required: endianness=str, dimensions=list and numericType=str")
-
-      # Read and unpack data into a Numeric array.
-      self.data = Numeric.array(struct.unpack(format_str, self.file.read()))
-      self.data.shape = tuple(map(int, kwargs['dimensions']))
-      
-      # If numericTransform or fillValue were provided, store them as 
-      # attributes.
-      if 'numericTransform' in kwargs:
-         self.numericTransform = NumericTransform.infixExpression(kwargs['numericTransform'])
-      if 'fillValue' in kwargs:
-         self.fillValue = kwargs['fillValue']
-
-
+        # Determine the numeric type:
+        if 'numericType' in kwargs:
+            try:
+                numericTypeCode = {
+                    'uint8':Numeric.UInt8,
+                    'uint16':Numeric.UInt16,
+                    'uint32':Numeric.UInt32,
+                    'int8':Numeric.Int8,
+                    'int16':Numeric.Int16,
+                    'int32':Numeric.Int32,
+                    'float':Numeric.Float32,
+                    'double':Numeric.Float64
+                }[kwargs['numericType']]
+            except KeyError:
+                raise TypeError("Invalid numericType: " + str(kwargs['numericType']))
+        else:
+            raise KeyError("numericType is mandatory.")
+        
+        # Read the file into a numpy array:
+        self.data = Numeric.fromstring(self.file.read(), numericTypeCode)
+        # If necessary, swap the byte order:
+        if 'endianess' in kwargs:
+            if ((kwargs['endianness'] == 'little' and not Numeric.LittleEndian) or (kwargs['endianness'] == 'big' and Numeric.LittleEndian)):
+                self.data = self.data.byteswapped()    
+        # Declare the shape of the array:
+        dimensions = map(int,kwargs['dimensions'])
+        dimensions.reverse()
+        self.data.shape = tuple(dimensions)
+        # If numericTransform or fillValue were provided, store them as
+        # attributes.
+        if 'numericTransform' in kwargs:
+            self.numericTransform = NumericTransform.infixExpression(kwargs['numericTransform'])
+            if 'fillValue' in kwargs:
+                self.fillValue = kwargs['fillValue']
+   
    # Return the fill value, if set, and transform if necessary:
    def getFillValue(self):
@@ -673 +674 @@
          # Requested upper bound of subset is beyond the size of the the full
          # data array, so raise an exception
-         raise IndexException("Subset out of range")
+         raise IndexError("Subset out of range")
       elif Numeric.sometrue(Numeric.less( kwargs['upper'], Numeric.zeros(len(self.data.shape)))):
          # Requested lower bound of subset is beyond the size of the the full
          # data array, so raise an exception
-         raise IndexException("Subset out of range")
+         raise IndexError("Subset out of range")
       elif Numeric.sometrue(Numeric.less_equal(kwargs['upper'], kwargs['lower'])):
          # lower bound <= upper_bound for at least one dimension, so raise an
          # exception
-         raise IndexException("Upper bound less than lower bound")
+         raise IndexError("Upper bound less than lower bound")
       elif tuple(kwargs['lower']) == (0,)*len(self.data.shape) and tuple(kwargs['upper']) == self.data.shape:
          # Special case of requested subset == entire data file.