parameters: (SourceFilePath)
return_statement: return np.asarray(Data,dtype=np.uint32).reshape(tuple(list(Shape)+[nChannel]),order="C")
docstring: Loads a file generated by StoreNDTextureHDR() and returns it as an array like 
         the one that goes into StoreNDTextureHDR() using data type np.uint32. On 
         failure it returns None.
docstring_summary: Loads a file generated by StoreNDTextureHDR() and returns it as an array like 
         the one that goes into StoreNDTextureHDR() using data type np.uint32. On 
         failure it returns None.
docstring_tokens: Loads a file generated by StoreNDTextureHDR () and returns it as an array like the one that goes into StoreNDTextureHDR () using data type np . uint32 . On failure it returns None .
function: def LoadNDTextureHDR(SourceFilePath):
      """Loads a file generated by StoreNDTextureHDR() and returns it as an array like 
         the one that goes into StoreNDTextureHDR() using data type np.uint32. On 
         failure it returns None."""
      # Load the meta data
      File=open(SourceFilePath,"rb");
      Version,nChannel,nDimension=struct.unpack_from("LLL",File.read(12));
      if(Version!=1):
          return None;
      Shape=struct.unpack_from("L"*nDimension,File.read(4*nDimension));
      nScalar=np.prod(Shape)*nChannel;
      Data=struct.unpack_from("L"*nScalar,File.read(4*nScalar));
      File.close();
      # Prepare the output
      return np.asarray(Data,dtype=np.uint32).reshape(tuple(list(Shape)+[nChannel]),order="C");
function_tokens: def LoadNDTextureHDR ( SourceFilePath ) : # Load the meta data File = open ( SourceFilePath , "rb" ) Version , nChannel , nDimension = struct . unpack_from ( "LLL" , File . read ( 12 ) ) if ( Version != 1 ) : return None Shape = struct . unpack_from ( "L" * nDimension , File . read ( 4 * nDimension ) ) nScalar = np . prod ( Shape ) * nChannel Data = struct . unpack_from ( "L" * nScalar , File . read ( 4 * nScalar ) ) File . close ( ) # Prepare the output return np . asarray ( Data , dtype = np . uint32 ) . reshape ( tuple ( list ( Shape ) + [ nChannel ] ) , order = "C" )