Speed up of about 33%, maybe? #210
Added a real fix for #209, seeing about a 22% speed up there.
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1 changed files with 14 additions and 18 deletions
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@ -1882,21 +1882,14 @@ class PaletteBox(Jp2kBox):
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fptr.write(write_buffer)
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bps = self.bits_per_component
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if any(b != bps[0] for b in bps):
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if all(b == bps[0] for b in bps):
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# All components are the same. Writing is straightforward.
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if self.bits_per_component[0] <= 8:
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code = 'B'
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dtype = np.uint8
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write_buffer = np.getbuffer(self.palette.astype(np.uint8))
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elif self.bits_per_component[0] <= 16:
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code = 'H'
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dtype = np.uint16
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write_buffer = np.getbuffer(self.palette.astype(np.uint16))
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elif self.bits_per_component[0] <= 32:
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code = 'I'
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dtype = np.uint32
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nelts = self.palette.shape[0] * self.palette.shape[1]
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fmt = '>{0}{1}'.format(nelts, code)
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write_buffer = struct.pack(fmt,
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self.palette.astype(dtype).flatten())
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write_buffer = np.getbuffer(self.palette.astype(np.uint32))
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fptr.write(write_buffer)
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else:
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# Not all the components are the same. More general, but much rarer
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@ -1937,19 +1930,22 @@ class PaletteBox(Jp2kBox):
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bps = [((x & 0x7f) + 1) for x in bps_signed]
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signed = [((x & 0x80) > 1) for x in bps_signed]
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if any(b != bps_signed[0] for b in bps_signed):
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if all(b == bps_signed[0] for b in bps_signed):
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# Ok the palette has the same datatype for all columns. We should
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# be able to efficiently read it.
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if bps <= 8:
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if bps[0] <= 8:
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nbytes_per_row = num_columns
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dtype = np.uint8
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elif bps <= 16:
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elif bps[0] <= 16:
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nbytes_per_row = 2 * num_columns
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dtype = np.uint16
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elif bps <= 32:
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elif bps[0] <= 32:
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nbytes_per_row = 3 * num_columns
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dtype = np.uint32
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read_buffer = fptr.read(num_entries * np.sum(bps) / 8)
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palette = np.frombuffer(read_buffer, dtype)
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palette.reshape((num_entries, num_columns))
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read_buffer = fptr.read(num_entries * nbytes_per_row)
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palette = np.frombuffer(read_buffer, dtype=dtype)
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palette = np.reshape(palette, (num_entries, num_columns))
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else:
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# General case where the columns may not be the same width.
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