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#!/usr/bin/env python
from __future__ import print_function
# Generate test HDF files using different compression configurations,
# and validate each resulting file to make sure its contents is OK.
# Adapted from example:
# "https://support.hdfgroup.org/doc_resource/SZIP/h4_examples/szip32.c".
# A bigger dataset is defined to better show the size reduction achieved
# by the SZIP compression.
# Note that when applied to HDF4 SDS, the word "pixels" as used inside
# the SZIP documentation should really be understood as a "data element",
# eg a cell value inside a multidimensional array.
#
# On our systems, the program produced the following file sizes :
#
# $ ls -l *.hdf
# -rw-r--r-- 1 root root 53389 Jun 29 14:20 SDS.COMP_DEFLATE.1.hdf
# -rw-r--r-- 1 root root 56524 Jun 29 14:24 SDS.COMP_DEFLATE.2.hdf
# -rw-r--r-- 1 root root 60069 Jun 29 14:24 SDS.COMP_DEFLATE.3.hdf
# -rw-r--r-- 1 root root 59725 Jun 29 14:24 SDS.COMP_DEFLATE.4.hdf
# -rw-r--r-- 1 root root 59884 Jun 29 14:24 SDS.COMP_DEFLATE.5.hdf
# -rw-r--r-- 1 root root 58596 Jun 29 14:24 SDS.COMP_DEFLATE.6.hdf
# -rw-r--r-- 1 root root 58450 Jun 29 14:24 SDS.COMP_DEFLATE.7.hdf
# -rw-r--r-- 1 root root 58437 Jun 29 14:24 SDS.COMP_DEFLATE.8.hdf
# -rw-r--r-- 1 root root 58446 Jun 29 14:24 SDS.COMP_DEFLATE.9.hdf
# -rw-r--r-- 1 root root 102920 Jun 29 14:20 SDS.COMP_NONE.hdf
# -rw-r--r-- 1 root root 103162 Jun 29 14:20 SDS.COMP_RLE.hdf
# -rw-r--r-- 1 root root 60277 Jun 29 14:20 SDS.COMP_SKPHUFF.2.hdf
# -rw-r--r-- 1 root root 52085 Jun 29 14:20 SDS.COMP_SKPHUFF.4.hdf
# -rw-r--r-- 1 root root 52085 Jun 29 14:20 SDS.COMP_SKPHUFF.8.hdf
# -rw-r--r-- 1 root root 71039 Jun 29 14:20 SDS.COMP_SZIP.EC.16.hdf
# -rw-r--r-- 1 root root 79053 Jun 29 14:20 SDS.COMP_SZIP.EC.32.hdf
# -rw-r--r-- 1 root root 66636 Jun 29 14:20 SDS.COMP_SZIP.EC.4.hdf
# -rw-r--r-- 1 root root 66984 Jun 29 14:20 SDS.COMP_SZIP.EC.8.hdf
# -rw-r--r-- 1 root root 39835 Jun 29 14:20 SDS.COMP_SZIP.NN.16.hdf
# -rw-r--r-- 1 root root 44554 Jun 29 14:20 SDS.COMP_SZIP.NN.32.hdf
# -rw-r--r-- 1 root root 38371 Jun 29 14:20 SDS.COMP_SZIP.NN.4.hdf
# -rw-r--r-- 1 root root 38092 Jun 29 14:20 SDS.COMP_SZIP.NN.8.hdf
#
# For the chosen data set, the best results were attained using
# SZIP compression with NN compression scheme and 8 pixels per block.
# Mileage will vary with the data set used.
import sys
import os.path
from pyhdf.SD import *
import numpy
# Array shape and data type.
LENGTH = 250
WIDTH = 100
NUMPY_DATATYPE = numpy.int32
HDF_DATATYPE = SDC.INT32
def doCompress(compType, value=0, v2=0):
"""Create and validate an HDF file using a compression scheme
specified by the parameters"""
# Build a significant file name
if compType == SDC.COMP_NONE:
fileName = "SDS.COMP_NONE"
elif compType == SDC.COMP_RLE:
fileName = "SDS.COMP_RLE"
elif compType == SDC.COMP_SKPHUFF:
fileName = "SDS.COMP_SKPHUFF.%d" % value
elif compType == SDC.COMP_DEFLATE:
fileName = "SDS.COMP_DEFLATE.%d" % value
elif compType == SDC.COMP_SZIP:
fileName = "SDS.COMP_SZIP"
if value == SDC.COMP_SZIP_NN:
fileName += ".NN"
elif value == SDC.COMP_SZIP_EC:
fileName += ".EC"
else:
print("illegal value")
sys.exit(1)
fileName += ".%s" % v2
else:
print("illegal compType")
sys.exit(1)
fileName += ".hdf"
SDS_NAME = "Data"
fill_value = 0
#LENGTH = 9
#WIDTH = 6
#
#data = numpy.array( ((100,100,200,200,300,400),
# (100,100,200,200,300,400),
# (100,100,200,200,300,400),
# (300,300, 0,400,300,400),
# (300,300, 0,400,300,400),
# (300,300, 0,400,300,400),
# (0, 0,600,600,300,400),
# (500,500,600,600,300,400),
# (0, 0,600,600,300,400)), NUMPY_DATATYPE)
# The above dataset is used in the original NCSA example.
# It is too small to show a significant size reduction after
# compression. The following is used for a more realistic example.
data = numpy.zeros((LENGTH, WIDTH), NUMPY_DATATYPE)
for i in range(LENGTH):
for j in range(WIDTH):
data[i,j] = (i+j)*(i-j)
# Create HDF file, wiping it out it it already exists.
sd_id = SD(fileName, SDC.WRITE | SDC.CREATE | SDC.TRUNC)
# Create dataset.
sds_id = sd_id.create(SDS_NAME, HDF_DATATYPE, (LENGTH, WIDTH))
# Fill dataset will fill value.
sds_id.setfillvalue(0)
# Apply compression.
try:
sds_id.setcompress(compType, # compression type
value, v2) # args depend on compression type
except HDF4Error as msg:
print(("Error compressing the dataset with params: "
"(%d,%d,%d) : %s" % (compType, value, v2, msg)))
sds_id.endaccess()
sd_id.end()
os.remove(fileName)
return
# Load data in the dataset.
sds_id[:] = data
# Close dataset.
sds_id.endaccess()
# Close hdf file to flush compressed data.
sd_id.end()
# Verify compressed data.
# ######################
# Reopen file and select first dataset.
sd_id = SD(fileName, SDC.READ)
sds_id = sd_id.select(0)
# Obtain compression info.
compInfo = sds_id.getcompress()
compType = compInfo[0]
print("file : %s" % fileName)
print(" size = %d" % os.path.getsize(fileName))
if compType == SDC.COMP_NONE:
print(" compType = COMP_NONE")
elif compType == SDC.COMP_RLE:
print(" compType = COMP_RLE")
elif compType == SDC.COMP_SKPHUFF:
print(" compType = COMP_SKPHUFF")
print(" dataSize = %d" % compInfo[1])
elif compType == SDC.COMP_DEFLATE:
print(" compType = COMP_DEFLATE (GZIP)")
print(" level = %d" % compInfo[1])
elif compType == SDC.COMP_SZIP:
print(" compType = COMP_SZIP")
optionMask = compInfo[1]
if optionMask & SDC.COMP_SZIP_NN:
print(" encoding scheme = NN")
elif optionMask & SDC.COMP_SZIP_EC:
print(" encoding scheme = EC")
else:
print(" unknown encoding scheme")
sys.exit(1)
pixelsPerBlock, pixelsPerScanline, bitsPerPixel, pixels = compInfo[2:]
print(" pixelsPerBlock = %d" % pixelsPerBlock)
print(" pixelsPerScanline = %d" % pixelsPerScanline)
print(" bitsPerPixel = %d" % bitsPerPixel)
print(" pixels = %d" % pixels)
else:
print(" unknown compression type")
sys.exit(1)
# Read dataset contents.
out_data = sds_id[:]
# Compare with original data.
num_errs = 0
for i in range(LENGTH):
for j in range(WIDTH):
if data[i,j] != out_data[i,j]:
print("bad value at %d,%d expected: %d got: %d" \
% (i,j,data[i,j],out_data[i,j]))
num_errs += 1
# Close dataset and hdf file.
sds_id.endaccess()
sd_id.end()
if num_errs == 0:
print(" file validated")
else:
print(" file invalid : %d errors" % num_errs)
print("")
# Try different compression configurations in turn.
# All the following calls will fail with a "Cannot execute" exception if pyhdf
# was installed with the NOCOMPRESS macro set.
# No compression
print("no compression")
doCompress(SDC.COMP_NONE)
# RLE compression
print("run-length encoding")
doCompress(SDC.COMP_RLE)
# Skipping-Huffman compression.
print("Skipping-Huffman encoding")
for size in 2,4,8:
doCompress(SDC.COMP_SKPHUFF, size) # size in bytes of the data elements
# Gzip compression
print("GZIP compression")
for level in 1,2,3,4,5,6,7,8,9:
doCompress(SDC.COMP_DEFLATE, level) # compression level, from 1 to 9
# SZIP compression
# Those calls will fail with an "Encoder not available" exception if
# pyhdf was installed with the NOSZIP macro set.
print("SZIP compression")
for scheme in SDC.COMP_SZIP_NN, SDC.COMP_SZIP_EC:
for ppb in 4,8,16,32:
doCompress(SDC.COMP_SZIP, scheme, ppb) # scheme, pixels per block
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