test_hdf5.py

#!/usr/bin/env python
# Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
#
# Copyright (C) 2011-2014 Idiap Research Institute, Martigny, Switzerland

"""Tests for the base HDF5 infrastructure."""

import random
import tempfile

import numpy as np

from bob.io.base import load, save


def read_write_check(data, numpy_assert=True):
    """Testing loading and save different file types."""
    with tempfile.NamedTemporaryFile(prefix="bobtest_", suffix=".hdf5") as f:
        save(data, f.name)
        data2 = load(f.name)
        if numpy_assert:
            assert np.allclose(data, data2, atol=10e-5, rtol=10e-5)
        else:
            assert data == data2


def test_type_support():
    # This test will go through all supported types for reading/writing data
    # from to HDF5 files. One single file will hold all data for this test.
    # This is also supported with HDF5: multiple variables in a single file.

    N = 100

    data = [int(random.uniform(0, 100)) for z in range(N)]

    read_write_check(np.array(data, np.int8))
    read_write_check(np.array(data, np.uint8))
    read_write_check(np.array(data, np.int16))
    read_write_check(np.array(data, np.uint16))
    read_write_check(np.array(data, np.int32))
    read_write_check(np.array(data, np.uint32))
    read_write_check(np.array(data, np.int64))
    read_write_check(np.array(data, np.uint64))
    read_write_check(np.array(data, np.float32))
    read_write_check(np.array(data, np.float64))
    read_write_check(np.array(data, np.complex64))
    read_write_check(np.array(data, np.complex128))


def test_scalar_support():
    for oracle in (1, 1.0, 1j, "a", True):
        read_write_check(oracle, numpy_assert=False)