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Load data from v7.3 *.mat files.

Project description

Load data from v7.3 *.mat files. Only reading is supported, no writing.

Usage

Provides a class Hdf5Matfile and a convience function load_hdf5mat.

To load all the variables from the file, use Hdf5Matfile.load_file:

with Hdf5Matfile(filename) as file:
    data = file.load_file()

To fully load a specific variable from disk, use Hdf5Matfile.load_variable:

with Hdf5Matfile(filename) as file:
    results = file.load_variable('results')

For partial loading, a mapping/dict-like interface is also supported:

with Hdf5Matfile(filename) as file:
    results = file['results']
    time = results[0, :]
    disp = results[1, :]
    ...

If you’re not using a context manager, make sure to close the file after you’re done:

file = Hdf5Matfile(filename)
data = file.load_file()
...
file.close()

By default, arrays are not squeezed; since MATLAB represents even scalars as 2-D arrays, this means that something you expect to be a scalar will in fact be a 1-by-1 np.ndarray. You can change this by passing squeeze=True to the constructor:

with Hdf5Matfile(filename, squeeze=True) as file:
    data = file.load_file()

Supported data types

Data type support is pretty limited; this isn’t a terribly fancy class. Supported MATLAB data types, and the Python objects or NumPy dtypes they map to:

MATLAB type

Python object

NumPy dtype

cell

np.ndarray

object

char

str

n/a

double

np.ndarray

np.double

int8

np.ndarray

np.int8

int16

np.ndarray

np.int16

int32

np.ndarray

np.int32

int64

np.ndarray

np.int64

logical

np.ndarray

np.bool8

single

np.ndarray

np.single

struct (scalar)

dict

n/a

struct (array)

np.ndarray

object (dict)

uint8

np.ndarray

np.uint8

uint16

np.ndarray

np.uint16

uint32

np.ndarray

np.uint32

uint64

np.ndarray

np.uint64

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