path: root/python-mat73.spec

%global _empty_manifest_terminate_build 0
Name:		python-mat73
Version:	0.60
Release:	1
Summary:	Load MATLAB .mat 7.3 into Python native data types (via h5/hd5/hdf5/h5py)
License:	GPL3
URL:		https://github.com/skjerns/mat7.3
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/8f/36/1f70c608ca2018a8b29dbce25ba11d8bdce6c3f4cdb9e48d1fc592c9eb0c/mat73-0.60.tar.gz
BuildArch:	noarch

Requires:	python3-h5py
Requires:	python3-numpy

%description
![Python package](https://github.com/skjerns/mat7.3/workflows/Python%20package/badge.svg)  ![pypi Version](https://img.shields.io/pypi/v/mat73)

# mat 7.3

Load MATLAB 7.3 .mat files into Python.

Starting with MATLAB 7.3, `.mat` files have been changed to store as custom `hdf5` files.
This means they cannot be loaded by `scipy.io.loadmat` any longer and raise.

```Python
NotImplementedError: Please use HDF reader for matlab v7.3 files
```

## Quickstart

This library loads MATLAB 7.3 HDF5 files into a Python dictionary.

```Python
import mat73
data_dict = mat73.loadmat('data.mat')
```

As easy as that!

By enabling `use_attrdict=True` you can even access sub-entries of `structs` as attributes, just like in MATLAB:

```Python
data_dict = mat73.loadmat('data.mat', use_attrdict=True) 
struct = data_dict['structure'] # assuming a structure was saved in the .mat
struct[0].var1 == struct[0]['var1'] # it's the same!
```

You can also specifiy to only load a specific variable or variable tree, useful to reduce loading times

```Python
data_dict = mat73.loadmat('data.mat', only_include='structure') 
struct = data_dict['structure'] # now only structure is loaded and nothing else

data_dict = mat73.loadmat('data.mat', only_include=['var/subvar/subsubvar', 'tree1/']) 
tree1 = data_dict['tree1'] # the entire tree has been loaded, so tree1 is a dict with all subvars of tree1
subsubvar = data_dict['var']['subvar']['subsubvar'] # this subvar has been loaded
```

## Installation

To install, run:

```
pip install mat73
```

Alternatively for most recent version:

```
pip install git+https://github.com/skjerns/mat7.3
```

## Datatypes

The following MATLAB datatypes can be loaded

| MATLAB                   | Python            |
| ------------------------ | ----------------- |
| logical                  | np.bool_          |
| single                   | np.float32        |
| double                   | np.float64        |
| int8/16/32/64            | np.int8/16/32/64  |
| uint8/16/32/64           | np.uint8/16/32/64 |
| complex                  | np.complex128     |
| char                     | str               |
| struct                   | list of dicts     |
| cell                     | list of lists     |
| canonical empty          | []                |
| missing                  | None              |
| sparse                   | scipy.sparse.csc  |
| Other (ie Datetime, ...) | Not supported     |

## Short-comings

- This library will __only__ load mat 7.3 files. For older versions use `scipy.io.loadmat`
- Proprietary MATLAB types (e.g `datetime`, `duriation`, etc) are not supported. If someone tells me how to convert them, I'll implement that
- For now, you can't save anything back to the .mat. It's a bit more difficult than expected, so it's not on the roadmap for now
- See also [hdf5storage](https://github.com/frejanordsiek/hdf5storage), which can indeed be used for saving .mat, but has less features for loading
- See also [pymatreader](https://gitlab.com/obob/pymatreader/) which has a (maybe even better) implementation of loading MAT files, even for older ones




%package -n python3-mat73
Summary:	Load MATLAB .mat 7.3 into Python native data types (via h5/hd5/hdf5/h5py)
Provides:	python-mat73
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-mat73
![Python package](https://github.com/skjerns/mat7.3/workflows/Python%20package/badge.svg)  ![pypi Version](https://img.shields.io/pypi/v/mat73)

# mat 7.3

Load MATLAB 7.3 .mat files into Python.

Starting with MATLAB 7.3, `.mat` files have been changed to store as custom `hdf5` files.
This means they cannot be loaded by `scipy.io.loadmat` any longer and raise.

```Python
NotImplementedError: Please use HDF reader for matlab v7.3 files
```

## Quickstart

This library loads MATLAB 7.3 HDF5 files into a Python dictionary.

```Python
import mat73
data_dict = mat73.loadmat('data.mat')
```

As easy as that!

By enabling `use_attrdict=True` you can even access sub-entries of `structs` as attributes, just like in MATLAB:

```Python
data_dict = mat73.loadmat('data.mat', use_attrdict=True) 
struct = data_dict['structure'] # assuming a structure was saved in the .mat
struct[0].var1 == struct[0]['var1'] # it's the same!
```

You can also specifiy to only load a specific variable or variable tree, useful to reduce loading times

```Python
data_dict = mat73.loadmat('data.mat', only_include='structure') 
struct = data_dict['structure'] # now only structure is loaded and nothing else

data_dict = mat73.loadmat('data.mat', only_include=['var/subvar/subsubvar', 'tree1/']) 
tree1 = data_dict['tree1'] # the entire tree has been loaded, so tree1 is a dict with all subvars of tree1
subsubvar = data_dict['var']['subvar']['subsubvar'] # this subvar has been loaded
```

## Installation

To install, run:

```
pip install mat73
```

Alternatively for most recent version:

```
pip install git+https://github.com/skjerns/mat7.3
```

## Datatypes

The following MATLAB datatypes can be loaded

| MATLAB                   | Python            |
| ------------------------ | ----------------- |
| logical                  | np.bool_          |
| single                   | np.float32        |
| double                   | np.float64        |
| int8/16/32/64            | np.int8/16/32/64  |
| uint8/16/32/64           | np.uint8/16/32/64 |
| complex                  | np.complex128     |
| char                     | str               |
| struct                   | list of dicts     |
| cell                     | list of lists     |
| canonical empty          | []                |
| missing                  | None              |
| sparse                   | scipy.sparse.csc  |
| Other (ie Datetime, ...) | Not supported     |

## Short-comings

- This library will __only__ load mat 7.3 files. For older versions use `scipy.io.loadmat`
- Proprietary MATLAB types (e.g `datetime`, `duriation`, etc) are not supported. If someone tells me how to convert them, I'll implement that
- For now, you can't save anything back to the .mat. It's a bit more difficult than expected, so it's not on the roadmap for now
- See also [hdf5storage](https://github.com/frejanordsiek/hdf5storage), which can indeed be used for saving .mat, but has less features for loading
- See also [pymatreader](https://gitlab.com/obob/pymatreader/) which has a (maybe even better) implementation of loading MAT files, even for older ones




%package help
Summary:	Development documents and examples for mat73
Provides:	python3-mat73-doc
%description help
![Python package](https://github.com/skjerns/mat7.3/workflows/Python%20package/badge.svg)  ![pypi Version](https://img.shields.io/pypi/v/mat73)

# mat 7.3

Load MATLAB 7.3 .mat files into Python.

Starting with MATLAB 7.3, `.mat` files have been changed to store as custom `hdf5` files.
This means they cannot be loaded by `scipy.io.loadmat` any longer and raise.

```Python
NotImplementedError: Please use HDF reader for matlab v7.3 files
```

## Quickstart

This library loads MATLAB 7.3 HDF5 files into a Python dictionary.

```Python
import mat73
data_dict = mat73.loadmat('data.mat')
```

As easy as that!

By enabling `use_attrdict=True` you can even access sub-entries of `structs` as attributes, just like in MATLAB:

```Python
data_dict = mat73.loadmat('data.mat', use_attrdict=True) 
struct = data_dict['structure'] # assuming a structure was saved in the .mat
struct[0].var1 == struct[0]['var1'] # it's the same!
```

You can also specifiy to only load a specific variable or variable tree, useful to reduce loading times

```Python
data_dict = mat73.loadmat('data.mat', only_include='structure') 
struct = data_dict['structure'] # now only structure is loaded and nothing else

data_dict = mat73.loadmat('data.mat', only_include=['var/subvar/subsubvar', 'tree1/']) 
tree1 = data_dict['tree1'] # the entire tree has been loaded, so tree1 is a dict with all subvars of tree1
subsubvar = data_dict['var']['subvar']['subsubvar'] # this subvar has been loaded
```

## Installation

To install, run:

```
pip install mat73
```

Alternatively for most recent version:

```
pip install git+https://github.com/skjerns/mat7.3
```

## Datatypes

The following MATLAB datatypes can be loaded

| MATLAB                   | Python            |
| ------------------------ | ----------------- |
| logical                  | np.bool_          |
| single                   | np.float32        |
| double                   | np.float64        |
| int8/16/32/64            | np.int8/16/32/64  |
| uint8/16/32/64           | np.uint8/16/32/64 |
| complex                  | np.complex128     |
| char                     | str               |
| struct                   | list of dicts     |
| cell                     | list of lists     |
| canonical empty          | []                |
| missing                  | None              |
| sparse                   | scipy.sparse.csc  |
| Other (ie Datetime, ...) | Not supported     |

## Short-comings

- This library will __only__ load mat 7.3 files. For older versions use `scipy.io.loadmat`
- Proprietary MATLAB types (e.g `datetime`, `duriation`, etc) are not supported. If someone tells me how to convert them, I'll implement that
- For now, you can't save anything back to the .mat. It's a bit more difficult than expected, so it's not on the roadmap for now
- See also [hdf5storage](https://github.com/frejanordsiek/hdf5storage), which can indeed be used for saving .mat, but has less features for loading
- See also [pymatreader](https://gitlab.com/obob/pymatreader/) which has a (maybe even better) implementation of loading MAT files, even for older ones




%prep
%autosetup -n mat73-0.60

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-mat73 -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Wed May 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.60-1
- Package Spec generated