Python package to translate between gdx (GAMS data) and pandas.
There are two main ways to use gdxpds. The first use case is the one that was
initially supported: direct conversion between GDX files on disk and pandas
DataFrames or a csv version thereof. The Version 1.0.0 rewrite intoduces a
second style of use, that is, interfacing with GDX files and symbols via the
gdxpds.gdx.GdxFile
and gdxpds.gdx.GdxSymbol
classes.
Direct Conversion | Backend Classes
The two primary points of reference for the direct conversion utilities are GDX
files on disk and python dicts of {symbol_name: pandas.DataFrame}, where
each pandas.DataFrame contains data for a single set, parameter, equation, or
variable. For sets and parameters, the last column of the DataFrame is assumed to
contain the value of the element, which for sets should be True
, and for
parameters should be a float
(or one of the gdxpds.gdx.NUMPY_SPECIAL_VALUES
).
Equations and variables have additional 'value' columns, in particular a level,
a marginal value, a lower bound, an upper bound, and a scale, as enumerated in
gdxpds.gdx.GamsValueType
. These values are all assumed to be found in the last
five columns of the DataFrame, also see gdxpds.gdx.GAMS_VALUE_COLS_MAP
.
The basic interface to convert from GDX to DataFrames is:
import gdxpds
gdx_file = 'C:\path_to_my_gdx\data.gdx'
dataframes = gdxpds.to_dataframes(gdx_file)
for symbol_name, df in dataframes.items():
print("Doing work with {}.".format(symbol_name))
And vice-versa:
import gdxpds
# assume we have a DataFrame df with last column 'value'
data_ready_for_GAMS = { 'symbol_name': df }
gdx_file = 'C:\path_to_my_output_gdx\data_to_send_to_gams.gdx'
gdx = gdxpds.to_gdx(data_ready_for_GAMS, gdx_file)
Note that providing a gdx_file is optional, and the returned gdx is an object of
type gdxpds.gdx.GdxFile
.
Additional functions include:
gdxpds.list_symbols
gdxpds.to_dataframe
(If the call to this method includes old_interface=False, then the return value will be a plain DataFrame, not a {'symbol_name': df} dict.)
The package also includes command line utilities for converting between GDX and CSV, see
python C:\your_python_path\Scripts\gdx_to_csv.py --help
python C:\your_python_path\Scripts\csv_to_gdx.py --help
The basic functionalities described above can also be achieved with direct use
of the backend classes now available in gdxpds.gdx
. To duplicate the GDX read
functionality shown above one would write:
import gdxpds
gdx_file = 'C:\path_to_my_gdx\data.gdx'
with gdxpds.gdx.GdxFile(lazy_load=False) as f:
f.read(gdx_file)
for symbol in f:
symbol_name = symbol.name
df = symbol.dataframe
print("Doing work with {}:\n{}".format(symbol_name,df.head()))
The backend especially gives more control over creating new data in GDX format. For example:
import gdxpds
out_file = 'my_new_gdx_data.gdx'
with gdxpds.gdx.GdxFile() as gdx:
# Create a new set with one dimension
gdx.append(gdxpds.gdx.GdxSymbol('my_set',gdxpds.gdx.GamsDataType.Set,dims=['u']))
data = pds.DataFrame([['u' + str(i)] for i in range(1,11)])
data['Value'] = True
gdx[-1].dataframe = data
# Create a new parameter with one dimension
gdx.append(gdxpds.gdx.GdxSymbol('my_parameter',gdxpds.gdx.GamsDataType.Parameter,dims=['u']))
data = pds.DataFrame([['u' + str(i), i*100] for i in range(1,11)],
columns=(gdx[-1].dims + gdx[-1].value_col_names))
gdx[-1].dataframe = data
gdx.write(out_file)
- Python 2.6 or higher 2.X; Python 3.4 or higher 3.X
- pandas (In general you will want the SciPy stack. Anaconda comes with it, or see my notes for Windows.)
- For Python versions < 3.4, enum34. Also uninstall the enum package if it is installed.
- psutil (optional--for monitoring memory use)
- pytest (optional--for running tests)
- GAMS Python bindings
-
See GAMS/win64/XX.X/apifiles/readme.txt on Windows, GAMS/gamsXX.X_osx_x64_64_sfx/apifiles/readme.txt on Mac, or /opt/gams/gamsXX.X_linux_x64_64_sfx/apifiles/readme.txt on Linux
-
Run the following for the correct version of the Python bindings
python setup.py install
or
python setup.py build --build-base=/path/to/somwhere/you/have/write/access install
with the latter being for the case when you can install packages into Python but don't have GAMS directory write access.
-
.../apifiles/Python/api/setup.py works for Python 2.7
-
For other versions of Python, especially 3.X, use .../apifiles/Python/api_XX/setup.py. For Python 3.X in particular you will need GAMS version >= 24.5.1 (Python 3.4, Windows and Linux), 24.7.4 (Python 3.4, Mac OS X), or >= 24.8.4 (Python 3.6)
-
pip install gdxpds
or
pip install git+https://github.com/NREL/gdx-pandas.git@v1.0.4
or
pip install git+https://github.com/NREL/gdx-pandas.git@master
Versions are listed at pypi and https://github.com/NREL/gdx-pandas/releases.
After installation, you can test the package using pytest:
pytest --pyargs gdxpds
If the tests fail due to permission IOErrors, apply chmod g+x
and chmod a+x
to the gdx-pandas/gdxpds/test
folder.
pip uninstall gdxpds