omegalpes.general.utils package

Submodules

omegalpes.general.utils.input_data module

This module includes the following utils for input data management

It contains the following methods:

  • select_csv_file_between_dates() : select data in a .csv file between two dates

  • read_enedis_data_csv_file() : select and rearrange the data in a .csv file of Enedis (the French Distribion System Operator company), possibly between two dates

omegalpes.general.utils.input_data.read_enedis_data_csv_file(file_path=None, start=None, end=None)[source]

Rearrange the Enedis data in cvs file in oder to have a Dataframe of the following form

DD MM YYYY HH:00 ; a DD MM YYYY HH:30 ; b …

Parameters:

  • file_path – path of the file to rearrange

  • start – DD MM YYYY HH:00 : first date which should be considered

  • end – DD MM YYYY HH:00 : last date which should be considered

Returns:

df_list: the data as a list

omegalpes.general.utils.input_data.resample_data(input_list=None, dt_origin=1.0, dt_final=1.0, fill_config='ffill', pick_config='mean')[source]

Changing data set in a dt_origin time step into data set in a dt_final time step :param input_list: list to be resample (list or dict) :param dt_origin: the time step of the input dataset (in hours) :param dt_final: the wanted time step for the output dataset (in hours) :param fill_config: choose the configuration of filling when dt_origin > dt_final by default: ffil, keeping the same data over the time steps other way: interpolate, taking into account the time steps) :param pick_config: choose the configuration of picking when dt_origin < dt_final by default: “mean” which determines the mean value of the time steps to be reduced :return: output_list: resampled list (pandas Series)

omegalpes.general.utils.input_data.select_csv_file_between_dates(file_path=None, start='DD/MM/YYYY HH:MM', end='DD/MM/YYYY HH:MM', v_cols=[], sep=';')[source]

Select data in a .csv file between two dates

Parameters:

  • file_path – path of the file to rearrange

  • start – DD MM YYYY HH:00 : first date which should be considered

  • end – DD MM YYYY HH:00 : last date which should be considered

  • v_cols – columns which should be considered

Returns:

df: a dataframe considering the dates

omegalpes.general.utils.maths module

This module includes the following maths utils

It contains the following methods:

  • def_abs_value() : Define easily absolute value for quantity

omegalpes.general.utils.maths.def_abs_value(quantity, q_min, q_max)[source]
Parameters:

  • quantity – Quantity whose absolute value is wanted

  • q_min – Minimal value of the quantity (negative value)

  • q_max – Maximal value of the quantity (positive value)

Returns:

A new Quantity whose values equal absolute values of the initial Quantity

omegalpes.general.utils.output_data module

This module includes the following utils for output data management

It contains the following methods:

  • save_energy_flows() : Save the optimisation results in a .csv file

omegalpes.general.utils.output_data.save_energy_flows(*nodes, file_name=None, sep='\t', decimal_sep='.')[source]

Save the optimisation results in a .csv file

Parameters:

  • nodes – one or several nodes from which should be collected the data

  • file_name – name of the file to save the data

  • sep – separator for the data

  • decimal_sep – separator dor the decimals of the data

omegalpes.general.utils.plots module

This module includes the following display utils:

  • plot_node_energy_flows() : enables one to plot the energy flows through an EnergyNode

  • plot_energy_mix() : enables one to plot the energy flows connected to a node

  • plot_pareto2D() : enables one to plot a pareto front based on two quantities

  • plot_quantity() : enables one to plot easily a Quantity

  • plot_quantity_bar() : enables one to plot easily a Quantity as a bar

  • sum_quantities_in_quantity() : enables one to to plot several quantities in one once the optimisation is done

class omegalpes.general.utils.plots.Backend(*values)[source]

Bases: str, Enum

Supported rendering backends.

MATPLOTLIB = 'matplotlib'
PLOTLY = 'plotly'
class omegalpes.general.utils.plots.FigureOptions(figsize: Tuple[float, float] | None = None, save_png: bool = False, save_path: str | Path | None = None, fontsize: int | None = None, dpi: int = 96)[source]

Bases: object

Portable figure size and PNG export settings accepted by every plotting functions in this module

Parameters:

  • figsize –

    (width, height) in inches.

    • Matplotlib – passed directly to plt.subplots(figsize=...).

    • Plotly – converted to pixels at dpi and applied via fig.update_layout(width=..., height=...).

    None keeps each backend’s own default size.

  • save_png – When True the finished figure is written to disk as a PNG. Requires save_path to be provided.

  • save_path – Destination file path for the PNG. The .png extension is appended automatically if absent. Parent directories are created on demand.

  • dpi –

    Dots-per-inch used when saving the figure (both backends) and when converting figsize inches → Plotly pixels. Defaults to 150 for crisp exports.

    Note

    Plotly PNG export requires the kaleido package:

    pip install kaleido

Examples

>>> opts = FigureOptions(figsize=(12, 4), save_png=True,
...                      save_path="out/flows.png", dpi=200)
>>> fig = plot_node_energy_flows(node, fig_opts=opts)
>>> fig.show()
dpi: int = 96
figsize: Tuple[float, float] | None = None
fontsize: int | None = None
property mpl_figsize: Tuple[float, float] | None

figsize ready for plt.subplots(figsize=...), or None.

property plotly_wh: Tuple[int | None, int | None]

(width_px, height_px) for Plotly, or (None, None).

property resolved_save_path: Path | None

Resolved Path with .png suffix, or None.

save_path: str | Path | None = None
save_png: bool = False
omegalpes.general.utils.plots.plot_energy_mix(node: EnergyNode, interactive: bool = False, fig_opts: FigureOptions = FigureOptions(figsize=None, save_png=False, save_path=None, fontsize=None, dpi=96))[source]

Description

This function allows to plot the energy flows through an EnergyNode

The display is realized :

  • with stacked bars for production and storage flow

  • with dotted lines for consumption and export flow

Parameters:

  • node (EnergyNode) – The node whose flows are to be visualised.

  • interactive (bool) – When True, uses Plotly; otherwise Matplotlib.

Raises:

  • TypeError – If node is not an EnergyNode.

  • ValueError – If no production units are connected to node.

Examples:

opts = FigureOptions(figsize=(14, 5), save_png=True,
                     save_path="results/flows.png", dpi=200)
fig = plot_energy_mix(node, interactive=True, fig_opts=opts)
fig.show()
omegalpes.general.utils.plots.plot_node_energy_flows(node: EnergyNode, interactive: bool = False, fig_opts: FigureOptions = FigureOptions(figsize=None, save_png=False, save_path=None, fontsize=None, dpi=96))[source]

Description

This function allows to plot the energy flows through an EnergyNode

The display is realized :

  • with stacked bars for production and storage flow

  • with dotted lines for consumption and export flow

Parameters:

  • node (EnergyNode) – The node whose flows are to be visualised.

  • interactive (bool) – When True, uses Plotly; otherwise Matplotlib.

Raises:

TypeError – If node is not an EnergyNode.

Examples:

opts = FigureOptions(figsize=(14, 5), save_png=True,
                     save_path="results/flows.png", dpi=200)
fig = plot_node_energy_flows(node, interactive=True, fig_opts=opts)
fig.show()
omegalpes.general.utils.plots.plot_pareto2D(model, quantity_1, quantity_2, title=None, legend_on=True, interactive=False, fig_opts=FigureOptions(figsize=None, save_png=False, save_path=None, fontsize=None, dpi=96))[source]

Description

Plot a Pareto front for two quantities. Before using it, you should have added in your model two objectives with the pareto parameter activated (pareto=True)

Parameters

Parameters:

  • model

  • quantity_1 – the first quantity for the pareto front

  • quantity_2 – the second quantity for the pareto front

  • title – Optional figure title; auto-generated when None

  • legend_on – Whether to annotate each Pareto point with its run index.

  • interactive – Selects the Plotly backend when True.

  • fig_opts – FigureOptions controlling figure size and PNG export

omegalpes.general.utils.plots.plot_quantity(time, quantity, fig=None, ax=None, color=None, label=None, xlabel=None, ylabel=None, title=None, interactive=False, fig_opts=FigureOptions(figsize=None, save_png=False, save_path=None, fontsize=None, dpi=96))[source]

Description

Function that plots a OMEGAlpes.general.optimisation.elements.Quantity

Parameters

  • time: TimeUnit for the studied horizon as defined in general.time

  • quantity: OMEGAlpes.general.optimisation.elements.Quantity

  • fig: Figure as defined in matplotlib.pyplot.Figure

  • ax: axes as defined in matplotlib.pyplot.Axes

  • color: color of the plot

  • label: label for the quantity

  • title: title of the plot

  • interactive: Boolean for interactive plot

  • fig_opts: FigureOptions controlling figure size and PNG export

Returns

  • arg1 the matplotlib.pyplot.Figure handle object

  • arg2 the matplotlib.pyplot.Axes handle object

  • arg3 the matplotlib.pyplot.Line2D handle object

omegalpes.general.utils.plots.plot_quantity_bar(time, quantity, fig=None, ax=None, color=None, label=None, xlabel=None, ylabel=None, title=None, interactive=False, fig_opts=FigureOptions(figsize=None, save_png=False, save_path=None, fontsize=None, dpi=96))[source]

Description

Function that plots a OMEGALPES.general.optimisation.elements.Quantity as a bar

Attributes

  • time: TimeUnit for the studied horizon as defined in general.time

  • quantity: OMEGAlpes.general.optimisation.elements.Quantity

  • fig: Existing figure to draw into; backend is inferred from its type.

  • ax: Existing Matplotlib Axes (ignored for the Plotly backend).

  • color: color of the plot

  • label: label for the quantity

  • title: title of the plot

  • interactive: Boolean for interactive plot

  • fig_opts: FigureOptions controlling figure size and PNG export

Returns

  • arg1 the matplotlib.pyplot.Figure handle object

  • arg2 the matplotlib.pyplot.Axes handle object

  • arg3 the matplotlib.pyplot.Line2D handle object

omegalpes.general.utils.plots.sum_quantities_in_quantity(quantities_list=[], tot_quantity_name='sum_quantity')[source]

Description

Function that creates a new quantity gathering several values of quantities Should be used in order to plot several quantities in one once the optimisation is done

Attributes

  • quantities_list: a list of Quantities (OMEGALPES.general.optimisation.elements.Quantity)

  • tot_quantity_name: string : name of the new quantity

Returns

  • tot_quantity: the new quantity created and filled

Raises

  • ValueError: If quantities_list is empty, or units / lengths are inconsistent.

  • TypeError: If an element is not a Quantity.

Module contents