flixopt.statistics_accessor ¶

Statistics accessor for FlowSystem.

This module provides a user-friendly API for analyzing optimization results directly from a FlowSystem.

Structure

.stats - Data/metrics access (cached xarray Datasets)
.stats.plot - Plotting methods using the statistics data

Example

flow_system.optimize(solver)

Data access¶

flow_system.stats.flow_rates flow_system.stats.flow_hours

Plotting¶

flow_system.stats.plot.balance('ElectricityBus') flow_system.stats.plot.heatmap('Boiler|on')

Attributes¶

SelectType `module-attribute` ¶

SelectType = dict[str, Any]

xarray-style selection dict: {'time': slice(...), 'scenario': 'base'}

FilterType `module-attribute` ¶

FilterType = str | list[str]

For include/exclude filtering: exact label(s) to match, e.g., 'Boiler(Q_th)' or ['Boiler(Q_th)', 'CHP(Q_th)']

FlowSankeySelect `module-attribute` ¶

FlowSankeySelect = dict[Literal['flow', 'bus', 'component', 'carrier', 'time', 'period', 'scenario'], Any]

Select options for flow-based sankey: flow, bus, component, carrier, time, period, scenario.

EffectsSankeySelect `module-attribute` ¶

EffectsSankeySelect = dict[Literal['effect', 'component', 'contributor', 'period', 'scenario'], Any]

Select options for effects sankey: effect, component, contributor, period, scenario.

Classes¶

StatisticsAccessor ¶

StatisticsAccessor(flow_system: FlowSystem)

Statistics accessor for FlowSystem. Access via flow_system.stats.

This accessor provides cached data properties for optimization results. Use .plot for visualization methods.

Data Properties

flow_rates : xr.Dataset Flow rates for all flows. flow_hours : xr.Dataset Flow hours (energy) for all flows. sizes : xr.Dataset Sizes for all flows. charge_states : xr.Dataset Charge states for all storage components. temporal_effects : xr.Dataset Temporal effects per contributor per timestep. periodic_effects : xr.Dataset Periodic (investment) effects per contributor. total_effects : xr.Dataset Total effects (temporal + periodic) per contributor. effect_share_factors : dict Conversion factors between effects.

Examples:

>>> flow_system.optimize(solver)
>>> flow_system.stats.flow_rates  # Get data
>>> flow_system.stats.plot.balance('Bus')  # Plot

Attributes¶

carrier_colors `property` ¶

carrier_colors: dict[str, str]

Cached mapping of carrier name to color.

Delegates to topology accessor for centralized color caching.

Returns:

Type	Description
`dict[str, str]`	Dict mapping carrier names (lowercase) to hex color strings.

component_colors `property` ¶

component_colors: dict[str, str]

Cached mapping of component label to color.

Delegates to topology accessor for centralized color caching.

Returns:

Type	Description
`dict[str, str]`	Dict mapping component labels to hex color strings.

flow_colors `property` ¶

flow_colors: dict[str, str]

Cached mapping of flow label_full to color (from parent component).

Delegates to topology accessor for centralized color caching.

Returns:

Type	Description
`dict[str, str]`	Dict mapping flow labels (e.g., 'Boiler(Q_th)') to hex color strings.

bus_colors `property` ¶

bus_colors: dict[str, str]

Cached mapping of bus label to color (from carrier).

Delegates to topology accessor for centralized color caching.

Returns:

Type	Description
`dict[str, str]`	Dict mapping bus labels to hex color strings.

carrier_units `property` ¶

carrier_units: dict[str, str]

Cached mapping of carrier name to unit string.

Delegates to topology accessor for centralized unit caching.

Returns:

Type	Description
`dict[str, str]`	Dict mapping carrier names (lowercase) to unit strings.

effect_units `property` ¶

effect_units: dict[str, str]

Cached mapping of effect label to unit string.

Delegates to topology accessor for centralized unit caching.

Returns:

Type	Description
`dict[str, str]`	Dict mapping effect labels to unit strings.

plot `property` ¶

plot: StatisticsPlotAccessor

Access plotting methods for statistics.

Returns:

Type	Description
`StatisticsPlotAccessor`	A StatisticsPlotAccessor instance.

Examples:

>>> flow_system.stats.plot.balance('ElectricityBus')
>>> flow_system.stats.plot.heatmap('Boiler|on')

flow_rates `property` ¶

flow_rates: Dataset

All flow rates as a Dataset with flow labels as variable names.

Each variable has attributes

'carrier': carrier type (e.g., 'heat', 'electricity', 'gas')
'unit': carrier unit (e.g., 'kW')

flow_hours `property` ¶

flow_hours: Dataset

All flow hours (energy) as a Dataset with flow labels as variable names.

Each variable has attributes

'carrier': carrier type (e.g., 'heat', 'electricity', 'gas')
'unit': energy unit (e.g., 'kWh', 'm3/s*h')

flow_sizes `property` ¶

flow_sizes: Dataset

Flow sizes as a Dataset with flow labels as variable names.

storage_sizes `property` ¶

storage_sizes: Dataset

Storage capacity sizes as a Dataset with storage labels as variable names.

sizes `property` ¶

sizes: Dataset

All investment sizes (flows and storage capacities) as a Dataset.

charge_states `property` ¶

charge_states: Dataset

All storage charge states as a Dataset with storage labels as variable names.

effect_share_factors `property` ¶

effect_share_factors: dict[str, dict]

Effect share factors for temporal and periodic modes.

Returns:

Type	Description
`dict[str, dict]`	Dict with 'temporal' and 'periodic' keys, each containing
`dict[str, dict]`	conversion factors between effects.

temporal_effects `property` ¶

temporal_effects: Dataset

Temporal effects per contributor per timestep.

Returns a Dataset where each effect is a data variable with dimensions [time, contributor] (plus period/scenario if present).

Coordinates

contributor: Individual contributor labels
component: Parent component label for groupby operations
component_type: Component type (e.g., 'Boiler', 'Source', 'Sink')

Examples:

>>> # Get costs per contributor per timestep
>>> statistics.temporal_effects['costs']
>>> # Sum over all contributors to get total costs per timestep
>>> statistics.temporal_effects['costs'].sum('contributor')
>>> # Group by component
>>> statistics.temporal_effects['costs'].groupby('component').sum()

Returns:

Type	Description
`Dataset`	xr.Dataset with effects as variables and contributor dimension.

periodic_effects `property` ¶

periodic_effects: Dataset

Periodic (investment) effects per contributor.

Returns a Dataset where each effect is a data variable with dimensions [contributor] (plus period/scenario if present).

Coordinates

contributor: Individual contributor labels
component: Parent component label for groupby operations
component_type: Component type (e.g., 'Boiler', 'Source', 'Sink')

Examples:

>>> # Get investment costs per contributor
>>> statistics.periodic_effects['costs']
>>> # Sum over all contributors to get total investment costs
>>> statistics.periodic_effects['costs'].sum('contributor')
>>> # Group by component
>>> statistics.periodic_effects['costs'].groupby('component').sum()

Returns:

Type	Description
`Dataset`	xr.Dataset with effects as variables and contributor dimension.

total_effects `property` ¶

total_effects: Dataset

Total effects (temporal + periodic) per contributor.

Returns a Dataset where each effect is a data variable with dimensions [contributor] (plus period/scenario if present).

Coordinates

contributor: Individual contributor labels
component: Parent component label for groupby operations
component_type: Component type (e.g., 'Boiler', 'Source', 'Sink')

Examples:

>>> # Get total costs per contributor
>>> statistics.total_effects['costs']
>>> # Sum over all contributors to get total system costs
>>> statistics.total_effects['costs'].sum('contributor')
>>> # Group by component
>>> statistics.total_effects['costs'].groupby('component').sum()
>>> # Group by component type
>>> statistics.total_effects['costs'].groupby('component_type').sum()

Returns:

Type	Description
`Dataset`	xr.Dataset with effects as variables and contributor dimension.

Functions¶

get_effect_shares ¶

get_effect_shares(element: str, effect: str, mode: Literal['temporal', 'periodic'] | None = None, include_flows: bool = False) -> xr.Dataset

Retrieve individual effect shares for a specific element and effect.

Parameters:

Name	Type	Description	Default
`element`	`str`	The element identifier (component or flow label).	required
`effect`	`str`	The effect identifier.	required
`mode`	`Literal['temporal', 'periodic'] \| None`	'temporal', 'periodic', or None for both.	`None`
`include_flows`	`bool`	Whether to include effects from flows connected to this element.	`False`

Returns:

Type	Description
`Dataset`	xr.Dataset containing the requested effect shares.

Raises:

Type	Description
`ValueError`	If the effect is not available or mode is invalid.

SankeyPlotAccessor ¶

SankeyPlotAccessor(plot_accessor: StatisticsPlotAccessor)

Sankey diagram accessor. Access via flow_system.stats.plot.sankey.

Provides typed methods for different sankey diagram types.

Examples:

>>> fs.stats.plot.sankey.flows(select={'bus': 'HeatBus'})
>>> fs.stats.plot.sankey.effects(select={'effect': 'costs'})
>>> fs.stats.plot.sankey.sizes(select={'component': 'Boiler'})

Functions¶

flows ¶

flows(*, aggregate: Literal['sum', 'mean'] = 'sum', select: FlowSankeySelect | None = None, colors: ColorType | None = None, show: bool | None = None, **plotly_kwargs: Any) -> PlotResult

Plot Sankey diagram of energy/material flow amounts.

Parameters:

Name	Type	Description	Default
`aggregate`	`Literal['sum', 'mean']`	How to aggregate over time ('sum' or 'mean').	`'sum'`
`select`	`FlowSankeySelect \| None`	Filter options: - flow: filter by flow label (e.g., 'Boiler\|Q_th') - bus: filter by bus label (e.g., 'HeatBus') - component: filter by component label (e.g., 'Boiler') - time: select specific time (e.g., 100 or '2023-01-01') - period, scenario: xarray dimension selection	`None`
`colors`	`ColorType \| None`	Color specification for nodes.	`None`
`show`	`bool \| None`	Whether to display the figure.	`None`
`**plotly_kwargs`	`Any`	Additional arguments passed to Plotly layout.	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with Sankey flow data and figure.

sizes ¶

sizes(*, select: FlowSankeySelect | None = None, max_size: float | None = None, colors: ColorType | None = None, show: bool | None = None, **plotly_kwargs: Any) -> PlotResult

Plot Sankey diagram of investment sizes/capacities.

Parameters:

Name	Type	Description	Default
`select`	`FlowSankeySelect \| None`	Filter options: - flow: filter by flow label (e.g., 'Boiler\|Q_th') - bus: filter by bus label (e.g., 'HeatBus') - component: filter by component label (e.g., 'Boiler') - period, scenario: xarray dimension selection	`None`
`max_size`	`float \| None`	Filter flows with sizes exceeding this value.	`None`
`colors`	`ColorType \| None`	Color specification for nodes.	`None`
`show`	`bool \| None`	Whether to display the figure.	`None`
`**plotly_kwargs`	`Any`	Additional arguments passed to Plotly layout.	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with Sankey size data and figure.

peak_flow ¶

peak_flow(*, select: FlowSankeySelect | None = None, colors: ColorType | None = None, show: bool | None = None, **plotly_kwargs: Any) -> PlotResult

Plot Sankey diagram of peak (maximum) flow rates.

Parameters:

Name	Type	Description	Default
`select`	`FlowSankeySelect \| None`	Filter options: - flow: filter by flow label (e.g., 'Boiler\|Q_th') - bus: filter by bus label (e.g., 'HeatBus') - component: filter by component label (e.g., 'Boiler') - time, period, scenario: xarray dimension selection	`None`
`colors`	`ColorType \| None`	Color specification for nodes.	`None`
`show`	`bool \| None`	Whether to display the figure.	`None`
`**plotly_kwargs`	`Any`	Additional arguments passed to Plotly layout.	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with Sankey peak flow data and figure.

effects ¶

effects(*, select: EffectsSankeySelect | None = None, colors: ColorType | None = None, show: bool | None = None, **plotly_kwargs: Any) -> PlotResult

Plot Sankey diagram of component contributions to effects.

Shows how each component contributes to costs, CO2, and other effects.

Parameters:

Name	Type	Description	Default
`select`	`EffectsSankeySelect \| None`	Filter options: - effect: filter which effects are shown (e.g., 'costs', ['costs', 'CO2']) - component: filter by component label (e.g., 'Boiler') - contributor: filter by contributor label (e.g., 'Boiler\|Q_th') - period, scenario: xarray dimension selection	`None`
`colors`	`ColorType \| None`	Color specification for nodes.	`None`
`show`	`bool \| None`	Whether to display the figure.	`None`
`**plotly_kwargs`	`Any`	Additional arguments passed to Plotly layout.	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with Sankey effects data and figure.

StatisticsPlotAccessor ¶

StatisticsPlotAccessor(statistics: StatisticsAccessor)

Plot accessor for statistics. Access via flow_system.stats.plot.

All methods return PlotResult with both data and figure.

Attributes¶

sankey `property` ¶

sankey: SankeyPlotAccessor

Access sankey diagram methods with typed select options.

Returns:

Type	Description
`SankeyPlotAccessor`	SankeyPlotAccessor with methods: flows(), sizes(), peak_flow(), effects()

Examples:

>>> fs.stats.plot.sankey.flows(select={'bus': 'HeatBus'})
>>> fs.stats.plot.sankey.effects(select={'effect': 'costs'})

Functions¶

balance ¶

balance(node: str, *, select: SelectType | None = None, include: FilterType | None = None, exclude: FilterType | None = None, unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate', colors: ColorType | None = None, round_decimals: int | None = 6, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot node balance (inputs vs outputs) for a Bus or Component.

Parameters:

Name	Type	Description	Default
`node`	`str`	Label of the Bus or Component to plot.	required
`select`	`SelectType \| None`	xarray-style selection dict.	`None`
`include`	`FilterType \| None`	Only include flows with these exact labels.	`None`
`exclude`	`FilterType \| None`	Exclude flows with these exact labels.	`None`
`unit`	`Literal['flow_rate', 'flow_hours']`	'flow_rate' (power) or 'flow_hours' (energy).	`'flow_rate'`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`round_decimals`	`int \| None`	Round values to this many decimal places to avoid numerical noise (e.g., tiny negative values from solver precision). Set to None to disable.	`6`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display the plot.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with .data and .figure.

carrier_balance ¶

carrier_balance(carrier: str, *, select: SelectType | None = None, include: FilterType | None = None, exclude: FilterType | None = None, unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate', colors: ColorType | None = None, round_decimals: int | None = 6, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot carrier-level balance showing all flows of a carrier type.

Shows production (positive) and consumption (negative) of a carrier across all buses of that carrier type in the system.

Parameters:

Name	Type	Description	Default
`carrier`	`str`	Carrier name (e.g., 'heat', 'electricity', 'gas').	required
`select`	`SelectType \| None`	xarray-style selection dict.	`None`
`include`	`FilterType \| None`	Only include flows with these exact labels.	`None`
`exclude`	`FilterType \| None`	Exclude flows with these exact labels.	`None`
`unit`	`Literal['flow_rate', 'flow_hours']`	'flow_rate' (power) or 'flow_hours' (energy).	`'flow_rate'`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`round_decimals`	`int \| None`	Round values to this many decimal places to avoid numerical noise (e.g., tiny negative values from solver precision). Set to None to disable.	`6`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display the plot.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with .data and .figure.

Examples:

>>> fs.stats.plot.carrier_balance('heat')
>>> fs.stats.plot.carrier_balance('electricity', unit='flow_hours')

Notes

Data is aggregated by component (not individual flows)
Supply (inputs to carrier buses) shown as positive
Demand (outputs from carrier buses) shown as negative
Components with both supply and demand get separate entries (e.g., 'Storage (supply)' and 'Storage (demand)')

heatmap ¶

heatmap(variables: str | list[str], *, select: SelectType | None = None, reshape: tuple[str, str] | Literal['auto'] | None = ('D', 'h'), colors: str | list[str] | None = None, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot heatmap of time series data.

By default, time is reshaped into days × hours for clear daily pattern visualization. For clustered data, the natural (cluster, time) shape is used instead.

Multiple variables are shown as facets. If no time dimension exists, reshaping is skipped and data dimensions are used directly.

Parameters:

Name	Type	Description	Default
`variables`	`str \| list[str]`	Flow label(s) or variable name(s). Flow labels like 'Boiler(Q_th)' are automatically resolved to 'Boiler(Q_th)\|flow_rate'. Full variable names like 'Storage\|charge_state' are used as-is.	required
`select`	`SelectType \| None`	xarray-style selection, e.g. {'scenario': 'Base Case'}.	`None`
`reshape`	`tuple[str, str] \| Literal['auto'] \| None`	Time reshape frequencies as (outer, inner). Default `('D', 'h')` reshapes into days × hours. Use None to disable reshaping and use data dimensions directly.	`('D', 'h')`
`colors`	`str \| list[str] \| None`	Colorscale name (str) or list of colors for heatmap coloring. Dicts are not supported for heatmaps (use str or list[str]).	`None`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display the figure.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to plotly accessor (e.g., facet_col, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with processed data and figure.

flows ¶

flows(*, start: str | list[str] | None = None, end: str | list[str] | None = None, component: str | list[str] | None = None, select: SelectType | None = None, unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate', colors: ColorType | None = None, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot flow rates filtered by start/end nodes or component.

Parameters:

Name	Type	Description	Default
`start`	`str \| list[str] \| None`	Filter by source node(s).	`None`
`end`	`str \| list[str] \| None`	Filter by destination node(s).	`None`
`component`	`str \| list[str] \| None`	Filter by parent component(s).	`None`
`select`	`SelectType \| None`	xarray-style selection.	`None`
`unit`	`Literal['flow_rate', 'flow_hours']`	'flow_rate' or 'flow_hours'.	`'flow_rate'`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with flow data.

sizes ¶

sizes(*, max_size: float | None = 1000000.0, select: SelectType | None = None, colors: ColorType | None = None, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot investment sizes (capacities) of flows.

Parameters:

Name	Type	Description	Default
`max_size`	`float \| None`	Maximum size to include (filters defaults).	`1000000.0`
`select`	`SelectType \| None`	xarray-style selection.	`None`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing non-invested components. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with size data.

duration_curve ¶

duration_curve(variables: str | list[str], *, select: SelectType | None = None, normalize: bool = False, colors: ColorType | None = None, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot load duration curves (sorted time series).

Parameters:

Name	Type	Description	Default
`variables`	`str \| list[str]`	Flow label(s) or variable name(s). Flow labels like 'Boiler(Q_th)' are looked up in flow_rates. Full variable names like 'Boiler(Q_th)\|flow_rate' are stripped to their flow label. Other variables (e.g., 'Storage\|charge_state') are looked up in the solution directly.	required
`select`	`SelectType \| None`	xarray-style selection.	`None`
`normalize`	`bool`	If True, normalize x-axis to 0-100%.	`False`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with sorted duration curve data.

effects ¶

effects(aspect: Literal['total', 'temporal', 'periodic'] = 'total', *, effect: str | None = None, by: Literal['component', 'contributor', 'time'] | None = None, select: SelectType | None = None, colors: ColorType | None = None, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot effect (cost, emissions, etc.) breakdown.

Parameters:

Name	Type	Description	Default
`aspect`	`Literal['total', 'temporal', 'periodic']`	Which aspect to plot - 'total', 'temporal', or 'periodic'.	`'total'`
`effect`	`str \| None`	Specific effect name to plot (e.g., 'costs', 'CO2'). If None, plots all effects.	`None`
`by`	`Literal['component', 'contributor', 'time'] \| None`	Group by 'component', 'contributor' (individual flows), 'time', or None to show aggregated totals per effect.	`None`
`select`	`SelectType \| None`	xarray-style selection.	`None`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with effect breakdown data.

Examples:

>>> flow_system.stats.plot.effects()  # Aggregated totals per effect
>>> flow_system.stats.plot.effects(effect='costs')  # Just costs
>>> flow_system.stats.plot.effects(by='component')  # Breakdown by component
>>> flow_system.stats.plot.effects(by='contributor')  # By individual flows
>>> flow_system.stats.plot.effects(aspect='temporal', by='time')  # Over time

charge_states ¶

charge_states(storages: str | list[str] | None = None, *, select: SelectType | None = None, colors: ColorType | None = None, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot storage charge states over time.

Parameters:

Name	Type	Description	Default
`storages`	`str \| list[str] \| None`	Storage label(s) to plot. If None, plots all storages.	`None`
`select`	`SelectType \| None`	xarray-style selection.	`None`
`colors`	`ColorType \| None`	Color specification (colorscale name, color list, or label-to-color dict).	`None`
`threshold`	`float \| None`	Filter out variables where max absolute value is below this. Useful for removing non-invested storages. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with charge state data.

storage ¶

storage(storage: str, *, select: SelectType | None = None, unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate', colors: ColorType | None = None, charge_state_color: str = 'black', round_decimals: int | None = 6, threshold: float | None = 1e-05, show: bool | None = None, data_only: bool = False, **plotly_kwargs: Any) -> PlotResult

Plot storage operation: balance and charge state in vertically stacked subplots.

Creates two subplots sharing the x-axis: - Top: Charging/discharging flows as stacked bars (inputs negative, outputs positive) - Bottom: Charge state over time as a line

Parameters:

Name	Type	Description	Default
`storage`	`str`	Storage component label.	required
`select`	`SelectType \| None`	xarray-style selection.	`None`
`unit`	`Literal['flow_rate', 'flow_hours']`	'flow_rate' (power) or 'flow_hours' (energy).	`'flow_rate'`
`colors`	`ColorType \| None`	Color specification for flow bars.	`None`
`charge_state_color`	`str`	Color for the charge state line overlay.	`'black'`
`round_decimals`	`int \| None`	Round values to this many decimal places to avoid numerical noise (e.g., tiny negative values from solver precision). Set to None to disable.	`6`
`threshold`	`float \| None`	Filter out flow variables where max absolute value is below this. Useful for removing solver noise. Set to None to disable.	`1e-05`
`show`	`bool \| None`	Whether to display.	`None`
`data_only`	`bool`	If True, skip figure creation and return only data (for performance).	`False`
`**plotly_kwargs`	`Any`	Additional arguments passed to the plotly accessor (e.g., facet_col, facet_row, animation_frame).	`{}`

Returns:

Type	Description
`PlotResult`	PlotResult with combined balance and charge state data.

Raises:

Type	Description
`KeyError`	If storage component not found.
`ValueError`	If component is not a storage.

flixopt.statistics_accessor ¶

Data access¶

Plotting¶

Attributes¶

SelectType module-attribute ¶

FilterType module-attribute ¶

FlowSankeySelect module-attribute ¶

EffectsSankeySelect module-attribute ¶

Classes¶

StatisticsAccessor ¶

Attributes¶

carrier_colors property ¶

component_colors property ¶

flow_colors property ¶

bus_colors property ¶

carrier_units property ¶

effect_units property ¶

plot property ¶

flow_rates property ¶

flow_hours property ¶

flow_sizes property ¶

storage_sizes property ¶

sizes property ¶

charge_states property ¶

effect_share_factors property ¶

temporal_effects property ¶

periodic_effects property ¶

total_effects property ¶

Functions¶

get_effect_shares ¶

SankeyPlotAccessor ¶

Functions¶

flows ¶

sizes ¶

peak_flow ¶

effects ¶

StatisticsPlotAccessor ¶

Attributes¶

sankey property ¶

Functions¶

balance ¶

carrier_balance ¶

heatmap ¶

flows ¶

sizes ¶

duration_curve ¶

effects ¶

charge_states ¶

storage ¶

Functions¶

SelectType `module-attribute` ¶

FilterType `module-attribute` ¶

FlowSankeySelect `module-attribute` ¶

EffectsSankeySelect `module-attribute` ¶

carrier_colors `property` ¶

component_colors `property` ¶

flow_colors `property` ¶

bus_colors `property` ¶

carrier_units `property` ¶

effect_units `property` ¶

plot `property` ¶

flow_rates `property` ¶

flow_hours `property` ¶

flow_sizes `property` ¶

storage_sizes `property` ¶

sizes `property` ¶

charge_states `property` ¶

effect_share_factors `property` ¶

temporal_effects `property` ¶

periodic_effects `property` ¶

total_effects `property` ¶

sankey `property` ¶