From 98a269dc9671703fd299d3e087934e056be0cc6c Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 14:43:04 +0100
Subject: [PATCH 1/7] Inline plotting methods to deprecate plotting.py

---
 flixopt/clustering.py          |  29 ++++----
 flixopt/statistics_accessor.py | 126 ++++++++++++++++++++++++++++++++-
 flixopt/topology_accessor.py   |  84 ++++++++++++++++++++--
 3 files changed, 219 insertions(+), 20 deletions(-)

diff --git a/flixopt/clustering.py b/flixopt/clustering.py
index 1c6f7511b..3d049132d 100644
--- a/flixopt/clustering.py
+++ b/flixopt/clustering.py
@@ -7,7 +7,6 @@
 
 import copy
 import logging
-import pathlib
 import timeit
 from typing import TYPE_CHECKING
 
@@ -29,6 +28,8 @@
 )
 
 if TYPE_CHECKING:
+    import pathlib
+
     import linopy
     import pandas as pd
     import plotly.graph_objects as go
@@ -145,7 +146,7 @@ def use_extreme_periods(self):
         return self.time_series_for_high_peaks or self.time_series_for_low_peaks
 
     def plot(self, colormap: str | None = None, show: bool = True, save: pathlib.Path | None = None) -> go.Figure:
-        from . import plotting
+        import plotly.express as px
 
         df_org = self.original_data.copy().rename(
             columns={col: f'Original - {col}' for col in self.original_data.columns}
@@ -156,10 +157,16 @@ def plot(self, colormap: str | None = None, show: bool = True, save: pathlib.Pat
         colors = list(
             process_colors(colormap or CONFIG.Plotting.default_qualitative_colorscale, list(df_org.columns)).values()
         )
-        fig = plotting.with_plotly(df_org.to_xarray(), 'line', colors=colors, xlabel='Time in h')
+
+        # Create line plot for original data (dashed)
+        df_org_long = df_org.reset_index().melt(id_vars='index', var_name='variable', value_name='value')
+        fig = px.line(df_org_long, x='index', y='value', color='variable', color_discrete_sequence=colors)
         for trace in fig.data:
-            trace.update(dict(line=dict(dash='dash')))
-        fig2 = plotting.with_plotly(df_agg.to_xarray(), 'line', colors=colors, xlabel='Time in h')
+            trace.update(line=dict(dash='dash'))
+
+        # Add aggregated data (solid lines)
+        df_agg_long = df_agg.reset_index().melt(id_vars='index', var_name='variable', value_name='value')
+        fig2 = px.line(df_agg_long, x='index', y='value', color='variable', color_discrete_sequence=colors)
         for trace in fig2.data:
             fig.add_trace(trace)
 
@@ -169,14 +176,10 @@ def plot(self, colormap: str | None = None, show: bool = True, save: pathlib.Pat
             yaxis_title='Value',
         )
 
-        plotting.export_figure(
-            figure_like=fig,
-            default_path=pathlib.Path('aggregated data.html'),
-            default_filetype='.html',
-            user_path=save,
-            show=show,
-            save=save is not None,
-        )
+        if save is not None:
+            fig.write_html(str(save))
+        if show:
+            fig.show()
 
         return fig
 
diff --git a/flixopt/statistics_accessor.py b/flixopt/statistics_accessor.py
index 9afcfd284..9a9cff17a 100644
--- a/flixopt/statistics_accessor.py
+++ b/flixopt/statistics_accessor.py
@@ -26,10 +26,10 @@
 
 import numpy as np
 import pandas as pd
+import plotly.express as px
 import plotly.graph_objects as go
 import xarray as xr
 
-from . import plotting
 from .config import CONFIG
 
 if TYPE_CHECKING:
@@ -46,6 +46,126 @@
 FilterType = str | list[str]
 """For include/exclude filtering: 'Boiler' or ['Boiler', 'CHP']"""
 
+ColorType = str | list[str] | None
+"""Colorscale type for plots."""
+
+
+def _reshape_time_for_heatmap(
+    data: xr.DataArray,
+    reshape: tuple[str, str],
+    fill: Literal['ffill', 'bfill'] | None = 'ffill',
+) -> xr.DataArray:
+    """Reshape time dimension into 2D (timeframe × timestep) for heatmap display.
+
+    Args:
+        data: DataArray with 'time' dimension.
+        reshape: Tuple of (outer_freq, inner_freq), e.g. ('D', 'h') for days × hours.
+        fill: Method to fill missing values after resampling.
+
+    Returns:
+        DataArray with 'time' replaced by 'timestep' and 'timeframe' dimensions.
+    """
+    if 'time' not in data.dims:
+        return data
+
+    timeframes, timesteps_per_frame = reshape
+
+    # Define formats for different combinations
+    formats = {
+        ('YS', 'W'): ('%Y', '%W'),
+        ('YS', 'D'): ('%Y', '%j'),
+        ('YS', 'h'): ('%Y', '%j %H:00'),
+        ('MS', 'D'): ('%Y-%m', '%d'),
+        ('MS', 'h'): ('%Y-%m', '%d %H:00'),
+        ('W', 'D'): ('%Y-w%W', '%w_%A'),
+        ('W', 'h'): ('%Y-w%W', '%w_%A %H:00'),
+        ('D', 'h'): ('%Y-%m-%d', '%H:00'),
+        ('D', '15min'): ('%Y-%m-%d', '%H:%M'),
+        ('h', '15min'): ('%Y-%m-%d %H:00', '%M'),
+        ('h', 'min'): ('%Y-%m-%d %H:00', '%M'),
+    }
+
+    format_pair = (timeframes, timesteps_per_frame)
+    if format_pair not in formats:
+        raise ValueError(f'{format_pair} is not a valid format. Choose from {list(formats.keys())}')
+    period_format, step_format = formats[format_pair]
+
+    # Resample along time dimension
+    resampled = data.resample(time=timesteps_per_frame).mean()
+
+    # Apply fill if specified
+    if fill == 'ffill':
+        resampled = resampled.ffill(dim='time')
+    elif fill == 'bfill':
+        resampled = resampled.bfill(dim='time')
+
+    # Create period and step labels
+    time_values = pd.to_datetime(resampled.coords['time'].values)
+    period_labels = time_values.strftime(period_format)
+    step_labels = time_values.strftime(step_format)
+
+    # Handle special case for weekly day format
+    if '%w_%A' in step_format:
+        step_labels = pd.Series(step_labels).replace('0_Sunday', '7_Sunday').values
+
+    # Add period and step as coordinates
+    resampled = resampled.assign_coords({'timeframe': ('time', period_labels), 'timestep': ('time', step_labels)})
+
+    # Convert to multi-index and unstack
+    resampled = resampled.set_index(time=['timeframe', 'timestep'])
+    result = resampled.unstack('time')
+
+    # Reorder: timestep, timeframe, then other dimensions
+    other_dims = [d for d in result.dims if d not in ['timestep', 'timeframe']]
+    return result.transpose('timestep', 'timeframe', *other_dims)
+
+
+def _heatmap_figure(
+    data: xr.DataArray,
+    colors: ColorType = None,
+    title: str = '',
+    facet_col: str | None = None,
+    animation_frame: str | None = None,
+    facet_col_wrap: int | None = None,
+    **imshow_kwargs: Any,
+) -> go.Figure:
+    """Create heatmap figure using px.imshow.
+
+    Args:
+        data: DataArray with 2-4 dimensions. First two are heatmap axes.
+        colors: Colorscale name.
+        title: Plot title.
+        facet_col: Dimension for subplot columns.
+        animation_frame: Dimension for animation slider.
+        facet_col_wrap: Max columns before wrapping.
+        **imshow_kwargs: Additional args for px.imshow.
+
+    Returns:
+        Plotly Figure.
+    """
+    if data.size == 0:
+        return go.Figure()
+
+    colors = colors or CONFIG.Plotting.default_sequential_colorscale
+    facet_col_wrap = facet_col_wrap or CONFIG.Plotting.default_facet_cols
+
+    imshow_args: dict[str, Any] = {
+        'img': data,
+        'color_continuous_scale': colors,
+        'title': title,
+        **imshow_kwargs,
+    }
+
+    if facet_col and facet_col in data.dims:
+        imshow_args['facet_col'] = facet_col
+        if facet_col_wrap < data.sizes[facet_col]:
+            imshow_args['facet_col_wrap'] = facet_col_wrap
+
+    if animation_frame and animation_frame in data.dims:
+        imshow_args['animation_frame'] = animation_frame
+
+    return px.imshow(**imshow_args)
+
 
 @dataclass
 class PlotResult:
@@ -771,7 +891,7 @@ def heatmap(
 
         # Reshape time only if we wouldn't lose data (all extra dims fit in facet + animation)
         if reshape and 'time' in da.dims and not would_drop:
-            da = plotting.reshape_data_for_heatmap(da, reshape)
+            da = _reshape_time_for_heatmap(da, reshape)
             heatmap_dims = ['timestep', 'timeframe']
         elif has_multiple_vars:
             # Can't reshape but have multiple vars: use variable + time as heatmap axes
@@ -797,7 +917,7 @@ def heatmap(
         if has_multiple_vars:
             da = da.rename('')
 
-        fig = plotting.heatmap_with_plotly_v2(
+        fig = _heatmap_figure(
             da,
             colors=colorscale,
             facet_col=actual_facet,
diff --git a/flixopt/topology_accessor.py b/flixopt/topology_accessor.py
index 0df05afa2..b4e18eb08 100644
--- a/flixopt/topology_accessor.py
+++ b/flixopt/topology_accessor.py
@@ -8,13 +8,12 @@
 from __future__ import annotations
 
 import logging
+import pathlib
 import warnings
 from itertools import chain
 from typing import TYPE_CHECKING, Literal
 
 if TYPE_CHECKING:
-    import pathlib
-
     import pyvis
 
     from .flow_system import FlowSystem
@@ -22,6 +21,84 @@
 logger = logging.getLogger('flixopt')
 
 
+def _plot_network(
+    node_infos: dict,
+    edge_infos: dict,
+    path: str | pathlib.Path | None = None,
+    controls: bool
+    | list[
+        Literal['nodes', 'edges', 'layout', 'interaction', 'manipulation', 'physics', 'selection', 'renderer']
+    ] = True,
+    show: bool = False,
+) -> pyvis.network.Network | None:
+    """Visualize network structure using PyVis.
+
+    Args:
+        node_infos: Dictionary of node information.
+        edge_infos: Dictionary of edge information.
+        path: Path to save HTML visualization.
+        controls: UI controls to add. True for all, or list of specific controls.
+        show: Whether to open in browser.
+
+    Returns:
+        Network instance, or None if pyvis not installed.
+    """
+    try:
+        from pyvis.network import Network
+    except ImportError:
+        logger.critical("Plotting the flow system network was not possible. Please install pyvis: 'pip install pyvis'")
+        return None
+
+    net = Network(directed=True, height='100%' if controls is False else '800px', font_color='white')
+
+    for node_id, node in node_infos.items():
+        net.add_node(
+            node_id,
+            label=node['label'],
+            shape={'Bus': 'circle', 'Component': 'box'}[node['class']],
+            color={'Bus': '#393E46', 'Component': '#00ADB5'}[node['class']],
+            title=node['infos'].replace(')', '\n)'),
+            font={'size': 14},
+        )
+
+    for edge in edge_infos.values():
+        net.add_edge(
+            edge['start'],
+            edge['end'],
+            label=edge['label'],
+            title=edge['infos'].replace(')', '\n)'),
+            font={'color': '#4D4D4D', 'size': 14},
+            color='#222831',
+        )
+
+    net.barnes_hut(central_gravity=0.8, spring_length=50, spring_strength=0.05, gravity=-10000)
+
+    if controls:
+        net.show_buttons(filter_=controls)
+    if not show and not path:
+        return net
+    elif path:
+        path = pathlib.Path(path) if isinstance(path, str) else path
+        net.write_html(path.as_posix())
+    elif show:
+        path = pathlib.Path('network.html')
+        net.write_html(path.as_posix())
+
+    if show:
+        try:
+            import webbrowser
+
+            worked = webbrowser.open(f'file://{path.resolve()}', 2)
+            if not worked:
+                logger.error(f'Showing the network in the Browser went wrong. Open it manually. Its saved under {path}')
+        except Exception as e:
+            logger.error(
+                f'Showing the network in the Browser went wrong. Open it manually. Its saved under {path}: {e}'
+            )
+
+    return net
+
+
 class TopologyAccessor:
     """
     Accessor for network topology inspection and visualization on FlowSystem.
@@ -136,11 +213,10 @@ def plot(
             Nodes are styled based on type (circles for buses, boxes for components)
             and annotated with node information.
         """
-        from . import plotting
         from .config import CONFIG
 
         node_infos, edge_infos = self.infos()
-        return plotting.plot_network(
+        return _plot_network(
             node_infos, edge_infos, path, controls, show if show is not None else CONFIG.Plotting.default_show
         )
 

From c41b21258b084f7aa2ab23c4c3e19e28f7e8a24d Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 15:14:51 +0100
Subject: [PATCH 2/7] Fix test

---
 tests/test_solution_and_plotting.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/test_solution_and_plotting.py b/tests/test_solution_and_plotting.py
index e302c4267..e5c96da33 100644
--- a/tests/test_solution_and_plotting.py
+++ b/tests/test_solution_and_plotting.py
@@ -349,10 +349,10 @@ def test_reshape_none_preserves_data(self, long_time_data):
 
     def test_heatmap_with_plotly_v2(self, long_time_data):
         """Test heatmap plotting with Plotly."""
-        # Convert to Dataset for plotting
-        data = long_time_data.to_dataset(name='power')
+        # Reshape data first (heatmap_with_plotly_v2 requires pre-reshaped data)
+        reshaped = plotting.reshape_data_for_heatmap(long_time_data, reshape_time=('D', 'h'))
 
-        fig = plotting.heatmap_with_plotly_v2(data['power'], reshape_time=('D', 'h'))
+        fig = plotting.heatmap_with_plotly_v2(reshaped)
         assert fig is not None
 
     def test_heatmap_with_matplotlib(self, long_time_data):

From d08dc520698ea9f43e09892f9a0cd539a3e056b6 Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 15:27:23 +0100
Subject: [PATCH 3/7] Simplify Color Management

---
 flixopt/statistics_accessor.py | 62 ++++++++++++++--------------------
 1 file changed, 26 insertions(+), 36 deletions(-)

diff --git a/flixopt/statistics_accessor.py b/flixopt/statistics_accessor.py
index 9a9cff17a..e7d0ec5fe 100644
--- a/flixopt/statistics_accessor.py
+++ b/flixopt/statistics_accessor.py
@@ -30,6 +30,7 @@
 import plotly.graph_objects as go
 import xarray as xr
 
+from .color_processing import process_colors
 from .config import CONFIG
 
 if TYPE_CHECKING:
@@ -46,8 +47,8 @@
 FilterType = str | list[str]
 """For include/exclude filtering: 'Boiler' or ['Boiler', 'CHP']"""
 
-ColorType = str | list[str] | None
-"""Colorscale type for plots."""
+ColorType = str | list[str] | dict[str, str] | None
+"""Flexible color input: colorscale name, color list, label-to-color dict, or None for default."""
 
 
 def _reshape_time_for_heatmap(
@@ -270,21 +271,19 @@ def _dataset_to_long_df(ds: xr.Dataset, value_name: str = 'value', var_name: str
 
 def _create_stacked_bar(
     ds: xr.Dataset,
-    colors: dict[str, str] | None,
+    colors: ColorType,
     title: str,
     facet_col: str | None,
     facet_row: str | None,
     **plotly_kwargs: Any,
 ) -> go.Figure:
     """Create a stacked bar chart from xarray Dataset."""
-    import plotly.express as px
-
     df = _dataset_to_long_df(ds)
     if df.empty:
         return go.Figure()
     x_col = 'time' if 'time' in df.columns else df.columns[0]
     variables = df['variable'].unique().tolist()
-    color_map = {var: colors.get(var) for var in variables if colors and var in colors} or None
+    color_map = process_colors(colors, variables)
     fig = px.bar(
         df,
         x=x_col,
@@ -303,21 +302,19 @@ def _create_stacked_bar(
 
 def _create_line(
     ds: xr.Dataset,
-    colors: dict[str, str] | None,
+    colors: ColorType,
     title: str,
     facet_col: str | None,
     facet_row: str | None,
     **plotly_kwargs: Any,
 ) -> go.Figure:
     """Create a line chart from xarray Dataset."""
-    import plotly.express as px
-
     df = _dataset_to_long_df(ds)
     if df.empty:
         return go.Figure()
     x_col = 'time' if 'time' in df.columns else df.columns[0]
     variables = df['variable'].unique().tolist()
-    color_map = {var: colors.get(var) for var in variables if colors and var in colors} or None
+    color_map = process_colors(colors, variables)
     return px.line(
         df,
         x=x_col,
@@ -751,7 +748,7 @@ def balance(
         include: FilterType | None = None,
         exclude: FilterType | None = None,
         unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate',
-        colors: dict[str, str] | None = None,
+        colors: ColorType = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -765,7 +762,7 @@ def balance(
             include: Only include flows containing these substrings.
             exclude: Exclude flows containing these substrings.
             unit: 'flow_rate' (power) or 'flow_hours' (energy).
-            colors: Color overrides for flows.
+            colors: Color specification (colorscale name, color list, or label-to-color dict).
             facet_col: Dimension for column facets.
             facet_row: Dimension for row facets.
             show: Whether to display the plot.
@@ -828,7 +825,7 @@ def heatmap(
         *,
         select: SelectType | None = None,
         reshape: tuple[str, str] | None = ('D', 'h'),
-        colorscale: str = 'viridis',
+        colors: ColorType = None,
         facet_col: str | None = 'period',
         animation_frame: str | None = 'scenario',
         show: bool | None = None,
@@ -845,7 +842,7 @@ def heatmap(
             select: xarray-style selection, e.g. {'scenario': 'Base Case'}.
             reshape: Time reshape frequencies as (outer, inner), e.g. ('D', 'h') for
                     days × hours. Set to None to disable reshaping.
-            colorscale: Plotly colorscale name.
+            colors: Colorscale name (e.g., 'viridis', 'plasma') for heatmap coloring.
             facet_col: Dimension for subplot columns (default: 'period').
                       With multiple variables, 'variable' is used instead.
             animation_frame: Dimension for animation slider (default: 'scenario').
@@ -919,7 +916,7 @@ def heatmap(
 
         fig = _heatmap_figure(
             da,
-            colors=colorscale,
+            colors=colors,
             facet_col=actual_facet,
             animation_frame=actual_animation,
             **plotly_kwargs,
@@ -941,7 +938,7 @@ def flows(
         component: str | list[str] | None = None,
         select: SelectType | None = None,
         unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate',
-        colors: dict[str, str] | None = None,
+        colors: ColorType = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -955,7 +952,7 @@ def flows(
             component: Filter by parent component(s).
             select: xarray-style selection.
             unit: 'flow_rate' or 'flow_hours'.
-            colors: Color overrides.
+            colors: Color specification (colorscale name, color list, or label-to-color dict).
             facet_col: Dimension for column facets.
             facet_row: Dimension for row facets.
             show: Whether to display.
@@ -1024,7 +1021,7 @@ def sankey(
         timestep: int | str | None = None,
         aggregate: Literal['sum', 'mean'] = 'sum',
         select: SelectType | None = None,
-        colors: dict[str, str] | None = None,
+        colors: ColorType = None,
         show: bool | None = None,
         **plotly_kwargs: Any,
     ) -> PlotResult:
@@ -1034,7 +1031,7 @@ def sankey(
             timestep: Specific timestep to show, or None for aggregation.
             aggregate: How to aggregate if timestep is None.
             select: xarray-style selection.
-            colors: Color overrides for flows/nodes.
+            colors: Color specification for nodes (colorscale name, color list, or label-to-color dict).
             show: Whether to display.
 
         Returns:
@@ -1099,11 +1096,8 @@ def sankey(
         node_list = list(nodes)
         node_indices = {n: i for i, n in enumerate(node_list)}
 
-        node_colors = [colors.get(node) if colors else None for node in node_list]
-        if any(node_colors):
-            node_colors = [c if c else 'lightgray' for c in node_colors]
-        else:
-            node_colors = None
+        color_map = process_colors(colors, node_list)
+        node_colors = [color_map[node] for node in node_list]
 
         fig = go.Figure(
             data=[
@@ -1139,7 +1133,7 @@ def sizes(
         *,
         max_size: float | None = 1e6,
         select: SelectType | None = None,
-        colors: dict[str, str] | None = None,
+        colors: ColorType = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -1150,7 +1144,7 @@ def sizes(
         Args:
             max_size: Maximum size to include (filters defaults).
             select: xarray-style selection.
-            colors: Color overrides.
+            colors: Color specification (colorscale name, color list, or label-to-color dict).
             facet_col: Dimension for column facets.
             facet_row: Dimension for row facets.
             show: Whether to display.
@@ -1158,8 +1152,6 @@ def sizes(
         Returns:
             PlotResult with size data.
         """
-        import plotly.express as px
-
         self._stats._require_solution()
         ds = self._stats.sizes
 
@@ -1176,7 +1168,7 @@ def sizes(
             fig = go.Figure()
         else:
             variables = df['variable'].unique().tolist()
-            color_map = {var: colors.get(var) for var in variables if colors and var in colors} or None
+            color_map = process_colors(colors, variables)
             fig = px.bar(
                 df,
                 x='variable',
@@ -1203,7 +1195,7 @@ def duration_curve(
         *,
         select: SelectType | None = None,
         normalize: bool = False,
-        colors: dict[str, str] | None = None,
+        colors: ColorType = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -1216,7 +1208,7 @@ def duration_curve(
                 Uses flow_rates from statistics.
             select: xarray-style selection.
             normalize: If True, normalize x-axis to 0-100%.
-            colors: Color overrides.
+            colors: Color specification (colorscale name, color list, or label-to-color dict).
             facet_col: Dimension for column facets.
             facet_row: Dimension for row facets.
             show: Whether to display.
@@ -1282,7 +1274,7 @@ def effects(
         effect: str | None = None,
         by: Literal['component', 'contributor', 'time'] = 'component',
         select: SelectType | None = None,
-        colors: dict[str, str] | None = None,
+        colors: ColorType = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -1296,7 +1288,7 @@ def effects(
                     If None, plots all effects.
             by: Group by 'component', 'contributor' (individual flows), or 'time'.
             select: xarray-style selection.
-            colors: Override colors.
+            colors: Color specification (colorscale name, color list, or label-to-color dict).
             facet_col: Dimension for column facets (ignored if not in data).
             facet_row: Dimension for row facets (ignored if not in data).
             show: Whether to display.
@@ -1310,8 +1302,6 @@ def effects(
             >>> flow_system.statistics.plot.effects(by='contributor')  # By individual flows
             >>> flow_system.statistics.plot.effects(aspect='temporal', by='time')  # Over time
         """
-        import plotly.express as px
-
         self._stats._require_solution()
 
         # Get the appropriate effects dataset based on aspect
@@ -1387,7 +1377,7 @@ def effects(
         # Build color map
         if color_col and color_col in df.columns:
             color_items = df[color_col].unique().tolist()
-            color_map = {item: colors.get(item) for item in color_items if colors and item in colors} or None
+            color_map = process_colors(colors, color_items)
         else:
             color_map = None
 

From 435ecd94dcef4fd7ce494a0ce250028dd877b124 Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 15:31:12 +0100
Subject: [PATCH 4/7]  ColorType is now defined in color_processing.py and
 imported into statistics_accessor.py.

---
 flixopt/color_processing.py    | 52 ++++++++++++++++++++++++++++++++++
 flixopt/plotting.py            | 52 +---------------------------------
 flixopt/statistics_accessor.py |  5 +---
 3 files changed, 54 insertions(+), 55 deletions(-)

diff --git a/flixopt/color_processing.py b/flixopt/color_processing.py
index 2959acc82..f09a3927d 100644
--- a/flixopt/color_processing.py
+++ b/flixopt/color_processing.py
@@ -15,6 +15,58 @@
 
 logger = logging.getLogger('flixopt')
 
+# Type alias for flexible color input
+ColorType = str | list[str] | dict[str, str] | None
+ColorType = str | list[str] | dict[str, str]
+"""Flexible color specification type supporting multiple input formats for visualization.
+
+Color specifications can take several forms to accommodate different use cases:
+
+**Named colorscales** (str):
+    - Standard colorscales: 'turbo', 'plasma', 'cividis', 'tab10', 'Set1'
+    - Energy-focused: 'portland' (custom flixopt colorscale for energy systems)
+    - Backend-specific maps available in Plotly and Matplotlib
+
+**Color Lists** (list[str]):
+    - Explicit color sequences: ['red', 'blue', 'green', 'orange']
+    - HEX codes: ['#FF0000', '#0000FF', '#00FF00', '#FFA500']
+    - Mixed formats: ['red', '#0000FF', 'green', 'orange']
+
+**Label-to-Color Mapping** (dict[str, str]):
+    - Explicit associations: {'Wind': 'skyblue', 'Solar': 'gold', 'Gas': 'brown'}
+    - Ensures consistent colors across different plots and datasets
+    - Ideal for energy system components with semantic meaning
+
+Examples:
+    ```python
+    # Named colorscale
+    colors = 'turbo'  # Automatic color generation
+
+    # Explicit color list
+    colors = ['red', 'blue', 'green', '#FFD700']
+
+    # Component-specific mapping
+    colors = {
+        'Wind_Turbine': 'skyblue',
+        'Solar_Panel': 'gold',
+        'Natural_Gas': 'brown',
+        'Battery': 'green',
+        'Electric_Load': 'darkred'
+    }
+    ```
+
+Color Format Support:
+    - **Named Colors**: 'red', 'blue', 'forestgreen', 'darkorange'
+    - **HEX Codes**: '#FF0000', '#0000FF', '#228B22', '#FF8C00'
+    - **RGB Tuples**: (255, 0, 0), (0, 0, 255) [Matplotlib only]
+    - **RGBA**: 'rgba(255,0,0,0.8)' [Plotly only]
+
+References:
+    - HTML Color Names: https://htmlcolorcodes.com/color-names/
+    - Matplotlib colorscales: https://matplotlib.org/stable/tutorials/colors/colorscales.html
+    - Plotly Built-in Colorscales: https://plotly.com/python/builtin-colorscales/
+"""
+
 
 def _rgb_string_to_hex(color: str) -> str:
     """Convert Plotly RGB/RGBA string format to hex.
diff --git a/flixopt/plotting.py b/flixopt/plotting.py
index db78ca19b..db5a3eb5c 100644
--- a/flixopt/plotting.py
+++ b/flixopt/plotting.py
@@ -39,7 +39,7 @@
 import plotly.offline
 import xarray as xr
 
-from .color_processing import process_colors
+from .color_processing import ColorType, process_colors
 from .config import CONFIG
 
 if TYPE_CHECKING:
@@ -66,56 +66,6 @@
         plt.register_cmap(name='portland', cmap=mcolors.LinearSegmentedColormap.from_list('portland', _portland_colors))
 
 
-ColorType = str | list[str] | dict[str, str]
-"""Flexible color specification type supporting multiple input formats for visualization.
-
-Color specifications can take several forms to accommodate different use cases:
-
-**Named colorscales** (str):
-    - Standard colorscales: 'turbo', 'plasma', 'cividis', 'tab10', 'Set1'
-    - Energy-focused: 'portland' (custom flixopt colorscale for energy systems)
-    - Backend-specific maps available in Plotly and Matplotlib
-
-**Color Lists** (list[str]):
-    - Explicit color sequences: ['red', 'blue', 'green', 'orange']
-    - HEX codes: ['#FF0000', '#0000FF', '#00FF00', '#FFA500']
-    - Mixed formats: ['red', '#0000FF', 'green', 'orange']
-
-**Label-to-Color Mapping** (dict[str, str]):
-    - Explicit associations: {'Wind': 'skyblue', 'Solar': 'gold', 'Gas': 'brown'}
-    - Ensures consistent colors across different plots and datasets
-    - Ideal for energy system components with semantic meaning
-
-Examples:
-    ```python
-    # Named colorscale
-    colors = 'turbo'  # Automatic color generation
-
-    # Explicit color list
-    colors = ['red', 'blue', 'green', '#FFD700']
-
-    # Component-specific mapping
-    colors = {
-        'Wind_Turbine': 'skyblue',
-        'Solar_Panel': 'gold',
-        'Natural_Gas': 'brown',
-        'Battery': 'green',
-        'Electric_Load': 'darkred'
-    }
-    ```
-
-Color Format Support:
-    - **Named Colors**: 'red', 'blue', 'forestgreen', 'darkorange'
-    - **HEX Codes**: '#FF0000', '#0000FF', '#228B22', '#FF8C00'
-    - **RGB Tuples**: (255, 0, 0), (0, 0, 255) [Matplotlib only]
-    - **RGBA**: 'rgba(255,0,0,0.8)' [Plotly only]
-
-References:
-    - HTML Color Names: https://htmlcolorcodes.com/color-names/
-    - Matplotlib colorscales: https://matplotlib.org/stable/tutorials/colors/colorscales.html
-    - Plotly Built-in Colorscales: https://plotly.com/python/builtin-colorscales/
-"""
-
 PlottingEngine = Literal['plotly', 'matplotlib']
 """Identifier for the plotting engine to use."""
 
diff --git a/flixopt/statistics_accessor.py b/flixopt/statistics_accessor.py
index e7d0ec5fe..53ad5fa51 100644
--- a/flixopt/statistics_accessor.py
+++ b/flixopt/statistics_accessor.py
@@ -30,7 +30,7 @@
 import plotly.graph_objects as go
 import xarray as xr
 
-from .color_processing import process_colors
+from .color_processing import ColorType, process_colors
 from .config import CONFIG
 
 if TYPE_CHECKING:
@@ -47,9 +47,6 @@
 FilterType = str | list[str]
 """For include/exclude filtering: 'Boiler' or ['Boiler', 'CHP']"""
 
-ColorType = str | list[str] | dict[str, str] | None
-"""Flexible color input: colorscale name, color list, label-to-color dict, or None for default."""
-
 
 def _reshape_time_for_heatmap(
     data: xr.DataArray,

From 2c8eb4e33dcd3c51e4e94a501790a25284b2b9fa Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 15:50:09 +0100
Subject: [PATCH 5/7] Fix ColorType typing

---
 flixopt/color_processing.py    |  1 -
 flixopt/statistics_accessor.py | 14 +++++++-------
 2 files changed, 7 insertions(+), 8 deletions(-)

diff --git a/flixopt/color_processing.py b/flixopt/color_processing.py
index f09a3927d..f6e9a3b9f 100644
--- a/flixopt/color_processing.py
+++ b/flixopt/color_processing.py
@@ -16,7 +16,6 @@
 logger = logging.getLogger('flixopt')
 
 # Type alias for flexible color input
-ColorType = str | list[str] | dict[str, str] | None
 ColorType = str | list[str] | dict[str, str]
 """Flexible color specification type supporting multiple input formats for visualization.
 
diff --git a/flixopt/statistics_accessor.py b/flixopt/statistics_accessor.py
index 53ad5fa51..eab6a7567 100644
--- a/flixopt/statistics_accessor.py
+++ b/flixopt/statistics_accessor.py
@@ -745,7 +745,7 @@ def balance(
         include: FilterType | None = None,
         exclude: FilterType | None = None,
         unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate',
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -822,7 +822,7 @@ def heatmap(
         *,
         select: SelectType | None = None,
         reshape: tuple[str, str] | None = ('D', 'h'),
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         facet_col: str | None = 'period',
         animation_frame: str | None = 'scenario',
         show: bool | None = None,
@@ -935,7 +935,7 @@ def flows(
         component: str | list[str] | None = None,
         select: SelectType | None = None,
         unit: Literal['flow_rate', 'flow_hours'] = 'flow_rate',
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -1018,7 +1018,7 @@ def sankey(
         timestep: int | str | None = None,
         aggregate: Literal['sum', 'mean'] = 'sum',
         select: SelectType | None = None,
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         show: bool | None = None,
         **plotly_kwargs: Any,
     ) -> PlotResult:
@@ -1130,7 +1130,7 @@ def sizes(
         *,
         max_size: float | None = 1e6,
         select: SelectType | None = None,
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -1192,7 +1192,7 @@ def duration_curve(
         *,
         select: SelectType | None = None,
         normalize: bool = False,
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,
@@ -1271,7 +1271,7 @@ def effects(
         effect: str | None = None,
         by: Literal['component', 'contributor', 'time'] = 'component',
         select: SelectType | None = None,
-        colors: ColorType = None,
+        colors: ColorType | None = None,
         facet_col: str | None = 'period',
         facet_row: str | None = 'scenario',
         show: bool | None = None,

From bff873fea25d2805f8760458b86900d2687dd32c Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 17:22:42 +0100
Subject: [PATCH 6/7]  statistics_accessor.py - Heatmap colors type safety
 (lines 121-148, 820-853)

  - Changed _heatmap_figure() parameter type from colors: ColorType = None to colors: str | list[str] | None = None
  - Changed heatmap() method parameter type similarly
  - Updated docstrings to clarify that dicts are not supported for heatmaps since px.imshow's color_continuous_scale only accepts colorscale names or lists

  2. statistics_accessor.py - Use configured qualitative colorscale (lines 284, 315)

  - Updated _create_stacked_bar() to use CONFIG.Plotting.default_qualitative_colorscale as the default colorscale
  - Updated _create_line() similarly
  - This ensures user-configured CONFIG.Plotting.default_qualitative_colorscale affects all bar/line plots consistently

  3. topology_accessor.py - Path type alignment (lines 219-222)

  - Added normalization of path=False to None before calling _plot_network()
  - This resolves the type mismatch where TopologyAccessor.plot() accepts bool | str | Path but _plot_network() only accepts str | Path | None
---
 flixopt/statistics_accessor.py | 14 ++++++++------
 flixopt/topology_accessor.py   |  8 +++++++-
 2 files changed, 15 insertions(+), 7 deletions(-)

diff --git a/flixopt/statistics_accessor.py b/flixopt/statistics_accessor.py
index eab6a7567..9f6bb01be 100644
--- a/flixopt/statistics_accessor.py
+++ b/flixopt/statistics_accessor.py
@@ -120,7 +120,7 @@ def _reshape_time_for_heatmap(
 
 def _heatmap_figure(
     data: xr.DataArray,
-    colors: ColorType = None,
+    colors: str | list[str] | None = None,
     title: str = '',
     facet_col: str | None = None,
     animation_frame: str | None = None,
@@ -131,7 +131,8 @@ def _heatmap_figure(
 
     Args:
         data: DataArray with 2-4 dimensions. First two are heatmap axes.
-        colors: Colorscale name.
+        colors: Colorscale name (str) or list of colors. Dicts are not supported
+            for heatmaps as color_continuous_scale requires a colorscale specification.
         title: Plot title.
         facet_col: Dimension for subplot columns.
         animation_frame: Dimension for animation slider.
@@ -280,7 +281,7 @@ def _create_stacked_bar(
         return go.Figure()
     x_col = 'time' if 'time' in df.columns else df.columns[0]
     variables = df['variable'].unique().tolist()
-    color_map = process_colors(colors, variables)
+    color_map = process_colors(colors, variables, default_colorscale=CONFIG.Plotting.default_qualitative_colorscale)
     fig = px.bar(
         df,
         x=x_col,
@@ -311,7 +312,7 @@ def _create_line(
         return go.Figure()
     x_col = 'time' if 'time' in df.columns else df.columns[0]
     variables = df['variable'].unique().tolist()
-    color_map = process_colors(colors, variables)
+    color_map = process_colors(colors, variables, default_colorscale=CONFIG.Plotting.default_qualitative_colorscale)
     return px.line(
         df,
         x=x_col,
@@ -822,7 +823,7 @@ def heatmap(
         *,
         select: SelectType | None = None,
         reshape: tuple[str, str] | None = ('D', 'h'),
-        colors: ColorType | None = None,
+        colors: str | list[str] | None = None,
         facet_col: str | None = 'period',
         animation_frame: str | None = 'scenario',
         show: bool | None = None,
@@ -839,7 +840,8 @@ def heatmap(
             select: xarray-style selection, e.g. {'scenario': 'Base Case'}.
             reshape: Time reshape frequencies as (outer, inner), e.g. ('D', 'h') for
                     days × hours. Set to None to disable reshaping.
-            colors: Colorscale name (e.g., 'viridis', 'plasma') for heatmap coloring.
+            colors: Colorscale name (str) or list of colors for heatmap coloring.
+                Dicts are not supported for heatmaps (use str or list[str]).
             facet_col: Dimension for subplot columns (default: 'period').
                       With multiple variables, 'variable' is used instead.
             animation_frame: Dimension for animation slider (default: 'scenario').
diff --git a/flixopt/topology_accessor.py b/flixopt/topology_accessor.py
index b4e18eb08..de4f83685 100644
--- a/flixopt/topology_accessor.py
+++ b/flixopt/topology_accessor.py
@@ -216,8 +216,14 @@ def plot(
         from .config import CONFIG
 
         node_infos, edge_infos = self.infos()
+        # Normalize path=False to None for _plot_network compatibility
+        normalized_path = None if path is False else path
         return _plot_network(
-            node_infos, edge_infos, path, controls, show if show is not None else CONFIG.Plotting.default_show
+            node_infos,
+            edge_infos,
+            normalized_path,
+            controls,
+            show if show is not None else CONFIG.Plotting.default_show,
         )
 
     def start_app(self) -> None:

From 26cfe30184c68dd458f2537c04733b943bef5bbc Mon Sep 17 00:00:00 2001
From: FBumann <117816358+FBumann@users.noreply.github.com>
Date: Sun, 7 Dec 2025 17:26:56 +0100
Subject: [PATCH 7/7] fix usage if index name in aggregation plot

---
 flixopt/clustering.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/flixopt/clustering.py b/flixopt/clustering.py
index 3d049132d..1595ace5d 100644
--- a/flixopt/clustering.py
+++ b/flixopt/clustering.py
@@ -159,14 +159,15 @@ def plot(self, colormap: str | None = None, show: bool = True, save: pathlib.Pat
         )
 
         # Create line plot for original data (dashed)
-        df_org_long = df_org.reset_index().melt(id_vars='index', var_name='variable', value_name='value')
-        fig = px.line(df_org_long, x='index', y='value', color='variable', color_discrete_sequence=colors)
+        index_name = df_org.index.name or 'index'
+        df_org_long = df_org.reset_index().melt(id_vars=index_name, var_name='variable', value_name='value')
+        fig = px.line(df_org_long, x=index_name, y='value', color='variable', color_discrete_sequence=colors)
         for trace in fig.data:
             trace.update(line=dict(dash='dash'))
 
         # Add aggregated data (solid lines)
-        df_agg_long = df_agg.reset_index().melt(id_vars='index', var_name='variable', value_name='value')
-        fig2 = px.line(df_agg_long, x='index', y='value', color='variable', color_discrete_sequence=colors)
+        df_agg_long = df_agg.reset_index().melt(id_vars=index_name, var_name='variable', value_name='value')
+        fig2 = px.line(df_agg_long, x=index_name, y='value', color='variable', color_discrete_sequence=colors)
         for trace in fig2.data:
             fig.add_trace(trace)