Timeseries plot style

modelskill/comparison/_comparer_plotter.py

@@ -26,6 +26,7 @@
     _xtick_directional,
     _ytick_directional,
     quantiles_xy,
+    _check_kwarg_and_convert_to_list,
 )
 from ..plotting import taylor_diagram, scatter, TaylorPoint
 from ..settings import options
@@ -62,6 +63,8 @@ def timeseries(
         ax=None,
         figsize: Tuple[float, float] | None = None,
         backend: str = "matplotlib",
+        style: list[str] | str | None = None,
+        color: list[str] | tuple | str | None = None,
         **kwargs,
     ):
         """Timeseries plot showing compared data: observation vs modelled
@@ -79,32 +82,66 @@ def timeseries(
         backend : str, optional
             use "plotly" (interactive) or "matplotlib" backend,
             by default "matplotlib"
+        style: list of str, optional
+            containing line styles of the model results. Cannot be passed together with color input.
+            by default None
+        color: list of str, optional
+            containing colors of the model results.
+            If len(colors) == num_models + 1, the first color will be used for the observations.
+            Cannot be passed together with style input.
+            by default None
         **kwargs
             other keyword arguments to fig.update_layout (plotly backend)
 
         Returns
         -------
         matplotlib.axes.Axes or plotly.graph_objects.Figure
         """
+
         from ._comparison import MOD_COLORS
 
         cmp = self.comparer
 
         if title is None:
             title = cmp.name
 
+        if color is not None and style is not None:
+            raise ValueError(
+                "It is not possible to pass both the color argument and the style argument. Choose one."
+            )
+
+        # Color for observations:
+        obs_color = cmp.data[cmp._obs_name].attrs["color"]
+
+        # if color is None and style is None:  # Use default values for colors
+        #     from ._comparison import MOD_COLORS
+
+        #     color = MOD_COLORS[: cmp.n_models]
+
+        color, style = _check_kwarg_and_convert_to_list(color, style, cmp.n_models)
+
+        if color is not None and len(color) > cmp.n_models:
+            # If more than n_models colors is given, the first color is used for the observations
+            obs_color = color[0]
+            color = color[1:]
+
         if backend == "matplotlib":
             fig, ax = _get_fig_ax(ax, figsize)
             for j in range(cmp.n_models):
                 key = cmp.mod_names[j]
                 mod = cmp.raw_mod_data[key]._values_as_series
-                mod.plot(ax=ax, color=MOD_COLORS[j])
+                if style is not None:
+                    mod.plot(ax=ax, style=style[j])
+                else:
+                    if color is None:
+                        color = MOD_COLORS
+                    mod.plot(ax=ax, color=color[j])
 
             ax.scatter(
                 cmp.time,
                 cmp.data[cmp._obs_name].values,
                 marker=".",
-                color=cmp.data[cmp._obs_name].attrs["color"],
+                color=obs_color,
             )
             ax.set_ylabel(cmp._unit_text)
             ax.legend([*cmp.mod_names, cmp._obs_name])

modelskill/plotting/_misc.py

@@ -184,3 +184,26 @@ def _format_skill_line(
     name = name.upper()
 
     return f"{name}", " =  ", f"{fvalue} {item_unit}"
+
+
+def _check_kwarg_and_convert_to_list(color, style, n_mod):
+    if isinstance(style, str):
+        # If style is str, convert to list (for looping)
+        style = [style]
+    if isinstance(color, str):
+        # Same with color
+        color = [color]
+
+    if color is not None and len(color) < n_mod:  # too few colors given?
+        raise ValueError(
+            "Number of colors in 'color' argument does not match the number of models in the comparer."
+        )
+
+    if (
+        style is not None and len(style) < n_mod and style[0] is not None
+    ):  # too few styles given?
+        raise ValueError(
+            "Number of styles in 'style' argument does not match the number of models in the comparer."
+        )
+
+    return color, style

tests/test_comparer.py

@@ -1,11 +1,12 @@
+import matplotlib.pyplot as plt
 import numpy as np
-import pytest
 import pandas as pd
+import pytest
 import xarray as xr
-import matplotlib.pyplot as plt
-from modelskill.comparison import Comparer
-from modelskill import __version__
+
 import modelskill as ms
+from modelskill import __version__
+from modelskill.comparison import Comparer
 
 
 @pytest.fixture
@@ -889,6 +890,26 @@ def test_from_matched_dfs0():
     ) == pytest.approx(0.0476569069177831)
 
 
+def test_timeseriesplot_accepts_style_color_input(pc):
+    # Check that it can take the inputs
+    ax = pc.plot.timeseries(color=["red", "blue"])
+    ax = pc.plot.timeseries(style=["b-", "g--"])
+    assert ax.lines[1].get_color() == "g"
+
+    # Check that errors are raised
+    with pytest.raises(ValueError, match="Choose one"):
+        ax = pc.plot.timeseries(color=["red", "blue"], style="b-")
+    with pytest.raises(ValueError, match="'color' argument"):
+        ax = pc.plot.timeseries(color=["red"])
+    with pytest.raises(ValueError, match="'style' argument"):
+        ax = pc.plot.timeseries(style=["b-"])
+
+    ax = pc.plot.timeseries(color=["red", "blue", "black"])
+    # first line is blue (red is for observations).
+    assert ax.lines[0].get_color() == "blue"
+    plt.show()
+
+
 def test_from_matched_x_or_x_item_not_both():
     with pytest.raises(ValueError, match="x and x_item cannot both be specified"):
         ms.from_matched(