diff --git a/docs/examples/howto_meshplotlib/plot_meshplotlib_2d.py b/docs/examples/howto_meshplotlib/plot_meshplotlib_2d.py
index 9be7ab03bbee74806a3a276ccb9f91e8a9ad28f3..006e86e3c2e3f449b88db95cf15ff74b6b0be742 100644
--- a/docs/examples/howto_meshplotlib/plot_meshplotlib_2d.py
+++ b/docs/examples/howto_meshplotlib/plot_meshplotlib_2d.py
@@ -38,6 +38,14 @@ fig = mpl.plot(mesh, presets.pressure.get_mask())
fig = mpl.plot(mesh, presets.velocity)
+# %%
+# Let's plot it again, this time log-scaled.
+mpl.setup.log_scaled = True
+mpl.setup.p_min = -8
+fig = mpl.plot(mesh, presets.velocity)
+mpl.setup.p_min = None
+mpl.setup.log_scaled = False
+
# %%
# We can also plot components of vector property:
diff --git a/ogstools/meshplotlib/core.py b/ogstools/meshplotlib/core.py
index 6ee8c65266ff756eb9af4d3a179b4c6de2ffa68e..4e7284265b7f7036748c9075c173714bcab983d0 100644
--- a/ogstools/meshplotlib/core.py
+++ b/ogstools/meshplotlib/core.py
@@ -1,6 +1,5 @@
"""Meshplotlib core utilitites."""
-import types
from copy import deepcopy
from math import nextafter
from typing import Literal, Optional, Union
@@ -13,7 +12,6 @@ from matplotlib import colors as mcolors
from matplotlib import figure as mfigure
from matplotlib import pyplot as plt
from matplotlib import ticker as mticker
-from matplotlib import transforms as mtransforms
from matplotlib.patches import Rectangle as Rect
from ogstools.meshlib import MeshSeries
@@ -23,7 +21,7 @@ from ogstools.propertylib.unit_registry import u_reg
from . import plot_features as pf
from . import setup
-from .levels import get_levels
+from .levels import get_levels, get_median_exponent
from .utils import get_style_cycler
# TODO: define default data_name for regions in setup
@@ -51,7 +49,7 @@ def get_data(
property.data_name not in mesh.point_data
and property.data_name not in mesh.cell_data
):
- msg = f"Property not found in mesh {mesh}."
+ msg = f"Property {property.data_name} not found in mesh."
raise IndexError(msg)
if masked:
return mesh.ctp(True).threshold(value=[1, 1], scalars=property.mask)[
@@ -103,25 +101,6 @@ def get_cmap_norm(
return cmap, norm
-# to fix scientific offset position
-# https://github.com/matplotlib/matplotlib/issues/4476#issuecomment-105627334
-def fix_scientific_offset_position(axis, func):
- axis._update_offset_text_position = types.MethodType(func, axis)
-
-
-def y_update_offset_text_position(self, bboxes, bboxes2): # noqa: ARG001
- x, y = self.offsetText.get_position()
- # y in axes coords, x in display coords
- self.offsetText.set_transform(
- mtransforms.blended_transform_factory(
- self.axes.transAxes, mtransforms.IdentityTransform()
- )
- )
- top = self.axes.bbox.ymax
- y = top + 2 * self.OFFSETTEXTPAD * self.figure.dpi / 72.0
- self.offsetText.set_position((x, y))
-
-
def add_colorbars(
fig: mfigure.Figure,
ax: Union[plt.Axes, list[plt.Axes]],
@@ -131,60 +110,63 @@ def add_colorbars(
labelsize: Optional[float] = None,
) -> None:
"""Add a colorbar to the matplotlib figure."""
- cmap, norm = get_cmap_norm(levels, property)
- cm = mcm.ScalarMappable(norm=norm, cmap=cmap)
- categoric = property.categoric or (len(levels) == 2)
- if categoric:
+ ticks = levels
+ if property.categoric or (len(levels) == 2):
bounds = get_level_boundaries(levels)
ticks = bounds[:-1] + 0.5 * np.diff(bounds)
- else:
- ticks = levels
+
+ cmap, norm = get_cmap_norm(levels, property)
+ cm = mcm.ScalarMappable(norm=norm, cmap=cmap)
+
cb = fig.colorbar(
cm, norm=norm, ax=ax, ticks=ticks, drawedges=True, location="right",
spacing="uniform", pad=pad, format="%.3g" # fmt: skip
)
- if setup.invert_colorbar:
- cb.ax.invert_yaxis()
- if property.is_mask():
- cb.ax.add_patch(Rect((0, 0.5), 1, -1, lw=0, fc="none", hatch="/"))
- if not categoric and setup.log_scaled:
- levels = 10**levels
-
- unit_str = (
- f" / {property.get_output_unit()}" if property.get_output_unit() else ""
- )
+ # Formatting the colorbar label
+ cb_label = property.output_name.replace("_", " ") + " / "
+ POWER_LIMIT = 3
+ if (
+ abs(median_exponent := get_median_exponent(ticks)) > POWER_LIMIT
+ ) and not (np.isclose(ticks[0], ticks[-1]) or setup.log_scaled):
+ ticks = ticks * 10**-median_exponent
+ cb_label += f"10$^{{{median_exponent}}}$ "
+ if unit := property.get_output_unit():
+ cb_label += f"{unit}"
+ if cb_label[-3:] == " / ":
+ cb_label = cb_label[:-3]
+ if setup.log_scaled:
+ cb_label = f"log$_{{10}}$( {cb_label} )"
labelsize = (
setup.rcParams_scaled["font.size"] if labelsize is None else labelsize
)
- cb.set_label(
- property.output_name.replace("_", " ") + unit_str, size=labelsize
- )
- cb.ax.tick_params(labelsize=labelsize, direction="out")
- mf = mticker.ScalarFormatter(useMathText=True, useOffset=True)
- mf.set_scientific(True)
- mf.set_powerlimits([-3, 3])
- fix_scientific_offset_position(cb.ax.yaxis, y_update_offset_text_position)
- cb.ax.yaxis.set_offset_position("left")
- cb.ax.yaxis.set_major_formatter(mf)
-
- if _q_zero_line(property, levels):
- cb.ax.axhline(
- y=0, color="w", lw=2 * setup.rcParams_scaled["lines.linewidth"]
- )
- if setup.log_scaled:
- cb.ax.set_yticklabels(10**ticks)
+ cb.set_label(cb_label, size=labelsize)
+
+ # formatting the colorbar ticks
+ cb.ax.tick_params(labelsize=labelsize, direction="out")
+ cb.ax.yaxis.set_major_formatter(mticker.FormatStrFormatter("%.3g"))
+ tick_labels = [
+ f"{round(tick, POWER_LIMIT):.{POWER_LIMIT}g}" for tick in ticks
+ ]
if property.data_name == "MaterialIDs" and setup.material_names is not None:
- region_names = []
- for mat_id in levels:
- if mat_id in setup.material_names:
- region_names += [setup.material_names[mat_id]]
- else:
- region_names += [mat_id]
- cb.ax.set_yticklabels(region_names)
+ tick_labels = [
+ setup.material_names.get(mat_id, mat_id) for mat_id in levels
+ ]
cb.ax.set_ylabel("")
elif property.categoric:
- cb.ax.set_yticklabels(levels.astype(int))
+ tick_labels = [str(level) for level in levels.astype(int)]
+ cb.ax.set_yticklabels(tick_labels)
+
+ # miscellaneous
+
+ if property.is_mask():
+ cb.ax.add_patch(Rect((0, 0.5), 1, -1, lw=0, fc="none", hatch="/"))
+ if setup.invert_colorbar:
+ cb.ax.invert_yaxis()
+ if _q_zero_line(property, ticks):
+ cb.ax.axhline(
+ y=0, color="w", lw=2 * setup.rcParams_scaled["lines.linewidth"]
+ )
def subplot(
diff --git a/ogstools/meshplotlib/levels.py b/ogstools/meshplotlib/levels.py
index 261e53503cd012cfa9a01f5411c02c107e17d6a6..3f0e7c13189c2fd78c1b80130002105fe996060e 100644
--- a/ogstools/meshplotlib/levels.py
+++ b/ogstools/meshplotlib/levels.py
@@ -1,5 +1,7 @@
"""Utilities to create nicely spaced levels."""
+from math import nextafter
+
import numpy as np
@@ -21,29 +23,14 @@ def nice_range(lower: float, upper: float, n_ticks: float) -> np.ndarray:
The length of the arrays will be close to n_ticks.
"""
- nice_range = nice_num(upper - lower)
- tick_spacing = nice_num(nice_range / (n_ticks - 1.0))
+ base = nice_num(upper - lower)
+ tick_spacing = nice_num(base / (n_ticks - 1.0))
nice_lower = np.ceil(lower / tick_spacing) * tick_spacing
nice_upper = np.ceil(upper / tick_spacing) * tick_spacing
res = np.arange(nice_lower, nice_upper, tick_spacing)
return res[(res > lower) & (res < upper)]
-def adaptive_rounding(vals: np.ndarray, precision: int) -> np.ndarray:
- """
- Return the given values rounded to significant digits.
-
- The significant digits are based of the median decimal exponent and the
- given precision.
- """
- if vals.size == 0:
- return vals
- log = np.log10(np.abs(vals), out=np.zeros_like(vals), where=(vals != 0.0))
- exponents = np.floor(log).astype(int)
- median_exp = int(np.median(exponents))
- return np.stack([np.round(v, precision - median_exp) for v in vals])
-
-
def get_levels(lower: float, upper: float, n_ticks: int) -> np.ndarray:
"""
Return an array in the interval [lower, upper] with terminating decimals.
@@ -51,10 +38,14 @@ def get_levels(lower: float, upper: float, n_ticks: int) -> np.ndarray:
The length of the arrays will be close to n_ticks.
At the boundaries the tickspacing may differ from the remaining array.
"""
- n_digits = 6
- if lower * (1 - 10**-n_digits) <= upper <= lower * (1 + 10**-n_digits):
- return lower + np.array([0.0, 10**-n_digits])
+ if lower == upper:
+ return np.asarray([lower, nextafter(lower, np.inf)])
levels = nice_range(lower, upper, n_ticks)
- return np.unique(
- np.append(np.append(lower, adaptive_rounding(levels, n_digits)), upper)
- )
+ return np.unique(np.append(np.append(lower, levels), upper))
+
+
+def get_median_exponent(vals: np.ndarray) -> int:
+ "Get the median exponent from an array of numbers."
+ log = np.log10(np.abs(vals), out=np.zeros_like(vals), where=(vals != 0.0))
+ exponents = np.floor(log).astype(int)
+ return int(np.median(exponents))
diff --git a/tests/test_meshplotlib.py b/tests/test_meshplotlib.py
index e74feedaaf4cbbadc882df0a933d64e335385808..bab263036aacb4c11f8e9dc7ede58e7d193c701b 100644
--- a/tests/test_meshplotlib.py
+++ b/tests/test_meshplotlib.py
@@ -21,7 +21,9 @@ from ogstools.meshplotlib.plot_features import plot_on_top
from ogstools.meshplotlib.utils import justified_labels
from ogstools.propertylib import Scalar, presets
-equality = partial(np.testing.assert_allclose, rtol=1e-7, verbose=True)
+equality = partial(
+ np.testing.assert_allclose, rtol=1e-7, atol=1e-100, verbose=True
+)
class MeshplotlibTest(unittest.TestCase):
@@ -42,8 +44,8 @@ class MeshplotlibTest(unittest.TestCase):
equality(get_levels(1e-3, 1.2, 5), [1e-3, *np.arange(0.2, 1.4, 0.2)])
equality(get_levels(1e5, 9e6, 20), [1e5, *np.arange(5e5, 9.5e6, 5e5)])
equality(get_levels(1, 40, 20), [1, *range(2, 42, 2)])
- equality(get_levels(0.0, 0.0, 10), [0.0, 1e-6])
- equality(get_levels(1e9, 1e9, 10), [1e9, 1e9 + 1e-6])
+ equality(get_levels(0.0, 0.0, 10), [0.0, 0.0])
+ equality(get_levels(1e9, 1e9, 10), [1e9, 1e9])
def test_justified_labels(self):
points = np.asarray(