Fix slicer re #363

discretize/mixins/mpl_mod.py

@@ -792,9 +792,6 @@ def plot_3d_slicer(
         # Connect figure to scrolling
         fig.canvas.mpl_connect("scroll_event", tracker.onscroll)
 
-        # Show figure
-        plt.show()
-
     # TensorMesh plotting
     def __plot_grid_tensor(
         self,
@@ -2458,6 +2455,7 @@ def __init__(
         """Initialize interactive figure."""
         _, plt = load_matplotlib()
         from matplotlib.widgets import Slider  # Lazy loaded
+        from matplotlib.colors import Normalize
 
         # 0. Some checks, not very extensive
         if "pcolorOpts" in kwargs:
@@ -2512,7 +2510,7 @@ def __init__(
 
         # Store data in self as (nx, ny, nz)
         self.v = mesh.reshape(v.reshape((mesh.nC, -1), order="F"), "CC", "CC", "M")
-        self.v = np.ma.masked_where(np.isnan(self.v), self.v)
+        self.v = np.ma.masked_array(self.v, np.isnan(self.v))
 
         # Store relevant information from mesh in self
         self.x = mesh.nodes_x  # x-node locations
@@ -2552,30 +2550,22 @@ def __init__(
         else:
             aspect3 = 1.0 / aspect2
 
-        # set color limits if clim is None (and norm doesn't have vmin, vmax).
-        if clim is None:
-            if "norm" in self.pc_props:
-                vmin = self.pc_props["norm"].vmin
-                vmax = self.pc_props["norm"].vmax
-            else:
-                vmin = vmax = None
-            clim = [
-                np.nanmin(self.v) if vmin is None else vmin,
-                np.nanmax(self.v) if vmax is None else vmax,
-            ]
-            # In the case of a homogeneous fullspace provide a small range to
-            # avoid problems with colorbar and the three subplots.
-            if clim[0] == clim[1]:
-                clim[0] *= 0.99
-                clim[1] *= 1.01
-
-        # ensure vmin/vmax of the norm is consistent with clim
-        if "norm" in self.pc_props:
-            self.pc_props["norm"].vmin = clim[0]
-            self.pc_props["norm"].vmax = clim[1]
+        # Ensure a consistent color normalization for the three plots.
+        if (norm := self.pc_props.get("norm", None)) is None:
+            # Create a default normalizer
+            norm = Normalize()
+            if clim is not None:
+                norm.vmin, norm.vmax = clim
+            self.pc_props["norm"] = norm
         else:
-            self.pc_props["vmin"] = clim[0]
-            self.pc_props["vmax"] = clim[1]
+            if clim is not None:
+                raise ValueError(
+                    "Passing a Normalize instance simultaneously with clim is not supported. "
+                    "Please pass vmin/vmax directly to the norm when creating it."
+                )
+
+        # Auto scales None values for norm.vmin and norm.vmax.
+        norm.autoscale_None(self.v[~self.v.mask].reshape(-1, order="A"))
 
         # 2. Start populating figure
 
@@ -2668,6 +2658,7 @@ def __init__(
 
         # Remove transparent value
         if isinstance(transparent, str) and transparent.lower() == "slider":
+            clim = (norm.vmin, norm.vmax)
             # Sliders
             self.ax_smin = plt.axes([0.7, 0.11, 0.15, 0.03])
             self.ax_smax = plt.axes([0.7, 0.15, 0.15, 0.03])

examples/plot_slicer_demo.py

@@ -9,10 +9,13 @@
 Using the inversion result from the example notebook
 `plot_laguna_del_maule_inversion.ipynb <http://docs.simpeg.xyz/content/examples/20-published/plot_laguna_del_maule_inversion.html>`_
 
-In the notebook, you have to use :code:`%matplotlib notebook`.
+You have to use :code:`%matplotlib notebook` in Jupyter Notebook, and
+:code:`%matplotlib widget` in Jupyter Lab (latter requires the package
+``ipympl``).
 """
 
 # %matplotlib notebook
+# %matplotlib widget
 import discretize
 import numpy as np
 import matplotlib.pyplot as plt
@@ -47,6 +50,7 @@
 # ^^^^^^^^^^^^^^^^^^^
 
 mesh.plot_3d_slicer(Lpout)
+plt.show()
 
 ###############################################################################
 # 1.2 Create a function to improve plots, labeling after creation
@@ -101,6 +105,7 @@ def beautify(title, fig=None):
 #
 mesh.plot_3d_slicer(Lpout)
 beautify("mesh.plot_3d_slicer(Lpout)")
+plt.show()
 
 ###############################################################################
 # 1.3 Set `xslice`, `yslice`, and `zslice`; transparent region
@@ -115,6 +120,7 @@ def beautify(title, fig=None):
     "mesh.plot_3d_slicer("
     "\nLpout, 370000, 6002500, -2500, transparent=[[-0.02, 0.1]])"
 )
+plt.show()
 
 ###############################################################################
 # 1.4 Set `clim`, use `pcolor_opts` to show grid lines
@@ -127,6 +133,7 @@ def beautify(title, fig=None):
     "mesh.plot_3d_slicer(\nLpout, clim=[-0.4, 0.2], "
     "pcolor_opts={'edgecolor': 'k', 'linewidth': 0.1})"
 )
+plt.show()
 
 ###############################################################################
 # 1.5 Use `pcolor_opts` to set `SymLogNorm`, and another `cmap`
@@ -139,6 +146,7 @@ def beautify(title, fig=None):
     "mesh.plot_3d_slicer(Lpout,"
     "\npcolor_opts={'norm': SymLogNorm(linthresh=0.01),'cmap': 'RdBu_r'})`"
 )
+plt.show()
 
 ###############################################################################
 # 1.6 Use :code:`aspect` and :code:`grid`
@@ -156,6 +164,7 @@ def beautify(title, fig=None):
 
 mesh.plot_3d_slicer(Lpout, aspect=["equal", 1.5], grid=[4, 4, 3])
 beautify("mesh.plot_3d_slicer(Lpout, aspect=['equal', 1.5], grid=[4, 4, 3])")
+plt.show()
 
 ###############################################################################
 # 1.7 Transparency-slider
@@ -166,6 +175,7 @@ def beautify(title, fig=None):
 
 mesh.plot_3d_slicer(Lpout, transparent="slider")
 beautify("mesh.plot_3d_slicer(Lpout, transparent='slider')")
+plt.show()
 
 
 ###############################################################################

tests/base/test_slicer.py

@@ -0,0 +1,56 @@
+import numpy as np
+import pytest
+from matplotlib.colors import Normalize
+import discretize
+from discretize.mixins.mpl_mod import Slicer
+
+
+@pytest.fixture()
+def mesh():
+    return discretize.TensorMesh([9, 10, 11])
+
+
+def test_slicer_errors(mesh):
+    model = np.ones(mesh.shape_cells)
+    with pytest.raises(
+        ValueError,
+        match="(Passing a Normalize instance simultaneously with clim is not supported).*",
+    ):
+        Slicer(mesh, model, clim=[0, 1], pcolor_opts={"norm": Normalize()})
+
+
+def test_slicer_default_clim(mesh):
+    model = np.ones(mesh.shape_cells)
+    model[0, 0, 0] = 0.5
+    slc = Slicer(mesh, model)
+    norm = slc.pc_props["norm"]
+    assert (norm.vmin, norm.vmax) == (0.5, 1.0)
+
+
+def test_slicer_set_clim(mesh):
+    model = np.ones(mesh.shape_cells)
+    slc = Slicer(mesh, model, clim=(0.5, 1.5))
+    norm = slc.pc_props["norm"]
+    assert (norm.vmin, norm.vmax) == (0.5, 1.5)
+
+
+def test_slicer_set_norm(mesh):
+    model = np.ones(mesh.shape_cells)
+    norm = Normalize(0.5, 1.5)
+    slc = Slicer(mesh, model, pcolor_opts={"norm": norm})
+    norm = slc.pc_props["norm"]
+    assert (norm.vmin, norm.vmax) == (0.5, 1.5)
+
+
+def test_slicer_ones_clim(mesh):
+    model = np.ones(mesh.shape_cells)
+    slc = Slicer(mesh, model)
+    norm = slc.pc_props["norm"]
+    assert (norm.vmin, norm.vmax) == (0.9, 1.1)
+
+
+def test_slicer_zeros_clim(mesh):
+    model = np.zeros(mesh.shape_cells)
+    slc = Slicer(mesh, model)
+    norm = slc.pc_props["norm"]
+    assert (norm.vmin, norm.vmax) == (-0.1, 0.1)