split clamping of the variable and the colorbar limits

examples/config/plotter.yaml

@@ -24,7 +24,8 @@
 #       - var: name of the scalar variable to be plotted (color scale)
 #       - scale: scaling of the variable (scaling done just before plotting)
 #       - log: use (or not) a log scale for the color axis
-#       - color_lim: clamping range for the color axis (null for complete range)
+#       - color_lim: limit range for the color axis (null for complete range)
+#       - clamp_lim: clamping range for the color axis (null for complete range)
 #       - filter_lim: hide voxels/points with values outside this range (null for complete range)
 #       - point_size: size of the marker used for plotting on the point cloud
 #
@@ -36,7 +37,8 @@
 #       - var_vector: name of the vector variable to be plotted (arrow direction)
 #       - scale: scaling of the scalar variable (scaling done just before plotting)
 #       - log: use (or not) a log scale for the color axis
-#       - color_lim: clamping range for the color axis (null for complete range)
+#       - color_lim: limit range for the color axis (null for complete range)
+#       - clamp_lim: clamping range for the color axis (null for complete range)
 #       - filter_lim: hide arrows with scalar values outside this range (null for complete range)
 #       - arrow_threshold: relative threshold for hiding arrows with small scalar values
 #       - arrow_scale: relative arrow length (with respect to the voxel size)
@@ -80,6 +82,7 @@
         "scale": 1.0
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "V_m_abs":
@@ -95,6 +98,7 @@
         "scale": 1.0
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "S_c_abs":
@@ -110,6 +114,7 @@
         "scale": 1.0e-9
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "Q_m_abs":
@@ -125,6 +130,7 @@
         "scale": 1.0
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "P_c_abs":
@@ -140,6 +146,7 @@
         "scale": 1.0e-6
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "P_m_abs":
@@ -155,6 +162,7 @@
         "scale": 1.0e-6
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "J_c_norm":
@@ -170,6 +178,7 @@
         "scale": 1.0e-6
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "J_c_vec":
@@ -186,6 +195,7 @@
         "scale": 1.0e-6
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "arrow_threshold": 1.0e-3
         "arrow_scale": 0.75
@@ -202,6 +212,7 @@
         "scale": 1.0e+3
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "B_m_vec":
@@ -218,6 +229,7 @@
         "scale": 1.0e+3
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "arrow_threshold": 1.0e-3
         "arrow_scale": 0.75
@@ -234,6 +246,7 @@
         "scale": 1.0
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "point_size": 10.0
 "H_vec":
@@ -250,6 +263,7 @@
         "scale": 1.0
         "log": false
         "color_lim": null
+        "clamp_lim": null
         "filter_lim": null
         "arrow_threshold": 1.0e-3
         "arrow_scale": 0.75

pypeec/lib_check/check_data_visualization.py

@@ -222,7 +222,7 @@ def _check_data_plot_plotter(layout, data_plot):
     # check the options for scalar and arrow plots
     if layout in ["scalar_voxel", "scalar_point", "arrow_voxel", "arrow_point"]:
         # check type
-        key_list = ["title", "scale", "log", "legend", "color_lim", "filter_lim"]
+        key_list = ["title", "scale", "log", "legend", "color_lim", "clamp_lim", "filter_lim"]
         datachecker.check_dict("data_plot", data_plot, key_list=key_list)
 
         # check data
@@ -231,6 +231,7 @@ def _check_data_plot_plotter(layout, data_plot):
         datachecker.check_string("legend", data_plot["legend"], can_be_empty=True)
         datachecker.check_float("scale", data_plot["scale"], is_positive=True, can_be_zero=True)
         datachecker.check_float_array("color_lim", data_plot["color_lim"], size=2, can_be_none=True)
+        datachecker.check_float_array("clamp_lim", data_plot["clamp_lim"], size=2, can_be_none=True)
         datachecker.check_float_array("filter_lim", data_plot["filter_lim"], size=2, can_be_none=True)
 
     # check the scalar options

pypeec/lib_visualization/manage_pyvista.py

@@ -235,7 +235,7 @@ def _get_filter_scalar(obj, var, filter_lim):
     return obj
 
 
-def _get_clamp_scalar(obj, var, color_lim):
+def _get_clamp_scalar(obj, var, clamp_lim):
     """
     Clamp a scalar variable between a lower and upper bound.
     """
@@ -245,11 +245,11 @@ def _get_clamp_scalar(obj, var, color_lim):
         return obj
 
     # handle None
-    if color_lim is None:
+    if clamp_lim is None:
         c_min = -float("inf")
         c_max = +float("inf")
     else:
-        (c_min, c_max) = color_lim
+        (c_min, c_max) = clamp_lim
 
     # get var
     data = obj[var]
@@ -277,6 +277,7 @@ def _plot_scalar(pl, obj, data_plot, plot_clip, plot_theme):
     scale = data_plot["scale"]
     log = data_plot["log"]
     filter_lim = data_plot["filter_lim"]
+    clamp_lim = data_plot["clamp_lim"]
     color_lim = data_plot["color_lim"]
     point_size = data_plot["point_size"]
     legend = data_plot["legend"]
@@ -298,12 +299,13 @@ def _plot_scalar(pl, obj, data_plot, plot_clip, plot_theme):
     obj_tmp = obj.copy(deep=True)
     obj_tmp = _get_scale_scalar(obj_tmp, var, scale)
     obj_tmp = _get_filter_scalar(obj_tmp, var, filter_lim)
-    obj_tmp = _get_clamp_scalar(obj_tmp, var, color_lim)
+    obj_tmp = _get_clamp_scalar(obj_tmp, var, clamp_lim)
 
     # add the resulting plot to the plotter
     arg = dict(
         scalars=var,
         log_scale=log,
+        clim=color_lim,
         point_size=point_size,
         scalar_bar_args=scalar_bar_args,
         render_points_as_spheres=True,
@@ -329,6 +331,7 @@ def _plot_arrow(pl, grid, obj, data_plot, plot_clip, plot_theme):
     scale = data_plot["scale"]
     log = data_plot["log"]
     filter_lim = data_plot["filter_lim"]
+    clamp_lim = data_plot["clamp_lim"]
     color_lim = data_plot["color_lim"]
     arrow_scale = data_plot["arrow_scale"]
     arrow_threshold = data_plot["arrow_threshold"]
@@ -357,14 +360,19 @@ def _plot_arrow(pl, grid, obj, data_plot, plot_clip, plot_theme):
     obj_tmp = _get_filter_vector(obj_tmp, var_norm, arrow_threshold)
     obj_tmp = _get_scale_scalar(obj_tmp, var_norm, scale)
     obj_tmp = _get_filter_scalar(obj_tmp, var_norm, filter_lim)
-    obj_tmp = _get_clamp_scalar(obj_tmp, var_norm, color_lim)
+    obj_tmp = _get_clamp_scalar(obj_tmp, var_norm, clamp_lim)
 
     # get arrow size
     d_char = min(grid.spacing)
     factor = d_char*arrow_scale
 
     # add the resulting plot to the plotter
-    arg = dict(scalars=var_norm, log_scale=log, scalar_bar_args=scalar_bar_args)
+    arg = dict(
+        scalars=var_norm,
+        log_scale=log,
+        clim=color_lim,
+        scalar_bar_args=scalar_bar_args,
+    )
     if obj_tmp.n_cells > 0:
         glyph_tmp = obj_tmp.glyph(orient=var_time, scale=False, factor=factor)
         _get_clip_mesh(pl, glyph_tmp, arg, plot_clip)