[gui] added a seperate visualize function for 1d in jupyter

notebooks/elliptic_oned.ipynb

@@ -15,8 +15,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pymor.basic import *\n",
-    "set_defaults({'pymor.discretizers.builtin.gui.jupyter.get_visualizer.backend': 'not pythreejs'})"
+    "from pymor.basic import *"
    ]
   },
   {
@@ -72,7 +71,7 @@
     "U = m.solution_space.empty()\n",
     "for mu in parameter_space.sample_uniformly(10):\n",
     "    U.append(m.solve(mu))\n",
-    "m.visualize(U, title='Solution for diffusionl in [0.1, 1]')"
+    "m.visualize(U, title='Solution for diffusionl in [0.1, 1]', separate_plots=False)"
    ]
   }
  ],

src/pymor/discretizers/builtin/gui/jupyter/__init__.py

@@ -13,7 +13,7 @@ inside the given notebook.
 import IPython
 
 from pymor.core.defaults import defaults
-from pymor.discretizers.builtin.gui.jupyter.patch import visualize_patch
+from pymor.discretizers.builtin.gui.jupyter.matplotlib import visualize_patch
 from pymor.core.config import config
 
 

src/pymor/discretizers/builtin/gui/jupyter/patch.py → src/pymor/discretizers/builtin/gui/jupyter/matplotlib.py

@@ -88,12 +88,8 @@ def visualize_patch(grid, U, bounding_box=([0, 0], [1, 1]), codim=2, title=None,
             for i, (vmin, vmax) in enumerate(zip(self.vmins, self.vmaxs)):
                 ax = figure.add_subplot(rows, columns, i+1)
                 axes.append(ax)
-                if grid.dim == 2:
-                    plots.append(MatplotlibPatchAxes(figure, grid, bounding_box=bounding_box, vmin=vmin, vmax=vmax,
-                                                     codim=codim, colorbar=separate_colorbars))
-                else:
-                    plots.append(Matplotlib1DAxes(figure, grid, bounding_box=bounding_box, vmin=vmin, vmax=vmax,
-                                                  codim=codim, colorbar=separate_colorbars))
+                plots.append(MatplotlibPatchAxes(figure, grid, bounding_box=bounding_box, vmin=vmin, vmax=vmax,
+                                                 codim=codim, colorbar=separate_colorbars))
                 if legend:
                     ax.set_title(legend[i])
 
@@ -127,3 +123,66 @@ def visualize_patch(grid, U, bounding_box=([0, 0], [1, 1]), codim=2, title=None,
         interact(set_time, t=IntSlider(min=0, max=len(U[0])-1, step=1, value=0))
 
     return None
+
+
+def visualize_matplotlib_1d(grid, U, codim=1, title=None, legend=None, separate_plots=False, columns=2):
+    assert isinstance(U, VectorArray) \
+        or (isinstance(U, tuple)
+            and all(isinstance(u, VectorArray) for u in U)
+            and all(len(u) == len(U[0]) for u in U))
+    U = (U.to_numpy(),) if isinstance(U, VectorArray) else tuple(u.to_numpy() for u in U)
+
+    if not config.HAVE_MATPLOTLIB:
+        raise ImportError('cannot visualize: import of matplotlib failed')
+    if not config.HAVE_IPYWIDGETS and len(U[0]) > 1:
+        raise ImportError('cannot visualize: import of ipywidgets failed')
+
+    if isinstance(legend, str):
+        legend = (legend,)
+    assert legend is None or isinstance(legend, tuple) and len(legend) == len(U)
+
+
+    class Plot:
+
+        def __init__(self):
+            if separate_plots:
+                self.vmins = tuple(np.min(u) for u in U[0])
+                self.vmaxs = tuple(np.max(u) for u in U[0])
+            else:
+                self.vmins = (min(np.min(u) for u in U),)
+                self.vmaxs = (max(np.max(u) for u in U),)
+
+            import matplotlib.pyplot as plt
+
+            rows = int(np.ceil(len(U[0]) / columns))
+            self.figure = plt.figure()
+
+            self.plots = []
+            axes = []
+            for i, (vmin, vmax) in enumerate(zip(self.vmins, self.vmaxs)):
+                if separate_plots:
+                    ax = self.figure.add_subplot(rows, columns, i+1)
+                else:
+                    ax = self.figure.gca()
+                axes.append(ax)
+                count = 1
+                if not separate_plots:
+                    count = len(U[0])
+                self.plots.append(Matplotlib1DAxes(ax, grid, count, vmin=vmin, vmax=vmax,
+                                                   codim=codim))
+                if legend:
+                    ax.set_title(legend[i])
+
+            plt.tight_layout()
+
+        def set(self, U):
+            if separate_plots:
+                for u, plot, vmin, vmax in zip(U, self.plots, self.vmins, self.vmaxs):
+                    plot.set(u[np.newaxis, ...], vmin=vmin, vmax=vmax)
+            else:
+                self.plots[0].set(U, vmin=self.vmins[0], vmax=self.vmaxs[0])
+
+    plot = Plot()
+    plot.set(U[0])
+
+    return None

src/pymor/discretizers/builtin/gui/matplotlib.py

@@ -59,14 +59,15 @@ class MatplotlibPatchAxes:
 
 class Matplotlib1DAxes:
 
-    def __init__(self, figure, grid, bounding_box=None, vmin=None, vmax=None, codim=1,
-                 colorbar=True):
+    def __init__(self, axes, grid, count, vmin=None, vmax=None, codim=1):
         assert isinstance(grid, OnedGrid)
         assert codim in (0, 1)
 
         self.codim = codim
         self.grid = grid
 
+        self.count = count
+
         centers = grid.centers(1)
         if grid.identify_left_right:
             centers = np.concatenate((centers, [[grid.domain[1]]]), axis=0)
@@ -77,22 +78,28 @@ class Matplotlib1DAxes:
             xs = centers
         else:
             xs = np.repeat(centers, 2)[1:-1]
-
-        self.axes = figure.gca()
-        self.lines, = self.axes.plot(xs, np.zeros_like(xs))
+        lines = ()
+        for i in range(count):
+            l, = axes.plot(xs, np.zeros_like(xs))
+            lines = lines + (l,)
+        pad = (vmax - vmin) * 0.1
+        axes.set_ylim(vmin - pad, vmax + pad)
+        self.axes = axes
+        self.lines = lines
 
 
     def set(self, U, vmin=None, vmax=None):
         self.vmin = self.vmin if vmin is None else vmin
         self.vmax = self.vmax if vmax is None else vmax
-        u = np.array(U)
-        if self.codim == 1:
-            if self.periodic:
-                self.lines.set_ydata(np.concatenate((u, [u[0]])))
+        for i in range(self.count):
+            u = np.array(U[i])
+            if self.codim == 1:
+                if self.periodic:
+                    self.lines[i].set_ydata(np.concatenate((u, [u[0]])))
+                else:
+                    self.lines[i].set_ydata(u)
             else:
-                self.lines.set_ydata(u)
-        else:
-            self.lines.set_ydata(np.repeat(u, 2))
+                self.lines[i].set_ydata(np.repeat(u, 2))
 
         self.axes.set_ylim(self.vmin, self.vmax)
 

src/pymor/discretizers/builtin/gui/visualizers.py

@@ -117,8 +117,8 @@ class OnedVisualizer(BasicObject):
         backend = backend or ('jupyter' if is_jupyter() else None)
         self.__auto_init(locals())
 
-    def visualize(self, U, m, title=None, legend=None, separate_colorbars=False,
-                  rescale_colorbars=False, block=None, filename=None, columns=2):
+    def visualize(self, U, m, title=None, legend=None, separate_plots=False,
+                  block=None, filename=None, columns=2):
         """Visualize the provided data.
 
         Parameters
@@ -143,10 +143,9 @@ class OnedVisualizer(BasicObject):
             raise NotImplementedError
 
         if self.backend == 'jupyter':
-            from pymor.discretizers.builtin.gui.jupyter import get_visualizer
-            return get_visualizer()(self.grid, U, bounding_box=self.grid.domain, codim=self.codim, title=title,
-                                    legend=legend, separate_colorbars=separate_colorbars,
-                                    rescale_colorbars=rescale_colorbars, columns=columns)
+            from pymor.discretizers.builtin.gui.jupyter.matplotlib import visualize_matplotlib_1d
+            return visualize_matplotlib_1d(self.grid, U, codim=self.codim, title=title, legend=legend,
+                                           separate_plots=separate_plots, columns=columns)
         else:
             block = self.block if block is None else block
             from pymor.discretizers.builtin.gui.qt import visualize_matplotlib_1d