interact2d cmap options

.github/workflows/python-test.yml

@@ -9,7 +9,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, windows-latest]
-        python-version: [3.6, 3.7, 3.8, 3.9]
+        python-version: [3.7, 3.8, 3.9]
 
     steps:
     - uses: actions/checkout@v2

CHANGELOG.md

@@ -5,9 +5,13 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/).
 
 ## [Unreleased]
 
-## Added
+### Added
+- `artists.interact2D` supports `cmap` kwarg.
 - iPython integration: autocomplete includes axis, variable, and channel names
 
+### Changed
+- `artists.interact2D` uses matplotlib norm objects to control colormap scaling
+
 ### Fixed
 - `kit.fft`: fixed bug where Fourier coefficients were off by a scalar factor.
 

WrightTools/artists/_interact.py

@@ -75,31 +75,42 @@ def get_channel(data, channel):
     return channel
 
 
-def get_colormap(channel):
-    if channel.signed:
-        cmap = "signed"
-    else:
-        cmap = "default"
+def get_colormap(signed):
+    cmap = "signed" if signed else "default"
     cmap = colormaps[cmap]
     cmap.set_bad([0.75] * 3, 1.0)
     cmap.set_under([0.75] * 3, 1.0)
     return cmap
 
 
-def get_clim(channel, current_state):
-    if current_state.local:
-        arr = current_state.dat[channel.natural_name][:]
-        if channel.signed:
-            mag = np.nanmax(np.abs(arr))
-            clim = [-mag, mag]
+def get_norm(channel, current_state) -> object:
+    if channel.signed:
+        if not current_state.local:
+            norm = mpl.colors.CenteredNorm(vcenter=channel.null, halfrange=channel.mag())
         else:
-            clim = [0, np.nanmax(arr)]
+            norm = mpl.colors.CenteredNorm(vcenter=channel.null)
+            norm.autoscale_None(current_state.dat[channel.natural_name][:])
+        if norm.halfrange == 0:
+            norm.halfrange = 1
     else:
-        if channel.signed:
-            clim = [-channel.mag(), channel.mag()]
+        if not current_state.local:
+            norm = mpl.colors.Normalize(vmin=channel.null, vmax=channel.max())
         else:
-            clim = [0, channel.max()]
-    return clim
+            norm = mpl.colors.Normalize(vmin=channel.null)
+            norm.autoscale_None(current_state.dat[channel.natural_name][:])
+        if norm.vmax == norm.vmin:
+            norm.vmax += 1
+    return norm
+
+
+def norm_to_ticks(norm) -> np.array:
+    if type(norm) == mpl.colors.CenteredNorm:
+        vmin = norm.vcenter - norm.halfrange
+        vmax = norm.vcenter + norm.halfrange
+    else:  # mpl.colors.Normalize
+        vmin = norm.vmin
+        vmax = norm.vmax
+    return np.linspace(vmin, vmax, 11)
 
 
 def gen_ticklabels(points, signed=None):
@@ -133,7 +144,14 @@ def norm(arr, signed, ignore_zero=True):
 
 
 def interact2D(
-    data: wt_data.Data, xaxis=0, yaxis=1, channel=0, local=False, use_imshow=False, verbose=True
+    data: wt_data.Data,
+    xaxis=0,
+    yaxis=1,
+    channel=0,
+    cmap=None,
+    local=False,
+    use_imshow=False,
+    verbose=True,
 ):
     """Interactive 2D plot of the dataset.
     Side plots show x and y projections of the slice (shaded gray).
@@ -151,10 +169,12 @@ def interact2D(
         Expression or index of y axis. Default is 1.
     channel : string, integer, or data.Channel object (optional)
         Name or index of channel to plot. Default is 0.
+    cmap : string or cm object (optional)
+        Name of colormap, or explicit colormap object.  Defaults to channel default.
     local : boolean (optional)
         Toggle plotting locally. Default is False.
     use_imshow : boolean (optional)
-        If true, matplotlib imshow is used to render the 2D slice.
+        If True, matplotlib imshow is used to render the 2D slice.
         Can give better performance, but is only accurate for
         uniform grids.  Default is False.
     verbose : boolean (optional)
@@ -163,10 +183,10 @@ def interact2D(
     # avoid changing passed data object
     data = data.copy()
     # unpack
-    data.prune(keep_channels=channel)
+    data.prune(keep_channels=channel, verbose=False)
     channel = get_channel(data, channel)
     xaxis, yaxis = get_axes(data, [xaxis, yaxis])
-    cmap = get_colormap(channel)
+    cmap = cmap if cmap is not None else get_colormap(channel.signed)
     current_state = SimpleNamespace()
     # create figure
     nsliders = data.ndim - 2
@@ -229,7 +249,7 @@ def interact2D(
                 *slider.ax.get_ylim(),
                 colors="k",
                 linestyle=":",
-                alpha=0.5
+                alpha=0.5,
             )
             slider.valtext.set_text(gen_ticklabels(axis.points)[0])
     current_state.focus = Focus([ax0] + [slider.ax for slider in sliders.values()])
@@ -240,25 +260,21 @@ def interact2D(
         at=_at_dict(data, sliders, xaxis, yaxis),
         verbose=False,
     )[0]
-    clim = get_clim(channel, current_state)
-    ticklabels = gen_ticklabels(np.linspace(*clim, 11), channel.signed)
-    if clim[0] == clim[1]:
-        clim = [-1 if channel.signed else 0, 1]
+    norm = get_norm(channel, current_state)
 
     gen_mesh = ax0.pcolormesh if not use_imshow else ax0.imshow
     obj2D = gen_mesh(
         current_state.dat,
         cmap=cmap,
-        vmin=clim[0],
-        vmax=clim[1],
+        norm=norm,
         ylabel=yaxis.label,
         xlabel=xaxis.label,
     )
     ax0.grid(b=True)
     # colorbar
-    colorbar = plot_colorbar(
-        cax, cmap=cmap, label=channel.natural_name, ticks=np.linspace(clim[0], clim[1], 11)
-    )
+    ticks = norm_to_ticks(norm)
+    ticklabels = gen_ticklabels(ticks, channel.signed)
+    colorbar = plot_colorbar(cax, cmap=cmap, label=channel.natural_name, ticks=ticks)
     colorbar.set_ticklabels(ticklabels)
     fig.canvas.draw_idle()
 
@@ -384,12 +400,10 @@ def update_local(index):
         if verbose:
             print("normalization:", index)
         current_state.local = radio.value_selected[1:] == "local"
-        clim = get_clim(channel, current_state)
-        ticklabels = gen_ticklabels(np.linspace(*clim, 11), channel.signed)
+        norm = get_norm(channel, current_state)
+        obj2D.set_norm(norm)
+        ticklabels = gen_ticklabels(np.linspace(norm.vmin, norm.vmax, 11), channel.signed)
         colorbar.set_ticklabels(ticklabels)
-        if clim[0] == clim[1]:
-            clim = [-1 if channel.signed else 0, 1]
-        obj2D.set_clim(*clim)
         fig.canvas.draw_idle()
 
     def update_slider(info, use_imshow=use_imshow):
@@ -416,11 +430,11 @@ def update_slider(info, use_imshow=use_imshow):
             obj2D.set_data(current_state.dat[channel.natural_name][:].transpose(transpose))
         else:
             obj2D.set_array(current_state.dat[channel.natural_name][:].ravel())
-        clim = get_clim(channel, current_state)
-        ticklabels = gen_ticklabels(np.linspace(*clim, 11), channel.signed)
-        if clim[0] == clim[1]:
-            clim = [-1 if channel.signed else 0, 1]
-        obj2D.set_clim(*clim)
+        norm = get_norm(channel, current_state)
+        obj2D.set_norm(norm)
+
+        ticks = norm_to_ticks(norm)
+        ticklabels = gen_ticklabels(ticks, channel.signed)
         colorbar.set_ticklabels(ticklabels)
         sp_x.collections.clear()
         sp_y.collections.clear()

setup.py

@@ -34,11 +34,11 @@ def read(fname):
     name="WrightTools",
     packages=find_packages(exclude=("tests", "tests.*")),
     package_data=extra_files,
-    python_requires=">=3.6",
+    python_requires=">=3.7",
     install_requires=[
         "h5py",
         "imageio",
-        "matplotlib>=3.3.0",
+        "matplotlib>=3.4.0",
         "numexpr",
         "numpy>=1.15.0",
         "pint",
@@ -74,8 +74,9 @@ def read(fname):
         "Framework :: Matplotlib",
         "Natural Language :: English",
         "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.6",
         "Programming Language :: Python :: 3.7",
+        "Programming Language :: Python :: 3.8",
+        "Programming Language :: Python :: 3.9",
         "Topic :: Scientific/Engineering",
     ],
 )