Hodograph Layer Coloring #482

mwilson14 · 2017-07-06T20:21:11Z

Uses the get_layer function to create a helper to plot different layers of a hodograph in different colors.

jrleeman

I'm curious how the UI of this compared to a segmented color map looks. Maybe this should be here, but us a segmented color map under the hood? @dopplershift likely has an opinion on this.

jrleeman · 2017-07-06T21:43:56Z

metpy/plots/tests/test_skewt.py

+@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)
+def test_hodograph_plot_layer():
+    """Test hodograph colored layers."""
+    u = np.arange(5., 65., 5) * units('knot')


Decimals after values here and in the test data shouldn't be necessary as we don't need to force them to be floats.

Fixed this.

jrleeman · 2017-07-06T21:44:14Z

metpy/plots/tests/test_skewt.py

@@ -175,3 +175,23 @@ def test_skewt_barb_color():
    skew.plot_barbs(p, u, u, c=u)

    return fig
+
+
+@pytest.mark.mpl_image_compare(tolerance=0, remove_text=True)


Will likely have to bump depending on Appveyor/Travis.

jrleeman · 2017-07-06T21:45:05Z

metpy/plots/skewt.py

+        """
+        line_args = self._form_line_args(kwargs)
+        u, v = delete_masked_points(u, v)
+        for i in range(bounds.shape[0] - 1):


I think in range(len(bounds) -1) should work.

Also fixed this one.

jrleeman

I think we can simplify and make plot_colormapped polymorphic here. Even though the snippet is only a couple of lines, this is a common enough use-case that it's boiler plate we don't want the user to need to write.

jrleeman · 2017-07-15T18:43:37Z

metpy/plots/skewt.py

+
+        """
+        line_args = self._form_line_args(kwargs)
+        u, v = delete_masked_points(u, v)


We can condense this and ditch the loop :) I think we should make plot_colormapped polymorphic. You can accept either a color map for continuous coloring or accept a bounds and colors kwarg to do a segmented coloring. Here's the snippet:

import matplotlib as mpl # Get data, etc. cmap = mpl.colors.ListedColormap(['r', 'g', 'b']) norm = mpl.colors.BoundaryNorm([0, 1, 3, 5], cmap.N) h = Hodograph(component_range=80.) h.plot_colormapped(u, v, hgt, cmap=cmap) h.add_grid(increment=20

Is this actually using height values for the bounds here? I just tried this and it plots the same segments no matter what I set as the norm (or even if I comment out the norm). It appears to just be breaking the hodograph into three arbitrary segments without regard to the heights I give it, but I'm guessing I might just be missing something in my code.

jrleeman

Are we keeping both functions? Not sure why we need plot_layers if plot_colormapped has the same functionality.

jrleeman · 2017-07-31T14:55:15Z

metpy/plots/skewt.py

@@ -770,10 +771,70 @@ def plot(self, u, v, **kwargs):
        u, v = delete_masked_points(u, v)
        return self.ax.plot(u, v, **line_args)

-    def plot_colormapped(self, u, v, c, **kwargs):
+    def plot_layers(self, u, v, hgt, bounds, colors, **kwargs):


Should make naming consistent with get_layer (i.e. heights)

jrleeman · 2017-07-31T14:55:38Z

metpy/plots/skewt.py

+
+        Parameters
+        ----------
+        u : array_like


All of these are pint.Quantity

jrleeman · 2017-07-31T14:58:50Z

metpy/plots/skewt.py

+        bounds = np.asarray(bounds + hgt[0]) * bounds.units
+        interp_vert = interp(bounds, hgt, hgt, u, v)
+        inds = np.searchsorted(hgt.magnitude, bounds.magnitude)
+        u = np.insert(u.magnitude, inds, interp_vert[1].magnitude)


Wouldn't it be more efficient to insert the bounds into heights and then interp? That way you'd get all the points plus the new ones for u and v from interp.

jrleeman · 2017-07-31T15:00:04Z

metpy/plots/skewt.py

@@ -770,10 +771,70 @@ def plot(self, u, v, **kwargs):
        u, v = delete_masked_points(u, v)
        return self.ax.plot(u, v, **line_args)

-    def plot_colormapped(self, u, v, c, **kwargs):
+    def plot_layers(self, u, v, hgt, bounds, colors, **kwargs):


Is this function sticking around after the functionality was implanted in plot_colormapped?

They've got slightly different functionalities. Plot_layers is designed specifically for layers in height coordinates and will interpolate to find the exact bounds, while the addition to plot_colormapped will color the hodograph by any arbitrary third variable without interpolating to the bounds. This difference is necessary because searchsorted doesn't work well with data that aren't increasing or decreasing monotonically, so adding the interpolated points when coloring the hodograph by temperature or wind speed doesn't work like it does with height.

jrleeman · 2017-08-02T20:02:49Z

@dopplershift - can you redeliver to CLA Hub and LGTM? Looks like they got stuck.

dopplershift

I like the approach. Just some things to improve in the docs mainly.

dopplershift · 2017-08-02T20:09:05Z

metpy/plots/skewt.py

+        Plots the wind data on the hodograph, but with a colormapped line. Takes a third
+        variable besides the winds and either a colormap to color it with or a series of
+        bounds and colors to create a custom colormap out of. The bounds must always be in
+        increasing order or matplotlib is not happy. For using custom bounds with height data,


I'd remove "or matplotlib is not happy"

dopplershift · 2017-08-02T20:09:54Z

metpy/plots/skewt.py

        r"""Plot u, v data, with line colored based on a third set of data.

-        Plots the wind data on the hodograph, but with a colormapped line.
+        Plots the wind data on the hodograph, but with a colormapped line. Takes a third
+        variable besides the winds and either a colormap to color it with or a series of


"...colormap and norm to control colormapping..."

dopplershift · 2017-08-02T20:11:25Z

metpy/plots/skewt.py

@@ -787,6 +793,10 @@ def plot_colormapped(self, u, v, c, **kwargs):
            v-component of wind
        c : array_like
            data to use for colormapping
+        bounds: array-like
+            Array of bounds for c to use in coloring the hodograph.
+        colors:


The type of colors is "list". Should also note that it's optional.

dopplershift · 2017-08-02T20:11:31Z

metpy/plots/skewt.py

@@ -787,6 +793,10 @@ def plot_colormapped(self, u, v, c, **kwargs):
            v-component of wind
        c : array_like
            data to use for colormapping
+        bounds: array-like


Bounds is optional.

dopplershift · 2017-08-02T20:36:18Z

metpy/plots/skewt.py

@@ -7,6 +7,7 @@
 `SkewT`, as well as a class for making a `Hodograph`.
 """

+import matplotlib as mpl


How about import matplotlib.colors as mcolors? That would be more standard with how I usually do it.

dopplershift

Minor doc style nits.

dopplershift · 2017-08-03T17:27:25Z

metpy/plots/skewt.py

@@ -787,6 +794,10 @@ def plot_colormapped(self, u, v, c, **kwargs):
            v-component of wind
        c : array_like
            data to use for colormapping
+        bounds: (optional) array-like


"array-like, optional"

dopplershift · 2017-08-03T17:27:30Z

metpy/plots/skewt.py

@@ -787,6 +794,10 @@ def plot_colormapped(self, u, v, c, **kwargs):
            v-component of wind
        c : array_like
            data to use for colormapping
+        bounds: (optional) array-like
+            Array of bounds for c to use in coloring the hodograph.
+        colors: (optional) list


dopplershift · 2017-08-03T20:08:44Z

@jrleeman good? (Travis failure is from egghead)

jrleeman

Looks good now!

jrleeman reviewed Jul 6, 2017

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dopplershift added Area: Plots Pertains to producing plots Type: Enhancement Enhancement to existing functionality labels Jul 7, 2017

dopplershift added this to the Summer 2017 milestone Jul 7, 2017

jrleeman suggested changes Jul 15, 2017

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mwilson14 force-pushed the hodograph_coloring branch 3 times, most recently from fc39f71 to bcdbed2 Compare July 24, 2017 20:52

mwilson14 requested a review from dopplershift as a code owner July 24, 2017 20:52

mwilson14 force-pushed the hodograph_coloring branch from bcdbed2 to 9a0887c Compare July 26, 2017 16:53

jrleeman suggested changes Jul 31, 2017

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mwilson14 force-pushed the hodograph_coloring branch from 9a0887c to d3bf290 Compare August 1, 2017 22:04

Added tests for coloring the hodograph by different variables

cb95bfb

mwilson14 force-pushed the hodograph_coloring branch from d3bf290 to 9f4452a Compare August 2, 2017 15:24

dopplershift requested changes Aug 2, 2017

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mwilson14 force-pushed the hodograph_coloring branch 2 times, most recently from 0470f75 to da1808e Compare August 2, 2017 21:04

dopplershift requested changes Aug 3, 2017

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Added code to plot layers on the hodograph colored by a third variable

8307dc4

mwilson14 force-pushed the hodograph_coloring branch from da1808e to 8307dc4 Compare August 3, 2017 18:36

dopplershift approved these changes Aug 3, 2017

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jrleeman approved these changes Aug 3, 2017

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dopplershift merged commit c193909 into Unidata:master Aug 3, 2017

zbruick mentioned this pull request Sep 3, 2019

Make it easy to color Hodograph by height, windspeed thresholds, or other variables #406

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Hodograph Layer Coloring #482

Hodograph Layer Coloring #482

mwilson14 commented Jul 6, 2017

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Hodograph Layer Coloring #482

Hodograph Layer Coloring #482

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jrleeman commented Aug 2, 2017

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dopplershift commented Aug 3, 2017

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