Add gridded data plotting capability (#134)

* Add gridded data plotting capability

* pycodestyle

* missed import

src/emcpy/plots/create_plots.py

@@ -260,6 +260,7 @@ def create_figure(self):
             'histogram': self._histogram,
             'density': self._density,
             'line_plot': self._lineplot,
+            'gridded_plot': self._gridded,
             'vertical_line': self._verticalline,
             'horizontal_line': self._horizontalline,
             'horizontal_span': self._horizontalspan,
@@ -538,6 +539,20 @@ def _scatter(self, plotobj, ax):
                     plotobj.linear_regression['color'] = inputs['color']
                 ax.plot(plotobj.x, y_pred, label=label, **plotobj.linear_regression)
 
+    def _gridded(self, plotobj, ax):
+        """
+        Uses Gridded object to plot on axis.
+        """
+        skipvars = ['plottype', 'plot_ax', 'x', 'y', 'z',
+                    'colorbar']
+        inputs = self._get_inputs_dict(skipvars, plotobj)
+
+        cs = ax.pcolormesh(plotobj.x, plotobj.y,
+                           plotobj.z, **inputs)
+
+        if plotobj.colorbar:
+            self.cs = cs
+
     def _skewt(self, plotobj, ax):
         """
         Creates a skewt-logp profile plot on axis.

src/emcpy/plots/plots.py

@@ -148,6 +148,33 @@ def __init__(self, x, y):
         self.label = None
 
 
+class GriddedPlot:
+
+    def __init__(self, x, y, z):
+        """
+        Constructor for GriddedPlot.
+        Args:
+            x : (array type)
+            y : (array type)
+            z : (array type)
+        """
+        super().__init__()
+        self.plottype = 'gridded_plot'
+
+        self.x = x
+        self.y = y
+        self.z = z
+
+        self.cmap = 'viridis'
+        self.norm = None
+        self.vmin = None
+        self.vmax = None
+        self.edgecolors = None
+        self.shading = 'auto'
+        self.alpha = None
+        self.colorbar = True
+
+
 class VerticalLine:
 
     def __init__(self, x):

src/tests/test_plots.py

@@ -1,9 +1,10 @@
 import numpy as np
+from scipy.ndimage.filters import gaussian_filter
 import matplotlib.pyplot as plt
 
 from emcpy.plots.plots import LinePlot, VerticalLine,\
     Histogram, Density, Scatter, HorizontalLine, BarPlot, \
-    HorizontalBar, HorizontalSpan, SkewT
+    GriddedPlot, HorizontalBar, HorizontalSpan, SkewT
 from emcpy.plots.create_plots import CreatePlot, CreateFigure
 
 
@@ -248,6 +249,26 @@ def test_bar_plot():
     fig.save_figure('test_bar_plot.png')
 
 
+def test_gridded_plot():
+    # Create gridded plot
+
+    x, y, z = _getGriddedData()
+
+    gp = GriddedPlot(x, y, z)
+    gp.cmap = 'plasma'
+
+    plot1 = CreatePlot()
+    plot1.plot_layers = [gp]
+    plot1.add_xlabel(xlabel='X Axis Label')
+    plot1.add_ylabel(ylabel='Y Axis Label')
+    plot1.add_title('Test Gridded Plot')
+
+    fig = CreateFigure()
+    fig.plot_list = [plot1]
+    fig.create_figure()
+    fig.save_figure('test_gridded_plot.png')
+
+
 def test_horizontal_bar_plot():
     # Create horizontal bar plot
 
@@ -522,6 +543,17 @@ def _getBarData():
     return x_pos, heights, variance
 
 
+def _getGriddedData():
+    # generate test data for gridded data
+
+    x = np.linspace(0, 1, 51)
+    y = np.linspace(0, 1, 51)
+    r = np.random.RandomState(25)
+    z = gaussian_filter(r.random_sample([50, 50]), sigma=5, mode='wrap')
+
+    return x, y, z
+
+
 def _getSkewTData():
     # use data for skew-t log-p plot
     from io import StringIO
@@ -616,6 +648,7 @@ def main():
     test_histogram_plot()
     test_scatter_plot()
     test_bar_plot()
+    test_gridded_plot()
     test_horizontal_bar_plot()
     test_multi_subplot()
     test_HorizontalSpan()