updated plot tests, fixed and visually validated all, added for hexbins

darianyang · Nov 10, 2023 · fae2616 · fae2616
1 parent 3975e4f
commit fae2616
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Showing 19 changed files with 41 additions and 39 deletions.
diff --git a/wedap/h5_plot.py b/wedap/h5_plot.py
@@ -161,7 +161,7 @@ def __init__(self, X=None, Y=None, Z=None, plot_mode="hist", cmap=None, smoothin
             elif self.p_units == "raw_norm":
                 self.cbar_label = "Normalized Counts"
         # if using 3 datasets, put blank name as default cbar
-        if self.plot_mode == "scatter3d":
+        if self.plot_mode == "scatter3d" or self.plot_mode == "hexbin3d":
             self.cbar_label = ""
         # overwrite and apply cbar_label attr if available/specified
         if cbar_label:

diff --git a/wedap/tests/data/plot_average_contour_dihedral_2_pcoord.npy b/wedap/tests/data/plot_average_contour_dihedral_2_pcoord.npy
diff --git a/wedap/tests/data/plot_average_contour_pcoord_dihedral_2.npy b/wedap/tests/data/plot_average_contour_pcoord_dihedral_2.npy
diff --git a/wedap/tests/data/plot_average_hexbin3d_dihedral_2_dihedral_3_pcoord.npy b/wedap/tests/data/plot_average_hexbin3d_dihedral_2_dihedral_3_pcoord.npy
diff --git a/wedap/tests/data/plot_average_hexbin3d_dihedral_2_pcoord_dihedral_3.npy b/wedap/tests/data/plot_average_hexbin3d_dihedral_2_pcoord_dihedral_3.npy
diff --git a/wedap/tests/data/plot_average_hexbin3d_pcoord_dihedral_2_dihedral_3.npy b/wedap/tests/data/plot_average_hexbin3d_pcoord_dihedral_2_dihedral_3.npy
diff --git a/wedap/tests/data/plot_average_line_dihedral_2.npy b/wedap/tests/data/plot_average_line_dihedral_2.npy
diff --git a/wedap/tests/data/plot_average_line_pcoord.npy b/wedap/tests/data/plot_average_line_pcoord.npy
diff --git a/wedap/tests/data/plot_evolution_hist_dihedral_2.npy b/wedap/tests/data/plot_evolution_hist_dihedral_2.npy
diff --git a/wedap/tests/data/plot_evolution_hist_pcoord.npy b/wedap/tests/data/plot_evolution_hist_pcoord.npy
diff --git a/wedap/tests/data/plot_instant_contour_dihedral_2_pcoord.npy b/wedap/tests/data/plot_instant_contour_dihedral_2_pcoord.npy
diff --git a/wedap/tests/data/plot_instant_contour_pcoord_dihedral_2.npy b/wedap/tests/data/plot_instant_contour_pcoord_dihedral_2.npy
diff --git a/wedap/tests/data/plot_instant_hexbin3d_dihedral_2_dihedral_3_pcoord.npy b/wedap/tests/data/plot_instant_hexbin3d_dihedral_2_dihedral_3_pcoord.npy
diff --git a/wedap/tests/data/plot_instant_hexbin3d_dihedral_2_pcoord_dihedral_3.npy b/wedap/tests/data/plot_instant_hexbin3d_dihedral_2_pcoord_dihedral_3.npy
diff --git a/wedap/tests/data/plot_instant_hexbin3d_pcoord_dihedral_2_dihedral_3.npy b/wedap/tests/data/plot_instant_hexbin3d_pcoord_dihedral_2_dihedral_3.npy
diff --git a/wedap/tests/data/plot_instant_line_dihedral_2.npy b/wedap/tests/data/plot_instant_line_dihedral_2.npy
diff --git a/wedap/tests/data/plot_instant_line_pcoord.npy b/wedap/tests/data/plot_instant_line_pcoord.npy
diff --git a/wedap/tests/make_h5_plot_test_data.py b/wedap/tests/make_h5_plot_test_data.py
@@ -1,50 +1,32 @@
-import wedap
+#import wedap
+#import matplotlib.pyplot as plt
+#import numpy as np
 
 import matplotlib
 matplotlib.use('agg')
-import matplotlib.pyplot as plt
-import numpy as np
 
 from wedap.tests.test_h5_plot import plot_data_gen
 
-# def plot_data_gen(h5, data_type, plot_mode, Xname, Yname=None, Zname=None, out=None):
-#     """
-#     Make plot and convert to npy binary data file.
-#     """
-#     plot = wedap.H5_Plot(h5=h5, data_type=data_type, plot_mode=plot_mode, 
-#                         Xname=Xname, Yname=Yname, Zname=Zname)
-#     plot.plot()
-#     fig = plot.fig
-
-#     #plt.show()
-#     #import sys; sys.exit(0)
-
-#     # If we haven't already shown or saved the plot, then we need to
-#     # draw the figure first...
-#     # tight since canvas is large
-#     fig.tight_layout(pad=0)
-#     fig.canvas.draw()
-
-#     # Now we can save it to a numpy array.
-#     data = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
-#     data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
-#     # save as np binary file
-#     if out:
-#         np.save(out, data)
-
 h5 = "wedap/data/p53.h5"
 
 # # 1 dataset plots
-# for dt in ["evolution", "average", "instant"]:
+# for dt in ["evolution"]:
+#     for pm in ["hist"]:
+#         for x in ["pcoord", "dihedral_2"]:
+#             plot_data_gen(h5, dt, pm, x, out=f"wedap/tests/data/plot_{dt}_{pm}_{x}.npy")
+            #plot_data_gen(h5, dt, pm, x, show=True)
+# for dt in ["average", "instant"]:
 #     for pm in ["line"]:
 #         for x in ["pcoord", "dihedral_2"]:
-#             plot_data_gen(h5, dt, pm, x, out=f"wedap/tests/data/data/plot_{dt}_{pm}_{x}.npy")
+#             plot_data_gen(h5, dt, pm, x, out=f"wedap/tests/data/plot_{dt}_{pm}_{x}.npy")
+#             #plot_data_gen(h5, dt, pm, x, show=True)
 
 # # 2 dataset plots
 # for dt in ["average", "instant"]:
 #     for pm in ["hist", "contour"]:
 #         for x, y in [["pcoord", "dihedral_2"], ["dihedral_2", "pcoord"]]:
 #             plot_data_gen(h5, dt, pm, x, y, out=f"wedap/tests/data/plot_{dt}_{pm}_{x}_{y}.npy")
+#             #plot_data_gen(h5, dt, pm, x, y, show=True)
 
 # 2 dataset plots with joint plots (TODO)
 # for jp in [True, False]:
@@ -55,8 +37,9 @@
 
 # # 3 dataset plots
 # for dt in ["average", "instant"]:
-#     for pm in ["scatter3d"]:
+#     for pm in ["scatter3d", "hexbin3d"]:
 #         for x, y, z in [["pcoord", "dihedral_2", "dihedral_3"], 
 #                         ["dihedral_2", "pcoord", "dihedral_3"], 
 #                         ["dihedral_2", "dihedral_3", "pcoord"]]:
-#             plot_data_gen(h5, dt, pm, x, y, z, out=f"wedap/tests/data/plot_{dt}_{pm}_{x}_{y}_{z}.npy")
+#             plot_data_gen(h5, dt, pm, x, y, z, out=f"wedap/tests/data/plot_{dt}_{pm}_{x}_{y}_{z}.npy")
+#             #plot_data_gen(h5, dt, pm, x, y, z, show=True)
diff --git a/wedap/tests/test_h5_plot.py b/wedap/tests/test_h5_plot.py
@@ -24,7 +24,7 @@
 #@pytest.mark.skip
 
 def plot_data_gen(h5, data_type, plot_mode, Xname, Yname=None, Zname=None, 
-                  jointplot=False, out=None):
+                  jointplot=False, out=None, show=False):
     """
     Make plot and return or convert to npy binary data file.
     """
@@ -34,6 +34,10 @@ def plot_data_gen(h5, data_type, plot_mode, Xname, Yname=None, Zname=None,
     plot.plot()
     fig = plot.fig
 
+    if show:
+        matplotlib.pyplot.show()
+        return
+
     # draw the figure 
     # tight since canvas is large
     fig.tight_layout(pad=0)
@@ -47,6 +51,8 @@ def plot_data_gen(h5, data_type, plot_mode, Xname, Yname=None, Zname=None,
     if out:
         np.save(out, data)
 
+    matplotlib.pyplot.close()
+
     return data
 
 class Test_H5_Plot():
@@ -55,9 +61,21 @@ class Test_H5_Plot():
     """
     h5 = "wedap/data/p53.h5"
 
-    @pytest.mark.parametrize("data_type", ["evolution", "average", "instant"])
+    @pytest.mark.parametrize("data_type", ["evolution"])
+    @pytest.mark.parametrize("Xname", ["pcoord", "dihedral_2"])
+    def test_1d_evolution_plots(self, data_type, Xname):
+        # make plot data array
+        plotdata = plot_data_gen(self.h5, data_type=data_type, plot_mode="hist", Xname=Xname)
+
+        # compare to previously generated plot data
+        data = np.load(f"wedap/tests/data/plot_{data_type}_hist_{Xname}.npy")
+        #np.testing.assert_allclose(plotdata, data)
+        # check to see if the amount of mismatches is less than 500 (<1% of 1 million items)
+        assert data.size - np.count_nonzero(plotdata==data) < 500
+
+    @pytest.mark.parametrize("data_type", ["average", "instant"])
     @pytest.mark.parametrize("Xname", ["pcoord", "dihedral_2"])
-    def test_1_dataset_plots(self, data_type, Xname):
+    def test_1d_avg_inst_plots(self, data_type, Xname):
         # make plot data array
         plotdata = plot_data_gen(self.h5, data_type=data_type, plot_mode="line", Xname=Xname)
 
@@ -85,17 +103,18 @@ def test_2_dataset_plots(self, data_type, plot_mode, Xname, Yname):#, jointplot)
         assert data.size - np.count_nonzero(plotdata==data) < 500
 
 
+    @pytest.mark.parametrize("plot_mode", ["scatter3d", "hexbin3d"])
     @pytest.mark.parametrize("data_type", ["average", "instant"])
     @pytest.mark.parametrize("Xname, Yname, Zname", [["pcoord", "dihedral_2", "dihedral_3"], 
                                                      ["dihedral_2", "pcoord", "dihedral_3"], 
                                                      ["dihedral_2", "dihedral_3", "pcoord"]])
-    def test_3_dataset_plots(self, data_type, Xname, Yname, Zname):
+    def test_3_dataset_plots(self, data_type, plot_mode, Xname, Yname, Zname):
         # make plot data array
-        plotdata = plot_data_gen(self.h5, data_type=data_type, plot_mode="scatter3d", 
+        plotdata = plot_data_gen(self.h5, data_type=data_type, plot_mode=plot_mode, 
                                  Xname=Xname, Yname=Yname, Zname=Zname)
 
         # compare to previously generated plot data
-        data = np.load(f"wedap/tests/data/plot_{data_type}_scatter3d_{Xname}_{Yname}_{Zname}.npy")
+        data = np.load(f"wedap/tests/data/plot_{data_type}_{plot_mode}_{Xname}_{Yname}_{Zname}.npy")
         #np.testing.assert_allclose(plotdata, data)
         # check to see if the amount of mismatches is less than 500 (<1% of ~1 million items)
         assert data.size - np.count_nonzero(plotdata==data) < 500