added support for returning matplot instead of showing on grid.visual…

…ize and grid.dB_map_2D

fdtd/visualization.py

@@ -42,6 +42,8 @@ def visualize(
     index=None,  # index for each frame of animation (visualize fn runs in a loop, loop variable is passed as index)
     save=False,  # True to save frames (requires parameters index, folder)
     folder=None,  # folder path to save frames
+    gradio_support=False, # True to return figure for gradio support
+
 ):
     """visualize a projection of the grid and the optical energy inside the grid
 
@@ -62,6 +64,8 @@ def visualize(
         save: save frames in a folder
         folder: path to folder to save frames
     """
+    if gradio_support:
+        plt.style.use("https://raw.githubusercontent.com/dracula/matplotlib/master/dracula.mplstyle")
     if norm not in ("linear", "lin", "log"):
         raise ValueError("Color map normalization should be 'linear' or 'log'.")
     # imports (placed here to circumvent circular imports)
@@ -327,8 +331,11 @@ def visualize(
     if show:
         plt.show()
 
+    if gradio_support:
+        return plt.gcf() # return figure for gradio support
+
 
-def dB_map_2D(block_det=None, choose_axis=2, interpolation="spline16"):
+def dB_map_2D(block_det=None, choose_axis=2, interpolation="spline16", gradio_support=False):
     """
     Displays detector readings from an 'fdtd.BlockDetector' in a decibel map spanning a 2D slice region inside the BlockDetector.
     Compatible with continuous sources (not pulse).
@@ -349,7 +356,8 @@ def dB_map_2D(block_det=None, choose_axis=2, interpolation="spline16"):
         )
 
     # TODO: convert all 2D slices (y-z, x-z plots) into x-y plot data structure
-
+    if gradio_support:
+        plt.style.use("https://raw.githubusercontent.com/dracula/matplotlib/master/dracula.mplstyle")
     plt.ioff()
     plt.close()
     a = []  # array to store wave intensities
@@ -374,7 +382,10 @@ def dB_map_2D(block_det=None, choose_axis=2, interpolation="spline16"):
     plt.imshow(a, cmap="inferno", interpolation=interpolation)
     cbar = plt.colorbar()
     cbar.ax.set_ylabel("dB scale", rotation=270)
-    plt.show()
+    if gradio_support:
+        return plt.gcf()
+    else:
+        plt.show()
 
 
 def plot_detection(detector_dict=None, specific_plot=None):