feat: add inversion_region to plot convergence

src/invert4geom/plotting.py

@@ -193,6 +193,7 @@ def plot_convergence(
     results: pd.DataFrame,
     iter_times: list[float] | None = None,
     logy: bool = False,
+    inversion_region: tuple[float, float, float, float] | None = None,
     figsize: tuple[float, float] = (5, 3.5),
 ) -> None:
     """
@@ -206,6 +207,8 @@ def plot_convergence(
         list of iteration execution times, by default None
     logy : bool, optional
         choose whether to plot y axis in log scale, by default False
+    inversion_region : tuple[float, float, float, float] | None, optional
+        inside region of inversion, by default None
     figsize : tuple[float, float], optional
         width and height of figure, by default (5, 3.5)
     """
@@ -223,23 +226,32 @@ def plot_convergence(
     # get misfit data at end of each iteration
     cols = [s for s in results.columns.to_list() if "_final_misfit" in s]
     iters = len(cols)
-    final_misfits = [utils.rmse(results[i]) for i in cols]
+    if inversion_region is not None:
+        misfits = [utils.rmse(results[results.inside][i]) for i in cols]
+        starting_misfit = utils.rmse(results[results.inside]["iter_1_initial_misfit"])
+    else:
+        misfits = [utils.rmse(results[i]) for i in cols]
+        starting_misfit = utils.rmse(results["iter_1_initial_misfit"])
+    # add starting misfit to the beginning of the list
+    misfits.insert(0, starting_misfit)
 
     _fig, ax1 = plt.subplots(figsize=figsize)
     plt.title("Inversion convergence")
-    ax1.plot(range(iters), final_misfits, "b-")
+    ax1.plot(range(iters + 1), misfits, "b-")
     ax1.set_xlabel("Iteration")
     if logy:
         ax1.set_yscale("log")
     ax1.set_ylabel("RMS (mGal)", color="b")
     ax1.tick_params(axis="y", colors="b", which="both")
 
     if iter_times is not None:
+        iter_times.insert(0, 0)
         ax2 = ax1.twinx()
-        ax2.plot(range(iters), np.cumsum(iter_times), "g-")
+        ax2.plot(range(iters + 1), np.cumsum(iter_times), "g-")
         ax2.set_ylabel("Cumulative time (s)", color="g")
         ax2.tick_params(axis="y", colors="g")
         ax2.grid(False)
+
     plt.tight_layout()