icon_merit_global: removed commented code

runs/icon_merit_global.py

@@ -120,15 +120,10 @@ def autoreload():
 
     dplot = diagnostics.diag_plotter(params, nhi, nhj)
 
-    # simplex_lon = triangles[tri_idx, :, 0]
-    # simplex_lat = triangles[tri_idx, :, 1]
 
     tri.tri_lon_verts = triangles[:, :, 0]
     tri.tri_lat_verts = triangles[:, :, 1]
 
-    # utils.get_lat_lon_segments(
-    #     simplex_lat, simplex_lon, cell, topo, rect=params.rect
-    # )
 
     simplex_lat = tri.tri_lat_verts[tri_idx]
     simplex_lon = tri.tri_lon_verts[tri_idx]
@@ -139,8 +134,6 @@ def autoreload():
     else:
         is_land = 1
 
-    # topo_orig = np.copy(cell.topo)
-
     if params.dfft_first_guess:
         # do tapering
         if params.taper_fa:
@@ -183,7 +176,7 @@ def autoreload():
 
     cell, ampls_sa, uw_sa, dat_2D_sa = sols
     v_extent = [dat_2D_sa.min(), dat_2D_sa.max()]
-    
+
     if params.dfft_first_guess:
         dplot.show(
         tri_idx, sols, kls=kls_fa, v_extent=v_extent, dfft_plot=True,
@@ -193,109 +186,3 @@ def autoreload():
         dplot.show(tri_idx, sols, v_extent=v_extent, output_fig=False)
 
 
-
-
-
-    # first_guess = interface.get_pmf(nhi, nhj, params.U, params.V)
-    # fobj_tri = fourier.f_trans(nhi, nhj)
-
-    # #######################################################
-    # # do fourier...
-
-    # if not params.dfft_first_guess:
-    #     freqs, uw_pmf_freqs, dat_2D_fg0 = first_guess.sappx(cell, params.lmbda_fa)
-
-    # #######################################################
-    # # do fourier using DFFT
-
-    # if params.dfft_first_guess:
-    #     ampls, uw_pmf_freqs, dat_2D_fg0, kls = first_guess.dfft(cell)
-    #     freqs = np.copy(ampls)
-
-    # print("uw_pmf_freqs_sum:", uw_pmf_freqs.sum())
-
-    # fq_cpy = np.copy(freqs)
-    # fq_cpy[
-    #     np.isnan(fq_cpy)
-    # ] = 0.0  # necessary. Otherwise, popping with fq_cpy.max() gives the np.nan entries first.
-
-    # indices = []
-    # max_ampls = []
-
-    # for ii in range(params.n_modes):
-    #     max_idx = np.unravel_index(fq_cpy.argmax(), fq_cpy.shape)
-    #     indices.append(max_idx)
-    #     max_ampls.append(fq_cpy[max_idx])
-    #     max_val = fq_cpy[max_idx]
-    #     fq_cpy[max_idx] = 0.0
-
-    # utils.get_lat_lon_segments(
-    #     simplex_lat, simplex_lon, cell, topo, rect=False
-    # )
-
-    # k_idxs = [pair[1] for pair in indices]
-    # l_idxs = [pair[0] for pair in indices]
-
-    # second_guess = interface.get_pmf(nhi, nhj, params.U, params.V)
-
-    # if params.dfft_first_guess:
-    #     second_guess.fobj.set_kls(
-    #         k_idxs, l_idxs, recompute_nhij=True, components="real"
-    #     )
-    # else:
-    #     second_guess.fobj.set_kls(k_idxs, l_idxs, recompute_nhij=False)
-
-    # freqs, uw, dat_2D_sg0 = second_guess.sappx(cell, lmbda=params.lmbda_sa, updt_analysis=True)
-
-    # cell.topo = topo_orig
-
-    # writer.output(c_idx, clat_rad[tri_idx], clon_rad[tri_idx], is_land, cell.analysis)
-
-    # cell.uw = uw
-
-    # if params.plot:
-    #     fs = (15, 9.0)
-    #     v_extent = [dat_2D_sg0.min(), dat_2D_sg0.max()]
-
-    #     fig, axs = plt.subplots(2, 2, figsize=fs)
-
-    #     fig_obj = plotter.fig_obj(
-    #         fig, second_guess.fobj.nhar_i, second_guess.fobj.nhar_j
-    #     )
-    #     axs[0, 0] = fig_obj.phys_panel(
-    #         axs[0, 0],
-    #         dat_2D_sg0,
-    #         title="T%i: Reconstruction" % tri_idx,
-    #         xlabel="longitude [km]",
-    #         ylabel="latitude [km]",
-    #         extent=[cell.lon.min(), cell.lon.max(), cell.lat.min(), cell.lat.max()],
-    #         v_extent=v_extent,
-    #     )
-
-    #     axs[0, 1] = fig_obj.phys_panel(
-    #         axs[0, 1],
-    #         cell.topo * cell.mask,
-    #         title="T%i: Reconstruction" % tri_idx,
-    #         xlabel="longitude [km]",
-    #         ylabel="latitude [km]",
-    #         extent=[cell.lon.min(), cell.lon.max(), cell.lat.min(), cell.lat.max()],
-    #         v_extent=v_extent,
-    #     )
-
-    #     if params.dfft_first_guess:
-    #         axs[1, 0] = fig_obj.fft_freq_panel(
-    #             axs[1, 0], freqs, kls[0], kls[1], typ="real"
-    #         )
-    #         axs[1, 1] = fig_obj.fft_freq_panel(
-    #             axs[1, 1], uw, kls[0], kls[1], title="PMF spectrum", typ="real"
-    #         )
-    #     else:
-    #         axs[1, 0] = fig_obj.freq_panel(axs[1, 0], freqs)
-    #         axs[1, 1] = fig_obj.freq_panel(axs[1, 1], uw, title="PMF spectrum")
-
-    #     plt.tight_layout()
-    #     plt.savefig("%sT%i.pdf" % (params.path_output, tri_idx))
-    #     plt.show()
-
-
-# %%