code: def plot_color_gradients(category, cmap_list):
      # Create figure and adjust figure height to number of colormaps
      nrows = len(cmap_list)
      figh = 0.35 + 0.15 + (nrows + (nrows - 1) * 0.1) * 0.22
      fig, axs = plt.subplots(nrows=nrows + 1, figsize=(6.4, figh))
      fig.subplots_adjust(
          top=1 - 0.35 / figh, bottom=0.15 / figh, left=0.2, right=0.99
      )
      axs[0].set_title(f"{category} colormaps", fontsize=14)
  
      for ax, name in zip(axs, cmap_list):
          ax.imshow(gradient, aspect="auto", cmap=mpl.colormaps[name])
          ax.text(
              -0.01,
              0.5,
              name,
              va="center",
              ha="right",
              fontsize=10,
              transform=ax.transAxes,
          )
  
      # Turn off *all* ticks & spines, not just the ones with colormaps.
      for ax in axs:
          ax.set_axis_off()
  
      # Save colormap list for later.
      cmaps[category] = cmap_list
  
imports: from colorspacious import cspace_converter
  import matplotlib.pyplot
  import numpy
  import matplotlib
label_desc: Use image node_id 1 for calling a global function with example usage: plot_color_gradients(category, cmap_list) without return types