docs: def experimental_designs(df, filepath=None):
      """
      For each experimental design it plot all the corresponding
      experimental conditions in a different plot
  
      Parameters
      ----------
      df: `pandas.DataFrame`_
          DataFrame with columns `id` and starting with `TR:`
  
      filepath: str
          Absolute path to a folder where to write the plot
  
  
      Returns
      -------
      list
          Generated plots
  
  
      .. _pandas.DataFrame: http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe
      """
  
      axes = []
      bw = matplotlib.colors.ListedColormap(['white', 'black'])
      cols = df.columns
      for i, dd in df.groupby("id"):
          cues = dd.drop([c for c in cols if not c.startswith("TR:")] + ["id"], axis=1).reset_index(drop=True)
          cues.columns = [c[3:] for c in cues.columns]
  
          plt.figure(figsize=(max((len(cues.columns)-1) * .5, 4), max(len(cues)*0.6, 2.5)))
  
          ax = sns.heatmap(cues, linewidths=.5, cbar=False, cmap=bw, linecolor='gray')
          _ = [t.set_color('r') if t.get_text().endswith('i') else t.set_color('g') for t in ax.xaxis.get_ticklabels()]
  
          ax.set_xlabel("Stimuli (green) and Inhibitors (red)")
          ax.set_ylabel("Experimental condition")
  
          plt.tight_layout()
          axes.append(ax)
  
          if filepath:
              plt.savefig(os.path.join(filepath, 'design-%s.pdf' % i))
  
      return axes