update export plots

scripts/run_herg_qc.py

@@ -1082,6 +1082,7 @@ def get_time_constant_of_first_decay(trace, times, protocol_desc, args, output_p
     peak_time = times[indices[peak_index]]
 
     indices = np.argwhere((times >= peak_time) & (times <= tend - 50))
+    print(indices)
 
     def fit_func(x):
         a, b, c = x
@@ -1109,16 +1110,33 @@ def fit_func(x):
 
     res = best_res
 
+    if not res:
+        logging.warning('finding 40mv decay timeconstant failed:' + str(res))
+
     if output_path and res:
-        fig = plt.figure(figsize=args.figsize)
-        ax = fig.subplots()
+        fig = plt.figure(figsize=args.figsize, constrained_layout=True)
+        axs = fig.subplots(2)
+
+        for ax in axs:
+            ax.spines[['top', 'right']].set_visible(False)
+            ax.set_ylabel(r'$I_\text{obs}$ (pA)')
+            ax.set_xlabel(r'$t$ (ms)')
+
+        protocol_ax, fit_ax = axs
+        protocol_ax.set_title('a', fontweight='bold')
+        fit_ax.set_title('b', fontweight='bold')
+        fit_ax.plot(peak_time, tend-50, alpha=.5)
 
-        ax.plot(times[indices], trace[indices], color='grey', alpha=.5)
         a, b, c = res.x
-        ax.plot(times[indices], c + a * np.exp(-(1.0/b) * (times[indices] - peak_time)),
-                color='red', linestyle='--')
+        fit_ax.plot(times[indices], c + a * np.exp(-(1.0/b) * (times[indices] - peak_time)),
+                    color='red', linestyle='--')
+
+        res_string = r'$\tau_{40\text{mV}} = ' f"{b:.1f}" r'\text{ms}$'
+        fit_ax.annotate(res_string, xy=(0.5, 0.05), xycoords='axes fraction')
+
+        protocol_ax.plot(times, trace)
+       # protocol_ax.axvspan(peak_time, tend - 50, alpha=.5, color='grey')
 
-        ax.set_title(f"timescale {b}ms")
         fig.savefig(output_path)
         plt.close(fig)
 

scripts/summarise_herg_export.py

@@ -186,7 +186,8 @@ def do_chronological_plots(df, normalise=False):
             'E_leak_after', 'E_rev', 'pre-drug leak magnitude',
             'post-drug leak magnitude',
             'E_rev_before', 'Cm', 'Rseries',
-            '40mV decay time constant']
+            '40mV decay time constant',
+            '40mV peak current']
 
     # df = df[leak_parameters_df['selected']]
     df = df[df['passed QC']].copy()
@@ -202,20 +203,24 @@ def do_chronological_plots(df, normalise=False):
         # 'E_leak_after':,
         # 'E_leak_before':,
         'pre-drug leak magnitude': 'pA',
-        '40mV_decay_time_constant': 'ms'
+        '40mV decay time constant': 'ms',
+        '40mV peak current': 'pA'
     }
 
     pretty_vars = {
         'pre-drug leak magnitude': r'$\bar{I}_\text{l}$',
-        'pre-drug leak magnitude': r'$\tau_{40\textrm{mV}}$'
+        '40mV decay time constant': r'$\tau_{40\text{mV}}$',
+        '40mV peak current': r'$I_\text{peak}$'
     }
 
+    def label_func(p, s):
+        p = p[1:-1]
+        return r'$' + str(p) + r'^{(' + str(s) + r')}$'
+
     for var in vars:
-        df['x'] = df.protocol.astype(str) + '_' + df.sweep.astype(str)
-        sns.scatterplot(data=df, x='x', y=var, hue='passed QC', ax=ax,
-                        hue_order=[False, True])
-        sns.lineplot(data=df, x='x', y=var, hue='passed QC', ax=ax, style='well', legend=True,
-                     legend_kws={'fontsize': 12})
+        df['x'] = [label_func(p, s) for p, s in zip(df.protocol, df.sweep)]
+        sns.lineplot(data=df, x='x', y=var, hue='well', style='well', ax=ax, 
+                     legend=True)
 
         if var == 'E_rev' and np.isfinite(args.reversal):
             ax.axhline(args.reversal, linestyle='--', color='grey', label='Calculated Nernst potential')