diff --git a/notebooks/Jungfrau/Jungfrau_Gain_Correct_and_Verify_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_Gain_Correct_and_Verify_NBC.ipynb index fbbbd563a272c05a1b803ad19a5be1f357843fb8..a5b646c7c26529cc5f7f4c8213059917515cb46a 100644 --- a/notebooks/Jungfrau/Jungfrau_Gain_Correct_and_Verify_NBC.ipynb +++ b/notebooks/Jungfrau/Jungfrau_Gain_Correct_and_Verify_NBC.ipynb @@ -840,7 +840,6 @@ " ax=ax,\n", " vmin=vmin,\n", " vmax=vmax,\n", - " cmap=\"jet\",\n", " colorbar={'shrink': 1, 'pad': 0.01},\n", ")\n", "ax.set_title(f'{karabo_id} - Mean RAW', size=18)\n", @@ -866,7 +865,7 @@ "corrected_mean = np.mean(corrected, axis=1)\n", "vmin, vmax = np.percentile(corrected_mean, [5, 95])\n", "\n", - "mean_plot_kwargs = dict(vmin=vmin, vmax=vmax, cmap=\"jet\")\n", + "mean_plot_kwargs = dict(vmin=vmin, vmax=vmax)\n", "\n", "if strixel_sensor:\n", " if strixel_sensor == \"A1256\":\n", @@ -932,7 +931,6 @@ "single_plot_kwargs = dict(\n", " vmin=vmin,\n", " vmax=vmax,\n", - " cmap=\"jet\"\n", ")\n", "\n", "if not strixel_sensor:\n", @@ -1059,7 +1057,6 @@ "geom.plot_data_fast(\n", " gain_max,\n", " ax=ax,\n", - " cmap=\"jet\",\n", " colorbar={'shrink': 1, 'pad': 0.01},\n", ")\n", "plt.show()" @@ -1080,7 +1077,14 @@ "outputs": [], "source": [ "table = []\n", - "for item in BadPixels:\n", + "badpixels = [\n", + " BadPixels.OFFSET_OUT_OF_THRESHOLD,\n", + " BadPixels.NOISE_OUT_OF_THRESHOLD,\n", + " BadPixels.OFFSET_NOISE_EVAL_ERROR,\n", + " BadPixels.NO_DARK_DATA,\n", + " BadPixels.WRONG_GAIN_VALUE,\n", + " ]\n", + "for item in badpixels:\n", " table.append(\n", " (item.name, f\"{item.value:016b}\"))\n", "md = display(Latex(tabulate.tabulate(\n", @@ -1106,16 +1110,17 @@ "display(Markdown(f\"#### Bad pixels image for train {tid}\"))\n", "\n", "fig, ax = plt.subplots(figsize=(18, 10))\n", + "vmin, vmax = (0, sorted([bp.value for bp in badpixels])[-2])\n", "if not strixel_sensor:\n", " geom.plot_data_fast(\n", " np.log2(mask_train),\n", " ax=ax,\n", - " vmin=0, vmax=32, cmap=\"jet\",\n", + " vmin=vmin, vmax=vmax,\n", " colorbar={'shrink': 1, 'pad': 0.01},\n", " )\n", "else:\n", " mask = ax.imshow(\n", - " mask_train.squeeze(), vmin=0, vmax=32, cmap='jet', aspect=aspect)\n", + " mask_train.squeeze(), vmin=vmin, vmax=vmax, aspect=aspect)\n", " plt.colorbar(mask)\n", "\n", "plt.show()"