refining figures
" print(\"Slice = {0}\".format(z_i)) \n",
" \n",
" plt.contourf(\n",
- " x_evaluation, y_evaluation, dose_evaluation[:, :, i].T, 30, \n",
+ " x_evaluation, y_evaluation, dose_evaluation[:, :, i].T, 100, \n",
" vmin=0, vmax=max_ref_dose, cmap=plt.get_cmap('viridis'))\n",
" plt.title(\"Evaluation\")\n",
" plt.colorbar()\n",
" plt.show()\n",
" \n",
" plt.contourf(\n",
- " x_evaluation, y_evaluation, reshaped_interpolatied_reference_dose, 30, \n",
+ " x_evaluation, y_evaluation, reshaped_interpolatied_reference_dose, 100, \n",
" vmin=0, vmax=max_ref_dose, cmap=plt.get_cmap('viridis'))\n",
" plt.title(\"Reference\") \n",
" plt.colorbar()\n",
" plt.show()\n",
" \n",
" plt.contourf(\n",
- " x_evaluation, y_evaluation, cut_off_gamma[:, :, i].T, 30, \n",
- " vmin=0, vmax=2, cmap=plt.get_cmap('bwr'))\n",
+ " x_evaluation, y_evaluation, cut_off_gamma[:, :, i].T, 100, \n",
+ " vmin=0, vmax=2, cmap=plt.get_cmap('coolwarm'))\n",
" plt.title(\"Gamma\")\n",
" plt.colorbar()\n",
" plt.show()\n",
" \n",
+ " plt.contourf(\n",
+ " x_evaluation, y_evaluation, dose_evaluation[:, :, i].T - reshaped_interpolatied_reference_dose, 100, \n",
+ " vmin=-max_ref_dose, vmax=max_ref_dose, cmap=plt.get_cmap('seismic'))\n",
+ " plt.title(\"Dose Diff\")\n",
+ " plt.colorbar()\n",
+ " plt.show()\n",
+ " \n",
" print(\"\\n\")"
]
},
