changed standard inversion to use ax=1

Author: teddi

infiltration.ipynb

@@ -1895,103 +1895,6 @@
     "ax[0].set_ylabel('Z (m)',fontsize=fs)\n",
     "plt.legend();\n"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "32.66093527534151\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# vectors for mesh\n",
-    "I2 = np.where(mesh.vectorCCx < max(survey.electrode_locations.T[0]))\n",
-    "I3 = np.where(mesh.vectorCCx > min(survey.electrode_locations.T[0]))\n",
-    "I4 = np.intersect1d(I2, I3)\n",
-    "I5 = np.where(mesh.vectorCCy > -5)\n",
-    "I6 = np.intersect1d(I4, I5)\n",
-    "\n",
-    "# grid for values\n",
-    "I2b = np.where(mesh.gridCC[:,0] < max(survey.electrode_locations.T[0]))\n",
-    "I3b = np.where(mesh.gridCC[:,0] > min(survey.electrode_locations.T[0]))\n",
-    "I4b = np.intersect1d(I2b, I3b)\n",
-    "I5b = np.where(mesh.gridCC[:,1] > -5)\n",
-    "I6b = np.intersect1d(I4b, I5b)\n",
-    "\n",
-    "mesh2 = discretize.TensorMesh([mesh.hx[I4], mesh.hy[I5]],x0=\"CN\")\n",
-    "dat = mesh2.plotImage(log(sig[I6b]),clim=[min(log(sig)),max(log(sig))])\n",
-    "\n",
-    "# moptB = np.load('mopt_infiltration_smooth.npy',encoding = 'latin1')\n",
-    "err_smooth = (abs(((mopt_smooth) - log(sig))/log(sig))*100)[I6b]\n",
-    "print(mean(err_smooth))\n",
-    "\n",
-    "err_hybrid = (abs((log(mopt_hybrid) - log(sig))/log(sig))*100)[I6b]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "32.66093527534151"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mean(err_smooth)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10.106842616846698"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mean(err_hybrid)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {