From a45c906ae857b29260bd1587c91f73bb99509ebc Mon Sep 17 00:00:00 2001
From: JP <peacock.jared@gmail.com>
Date: Tue, 22 Oct 2024 17:04:30 -0700
Subject: [PATCH] Update 13_2d_from_mtpy_example_sk_jp.ipynb

---
 .../13_2d_from_mtpy_example_sk_jp.ipynb       | 348 +++---------------
 1 file changed, 45 insertions(+), 303 deletions(-)

diff --git a/notebooks/simpeg/13_2d_from_mtpy_example_sk_jp.ipynb b/notebooks/simpeg/13_2d_from_mtpy_example_sk_jp.ipynb
index c67fe91..19dd45f 100644
--- a/notebooks/simpeg/13_2d_from_mtpy_example_sk_jp.ipynb
+++ b/notebooks/simpeg/13_2d_from_mtpy_example_sk_jp.ipynb
@@ -64,7 +64,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m24:10:22T16:47:24 | INFO | line:777 |mth5.mth5 | close_mth5 | Flushing and closing ..\\..\\data\\transfer_functions\\forward_profiles.h5\u001b[0m\n"
+      "\u001b[1m24:10:22T16:58:57 | INFO | line:777 |mth5.mth5 | close_mth5 | Flushing and closing ..\\..\\data\\transfer_functions\\forward_profiles.h5\u001b[0m\n"
      ]
     }
    ],
@@ -139,7 +139,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[33m\u001b[1m24:10:22T16:47:25 | WARNING | line:163 |mtpy.imaging.plot_stations | plot | Could not add base map because HTTPSConnectionPool(host='basemap.nationalmap.gov', port=443): Max retries exceeded with url: /arcgis/rest/services/USGSTopo/MapServer/tile/12/2408/3636 (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1129)')))\u001b[0m\n"
+      "\u001b[33m\u001b[1m24:10:22T16:58:58 | WARNING | line:163 |mtpy.imaging.plot_stations | plot | Could not add base map because HTTPSConnectionPool(host='basemap.nationalmap.gov', port=443): Max retries exceeded with url: /arcgis/rest/services/USGSTopo/MapServer/tile/12/2408/3636 (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1129)')))\u001b[0m\n"
      ]
     },
     {
@@ -203,7 +203,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[33m\u001b[1m24:10:22T16:47:28 | WARNING | line:163 |mtpy.imaging.plot_stations | plot | Could not add base map because HTTPSConnectionPool(host='basemap.nationalmap.gov', port=443): Max retries exceeded with url: /arcgis/rest/services/USGSTopo/MapServer/tile/12/2408/3636 (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1129)')))\u001b[0m\n"
+      "\u001b[33m\u001b[1m24:10:22T16:59:01 | WARNING | line:163 |mtpy.imaging.plot_stations | plot | Could not add base map because HTTPSConnectionPool(host='basemap.nationalmap.gov', port=443): Max retries exceeded with url: /arcgis/rest/services/USGSTopo/MapServer/tile/12/2408/3636 (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1129)')))\u001b[0m\n"
      ]
     },
     {
@@ -924,26 +924,6 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01])"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "frequencies"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
    "metadata": {
     "tags": []
    },
@@ -955,95 +935,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(30, 70)"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "te_pred = sim_te.dpred(m0)\n",
-    "tm_pred = sim_tm.dpred(m0)\n",
-    "te_pred_mtpy = simpeg_2d.te_simulation.dpred(m0)\n",
-    "tm_pred_mtpy = simpeg_2d.tm_simulation.dpred(m0)\n",
-    "TM_PRED = tm_pred.reshape((len(frequencies), 2, 31))\n",
-    "TE_PRED = te_pred.reshape((len(frequencies), 2, 31))\n",
-    "TM_PRED_mtpy = tm_pred_mtpy.reshape((len(frequencies), 2, 31))\n",
-    "TE_PRED_mtpy = te_pred_mtpy.reshape((len(frequencies), 2, 31))\n",
-    "plt.semilogy(TE_PRED[:,0,:].flatten(), '.', label=\"te_simpeg\")\n",
-    "plt.semilogy(TM_PRED[:,0,:].flatten(), '.', label=\"tm_simpeg\")\n",
-    "plt.semilogy(TE_PRED_mtpy[:,0,:].flatten(), 's', label=\"te_mtpy\")\n",
-    "plt.semilogy(TM_PRED_mtpy[:,0,:].flatten(), 'o', label=\"tm_mtpy\")\n",
-    "plt.legend()\n",
-    "plt.ylim(30, 70)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(-270.0, 90.0)"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.plot(TE_PRED[:,1,:].flatten(), 'rv')\n",
-    "plt.plot(TM_PRED[:,1,:].flatten(), 'bv')\n",
-    "plt.plot(TE_PRED_mtpy[:,1,:].flatten()-5, 'ko')\n",
-    "plt.plot(TM_PRED_mtpy[:,1,:].flatten()+5, 'go')\n",
-    "plt.ylim(-270, 90)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 28,
    "metadata": {
     "tags": []
    },
@@ -1055,7 +947,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 29,
    "metadata": {
     "tags": []
    },
@@ -1075,7 +967,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 30,
    "metadata": {
     "tags": []
    },
@@ -1089,7 +981,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 31,
    "metadata": {
     "tags": []
    },
@@ -1109,46 +1001,26 @@
       "  #     beta     phi_d     phi_m       f      |proj(x-g)-x|  LS    Comment   \n",
       "-----------------------------------------------------------------------------\n",
       "x0 has any nan: 0\n",
-      "   0  1.17e+00  3.74e+05  0.00e+00  3.74e+05    4.94e+04      0              \n",
-      "   1  5.86e-01  5.53e+04  1.63e-03  5.53e+04    7.96e+03      0              \n",
-      "   2  2.93e-01  2.10e+04  4.92e-03  2.10e+04    1.50e+03      0   Skip BFGS  \n",
-      "   3  1.46e-01  4.29e+03  8.31e+01  4.30e+03    5.14e+02      1   Skip BFGS  \n",
-      "   4  7.32e-02  6.29e+02  1.89e+02  6.43e+02    5.04e+02      0   Skip BFGS  \n",
-      "   5  3.66e-02  7.88e+01  1.93e+02  8.59e+01    3.51e+01      0              \n",
-      "   6  1.83e-02  5.53e+01  1.99e+02  5.90e+01    1.85e+01      0              \n",
-      "   7  9.15e-03  4.74e+01  2.07e+02  4.92e+01    2.53e+01      0              \n",
-      "   8  4.57e-03  3.98e+01  2.20e+02  4.08e+01    2.54e+01      0              \n",
-      "   9  2.29e-03  3.56e+01  2.25e+02  3.61e+01    2.34e+01      0              \n",
-      "  10  1.14e-03  3.17e+01  2.37e+02  3.20e+01    2.39e+01      0              \n",
-      "  11  5.72e-04  2.86e+01  2.47e+02  2.87e+01    2.37e+01      0              \n",
-      "  12  2.86e-04  2.58e+01  2.76e+02  2.59e+01    1.97e+01      0              \n",
-      "  13  1.43e-04  2.45e+01  2.71e+02  2.45e+01    1.95e+01      0              \n",
-      "  14  7.15e-05  2.30e+01  2.87e+02  2.30e+01    2.13e+01      0              \n",
-      "  15  3.57e-05  2.15e+01  2.92e+02  2.15e+01    1.17e+01      0              \n",
-      "  16  1.79e-05  1.88e+01  3.08e+02  1.88e+01    1.64e+01      0   Skip BFGS  \n",
-      "  17  8.93e-06  1.76e+01  3.12e+02  1.76e+01    1.10e+01      0              \n",
-      "  18  4.47e-06  1.68e+01  3.21e+02  1.68e+01    8.05e+00      0              \n",
-      "  19  2.23e-06  1.58e+01  3.19e+02  1.58e+01    1.04e+01      0   Skip BFGS  \n",
-      "  20  1.12e-06  1.54e+01  3.19e+02  1.54e+01    7.56e+00      0              \n",
-      "  21  5.58e-07  1.49e+01  3.21e+02  1.49e+01    7.54e+00      0   Skip BFGS  \n",
-      "  22  2.79e-07  1.46e+01  3.22e+02  1.46e+01    8.15e+00      0              \n",
-      "  23  1.40e-07  1.40e+01  3.30e+02  1.40e+01    6.98e+00      0              \n",
-      "  24  6.98e-08  1.32e+01  3.42e+02  1.32e+01    9.03e+00      0   Skip BFGS  \n",
-      "  25  3.49e-08  1.27e+01  3.45e+02  1.27e+01    9.76e+00      0              \n",
-      "  26  1.75e-08  1.18e+01  3.57e+02  1.18e+01    8.93e+00      0   Skip BFGS  \n",
-      "  27  8.73e-09  1.14e+01  3.65e+02  1.14e+01    9.26e+00      0              \n",
-      "  28  4.36e-09  1.05e+01  3.94e+02  1.05e+01    1.09e+01      0   Skip BFGS  \n",
-      "  29  2.18e-09  1.02e+01  3.98e+02  1.02e+01    1.04e+01      0              \n",
-      "  30  1.09e-09  9.54e+00  4.14e+02  9.54e+00    9.37e+00      0   Skip BFGS  \n",
+      "   0  1.11e+00  3.74e+05  0.00e+00  3.74e+05    4.94e+04      0              \n",
+      "   1  5.55e-01  5.53e+04  1.63e-03  5.53e+04    7.96e+03      0              \n",
+      "   2  2.78e-01  2.10e+04  4.92e-03  2.10e+04    1.50e+03      0   Skip BFGS  \n",
+      "   3  1.39e-01  4.28e+03  8.32e+01  4.29e+03    5.15e+02      1   Skip BFGS  \n",
+      "   4  6.94e-02  6.28e+02  1.89e+02  6.41e+02    5.04e+02      0   Skip BFGS  \n",
+      "   5  3.47e-02  7.88e+01  1.93e+02  8.55e+01    3.53e+01      0              \n",
+      "   6  1.74e-02  5.53e+01  1.99e+02  5.87e+01    1.88e+01      0              \n",
+      "   7  8.68e-03  4.81e+01  2.06e+02  4.99e+01    2.40e+01      0              \n",
+      "   8  4.34e-03  4.05e+01  2.19e+02  4.15e+01    2.53e+01      0              \n",
+      "   9  2.17e-03  3.61e+01  2.24e+02  3.66e+01    2.07e+01      0              \n",
+      "  10  1.08e-03  3.15e+01  2.43e+02  3.18e+01    2.32e+01      0              \n",
       "------------------------- STOP! -------------------------\n",
-      "1 : |fc-fOld| = 6.3894e-01 <= tolF*(1+|f0|) = 3.7393e+04\n",
-      "0 : |xc-x_last| = 3.2430e+00 <= tolX*(1+|x0|) = 3.5477e-28\n",
-      "0 : |proj(x-g)-x|    = 9.3714e+00 <= tolG          = 1.0000e-01\n",
-      "0 : |proj(x-g)-x|    = 9.3714e+00 <= 1e3*eps       = 1.0000e-02\n",
-      "1 : maxIter   =      30    <= iter          =     30\n",
+      "1 : |fc-fOld| = 4.8145e+00 <= tolF*(1+|f0|) = 3.7393e+04\n",
+      "0 : |xc-x_last| = 1.1533e+01 <= tolX*(1+|x0|) = 3.5477e-28\n",
+      "0 : |proj(x-g)-x|    = 2.3227e+01 <= tolG          = 1.0000e-01\n",
+      "0 : |proj(x-g)-x|    = 2.3227e+01 <= 1e3*eps       = 1.0000e-02\n",
+      "1 : maxIter   =      10    <= iter          =     10\n",
       "------------------------- DONE! -------------------------\n",
-      "CPU times: total: 26min 44s\n",
-      "Wall time: 5min 28s\n"
+      "CPU times: total: 7min 33s\n",
+      "Wall time: 1min 25s\n"
      ]
     }
    ],
@@ -1245,7 +1117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 32,
    "metadata": {
     "tags": []
    },
@@ -1256,7 +1128,7 @@
        "620"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1267,7 +1139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 33,
    "metadata": {
     "tags": []
    },
@@ -1278,7 +1150,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 34,
    "metadata": {
     "tags": []
    },
@@ -1289,13 +1161,13 @@
        "(-15000.0, 5000.0)"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 1000x200 with 2 Axes>"
       ]
@@ -1323,7 +1195,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 35,
    "metadata": {
     "tags": []
    },
@@ -1338,7 +1210,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 36,
    "metadata": {
     "tags": []
    },
@@ -1350,33 +1222,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {
     "tags": []
    },
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
-      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
-      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x26394e22cd0>]"
+       "<matplotlib.legend.Legend at 0x203afc911c0>"
       ]
      },
-     "execution_count": 40,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x300 with 4 Axes>"
       ]
@@ -1386,6 +1249,9 @@
     }
    ],
    "source": [
+    "## With these plot frequency goes from high on the left to low on the right. \n",
+    "## Moving shallow to deep from left to right.\n",
+    "\n",
     "fig = plt.figure(figsize=(10, 3))\n",
     "ax1 = fig.add_subplot(2, 2, 1)\n",
     "ax2 = fig.add_subplot(2, 2, 2, sharex=ax1)\n",
@@ -1397,153 +1263,29 @@
     "ax1.semilogy(TE_PRED[:,0,:].flatten(), 'r.', label='predicted')\n",
     "ax1.set_title(\"TE\")\n",
     "ax1.set_ylabel(\"Apparent Resistivity\")\n",
-    "plt.legend()\n",
+    "ax1.set_xlim((simpeg_2d.data.n_stations*simpeg_2d.data.n_frequencies, 0))\n",
+    "ax1.legend()\n",
     "\n",
     "# plot TM Resistivity\n",
     "ax2.semilogy(TM_OBS[:,0,:].flatten(), 'b.', label='observed')\n",
     "ax2.semilogy(TM_PRED[:,0,:].flatten(), 'r.', label='predicted')\n",
     "ax2.set_title(\"TM\")\n",
-    "plt.legend()\n",
+    "ax2.legend()\n",
     "\n",
     "# plot TE Phase\n",
     "ax3.plot(TE_OBS[:,1,:].flatten(), 'b.', label='observed')\n",
     "ax3.plot(TE_PRED[:,1,:].flatten(), 'r.', label='predicted')\n",
     "ax3.set_xlabel(\"data point\")\n",
-    "plt.legend()\n",
+    "ax3.legend()\n",
     "\n",
     "# plot TM Phase\n",
     "ax4.plot(TM_OBS[:,1,:].flatten(), 'b.', label='observed')\n",
     "ax4.plot(TM_PRED[:,1,:].flatten(), 'r.', label='predicted')\n",
+    "ax3.legend()\n",
     "\n",
     "# plt.ylim(10, 1000)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x2639c3b8f70>"
-      ]
-     },
-     "execution_count": 41,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(10, 3))\n",
-    "plt.semilogy(TM_OBS[:,0,:].flatten(), '.', label='obs')\n",
-    "plt.semilogy(TM_PRED[:,0,:].flatten(), '.', label='PRED')\n",
-    "plt.legend()\n",
-    "# plt.ylim(10, 1000)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x2639711a340>]"
-      ]
-     },
-     "execution_count": 42,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(10, 3))\n",
-    "plt.plot(TE_OBS[:,1,:].flatten(), 'b.', label='OBS')\n",
-    "plt.plot(TE_PRED[:,1,:].flatten(), 'r.', label='PRED')\n",
-    "\n",
-    "# plt.ylim(10, 1000)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x26396840280>]"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(10, 3))\n",
-    "plt.plot(TM_PRED[:,1,:].flatten(), '.')\n",
-    "plt.plot(TM_OBS[:,1,:].flatten(), '.')\n",
-    "# plt.ylim(0, 90)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01])"
-      ]
-     },
-     "execution_count": 43,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "frequencies"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,