Clients

docs/examples/notebooks/fdsn_request.csv

@@ -0,0 +1,6 @@
+,network,station,location,channel,start,end
+0,8P,CAS04,,LFE,2020-06-02T19:00:00,2020-07-13T19:00:00
+1,8P,CAS04,,LFN,2020-06-02T19:00:00,2020-07-13T19:00:00
+2,8P,CAS04,,LFZ,2020-06-02T19:00:00,2020-07-13T19:00:00
+3,8P,CAS04,,LQE,2020-06-02T19:00:00,2020-07-13T19:00:00
+4,8P,CAS04,,LQN,2020-06-02T19:00:00,2020-07-13T19:00:00

docs/examples/notebooks/make_mth5_driver_v0.1.0.ipynb

@@ -6,6 +6,10 @@
    "source": [
     "# Make MTH5 from IRIS Data Managment Center v0.1.0 \n",
     "\n",
+    "This example demonstrates how to build an MTH5 from data archived at IRIS, it could work with any MT data stored at an FDSN data center (probably).\n",
+    "\n",
+    "We will use the `mth5.clients.FDSN` class to build the file.  There is also second way using the more generic `mth5.clients.MakeMTH5` class, which will be highlighted below. \n",
+    "\n",
     "**Note:** this example assumes that data availability (Network, Station, Channel, Start, End) are all previously known.  If you do not know the data that you want to download use [IRIS tools](https://ds.iris.edu/ds/nodes/dmc/tools/##) to get data availability.   "
    ]
   },
@@ -18,7 +22,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2022-09-12 17:00:41,562 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\OneDrive - DOI\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n"
+      "2023-03-23 14:32:18,703 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\OneDrive - DOI\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n"
      ]
     }
    ],
@@ -28,7 +32,7 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "from mth5.mth5 import MTH5\n",
-    "from mth5.clients.make_mth5 import MakeMTH5\n",
+    "from mth5.clients import FDSN\n",
     "\n",
     "from matplotlib import pyplot as plt\n",
     "%matplotlib widget"
@@ -67,8 +71,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "m = MakeMTH5(mth5_version='0.1.0')\n",
-    "m.client = \"IRIS\""
+    "fdsn_object = FDSN(mth5_version='0.1.0')\n",
+    "fdsn_object.client = \"IRIS\""
    ]
   },
   {
@@ -95,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -186,7 +190,7 @@
        "4      8P   CAS04              LQN  2020-06-02T19:00:00  2020-07-13T19:00:00"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -203,7 +207,7 @@
     "        )\n",
     "\n",
     "# Turn list into dataframe\n",
-    "request_df =  pd.DataFrame(request_list, columns=m.column_names) \n",
+    "request_df =  pd.DataFrame(request_list, columns=fdsn_object.request_columns) \n",
     "request_df"
    ]
   },
@@ -218,7 +222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -236,11 +240,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
-    "inventory, data = m.get_inventory_from_df(request_df, data=False)"
+    "inventory, data = fdsn_object.get_inventory_from_df(request_df, data=False)"
    ]
   },
   {
@@ -252,13 +256,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Inventory created at 2022-09-13T00:00:42.935166Z\n",
+       "Inventory created at 2023-03-23T21:32:59.642492Z\n",
        "\tCreated by: ObsPy 1.3.0\n",
        "\t\t    https://www.obspy.org\n",
        "\tSending institution: MTH5\n",
@@ -267,12 +271,12 @@
        "\t\t\t8P\n",
        "\t\tStations (1):\n",
        "\t\t\t8P.CAS04 (Corral Hollow, CA, USA)\n",
-       "\t\tChannels (8):\n",
-       "\t\t\t8P.CAS04..LFZ, 8P.CAS04..LFN, 8P.CAS04..LFE, 8P.CAS04..LQN (2x), \n",
-       "\t\t\t8P.CAS04..LQE (3x)"
+       "\t\tChannels (5):\n",
+       "\t\t\t8P.CAS04..LFZ, 8P.CAS04..LFN, 8P.CAS04..LFE, 8P.CAS04..LQN, \n",
+       "\t\t\t8P.CAS04..LQE"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -291,7 +295,18 @@
     "\n",
     "We are going to time it just to get an indication how long it might take.  Should take about 4 minutes.\n",
     "\n",
-    "**Note:** we are setting `interact=False`.  If you want to just to keep the file open to interogat it set `interact=True`. "
+    "**Note:** we are setting `interact=False`.  If you want to just to keep the file open to interogat it set `interact=True`. \n",
+    "\n",
+    "### Make an MTH5 using MakeMTH5\n",
+    "\n",
+    "Another way to make a file is using the `mth5.clients.MakeMTH5` class, which is more generic than FDSN, but doesn't have as many methods.  The `MakeMTH5` class is meant to be a convienence method for the various clients.\n",
+    "\n",
+    "```\n",
+    "from mth5.clients import MakeMTH5\n",
+    "\n",
+    "make_mth5_object = MakeMTH5(mth5_version='0.1.0', interact=False)\n",
+    "mth5_filename = make_mth5_object.from_fdsn_client(request_df, client=\"IRIS\")\n",
+    "```"
    ]
   },
   {
@@ -352,7 +367,7 @@
    "source": [
     "%%time\n",
     "\n",
-    "mth5_filename = m.make_mth5_from_fdsnclient(request_df, interact=False)\n",
+    "mth5_filename = fdsn_object.make_mth5_from_fdsn_client(request_df, interact=False)\n",
     "\n",
     "print(f\"Created {mth5_filename}\")"
    ]

docs/examples/notebooks/make_mth5_driver_v0.2.0.ipynb

@@ -6,6 +6,10 @@
    "source": [
     "# Make MTH5 from IRIS Data Managment Center v0.2.0 \n",
     "\n",
+    "This example demonstrates how to build an MTH5 from data archived at IRIS, it could work with any MT data stored at an FDSN data center (probably).\n",
+    "\n",
+    "We will use the `mth5.clients.FDSN` class to build the file.  There is also second way using the more generic `mth5.clients.MakeMTH5` class, which will be highlighted below. \n",
+    "\n",
     "**Note:** this example assumes that data availability (Network, Station, Channel, Start, End) are all previously known.  If you do not know the data that you want to download use [IRIS tools](https://ds.iris.edu/ds/nodes/dmc/tools/##) to get data availability.   "
    ]
   },
@@ -18,7 +22,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2022-09-12 15:28:25,328 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\OneDrive - DOI\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n"
+      "2023-03-23 14:50:15,143 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\OneDrive - DOI\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n"
      ]
     }
    ],
@@ -28,7 +32,7 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "from mth5.mth5 import MTH5\n",
-    "from mth5.clients.make_mth5 import MakeMTH5\n",
+    "from mth5.clients.make_mth5 import FDSN\n",
     "\n",
     "from matplotlib import pyplot as plt\n",
     "%matplotlib widget"
@@ -67,8 +71,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "m = MakeMTH5(mth5_version='0.2.0')\n",
-    "m.client = \"IRIS\""
+    "fdsn_object = FDSN(mth5_version='0.2.0')\n",
+    "fdsn_object.client = \"IRIS\""
    ]
   },
   {
@@ -254,7 +258,7 @@
     "        )\n",
     "\n",
     "# Turn list into dataframe\n",
-    "request_df =  pd.DataFrame(request_list, columns=m.column_names) \n",
+    "request_df =  pd.DataFrame(request_list, columns=fdsn_object.request_columns) \n",
     "request_df"
    ]
   },
@@ -291,7 +295,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "inventory, data = m.get_inventory_from_df(request_df, data=False)"
+    "inventory, data = fdsn_object.get_inventory_from_df(request_df, data=False)"
    ]
   },
   {
@@ -344,7 +348,18 @@
     "\n",
     "We are going to time it just to get an indication how long it might take.  Should take about 4 minutes.\n",
     "\n",
-    "**Note:** we are setting `interact=False`.  If you want to just to keep the file open to interogat it set `interact=True`. "
+    "**Note:** we are setting `interact=False`.  If you want to just to keep the file open to interogat it set `interact=True`. \n",
+    "\n",
+    "### Make an MTH5 using MakeMTH5\n",
+    "\n",
+    "Another way to make a file is using the `mth5.clients.MakeMTH5` class, which is more generic than FDSN, but doesn't have as many methods.  The `MakeMTH5` class is meant to be a convienence method for the various clients.\n",
+    "\n",
+    "```\n",
+    "from mth5.clients import MakeMTH5\n",
+    "\n",
+    "make_mth5_object = MakeMTH5(mth5_version='0.2.0', interact=False)\n",
+    "mth5_filename = make_mth5_object.from_fdsn_client(request_df, client=\"IRIS\")\n",
+    "```"
    ]
   },
   {
@@ -428,7 +443,7 @@
    "source": [
     "%%time\n",
     "\n",
-    "mth5_object = m.make_mth5_from_fdsnclient(request_df, interact=False)\n",
+    "mth5_object = fdsn_object.make_mth5_from_fdsn_client(request_df, interact=False)\n",
     "\n",
     "print(f\"Created {mth5_object}\")"
    ]