diff --git a/notebooks/aurora/04_CAS04.ipynb b/notebooks/aurora/04_CAS04.ipynb deleted file mode 100644 index ad0be96..0000000 --- a/notebooks/aurora/04_CAS04.ipynb +++ /dev/null @@ -1,3616 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Process CAS04 Data with Aurora" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "CAS04 was a trial station selected because it was first in alphabetical order from a collection of \"recent\" stations. This station was used as a proof of concept to show that aurora could reproduce EMTF results for USArray data." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The steps are similar to the synthetic data workbook, but in this case we have a larger data set with more interesting things happening.\n", - "\n", - "The data are already created and available on the IRIS ftp website:\n", - "\n", - "http://ftp.iris.washington.edu/pub/dropoff/buffer/MT_test_data/\n", - "\n", - "but they can also be generated using aurora/tests/CAS04/01_make_cas04_mth5.py\n", - "\n", - "This notebook starts from an existing h5 file.\n", - "\n", - "1. Create the synthetic mth5 [IGNORE]\n", - "2. Get a Run Summary from the mth5\n", - "3. Select the station to process and optionally the remote reference station\n", - "4. Create a processing config\n", - "5. Generate TFs\n", - "6. Archive the TFs (in emtf_xml or z-file)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "# Uncomment the following line to make plots interactive.\n", - "# %matplotlib widget" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Here are the modules we will need to import " - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-10-15 18:22:25,980 [line 135] mth5.setup_logger - INFO: Logging file can be found /home/kkappler/software/irismt/mth5/logs/mth5_debug.log\n" - ] - } - ], - "source": [ - "import pathlib\n", - "import warnings\n", - "\n", - "import pandas as pd\n", - "\n", - "from aurora.config.config_creator import ConfigCreator\n", - "from aurora.pipelines.process_mth5 import process_mth5\n", - "from aurora.pipelines.run_summary import RunSummary\n", - "from aurora.test_utils.synthetic.make_mth5_from_asc import create_test12rr_h5\n", - "from aurora.test_utils.synthetic.paths import DATA_PATH\n", - "from aurora.transfer_function.kernel_dataset import KernelDataset\n", - "from mth5.utils.helpers import initialize_mth5\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "tags": [] - }, - "source": [ - "## Define mth5 file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The file should probably be placed into a dedicated data directory but for this test the data are put here, in the same directory as this notebook." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "mth5_path = pathlib.Path(\"8P_CAS04_CAV07_NVR11_REV06.h5\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "m = initialize_mth5(mth5_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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surveystationrunlatitudelongitudeelevationcomponentstartendn_samplessample_ratemeasurement_typeazimuthtiltunitshdf5_referencerun_hdf5_referencestation_hdf5_reference
0CONUS SouthCAS04a37.633351-121.468382329.38750ex2020-06-02 18:41:43+00:002020-06-02 22:07:46+00:00123641.0electric13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
1CONUS SouthCAS04a37.633351-121.468382329.38750ey2020-06-02 18:41:43+00:002020-06-02 22:07:46+00:00123641.0electric103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
2CONUS SouthCAS04a37.633351-121.468382329.38750hx2020-06-02 18:41:43+00:002020-06-02 22:07:46+00:00123641.0magnetic13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
3CONUS SouthCAS04a37.633351-121.468382329.38750hy2020-06-02 18:41:43+00:002020-06-02 22:07:46+00:00123641.0magnetic103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
4CONUS SouthCAS04a37.633351-121.468382329.38750hz2020-06-02 18:41:43+00:002020-06-02 22:07:46+00:00123641.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
5CONUS SouthCAS04b37.633351-121.468382329.38750ex2020-06-02 22:24:55+00:002020-06-12 17:52:23+00:008476491.0electric13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
6CONUS SouthCAS04b37.633351-121.468382329.38750ey2020-06-02 22:24:55+00:002020-06-12 17:52:23+00:008476491.0electric103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
7CONUS SouthCAS04b37.633351-121.468382329.38750hx2020-06-02 22:24:55+00:002020-06-12 17:52:23+00:008476491.0magnetic13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
8CONUS SouthCAS04b37.633351-121.468382329.38750hy2020-06-02 22:24:55+00:002020-06-12 17:52:23+00:008476491.0magnetic103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
9CONUS SouthCAS04b37.633351-121.468382329.38750hz2020-06-02 22:24:55+00:002020-06-12 17:52:23+00:008476491.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
10CONUS SouthCAS04c37.633351-121.468382329.38750ex2020-06-12 18:32:17+00:002020-07-01 17:32:59+00:0016380431.0electric13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
11CONUS SouthCAS04c37.633351-121.468382329.38750ey2020-06-12 18:32:17+00:002020-07-01 17:32:59+00:0016380431.0electric103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
12CONUS SouthCAS04c37.633351-121.468382329.38750hx2020-06-12 18:32:17+00:002020-07-01 17:32:59+00:0016380431.0magnetic13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
13CONUS SouthCAS04c37.633351-121.468382329.38750hy2020-06-12 18:32:17+00:002020-07-01 17:32:59+00:0016380431.0magnetic103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
14CONUS SouthCAS04c37.633351-121.468382329.38750hz2020-06-12 18:32:17+00:002020-07-01 17:32:59+00:0016380431.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
15CONUS SouthCAS04d37.633351-121.468382329.38750ex2020-07-01 19:36:55+00:002020-07-13 21:46:12+00:0010445581.0electric13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
16CONUS SouthCAS04d37.633351-121.468382329.38750ey2020-07-01 19:36:55+00:002020-07-13 21:46:12+00:0010445581.0electric103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
17CONUS SouthCAS04d37.633351-121.468382329.38750hx2020-07-01 19:36:55+00:002020-07-13 21:46:12+00:0010445581.0magnetic13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
18CONUS SouthCAS04d37.633351-121.468382329.38750hy2020-07-01 19:36:55+00:002020-07-13 21:46:12+00:0010445581.0magnetic103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
19CONUS SouthCAS04d37.633351-121.468382329.38750hz2020-07-01 19:36:55+00:002020-07-13 21:46:12+00:0010445581.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
20CONUS SouthCAV07a35.586754-118.797662874.20000ex2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:0019891.0electric12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
21CONUS SouthCAV07a35.586754-118.797662874.20000ey2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:0019891.0electric102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
22CONUS SouthCAV07a35.586754-118.797662874.20000hx2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:0019891.0magnetic12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
23CONUS SouthCAV07a35.586754-118.797662874.20000hy2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:0019891.0magnetic102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
24CONUS SouthCAV07a35.586754-118.797662874.20000hz2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:0019891.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
25CONUS SouthCAV07b35.586754-118.797662874.20000ex2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:009351.0electric12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
26CONUS SouthCAV07b35.586754-118.797662874.20000ey2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:009351.0electric102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
27CONUS SouthCAV07b35.586754-118.797662874.20000hx2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:009351.0magnetic12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
28CONUS SouthCAV07b35.586754-118.797662874.20000hy2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:009351.0magnetic102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
29CONUS SouthCAV07b35.586754-118.797662874.20000hz2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:009351.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
30CONUS SouthCAV07c35.586754-118.797662874.20000ex2020-06-10 03:50:04+00:002020-06-23 17:35:37+00:0011727341.0electric12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
31CONUS SouthCAV07c35.586754-118.797662874.20000ey2020-06-10 03:50:04+00:002020-06-23 17:35:37+00:0011727341.0electric102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
32CONUS SouthCAV07c35.586754-118.797662874.20000hx2020-06-10 03:50:04+00:002020-06-23 17:35:37+00:0011727341.0magnetic12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
33CONUS SouthCAV07c35.586754-118.797662874.20000hy2020-06-10 03:50:04+00:002020-06-23 17:35:37+00:0011727341.0magnetic102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
34CONUS SouthCAV07c35.586754-118.797662874.20000hz2020-06-10 03:50:04+00:002020-06-23 17:35:37+00:0011727341.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
35CONUS SouthCAV07d35.586754-118.797662874.20000ex2020-06-23 18:38:51+00:002020-07-06 16:31:12+00:0011155421.0electric12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
36CONUS SouthCAV07d35.586754-118.797662874.20000ey2020-06-23 18:38:51+00:002020-07-06 16:31:12+00:0011155421.0electric102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
37CONUS SouthCAV07d35.586754-118.797662874.20000hx2020-06-23 18:38:51+00:002020-07-06 16:31:12+00:0011155421.0magnetic12.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
38CONUS SouthCAV07d35.586754-118.797662874.20000hy2020-06-23 18:38:51+00:002020-07-06 16:31:12+00:0011155421.0magnetic102.30.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
39CONUS SouthCAV07d35.586754-118.797662874.20000hz2020-06-23 18:38:51+00:002020-07-06 16:31:12+00:0011155421.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
40CONUS SouthNVR11none38.281043-115.6683951561.86875ex2020-06-12 21:10:38+00:002020-06-12 21:59:40+00:0029431.0electric0.00.0counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
41CONUS SouthNVR11none38.281043-115.6683951561.86875ey2020-06-12 21:10:38+00:002020-06-12 21:59:40+00:0029431.0electric0.00.0counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
42CONUS SouthNVR11none38.281043-115.6683951561.86875hx2020-06-12 21:10:38+00:002020-06-12 21:59:40+00:0029431.0magnetic0.00.0counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
43CONUS SouthNVR11none38.281043-115.6683951561.86875hy2020-06-12 21:10:38+00:002020-06-12 21:59:40+00:0029431.0magnetic0.00.0counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
44CONUS SouthNVR11none38.281043-115.6683951561.86875hz2020-06-12 21:10:38+00:002020-06-12 21:59:40+00:0029431.0magnetic0.00.0counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
45CONUS SouthNVR11a38.281043-115.6683951561.86875ex2020-06-12 22:13:24+00:002020-06-26 19:35:21+00:0012001181.0electric12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
46CONUS SouthNVR11a38.281043-115.6683951561.86875ey2020-06-12 22:13:24+00:002020-06-26 19:35:21+00:0012001181.0electric102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
47CONUS SouthNVR11a38.281043-115.6683951561.86875hx2020-06-12 22:13:24+00:002020-06-26 19:35:21+00:0012001181.0magnetic12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
48CONUS SouthNVR11a38.281043-115.6683951561.86875hy2020-06-12 22:13:24+00:002020-06-26 19:35:21+00:0012001181.0magnetic102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
49CONUS SouthNVR11a38.281043-115.6683951561.86875hz2020-06-12 22:13:24+00:002020-06-26 19:35:21+00:0012001181.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
50CONUS SouthNVR11b38.281043-115.6683951561.86875ex2020-06-26 22:04:35+00:002020-06-27 17:16:51+00:00691371.0electric12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
51CONUS SouthNVR11b38.281043-115.6683951561.86875ey2020-06-26 22:04:35+00:002020-06-27 17:16:51+00:00691371.0electric102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
52CONUS SouthNVR11b38.281043-115.6683951561.86875hx2020-06-26 22:04:35+00:002020-06-27 17:16:51+00:00691371.0magnetic12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
53CONUS SouthNVR11b38.281043-115.6683951561.86875hy2020-06-26 22:04:35+00:002020-06-27 17:16:51+00:00691371.0magnetic102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
54CONUS SouthNVR11b38.281043-115.6683951561.86875hz2020-06-26 22:04:35+00:002020-06-27 17:16:51+00:00691371.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
55CONUS SouthNVR11c38.281043-115.6683951561.86875ex2020-06-27 18:32:12+00:002020-07-10 18:17:08+00:0011222971.0electric12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
56CONUS SouthNVR11c38.281043-115.6683951561.86875ey2020-06-27 18:32:12+00:002020-07-10 18:17:08+00:0011222971.0electric102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
57CONUS SouthNVR11c38.281043-115.6683951561.86875hx2020-06-27 18:32:12+00:002020-07-10 18:17:08+00:0011222971.0magnetic12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
58CONUS SouthNVR11c38.281043-115.6683951561.86875hy2020-06-27 18:32:12+00:002020-07-10 18:17:08+00:0011222971.0magnetic102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
59CONUS SouthNVR11c38.281043-115.6683951561.86875hz2020-06-27 18:32:12+00:002020-07-10 18:17:08+00:0011222971.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
60CONUS SouthNVR11d38.281043-115.6683951561.86875ex2020-07-10 19:18:48+00:002020-07-23 21:19:08+00:0011304211.0electric12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
61CONUS SouthNVR11d38.281043-115.6683951561.86875ey2020-07-10 19:18:48+00:002020-07-23 21:19:08+00:0011304211.0electric102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
62CONUS SouthNVR11d38.281043-115.6683951561.86875hx2020-07-10 19:18:48+00:002020-07-23 21:19:08+00:0011304211.0magnetic12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
63CONUS SouthNVR11d38.281043-115.6683951561.86875hy2020-07-10 19:18:48+00:002020-07-23 21:19:08+00:0011304211.0magnetic102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
64CONUS SouthNVR11d38.281043-115.6683951561.86875hz2020-07-10 19:18:48+00:002020-07-23 21:19:08+00:0011304211.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
65CONUS SouthNVR11e38.281043-115.6683951561.86875ex2020-08-06 21:19:09+00:002020-08-06 21:25:59+00:004111.0electric12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
66CONUS SouthNVR11e38.281043-115.6683951561.86875ey2020-08-06 21:19:09+00:002020-08-06 21:25:59+00:004111.0electric102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
67CONUS SouthNVR11e38.281043-115.6683951561.86875hx2020-08-06 21:19:09+00:002020-08-06 21:25:59+00:004111.0magnetic12.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
68CONUS SouthNVR11e38.281043-115.6683951561.86875hy2020-08-06 21:19:09+00:002020-08-06 21:25:59+00:004111.0magnetic102.00.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
69CONUS SouthNVR11e38.281043-115.6683951561.86875hz2020-08-06 21:19:09+00:002020-08-06 21:25:59+00:004111.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
70CONUS SouthREV06a35.712621-119.46641461.05000ex2020-06-06 18:38:28+00:002020-06-06 20:12:26+00:0056391.0electric12.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
71CONUS SouthREV06a35.712621-119.46641461.05000ey2020-06-06 18:38:28+00:002020-06-06 20:12:26+00:0056391.0electric102.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
72CONUS SouthREV06a35.712621-119.46641461.05000hx2020-06-06 18:38:28+00:002020-06-06 20:12:26+00:0056391.0magnetic12.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
73CONUS SouthREV06a35.712621-119.46641461.05000hy2020-06-06 18:38:28+00:002020-06-06 20:12:26+00:0056391.0magnetic102.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
74CONUS SouthREV06a35.712621-119.46641461.05000hz2020-06-06 18:38:28+00:002020-06-06 20:12:26+00:0056391.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
75CONUS SouthREV06b35.712621-119.46641461.05000ex2020-06-06 20:24:28+00:002020-06-22 18:33:58+00:0013757711.0electric12.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
76CONUS SouthREV06b35.712621-119.46641461.05000ey2020-06-06 20:24:28+00:002020-06-22 18:33:58+00:0013757711.0electric102.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
77CONUS SouthREV06b35.712621-119.46641461.05000hx2020-06-06 20:24:28+00:002020-06-22 18:33:58+00:0013757711.0magnetic12.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
78CONUS SouthREV06b35.712621-119.46641461.05000hy2020-06-06 20:24:28+00:002020-06-22 18:33:58+00:0013757711.0magnetic102.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
79CONUS SouthREV06b35.712621-119.46641461.05000hz2020-06-06 20:24:28+00:002020-06-22 18:33:58+00:0013757711.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
80CONUS SouthREV06c35.712621-119.46641461.05000ex2020-06-22 20:30:36+00:002020-07-05 18:10:47+00:0011148121.0electric12.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
81CONUS SouthREV06c35.712621-119.46641461.05000ey2020-06-22 20:30:36+00:002020-07-05 18:10:47+00:0011148121.0electric102.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
82CONUS SouthREV06c35.712621-119.46641461.05000hx2020-06-22 20:30:36+00:002020-07-05 18:10:47+00:0011148121.0magnetic12.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
83CONUS SouthREV06c35.712621-119.46641461.05000hy2020-06-22 20:30:36+00:002020-07-05 18:10:47+00:0011148121.0magnetic102.40.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
84CONUS SouthREV06c35.712621-119.46641461.05000hz2020-06-22 20:30:36+00:002020-07-05 18:10:47+00:0011148121.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
\n", - "
" - ], - "text/plain": [ - " survey station run latitude longitude elevation component \\\n", - "0 CONUS South CAS04 a 37.633351 -121.468382 329.38750 ex \n", - "1 CONUS South CAS04 a 37.633351 -121.468382 329.38750 ey \n", - "2 CONUS South CAS04 a 37.633351 -121.468382 329.38750 hx \n", - "3 CONUS South CAS04 a 37.633351 -121.468382 329.38750 hy \n", - "4 CONUS South CAS04 a 37.633351 -121.468382 329.38750 hz \n", - "5 CONUS South CAS04 b 37.633351 -121.468382 329.38750 ex \n", - "6 CONUS South CAS04 b 37.633351 -121.468382 329.38750 ey \n", - "7 CONUS South CAS04 b 37.633351 -121.468382 329.38750 hx \n", - "8 CONUS South CAS04 b 37.633351 -121.468382 329.38750 hy \n", - "9 CONUS South CAS04 b 37.633351 -121.468382 329.38750 hz \n", - "10 CONUS South CAS04 c 37.633351 -121.468382 329.38750 ex \n", - "11 CONUS South CAS04 c 37.633351 -121.468382 329.38750 ey \n", - "12 CONUS South CAS04 c 37.633351 -121.468382 329.38750 hx \n", - "13 CONUS South CAS04 c 37.633351 -121.468382 329.38750 hy \n", - "14 CONUS South CAS04 c 37.633351 -121.468382 329.38750 hz \n", - "15 CONUS South CAS04 d 37.633351 -121.468382 329.38750 ex \n", - "16 CONUS South CAS04 d 37.633351 -121.468382 329.38750 ey \n", - "17 CONUS South CAS04 d 37.633351 -121.468382 329.38750 hx \n", - "18 CONUS South CAS04 d 37.633351 -121.468382 329.38750 hy \n", - "19 CONUS South CAS04 d 37.633351 -121.468382 329.38750 hz \n", - "20 CONUS South CAV07 a 35.586754 -118.797662 874.20000 ex \n", - "21 CONUS South CAV07 a 35.586754 -118.797662 874.20000 ey \n", - "22 CONUS South CAV07 a 35.586754 -118.797662 874.20000 hx \n", - "23 CONUS South CAV07 a 35.586754 -118.797662 874.20000 hy \n", - "24 CONUS South CAV07 a 35.586754 -118.797662 874.20000 hz \n", - "25 CONUS South CAV07 b 35.586754 -118.797662 874.20000 ex \n", - "26 CONUS South CAV07 b 35.586754 -118.797662 874.20000 ey \n", - "27 CONUS South CAV07 b 35.586754 -118.797662 874.20000 hx \n", - "28 CONUS South CAV07 b 35.586754 -118.797662 874.20000 hy \n", - "29 CONUS South CAV07 b 35.586754 -118.797662 874.20000 hz \n", - "30 CONUS South CAV07 c 35.586754 -118.797662 874.20000 ex \n", - "31 CONUS South CAV07 c 35.586754 -118.797662 874.20000 ey \n", - "32 CONUS South CAV07 c 35.586754 -118.797662 874.20000 hx \n", - "33 CONUS South CAV07 c 35.586754 -118.797662 874.20000 hy \n", - "34 CONUS South CAV07 c 35.586754 -118.797662 874.20000 hz \n", - "35 CONUS South CAV07 d 35.586754 -118.797662 874.20000 ex \n", - "36 CONUS South CAV07 d 35.586754 -118.797662 874.20000 ey \n", - "37 CONUS South CAV07 d 35.586754 -118.797662 874.20000 hx \n", - "38 CONUS South CAV07 d 35.586754 -118.797662 874.20000 hy \n", - "39 CONUS South CAV07 d 35.586754 -118.797662 874.20000 hz \n", - "40 CONUS South NVR11 none 38.281043 -115.668395 1561.86875 ex \n", - "41 CONUS South NVR11 none 38.281043 -115.668395 1561.86875 ey \n", - "42 CONUS South NVR11 none 38.281043 -115.668395 1561.86875 hx \n", - "43 CONUS South NVR11 none 38.281043 -115.668395 1561.86875 hy \n", - "44 CONUS South NVR11 none 38.281043 -115.668395 1561.86875 hz \n", - "45 CONUS South NVR11 a 38.281043 -115.668395 1561.86875 ex \n", - "46 CONUS South NVR11 a 38.281043 -115.668395 1561.86875 ey \n", - "47 CONUS South NVR11 a 38.281043 -115.668395 1561.86875 hx \n", - "48 CONUS South NVR11 a 38.281043 -115.668395 1561.86875 hy \n", - "49 CONUS South NVR11 a 38.281043 -115.668395 1561.86875 hz \n", - "50 CONUS South NVR11 b 38.281043 -115.668395 1561.86875 ex \n", - "51 CONUS South NVR11 b 38.281043 -115.668395 1561.86875 ey \n", - "52 CONUS South NVR11 b 38.281043 -115.668395 1561.86875 hx \n", - "53 CONUS South NVR11 b 38.281043 -115.668395 1561.86875 hy \n", - "54 CONUS South NVR11 b 38.281043 -115.668395 1561.86875 hz \n", - "55 CONUS South NVR11 c 38.281043 -115.668395 1561.86875 ex \n", - "56 CONUS South NVR11 c 38.281043 -115.668395 1561.86875 ey \n", - "57 CONUS South NVR11 c 38.281043 -115.668395 1561.86875 hx \n", - "58 CONUS South NVR11 c 38.281043 -115.668395 1561.86875 hy \n", - "59 CONUS South NVR11 c 38.281043 -115.668395 1561.86875 hz \n", - "60 CONUS South NVR11 d 38.281043 -115.668395 1561.86875 ex \n", - "61 CONUS South NVR11 d 38.281043 -115.668395 1561.86875 ey \n", - "62 CONUS South NVR11 d 38.281043 -115.668395 1561.86875 hx \n", - "63 CONUS South NVR11 d 38.281043 -115.668395 1561.86875 hy \n", - "64 CONUS South NVR11 d 38.281043 -115.668395 1561.86875 hz \n", - "65 CONUS South NVR11 e 38.281043 -115.668395 1561.86875 ex \n", - "66 CONUS South NVR11 e 38.281043 -115.668395 1561.86875 ey \n", - "67 CONUS South NVR11 e 38.281043 -115.668395 1561.86875 hx \n", - "68 CONUS South NVR11 e 38.281043 -115.668395 1561.86875 hy \n", - "69 CONUS South NVR11 e 38.281043 -115.668395 1561.86875 hz \n", - "70 CONUS South REV06 a 35.712621 -119.466414 61.05000 ex \n", - "71 CONUS South REV06 a 35.712621 -119.466414 61.05000 ey \n", - "72 CONUS South REV06 a 35.712621 -119.466414 61.05000 hx \n", - "73 CONUS South REV06 a 35.712621 -119.466414 61.05000 hy \n", - "74 CONUS South REV06 a 35.712621 -119.466414 61.05000 hz \n", - "75 CONUS South REV06 b 35.712621 -119.466414 61.05000 ex \n", - "76 CONUS South REV06 b 35.712621 -119.466414 61.05000 ey \n", - "77 CONUS South REV06 b 35.712621 -119.466414 61.05000 hx \n", - "78 CONUS South REV06 b 35.712621 -119.466414 61.05000 hy \n", - "79 CONUS South REV06 b 35.712621 -119.466414 61.05000 hz \n", - "80 CONUS South REV06 c 35.712621 -119.466414 61.05000 ex \n", - "81 CONUS South REV06 c 35.712621 -119.466414 61.05000 ey \n", - "82 CONUS South REV06 c 35.712621 -119.466414 61.05000 hx \n", - "83 CONUS South REV06 c 35.712621 -119.466414 61.05000 hy \n", - "84 CONUS South REV06 c 35.712621 -119.466414 61.05000 hz \n", - "\n", - " start end n_samples \\\n", - "0 2020-06-02 18:41:43+00:00 2020-06-02 22:07:46+00:00 12364 \n", - "1 2020-06-02 18:41:43+00:00 2020-06-02 22:07:46+00:00 12364 \n", - "2 2020-06-02 18:41:43+00:00 2020-06-02 22:07:46+00:00 12364 \n", - "3 2020-06-02 18:41:43+00:00 2020-06-02 22:07:46+00:00 12364 \n", - "4 2020-06-02 18:41:43+00:00 2020-06-02 22:07:46+00:00 12364 \n", - "5 2020-06-02 22:24:55+00:00 2020-06-12 17:52:23+00:00 847649 \n", - "6 2020-06-02 22:24:55+00:00 2020-06-12 17:52:23+00:00 847649 \n", - "7 2020-06-02 22:24:55+00:00 2020-06-12 17:52:23+00:00 847649 \n", - "8 2020-06-02 22:24:55+00:00 2020-06-12 17:52:23+00:00 847649 \n", - "9 2020-06-02 22:24:55+00:00 2020-06-12 17:52:23+00:00 847649 \n", - "10 2020-06-12 18:32:17+00:00 2020-07-01 17:32:59+00:00 1638043 \n", - "11 2020-06-12 18:32:17+00:00 2020-07-01 17:32:59+00:00 1638043 \n", - "12 2020-06-12 18:32:17+00:00 2020-07-01 17:32:59+00:00 1638043 \n", - "13 2020-06-12 18:32:17+00:00 2020-07-01 17:32:59+00:00 1638043 \n", - "14 2020-06-12 18:32:17+00:00 2020-07-01 17:32:59+00:00 1638043 \n", - "15 2020-07-01 19:36:55+00:00 2020-07-13 21:46:12+00:00 1044558 \n", - "16 2020-07-01 19:36:55+00:00 2020-07-13 21:46:12+00:00 1044558 \n", - "17 2020-07-01 19:36:55+00:00 2020-07-13 21:46:12+00:00 1044558 \n", - "18 2020-07-01 19:36:55+00:00 2020-07-13 21:46:12+00:00 1044558 \n", - "19 2020-07-01 19:36:55+00:00 2020-07-13 21:46:12+00:00 1044558 \n", - "20 2020-06-09 23:21:35+00:00 2020-06-09 23:54:43+00:00 1989 \n", - "21 2020-06-09 23:21:35+00:00 2020-06-09 23:54:43+00:00 1989 \n", - "22 2020-06-09 23:21:35+00:00 2020-06-09 23:54:43+00:00 1989 \n", - "23 2020-06-09 23:21:35+00:00 2020-06-09 23:54:43+00:00 1989 \n", - "24 2020-06-09 23:21:35+00:00 2020-06-09 23:54:43+00:00 1989 \n", - "25 2020-06-10 03:20:38+00:00 2020-06-10 03:36:12+00:00 935 \n", - "26 2020-06-10 03:20:38+00:00 2020-06-10 03:36:12+00:00 935 \n", - "27 2020-06-10 03:20:38+00:00 2020-06-10 03:36:12+00:00 935 \n", - "28 2020-06-10 03:20:38+00:00 2020-06-10 03:36:12+00:00 935 \n", - "29 2020-06-10 03:20:38+00:00 2020-06-10 03:36:12+00:00 935 \n", - "30 2020-06-10 03:50:04+00:00 2020-06-23 17:35:37+00:00 1172734 \n", - "31 2020-06-10 03:50:04+00:00 2020-06-23 17:35:37+00:00 1172734 \n", - "32 2020-06-10 03:50:04+00:00 2020-06-23 17:35:37+00:00 1172734 \n", - "33 2020-06-10 03:50:04+00:00 2020-06-23 17:35:37+00:00 1172734 \n", - "34 2020-06-10 03:50:04+00:00 2020-06-23 17:35:37+00:00 1172734 \n", - "35 2020-06-23 18:38:51+00:00 2020-07-06 16:31:12+00:00 1115542 \n", - "36 2020-06-23 18:38:51+00:00 2020-07-06 16:31:12+00:00 1115542 \n", - "37 2020-06-23 18:38:51+00:00 2020-07-06 16:31:12+00:00 1115542 \n", - "38 2020-06-23 18:38:51+00:00 2020-07-06 16:31:12+00:00 1115542 \n", - "39 2020-06-23 18:38:51+00:00 2020-07-06 16:31:12+00:00 1115542 \n", - "40 2020-06-12 21:10:38+00:00 2020-06-12 21:59:40+00:00 2943 \n", - "41 2020-06-12 21:10:38+00:00 2020-06-12 21:59:40+00:00 2943 \n", - "42 2020-06-12 21:10:38+00:00 2020-06-12 21:59:40+00:00 2943 \n", - "43 2020-06-12 21:10:38+00:00 2020-06-12 21:59:40+00:00 2943 \n", - "44 2020-06-12 21:10:38+00:00 2020-06-12 21:59:40+00:00 2943 \n", - "45 2020-06-12 22:13:24+00:00 2020-06-26 19:35:21+00:00 1200118 \n", - "46 2020-06-12 22:13:24+00:00 2020-06-26 19:35:21+00:00 1200118 \n", - "47 2020-06-12 22:13:24+00:00 2020-06-26 19:35:21+00:00 1200118 \n", - "48 2020-06-12 22:13:24+00:00 2020-06-26 19:35:21+00:00 1200118 \n", - "49 2020-06-12 22:13:24+00:00 2020-06-26 19:35:21+00:00 1200118 \n", - "50 2020-06-26 22:04:35+00:00 2020-06-27 17:16:51+00:00 69137 \n", - "51 2020-06-26 22:04:35+00:00 2020-06-27 17:16:51+00:00 69137 \n", - "52 2020-06-26 22:04:35+00:00 2020-06-27 17:16:51+00:00 69137 \n", - "53 2020-06-26 22:04:35+00:00 2020-06-27 17:16:51+00:00 69137 \n", - "54 2020-06-26 22:04:35+00:00 2020-06-27 17:16:51+00:00 69137 \n", - "55 2020-06-27 18:32:12+00:00 2020-07-10 18:17:08+00:00 1122297 \n", - "56 2020-06-27 18:32:12+00:00 2020-07-10 18:17:08+00:00 1122297 \n", - "57 2020-06-27 18:32:12+00:00 2020-07-10 18:17:08+00:00 1122297 \n", - "58 2020-06-27 18:32:12+00:00 2020-07-10 18:17:08+00:00 1122297 \n", - "59 2020-06-27 18:32:12+00:00 2020-07-10 18:17:08+00:00 1122297 \n", - "60 2020-07-10 19:18:48+00:00 2020-07-23 21:19:08+00:00 1130421 \n", - "61 2020-07-10 19:18:48+00:00 2020-07-23 21:19:08+00:00 1130421 \n", - "62 2020-07-10 19:18:48+00:00 2020-07-23 21:19:08+00:00 1130421 \n", - "63 2020-07-10 19:18:48+00:00 2020-07-23 21:19:08+00:00 1130421 \n", - "64 2020-07-10 19:18:48+00:00 2020-07-23 21:19:08+00:00 1130421 \n", - "65 2020-08-06 21:19:09+00:00 2020-08-06 21:25:59+00:00 411 \n", - "66 2020-08-06 21:19:09+00:00 2020-08-06 21:25:59+00:00 411 \n", - "67 2020-08-06 21:19:09+00:00 2020-08-06 21:25:59+00:00 411 \n", - "68 2020-08-06 21:19:09+00:00 2020-08-06 21:25:59+00:00 411 \n", - "69 2020-08-06 21:19:09+00:00 2020-08-06 21:25:59+00:00 411 \n", - "70 2020-06-06 18:38:28+00:00 2020-06-06 20:12:26+00:00 5639 \n", - "71 2020-06-06 18:38:28+00:00 2020-06-06 20:12:26+00:00 5639 \n", - "72 2020-06-06 18:38:28+00:00 2020-06-06 20:12:26+00:00 5639 \n", - "73 2020-06-06 18:38:28+00:00 2020-06-06 20:12:26+00:00 5639 \n", - "74 2020-06-06 18:38:28+00:00 2020-06-06 20:12:26+00:00 5639 \n", - "75 2020-06-06 20:24:28+00:00 2020-06-22 18:33:58+00:00 1375771 \n", - "76 2020-06-06 20:24:28+00:00 2020-06-22 18:33:58+00:00 1375771 \n", - "77 2020-06-06 20:24:28+00:00 2020-06-22 18:33:58+00:00 1375771 \n", - "78 2020-06-06 20:24:28+00:00 2020-06-22 18:33:58+00:00 1375771 \n", - "79 2020-06-06 20:24:28+00:00 2020-06-22 18:33:58+00:00 1375771 \n", - "80 2020-06-22 20:30:36+00:00 2020-07-05 18:10:47+00:00 1114812 \n", - "81 2020-06-22 20:30:36+00:00 2020-07-05 18:10:47+00:00 1114812 \n", - "82 2020-06-22 20:30:36+00:00 2020-07-05 18:10:47+00:00 1114812 \n", - "83 2020-06-22 20:30:36+00:00 2020-07-05 18:10:47+00:00 1114812 \n", - "84 2020-06-22 20:30:36+00:00 2020-07-05 18:10:47+00:00 1114812 \n", - "\n", - " sample_rate measurement_type azimuth tilt units \\\n", - "0 1.0 electric 13.2 0.0 digital counts \n", - "1 1.0 electric 103.2 0.0 digital counts \n", - "2 1.0 magnetic 13.2 0.0 digital counts \n", - "3 1.0 magnetic 103.2 0.0 digital counts \n", - "4 1.0 magnetic 0.0 90.0 digital counts \n", - "5 1.0 electric 13.2 0.0 digital counts \n", - "6 1.0 electric 103.2 0.0 digital counts \n", - "7 1.0 magnetic 13.2 0.0 digital counts \n", - "8 1.0 magnetic 103.2 0.0 digital counts \n", - "9 1.0 magnetic 0.0 90.0 digital counts \n", - "10 1.0 electric 13.2 0.0 digital counts \n", - "11 1.0 electric 103.2 0.0 digital counts \n", - "12 1.0 magnetic 13.2 0.0 digital counts \n", - "13 1.0 magnetic 103.2 0.0 digital counts \n", - "14 1.0 magnetic 0.0 90.0 digital counts \n", - "15 1.0 electric 13.2 0.0 digital counts \n", - "16 1.0 electric 103.2 0.0 digital counts \n", - "17 1.0 magnetic 13.2 0.0 digital counts \n", - "18 1.0 magnetic 103.2 0.0 digital counts \n", - "19 1.0 magnetic 0.0 90.0 digital counts \n", - "20 1.0 electric 12.3 0.0 digital counts \n", - "21 1.0 electric 102.3 0.0 digital counts \n", - "22 1.0 magnetic 12.3 0.0 digital counts \n", - "23 1.0 magnetic 102.3 0.0 digital counts \n", - "24 1.0 magnetic 0.0 90.0 digital counts \n", - "25 1.0 electric 12.3 0.0 digital counts \n", - "26 1.0 electric 102.3 0.0 digital counts \n", - "27 1.0 magnetic 12.3 0.0 digital counts \n", - "28 1.0 magnetic 102.3 0.0 digital counts \n", - "29 1.0 magnetic 0.0 90.0 digital counts \n", - "30 1.0 electric 12.3 0.0 digital counts \n", - "31 1.0 electric 102.3 0.0 digital counts \n", - "32 1.0 magnetic 12.3 0.0 digital counts \n", - "33 1.0 magnetic 102.3 0.0 digital counts \n", - "34 1.0 magnetic 0.0 90.0 digital counts \n", - "35 1.0 electric 12.3 0.0 digital counts \n", - "36 1.0 electric 102.3 0.0 digital counts \n", - "37 1.0 magnetic 12.3 0.0 digital counts \n", - "38 1.0 magnetic 102.3 0.0 digital counts \n", - "39 1.0 magnetic 0.0 90.0 digital counts \n", - "40 1.0 electric 0.0 0.0 counts \n", - "41 1.0 electric 0.0 0.0 counts \n", - "42 1.0 magnetic 0.0 0.0 counts \n", - "43 1.0 magnetic 0.0 0.0 counts \n", - "44 1.0 magnetic 0.0 0.0 counts \n", - "45 1.0 electric 12.0 0.0 digital counts \n", - "46 1.0 electric 102.0 0.0 digital counts \n", - "47 1.0 magnetic 12.0 0.0 digital counts \n", - "48 1.0 magnetic 102.0 0.0 digital counts \n", - "49 1.0 magnetic 0.0 90.0 digital counts \n", - "50 1.0 electric 12.0 0.0 digital counts \n", - "51 1.0 electric 102.0 0.0 digital counts \n", - "52 1.0 magnetic 12.0 0.0 digital counts \n", - "53 1.0 magnetic 102.0 0.0 digital counts \n", - "54 1.0 magnetic 0.0 90.0 digital counts \n", - "55 1.0 electric 12.0 0.0 digital counts \n", - "56 1.0 electric 102.0 0.0 digital counts \n", - "57 1.0 magnetic 12.0 0.0 digital counts \n", - "58 1.0 magnetic 102.0 0.0 digital counts \n", - "59 1.0 magnetic 0.0 90.0 digital counts \n", - "60 1.0 electric 12.0 0.0 digital counts \n", - "61 1.0 electric 102.0 0.0 digital counts \n", - "62 1.0 magnetic 12.0 0.0 digital counts \n", - "63 1.0 magnetic 102.0 0.0 digital counts \n", - "64 1.0 magnetic 0.0 90.0 digital counts \n", - "65 1.0 electric 12.0 0.0 digital counts \n", - "66 1.0 electric 102.0 0.0 digital counts \n", - "67 1.0 magnetic 12.0 0.0 digital counts \n", - "68 1.0 magnetic 102.0 0.0 digital counts \n", - "69 1.0 magnetic 0.0 90.0 digital counts \n", - "70 1.0 electric 12.4 0.0 digital counts \n", - "71 1.0 electric 102.4 0.0 digital counts \n", - "72 1.0 magnetic 12.4 0.0 digital counts \n", - "73 1.0 magnetic 102.4 0.0 digital counts \n", - "74 1.0 magnetic 0.0 90.0 digital counts \n", - "75 1.0 electric 12.4 0.0 digital counts \n", - "76 1.0 electric 102.4 0.0 digital counts \n", - "77 1.0 magnetic 12.4 0.0 digital counts \n", - "78 1.0 magnetic 102.4 0.0 digital counts \n", - "79 1.0 magnetic 0.0 90.0 digital counts \n", - "80 1.0 electric 12.4 0.0 digital counts \n", - "81 1.0 electric 102.4 0.0 digital counts \n", - "82 1.0 magnetic 12.4 0.0 digital counts \n", - "83 1.0 magnetic 102.4 0.0 digital counts \n", - "84 1.0 magnetic 0.0 90.0 digital counts \n", - "\n", - " hdf5_reference run_hdf5_reference station_hdf5_reference \n", - "0 \n", - "1 \n", - "2 \n", - "3 \n", - "4 \n", - "5 \n", - "6 \n", - "7 \n", - "8 \n", - "9 \n", - "10 \n", - "11 \n", - "12 \n", - "13 \n", - "14 \n", - "15 \n", - "16 \n", - "17 \n", - "18 \n", - "19 \n", - "20 \n", - "21 \n", - "22 \n", - "23 \n", - "24 \n", - "25 \n", - "26 \n", - "27 \n", - "28 \n", - "29 \n", - "30 \n", - "31 \n", - "32 \n", - "33 \n", - "34 \n", - "35 \n", - "36 \n", - "37 \n", - "38 \n", - "39 \n", - "40 \n", - "41 \n", - "42 \n", - "43 \n", - "44 \n", - "45 \n", - "46 \n", - "47 \n", - "48 \n", - "49 \n", - "50 \n", - "51 \n", - "52 \n", - "53 \n", - "54 \n", - 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"text": [ - "2022-10-15 18:22:26,542 [line 753] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing 8P_CAS04_CAV07_NVR11_REV06.h5\n" - ] - }, - { - "data": { - "text/html": [ - "
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surveystation_idrun_idstartend
0CONUS SouthCAS04a2020-06-02 18:41:43+00:002020-06-02 22:07:46+00:00
1CONUS SouthCAS04b2020-06-02 22:24:55+00:002020-06-12 17:52:23+00:00
2CONUS SouthCAS04c2020-06-12 18:32:17+00:002020-07-01 17:32:59+00:00
3CONUS SouthCAS04d2020-07-01 19:36:55+00:002020-07-13 21:46:12+00:00
4CONUS SouthCAV07a2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:00
5CONUS SouthCAV07b2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:00
6CONUS SouthCAV07c2020-06-10 03:50:04+00:002020-06-23 17:35:37+00:00
7CONUS SouthCAV07d2020-06-23 18:38:51+00:002020-07-06 16:31:12+00:00
8CONUS SouthNVR11none2020-06-12 21:10:38+00:002020-06-12 21:59:40+00:00
9CONUS SouthNVR11a2020-06-12 22:13:24+00:002020-06-26 19:35:21+00:00
10CONUS SouthNVR11b2020-06-26 22:04:35+00:002020-06-27 17:16:51+00:00
11CONUS SouthNVR11c2020-06-27 18:32:12+00:002020-07-10 18:17:08+00:00
12CONUS SouthNVR11d2020-07-10 19:18:48+00:002020-07-23 21:19:08+00:00
13CONUS SouthNVR11e2020-08-06 21:19:09+00:002020-08-06 21:25:59+00:00
14CONUS SouthREV06a2020-06-06 18:38:28+00:002020-06-06 20:12:26+00:00
15CONUS SouthREV06b2020-06-06 20:24:28+00:002020-06-22 18:33:58+00:00
16CONUS SouthREV06c2020-06-22 20:30:36+00:002020-07-05 18:10:47+00:00
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" - ], - "text/plain": [ - " survey station_id run_id start \\\n", - "0 CONUS South CAS04 a 2020-06-02 18:41:43+00:00 \n", - "1 CONUS South CAS04 b 2020-06-02 22:24:55+00:00 \n", - "2 CONUS South CAS04 c 2020-06-12 18:32:17+00:00 \n", - "3 CONUS South CAS04 d 2020-07-01 19:36:55+00:00 \n", - "4 CONUS South CAV07 a 2020-06-09 23:21:35+00:00 \n", - "5 CONUS South CAV07 b 2020-06-10 03:20:38+00:00 \n", - "6 CONUS South CAV07 c 2020-06-10 03:50:04+00:00 \n", - "7 CONUS South CAV07 d 2020-06-23 18:38:51+00:00 \n", - "8 CONUS South NVR11 none 2020-06-12 21:10:38+00:00 \n", - "9 CONUS South NVR11 a 2020-06-12 22:13:24+00:00 \n", - "10 CONUS South NVR11 b 2020-06-26 22:04:35+00:00 \n", - "11 CONUS South NVR11 c 2020-06-27 18:32:12+00:00 \n", - "12 CONUS South NVR11 d 2020-07-10 19:18:48+00:00 \n", - "13 CONUS South NVR11 e 2020-08-06 21:19:09+00:00 \n", - "14 CONUS South REV06 a 2020-06-06 18:38:28+00:00 \n", - "15 CONUS South REV06 b 2020-06-06 20:24:28+00:00 \n", - "16 CONUS South REV06 c 2020-06-22 20:30:36+00:00 \n", - "\n", - " end \n", - "0 2020-06-02 22:07:46+00:00 \n", - "1 2020-06-12 17:52:23+00:00 \n", - "2 2020-07-01 17:32:59+00:00 \n", - "3 2020-07-13 21:46:12+00:00 \n", - "4 2020-06-09 23:54:43+00:00 \n", - "5 2020-06-10 03:36:12+00:00 \n", - "6 2020-06-23 17:35:37+00:00 \n", - "7 2020-07-06 16:31:12+00:00 \n", - "8 2020-06-12 21:59:40+00:00 \n", - "9 2020-06-26 19:35:21+00:00 \n", - "10 2020-06-27 17:16:51+00:00 \n", - "11 2020-07-10 18:17:08+00:00 \n", - "12 2020-07-23 21:19:08+00:00 \n", - "13 2020-08-06 21:25:59+00:00 \n", - "14 2020-06-06 20:12:26+00:00 \n", - "15 2020-06-22 18:33:58+00:00 \n", - "16 2020-07-05 18:10:47+00:00 " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mth5_run_summary = RunSummary()\n", - "mth5_run_summary.from_mth5s([mth5_path,])\n", - "run_summary = mth5_run_summary.clone()\n", - "run_summary.mini_summary" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here we can see that the run summary is much more interesting than the synthetic example. We have four stations and each station has mulitple runs.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Select Stations to Process" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Process CAS04, with respect to CAV07" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Define a Kernel Dataset\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "local_station_id = \"CAS04\"\n", - "remote_station_id = \"CAV07\" " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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0CONUS SouthCAS04b2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:00
1CONUS SouthCAV07a2020-06-09 23:21:35+00:002020-06-09 23:54:43+00:00
2CONUS SouthCAS04b2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:00
3CONUS SouthCAV07b2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:00
4CONUS SouthCAS04b2020-06-10 03:50:04+00:002020-06-12 17:52:23+00:00
5CONUS SouthCAV07c2020-06-10 03:50:04+00:002020-06-12 17:52:23+00:00
6CONUS SouthCAS04c2020-06-12 18:32:17+00:002020-06-23 17:35:37+00:00
7CONUS SouthCAV07c2020-06-12 18:32:17+00:002020-06-23 17:35:37+00:00
8CONUS SouthCAS04c2020-06-23 18:38:51+00:002020-07-01 17:32:59+00:00
9CONUS SouthCAV07d2020-06-23 18:38:51+00:002020-07-01 17:32:59+00:00
10CONUS SouthCAS04d2020-07-01 19:36:55+00:002020-07-06 16:31:12+00:00
11CONUS SouthCAV07d2020-07-01 19:36:55+00:002020-07-06 16:31:12+00:00
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" - ], - "text/plain": [ - " survey station_id run_id start \\\n", - "0 CONUS South CAS04 b 2020-06-09 23:21:35+00:00 \n", - "1 CONUS South CAV07 a 2020-06-09 23:21:35+00:00 \n", - "2 CONUS South CAS04 b 2020-06-10 03:20:38+00:00 \n", - "3 CONUS South CAV07 b 2020-06-10 03:20:38+00:00 \n", - "4 CONUS South CAS04 b 2020-06-10 03:50:04+00:00 \n", - "5 CONUS South CAV07 c 2020-06-10 03:50:04+00:00 \n", - "6 CONUS South CAS04 c 2020-06-12 18:32:17+00:00 \n", - "7 CONUS South CAV07 c 2020-06-12 18:32:17+00:00 \n", - "8 CONUS South CAS04 c 2020-06-23 18:38:51+00:00 \n", - "9 CONUS South CAV07 d 2020-06-23 18:38:51+00:00 \n", - "10 CONUS South CAS04 d 2020-07-01 19:36:55+00:00 \n", - "11 CONUS South CAV07 d 2020-07-01 19:36:55+00:00 \n", - "\n", - " end \n", - "0 2020-06-09 23:54:43+00:00 \n", - "1 2020-06-09 23:54:43+00:00 \n", - "2 2020-06-10 03:36:12+00:00 \n", - "3 2020-06-10 03:36:12+00:00 \n", - "4 2020-06-12 17:52:23+00:00 \n", - "5 2020-06-12 17:52:23+00:00 \n", - "6 2020-06-23 17:35:37+00:00 \n", - "7 2020-06-23 17:35:37+00:00 \n", - "8 2020-07-01 17:32:59+00:00 \n", - "9 2020-07-01 17:32:59+00:00 \n", - "10 2020-07-06 16:31:12+00:00 \n", - "11 2020-07-06 16:31:12+00:00 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "kernel_dataset = KernelDataset()\n", - "kernel_dataset.from_run_summary(run_summary, local_station_id, remote_station_id)\n", - "kernel_dataset.mini_summary" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "THere are som short runs here, see the \"duration\" column in the full df:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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surveystation_idrun_idstartendsample_rateinput_channelsoutput_channelschannel_scale_factorsmth5_pathremoteduration
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2CONUS SouthCAS04b2020-06-10 03:20:38+00:002020-06-10 03:36:12+00:001.0[hx, hy][ex, ey, hz]{'ex': 1.0, 'ey': 1.0, 'hx': 1.0, 'hy': 1.0, '...8P_CAS04_CAV07_NVR11_REV06.h5False934.0
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4CONUS SouthCAS04b2020-06-10 03:50:04+00:002020-06-12 17:52:23+00:001.0[hx, hy][ex, ey, hz]{'ex': 1.0, 'ey': 1.0, 'hx': 1.0, 'hy': 1.0, '...8P_CAS04_CAV07_NVR11_REV06.h5False223339.0
5CONUS SouthCAV07c2020-06-10 03:50:04+00:002020-06-12 17:52:23+00:001.0[hx, hy][ex, ey, hz]{'ex': 1.0, 'ey': 1.0, 'hx': 1.0, 'hy': 1.0, '...8P_CAS04_CAV07_NVR11_REV06.h5True223339.0
6CONUS SouthCAS04c2020-06-12 18:32:17+00:002020-06-23 17:35:37+00:001.0[hx, hy][ex, ey, hz]{'ex': 1.0, 'ey': 1.0, 'hx': 1.0, 'hy': 1.0, '...8P_CAS04_CAV07_NVR11_REV06.h5False947000.0
7CONUS SouthCAV07c2020-06-12 18:32:17+00:002020-06-23 17:35:37+00:001.0[hx, hy][ex, ey, hz]{'ex': 1.0, 'ey': 1.0, 'hx': 1.0, 'hy': 1.0, '...8P_CAS04_CAV07_NVR11_REV06.h5True947000.0
8CONUS SouthCAS04c2020-06-23 18:38:51+00:002020-07-01 17:32:59+00:001.0[hx, hy][ex, ey, hz]{'ex': 1.0, 'ey': 1.0, 'hx': 1.0, 'hy': 1.0, '...8P_CAS04_CAV07_NVR11_REV06.h5False687248.0
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surveystation_idrun_idstartend
0CONUS SouthCAS04b2020-06-10 03:50:04+00:002020-06-12 17:52:23+00:00
1CONUS SouthCAV07c2020-06-10 03:50:04+00:002020-06-12 17:52:23+00:00
2CONUS SouthCAS04c2020-06-12 18:32:17+00:002020-06-23 17:35:37+00:00
3CONUS SouthCAV07c2020-06-12 18:32:17+00:002020-06-23 17:35:37+00:00
4CONUS SouthCAS04c2020-06-23 18:38:51+00:002020-07-01 17:32:59+00:00
5CONUS SouthCAV07d2020-06-23 18:38:51+00:002020-07-01 17:32:59+00:00
6CONUS SouthCAS04d2020-07-01 19:36:55+00:002020-07-06 16:31:12+00:00
7CONUS SouthCAV07d2020-07-01 19:36:55+00:002020-07-06 16:31:12+00:00
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" - ], - "text/plain": [ - " survey station_id run_id start \\\n", - "0 CONUS South CAS04 b 2020-06-10 03:50:04+00:00 \n", - "1 CONUS South CAV07 c 2020-06-10 03:50:04+00:00 \n", - "2 CONUS South CAS04 c 2020-06-12 18:32:17+00:00 \n", - "3 CONUS South CAV07 c 2020-06-12 18:32:17+00:00 \n", - "4 CONUS South CAS04 c 2020-06-23 18:38:51+00:00 \n", - "5 CONUS South CAV07 d 2020-06-23 18:38:51+00:00 \n", - "6 CONUS South CAS04 d 2020-07-01 19:36:55+00:00 \n", - "7 CONUS South CAV07 d 2020-07-01 19:36:55+00:00 \n", - "\n", - " end \n", - "0 2020-06-12 17:52:23+00:00 \n", - "1 2020-06-12 17:52:23+00:00 \n", - "2 2020-06-23 17:35:37+00:00 \n", - "3 2020-06-23 17:35:37+00:00 \n", - "4 2020-07-01 17:32:59+00:00 \n", - "5 2020-07-01 17:32:59+00:00 \n", - "6 2020-07-06 16:31:12+00:00 \n", - "7 2020-07-06 16:31:12+00:00 " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "kernel_dataset.mini_summary" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Now define the processing Configuration\n", - "\n", - "The only things we need to provide are our band processing scheme, and the data sample rate to generate a default processing configuration.\n", - "\n", - "The config is then told about the stations via the kernel dataset.\n", - "\n", - "**When doing only single station processing you need to specify RME processing (rather than remote reference processing which expects extra time series from another station)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Bands not defined; setting to EMTF BANDS_DEFAULT_FILE\n", - "/home/kkappler/software/irismt/aurora/aurora/config/emtf_band_setup/bs_test.cfg\n", - "OK\n" - ] - } - ], - "source": [ - "cc = ConfigCreator()\n", - "config = cc.create_from_kernel_dataset(kernel_dataset)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "for decimation in config.decimations:\n", - " decimation.window.type = \"hamming\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Call process_mth5" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DATASET DF POPULATED\n", - "Processing config indicates 4 decimation levels \n", - "DATASET DF UPDATED\n", - "Processing band 25.728968s\n", - "Processing band 19.929573s\n", - "Processing band 15.164131s\n", - "Processing band 11.746086s\n", - "Processing band 9.195791s\n", - "Processing band 7.362526s\n", - "Processing band 5.856115s\n", - "Processing band 4.682492s\n" - ] - }, - { - "data": { - "image/png": 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\n", 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77kmehJYsiab966+P/iR+RUV65dKzKDlItzdvXjDt0twc/MzETXaZTkKZGAXdfnt2RlVSmJQcRCKS6SQUdQLK1qhKCpNOSIuI9FA6IS0iImkp6OSgJbtFRDKjoJODa8luEZGMKOjkICIimaHkICIiIUoOIiISouQgIiIhSg4iIhKi5CAiIiFKDiIiEqLkICIiIUoOIiIS0jvXAbRlZgOBfwMOA792dz2mXUQky7IycjCz+8xst5ltalM+y8zqzWyLmd0UK54NrHT3RcBXshGfiIi0lq1ppfuBWYkFZtYL+Ffgy8Ak4AozmwScDHwQq3YsS/GJiEiCrEwruftqM6tsU3wWsMXd3wUws58ClwI7CBLEa7STvMysBqiJvT1gZvURh51MGVBoS8DmQ8zZiCHqPqJoryttdGbfdPcZDuxNsw/Jj39T6UoVc8qHwubynMNoPhshQJAUzgZ+ANxtZn8EPJlqZ3evBWozGmEbZlbr7jXHr5k/8iHmbMQQdR9RtNeVNjqzb7r7mNnaVA96kdTy4d9UujoTcy6TgyUpc3c/CHwz28F0UMpklcfyIeZsxBB1H1G015U2OrNvPvy37gkK8e+cdsxZe0xobFrpKXefEnt/DnCbu/9h7P3NAO7+vawEJNLDaeQg7cnlfQ6vAqea2Vgz6wt8A/h5DuMR6WmyOi0rhSVbl7I+CLwMnGZmO8zsGnc/ClwLrAI2Aw+5+5vZiEdE4uftRJLK2rSSiIgUDi2fISIiIUoOIiISouQgIiIhSg4iAoCZfdXM7jWzJ8xsZq7jkdxSchDpxtJZ9NLdH48teLkQmJuDcCWPKDmIdG/30/FFL1v8dWy79GBKDiLdmLuvBva1KY4veunuh4GfApda4B+Ap919fbZjlfySdw/7EZGMS7Xo5XXAhUCZmY139x/lIjjJD0oOIj1PqkUvf0CwKrKIppVEeqAdwJiE9ycDO3MUi+QpJQeRnkeLXspxKTmIdGNa9FI6SwvviYhISLc4IT18+HCvrKzMdRgiIgVl3bp1e919RLJt3SI5VFZWsnbt2lyHISJSUMxsW6ptOucgIiIhSg4iIhKi5CAiIiFKDiIiEqLkICIiIUoOIiISouQgIiIhSg4iIhKi5CAiIiFKDhnW1NTEnXfeyTnnnENZWRkDBgzg1FNP5ZprrmHz5s3xep9++ilDhgzBzDAzbrjhhqTtrVy5knPPPZehQ4cyYMAATj75ZC644AKWL1/eqt6WLVuYM2cOQ4cOpX///kyfPp0HH3wwZZw33HBDvO/q6upoPryIFC53L/jXmWee6flo3759Pm3aNAcc8JKSEp86daoPHjzYAb/zzjvjdR944IF4PcBHjhzpR44cadXe448/Ht8+atQonzZtmo8cOdIBX7BgQbzezp07/YQTTnDABw0a5GPHjo3vt2TJklCczz33nJtZvE6+/j1FJFrAWk9xXNXIIYOuvfZaNmzYAMB3vvMd9u3bx8aNG/n44495/vnnmTp1arzusmXLADjzzDMxM3bt2sXTTz/dqr2Wb/4zZsxg586drF+/no8++ogtW7awcOHCeL3vfe977N69m9LSUjZv3sy7777LZZddBsBNN93E4cOH43X37dvHVVddxSmnnML06dMz8ncQkcKTs+RgZqeZ2WsJr/1mttjMbjOz/0kovzhXMXZFQ0MDDz30EABnnHEG3//+9+nTp098+5e+9CUuuOACAD744AOee+45AG688UZmzJgBfJYwWjQ3NwNQX1/P8uXL2bJlC+7OuHHj+OIXvxiv15JUzjnnHE466SQAZs+eDcDevXtZt25dvG5NTQ27du2irq6O0tLSyD6/iBS2nCUHd6939yp3rwLOBA4Bj8U239myzd1/kasYu+Ltt9/m6NGjAJx//vmYJXtsb+DHP/4xzc3NDB48mK985SvMnz8fgKeeeoq9e/fG69XU1NCrVy8++ugjFi5cyKmnnsqoUaO4+uqr2b59e7zeBx8Ez44/4YQT4mUjR46M/95Sd+nSpTzyyCPcdtttnH322RF8ahHpLvJlWukCYKu7p1w+ttB4wkOU2ksMECQHgLlz59KvXz/mzJnDgAEDOHLkCHV1dfF6F154Ia+++ipXX301o0ePBmD37t0sW7aM888/n0OHDnUoHggSyOLFi/nCF77AzTffnPbnE5HuLV+SwzeAxEtprjWzjWZ2n5kNSbaDmdWY2VozW7tnz57sRJmG0047jd69g8dlvPjii6GDc4sXXniBLVu2ALB8+XIGDx5MeXk5TU1NQHhqadq0aSxdupQdO3bw3nvvxUcZ27dvj5/fGDMmeHb87t274/sl/j5mzBi2bt3KgQMHeOWVVxg0aBAlJSW88MILAGzYsIGSkhLeeOONLv8dRKQw5Tw5xB5w/hXg4VjRPcA4oAr4ELgj2X7uXuvu1e5ePWJE0gcZ5VRZWRmXX345EBxsb7nllvg0E8Dq1at5/vnnWx38GxsbaWhooKGhIX5+4fXXX48f9O+++24ee+wxjhw5AgQPOTr//PPj+w8aNAiAWbNmAfDyyy+zc+dOAB599FEAhg0b1upS1aamJg4ePMjBgwfjfTY3N3Pw4EGOHTsW4V9ERApKqsuYsvUCLgV+mWJbJbDpeG3k66WXbS9lLS0t9alTp/qwYcMc8L/7u7/zkpISB/y6665rtW9jY2No29y5cx3wPn36+IQJE3zSpEnxS1Crqqril77u2LHDhw8fnvRS1tra2pTxzpgxQ5eyivQg5PmlrFeQMKVkZicmbPsasCnrEUVkyJAhvPTSS9xxxx2cddZZQHCiurS0lAULFjBkyBAOHDgAfHY1UYv+/ftz8cXBhVoPPPAAhw8fZtGiRSxcuJBx48axa9cu6uvrGTVqFPPnz+fJJ5+MT2ONHj2aNWvWMHv2bMyMnTt3UlVVxYoVK1i0aFEW/wIiUqjMU8yFZ6Vzs2LgA+AUd2+Ilf2EYErJgfeBP3P3D9trp7q62vUMaRGR9JjZOndPuiRC72wHk8jdDwHD2pTNz1E4IiISkw/TSiIikmeUHEREJETJQUREQpQcREQkRMlBRERClBxERCREyUFEREKUHEREJCTy5GBmRWY2KOp2RUQkeyJJDmb2gJkNMrOBwG+BejO7IYq2RUQk+6IaOUxy9/3AV4FfAOWAlsEoEBddBGafvfr3h9NPh8WLcx2ZiORKVMmhj5n1IUgOT7j7EYKF86QAfNhmWcOmJnj7bXjrrcz01zYZtSSk2GMoRCQPRJUc/p1gBdWBwGozqwD2R9S2ZFhs1fBWmpszlxySaWqC556DhKeiikgOZWzJbjPr7e5Hj1+z67Rkd9cUFUGy/w3MgiSRCZWVsC3JE8MrKuD99zPTp4i01t6S3VGdkB5pZkvN7OnY+0nAgijalswrKUle3q9fZvpbvDh5YgDYvj36/urqgmRUVBT81OhE5Piimla6H1gFnBR7/zawOKK2JcPOPTc4cLY1blzm+kyVeMrLo+uj5dzGlVcGycg9+LlwoRKEyPFElRyGu/tDQDNAbDpJT6cvEM88A8uXB1M6ZsHPFStgU4Ye0HrXXbB0KRQXty4vLobbb89Mn4mOHoVbb818PyKFLKrkcNDMhhG7QsnMPg80RNS2ZMG8ecFcf3Nz8HPevMz3V1vbOiHV1kbb7+TJqbdlYvpKpDuJ6jGh/xv4OTDOzNYAI4A5x9vJzN4Hfkcwyjjq7tVmNhT4GVBJcAXU5e7+cURxSh6ZNy/zSahfv+BKqLainL4S6Y4iGTm4+3pgBnAu8GfAZHff2MHdv+TuVQlnzG8CnnP3U4HnYu9F0pbt6Sud+JbuJKqrlYoJDuKL3X0TUGlmf9zJ5i4Ffhz7/ccEN9aJdEo2pq8ApkwJn/i+6ird2CeFK5L7HMzsZ8A64Cp3n2JmA4CX3b3qOPu9B3xMcK7i39291sw+cffBCXU+dvchSfatAWoAysvLz9yW6tpIkSwYMAA+/TRcXloK+3U7qOSpjN/nAIxz9+8DRwDcvRGwDux3nrtPB74MfMvMvtDRDt291t2r3b16xIgRnQpaJCrJEgPA736X3ThEohJVcjgcGy20XK00DkhyGrA1d98Z+7kbeAw4C9hlZifG2jkR2B1RjCIZU1qavLx//2j70XkNyZaoksN3gWeAMWZWR3Ai+a/a28HMBppZacvvwExgE8FVTy13Vy8AnogoRpGMueee5Ce+lyyJpn3d0CfZ1uXkYGZFwBBgNrAQeBCodvdfH2fXkcCLZvY68N/Af7j7M8DfAxeZ2TvARbH3InktWye+29INfZIpUZ2QXu3uHT5fEDUtvCc9QS4WSJTuLRsnpP/TzL5jZmPMbGjLK6K2RXq8xYuhb9/k27pyQ5/OYUgqUd0hfXXs57cSyhw4JaL2RXq8sWODhzAljhKKijp/Q9+UKfDmm5+9b7k34yc/Cdbbkp4tqjukxyZ5KTGIROSuu2Dz5vACicuXd/68xtat4bLmZnjppS6FKt1EJCMHM5udpLgBeCN2maqIRCDK9ah0b4a0J6pzDtcAS4B5sde9BIvxrTGz+RH1IZmkyeceJ1v3Zkhhiio5NAOnu/tl7n4ZMIngJrizgRsj6kMyJVcLAykh5VSm782QwhZVcqh0910J73cDE9x9H7ElNSSP5WLyua4OampaJ6SamswkCCWhpHJ1b4YUhqiSwwtm9pSZLTCzBQR3Oa+O3fn8SUR9SKZke/L5oouCkcqhQ63LDx2K9o6ubN9WXIBJKNsPeZLCEdVNcEZwh/TvEyy49yLwiEfReAfoJrguGjQoeSLo3x8aG6Pvz9pZkzHKO7ra66eiIjgaRqVlJJSY8IqL9VVc8lrGb4KLJYG1BEtgLAZ+AZRE0bZkQbYnn6+/PnhEWzJRPqLt+utTb4v6OaF/+qfJR0J/8RfR9lOAoxMpTFE97GcRsBL491jRaODxKNqWLMj25HO2HtF2113BZ0km6ueEZmNqLpvnaaTHi+qcw7eA84D9AO7+DnBCRG1LNmR78jlbCen227PznNBMXxeaqfM0GolIClElhyZ3P9zyxsx6E3u2g0hK2UhI2UpCmZ6ae/bZ1Ns6O0WmZ5tKO6JKDr8xs1uAAWZ2EfAw8GREbYt0TXdIQpk4T5O4sFKL5mZYtapz7Um3EtXVSkUEd0nPJLhaaRWwRFcriUQo6iui2ruaKzv/dCXH2rtaKZK1ldy92cweBx539z1RtCkibbQkgFtvDaaSysuDcyedHZ1UVARTScnKpcfr0rSSBW4zs73AW0C9me0xs/8TTXgi0kqUU2TZOlkvBamr5xwWE1yl9HvuPszdhxKsp3Semf1lV4MTkQzS+hnSji6dczCzDcBF7r63TfkI4JfuPq2dfccAy4FRBAv31br7v5jZbcAioGV66hZ3/0V7ceicg4hI+jJ5zqFP28QA4O57zKzPcfY9Cnzb3debWSmwzsz+M7btTnf/py7GJiIindTV5HC4k9tw9w+BD2O//87MNhPcWS0iIjnW1XMOZ5jZ/iSv3wFTO9qImVUC04BXYkXXmtlGM7vPzIZ0MUYREUlTl5KDu/dy90FJXqXufrxpJQDMrAR4BFjs7vuBe4BxQBXByOKOFPvVmNlaM1u7Z4+unhURiVJUd0h3Suy8xCNAnbs/CuDuu9z9mLs3Ezxu9Kxk+7p7rbtXu3v1iBEjshe0iEgPkLPkEHsGxFJgs7v/c0L5iQnVvgZsynZsIiI9XSR3SHfSecB84A0zey1WdgtwhZlVESzc9z7wZ7kITkSkJ8tZcnD3FwnWYWqr3XsaREQk83J6zkFERPKTkoOIiIQoOYiISIiSg4iIhCg5iIhIiJKDiIiEKDmIiEiIkoOIiIQoOYiISIiSg4iIhCg5iIhIiJKDiIiEKDmIiEiIkoOIiIQoOYiISIiSg4iIhCg5iIhIiJKDiIiEKDmIiEhIXiYHM5tlZvVmtsXMbsp1PCIiPU3eJQcz6wX8K/BlYBJwhZlNym1UIiI9S94lB+AsYIu7v+vuh4GfApfmOCYRkR6ld64DSGI08EHC+x3A2W0rmVkNUBN7e8DM6rMQWxnQkIV+opQPMWcjhqj7iKK9rrTRmX3T3Wc4sDfNPiQ//k2lK1XMFal2yMfkYEnKPFTgXgvUZj6cz5hZrbvXHL9m/siHmLMRQ9R9RNFeV9rozL7p7mNma929Ov3oerZ8+DeVrs7EnI/TSjuAMQnvTwZ25iiWtp7MdQCdkA8xZyOGqPuIor2utNGZffPhv3VPUIh/57RjNvfQl/KcMrPewNvABcD/AK8Cf+Lub+Y0MJFuRiMHaU/eTSu5+1EzuxZYBfQC7lNiEMmIrE7LSmHJu5GDiIjkXj6ecxARkRxTchARkRAlBxERCVFyEBGRECUHEQHAzL5qZvea2RNmNjPX8UhuKTmIdGNmdp+Z7TazTW3KQysfu/vj7r4IWAjMzUG4kkeUHES6t/uBWYkFHVj5+K9j26UHU3IQ6cbcfTWwr01x0pWPLfAPwNPuvj7bsUp+ybs7pEUk41KtfHwdcCFQZmbj3f1HuQhO8oOSg0jPk3TlY3f/AfCDbAcj+UnTSiI9Tz6vfCx5QslBpOd5FTjVzMaaWV/gG8DPcxyT5BklB5FuzMweBF4GTjOzHWZ2jbsfBVpWPt4MPKSVj6UtrcoqIiIhGjmIiEiIkoOIiIQoOYiISIiSg4iIhCg5iIhIiJKDiIiEKDmIAGZ2zMxeM7NNZvawmRWnse9JZrYyzf5+bWbVKbatNLNT2tn3n8zsD9LpTyRdSg4igUZ3r3L3KcBh4M87spOZ9Xb3ne4+J4ogzGwy0Mvd322n2g+Bm6LoTyQVJQeRsBeA8WY2MPawnFfNbIOZXQpgZgtjo4sngV+aWWXLw3TMrL+ZLTOzN2L7fClWPsDMfmpmG83sZ8CAFH3PA56I7dPLzO6PjWbeMLO/BHD3bcAwMxuV2T+D9GRalVUkgZn1JngIzjPArcDz7n61mQ0G/tvMno1VPQf4nLvvM7PKhCa+BeDuU81sIkHymAD8BXDI3T9nZp8DUj0v4TzgwdjvVcDo2GiGWAwt1sfqPtKFjyuSkkYOIoEBZvYasBbYDiwFZgI3xcp/DfQHymP1/9Pd2z5EB+D3gZ8AuPtbwDZgAvAFYEWsfCOwMUUcJwJ7Yr+/C5xiZj80s1nA/oR6u4GT0v2QIh2lkYNIoNHdqxILzMyAy9y9vk352cDBFO0ke1ZCi44sZNZIkIRw94/N7AzgDwlGJJcDV8fq9Y/VFckIjRxEUlsFXBdLEpjZtA7ss5rgvAGx6aRyoL5N+RTgcyn23wyMj9UbDhS5+yPA3wDTE+pNADal+XlEOkzJQSS1vwX6ABtjJ5z/tgP7/BvQy8zeAH4GLHT3JuAeoMTMNgJ/Bfx3iv3/A/hi7PfRwK9j01r3AzcDmFkfggSyNv2PJNIxWrJbJI+Y2QDgV8B57n4sRZ2vAdPd/W+yGpz0KBo5iOQRd28EvkswakilN3BHdiKSnkojBxERCdHIQUREQpQcREQkRMlBRERClBxERCREyUFEREL+PxqwKV2Tr7EQAAAAAElFTkSuQmCC\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-10-15 18:23:56,278 [line 753] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing 8P_CAS04_CAV07_NVR11_REV06.h5\n", - "2022-10-15 18:23:56,554 [line 753] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing 8P_CAS04_CAV07_NVR11_REV06.h5\n" - ] - } - ], - "source": [ - "show_plot = True\n", - "tf_cls = process_mth5(config,\n", - " kernel_dataset,\n", - " units=\"MT\",\n", - " show_plot=show_plot,\n", - " z_file_path=None,\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-10-15 18:23:56,651 [line 205] mt_metadata.transfer_functions.io.readwrite.write_file - INFO: Wrote CAS04_RRCAV07.xml\n" - ] - }, - { - "data": { - "text/plain": [ - "EMTFXML(station='CAS04', latitude=37.63, longitude=-121.47, elevation=329.39)" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "xml_file_base = f\"{local_station_id}_RR{remote_station_id}.xml\"\n", - "tf_cls.write_tf_file(fn=xml_file_base, file_type=\"emtfxml\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### The Default Processing Configuration is \"tuned\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can modify some of the processing parameters. Here is an example that shows a more naive processing configuration can give less trustworthy results." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "for decimation in config.decimations:\n", - " decimation.prewhitening_type = \"\"\n", - " decimation.window.type = \"boxcar\"\n", - " decimation.extra_pre_fft_detrend_type = None\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "DATASET DF POPULATED\n", - "Processing config indicates 4 decimation levels \n", - "DATASET DF UPDATED\n", - "Processing band 25.728968s\n", - "Processing band 19.929573s\n", - "Processing band 15.164131s\n", - "Processing band 11.746086s\n", - "Processing band 9.195791s\n", - "Processing band 7.362526s\n", - "Processing band 5.856115s\n", - "Processing band 4.682492s\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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hNrYuAdCpEyxaFP2ONx3vSdoH3Q9EpAlTp8I11xy/o4XgeTrOP0jVeQ4aIUi2UAKRNquxUUGdKM8/yMR5DlpPkGygBCJplc7rId18c/rOP9B5DtIeKYFI2px5ZjCltGULuAc/r70Wpk1LTX/NHVEU5fkH6epHJNsogUjarF9/YlltLSxdmro+07VeoHUJaY90FJakjVnTr7WBf0ORnNOuj8LSiYS5pbFrLDVXLiLZLacTiE4kzC3z5mmdQKQtyekEIrlF6wQibYuuxitpVVyshCHSVmgEIiIioSiBiIhIKEogIiISihKIiIiEogQiIiKhKIGIiEgoSiAiIhJK1p0HYmbdgX8DDgGvuXsKL/gtIiJhpWUEYmYPmdkuM1vXoHyamVWa2SYzuy1WPB1Y4u5zgMvTEZ+IiCQuXVNYi4Dj7vpgZh2BfwW+BowFrjazscBgYFtss6Npik9ERBKUliksd19uZoUNis8GNrn7RwBm9kvgCmA7QRJ5h2YSnJmVAqWxp/vNrDLCkAuAZC/xm0wbYesmUq8fsCdEH+1dFP8b6ZbpmNPRfyr6yMX9QKJ1RifY/vHcPS0PoBBYV+/5DODBes9nAfcC3YGFwH1AcbriaxBrWSbbCFs3kXpARSY+21x/RPG/0d5iTkf/qegjF/cDidZJdj+QyUX0xm4v5O5eDXw33cE08EKG2whbN4q4pXm5+BlnOuZ09J+KPnJxP5DWv3Xa7kgYm8J60d3PjD0/D7jL3b8ae347gLv/NC0BtXNmVuFJ3IlMRHJfsvuBTJ4HshI43cyGm9lJwLeB5zMYT3tTlukARCTjktoPpGUEYmaPAxcSLNzuBH7s7gvM7DJgPtAReMjddW86EZEckbYpLBERaVt0KRMREQlFCUREREJRAhERkVCUQAQAM/uGmT1gZs+Z2aWZjkdE0svMzjCz+81siZnd0Jo6SiBtWCIXsXT3Zz24gGUJMDMD4YpIxBLcB2xw9+8DVwGtOjdECaRtW0TrL2JZ529jr4tI7ltEAvsAM7sceANY1prGlUDaMHdfDuxtUBy/iKW7HwJ+CVxhgX8EXnL31emOVUSil8g+ILb98+7+JaC4Ne1n3Q2lJOUGcexy+RBc/fgc4CbgEqDAzEa6+/2ZCE5EUq7RfYCZXUhwP6YuwK9a05ASSPvT1EUsfw78PN3BiEjaNbUPeA14LZGGNIXV/mwHhtR7PhjYkaFYRCT9ItsHKIG0P7qIpUj7Ftk+QAmkDYtdxPItYLSZbTez6939CHAjsBTYADzh7uszGaeIpEaq9wG6mKKIiITSJhbR+/Xr54WFhZkOQ0Qkp6xatWqPu/cPW79NJJDCwkIqKioyHYaISE4xsy3J1NcaiIiIhKIEIiIioSiBiIhIKEogIiISihKIiIiEogQiIiKhKIGIiEgoSiAiIhKKEoiIiISiBJIiNTU13HPPPZx33nkUFBTQrVs3Tj/9dK6//no2bNgQ3+5Pf/oTvXv3xswwM2655ZZG21uyZAlf+tKX6NOnD926dWPw4MFcfPHFPPLII8dtt2nTJmbMmEGfPn3o2rUrkyZN4vHHH28yzltuuSXed1FRq26DLCIScPecf0yePNmzyd69e33ixIkOOOA9evTw8ePHe69evRzwe+65J77tY489Ft8O8AEDBvjhw4ePa+/ZZ5+Nvz5w4ECfOHGiDxgwwAGfPXt2fLsdO3b4ySef7ID37NnThw8fHq/34IMPnhDnsmXL3Mzi22Tb5ygiqQVUeBL7Xo1AUuDGG29kzZo1APzoRz9i7969rF27ls8++4xXX32V8ePHx7dduHAhAJMnT8bM2LlzJy+99NJx7dWNIKZMmcKOHTtYvXo1n376KZs2baKkpCS+3U9/+lN27dpFfn4+GzZs4KOPPuLKK68E4LbbbuPQoUPxbffu3cu1117LaaedxqRJk1LyOYhI25axBGJmo83snXqPfWY218zuMrP/rld+WaZiDKOqqoonnngCgLPOOouf/exndO7cOf76RRddxMUXXwzAtm3bWLZsGQC33norU6ZMAY4llTq1tbUAVFZW8sgjj7Bp0ybcnREjRnDhhRfGt6tLPOeddx6nnnoqANOnTwdgz549rFq1Kr5taWkpO3fupLy8nPz8/Mjev4i0HxlLIO5e6e4T3H0CMBk4ADwTe/meutfcvVU3d88WGzdu5MiRIwBccMEFmDV2++HAww8/TG1tLb169eLyyy9n1qxZALz44ovs2bMnvl1paSkdO3bk008/paSkhNNPP52BAwdy3XXXsXXr1vh227ZtA+Dkk0+Olw0YMCD+e922CxYs4KmnnuKuu+7inHPOieBdi0h7lC1TWBcDH7p7UpcWzgZe7wZdzSUPCBIIwMyZM+nSpQszZsygW7duHD58mPLy8vh2l1xyCStXruS6665j0KBBAOzatYuFCxdywQUXcODAgVbFA0GSmTt3Ll/5yle4/fbbE35/IiJ1siWBfBuof6jQjWa21sweMrPejVUws1IzqzCzit27d6cnylYYPXo0nToFt1l54403TtiB13n99dfZtGkTAI888gi9evVi6NCh1NTUACdOY02cOJEFCxawfft2Pv744/hoZevWrfH1liFDhgBBcqlT//chQ4bw4Ycfsn//ft5++2169uxJjx49eP311wFYs2YNPXr04L333kv6cxCRti/jCSR2U/fLgSdjRfcBI4AJwCfA3Y3Vc/cydy9y96L+/UPfUCtyBQUFXHXVVUCwQ77jjjviU1oAy5cv59VXXz0uQRw8eJCqqiqqqqri6x3vvvtuPDHce++9PPPMMxw+fBgIbqB1wQUXxOv37NkTgGnTpgHw1ltvsWPHDgCefvppAPr27XvcYbo1NTVUV1dTXV0d77O2tpbq6mqOHj0a4SciIm1WModwRfEArgB+08RrhcC6ltrItsNPGx7Gm5+f7+PHj/e+ffs64D/5yU+8R48eDvhNN910XN2DBw+e8NrMmTMd8M6dO/uoUaN87Nix8cNvJ0yYED/sd/v27d6vX79GD+MtKytrMt4pU6boMF6Rdog2cBjv1dSbvjKzU+q99k1gXdojSlLv3r158803ufvuuzn77LOBYHE9Pz+f2bNn07t3b/bv3w8cO0qqTteuXbnssuDAs8cee4xDhw4xZ84cSkpKGDFiBDt37qSyspKBAwcya9YsXnjhhfiU2aBBg1ixYgXTp0/HzNixYwcTJkxg8eLFzJkzJ42fgIi0B+ZNzNGnpXOzPGAbcJq7V8XKHiWYvnJgM/A9d/+kuXaKiopc90QXEUmMma1y99CXoOgUZTCJcvcDQN8GZbMyFI6IiCQgG6awREQkBymBiIhIKEogIiISihKIiIiEogQiIiKhKIGIiEgoSiAiIhKKEoiIiIQSeQIxsw5m1jPqdkVEJLtEkkDM7DEz62lm3YE/AJVmdksUbYuISHaKagQy1t33Ad8AfgUMBXRJEhGRNiyqBNLZzDoTJJDn3P0wwcUQRUSkjYoqgfw7wZVzuwPLzWwYsC+itkVEJAtFcjVed/858PN6RVvM7KIo2hYRkewU1SL6ADNbYGYvxZ6PBWZH0baIiGSnqKawFgFLgVNjzzcCcyNqW0REslBUCaSfuz8B1AK4+xHgaERti4hIFooqgVSbWV9iR16Z2blAVURti4hIForqlrZ/DTwPjDCzFUB/YEZLlcxsM/BHgtHKEXcvMrM+wH8AhQRHdl3l7p9FFKeIiEQkkhGIu68GpgBfAr4HjHP3ta2sfpG7T6h3Y/fbgGXufjqwLPZcRESyTFRHYeUR7Ojnuvs6oNDM/jxkc1cAD8d+f5jg5EQREckyUa2BLAQOAefFnm8HftKKeg78xsxWmVlprGyAu38CEPt5cmMVzazUzCrMrGL37t3JRS8iIgmLKoGMcPefAYcB3P0gYK2od767TwK+BvzAzL7S2g7dvczdi9y9qH///qGCFhGR8KJKIIfMrBvHjsIaAdS0VMndd8R+7gKeAc4GdprZKbF2TgF2RRSjiIhEKKoE8mPg18AQMysnWPz+m+YqmFl3M8uv+x24FFhHcDRX3Vnss4HnIopRREQilPRhvGbWAegNTAfOJZi6utnd97RQdQDwjJnVxfGYu//azFYCT5jZ9cBW4FvJxigiItFLOoG4e62Z3Rg7E/0/E6j3EXBWI+X/A1ycbFwiIpJaUU1hvWxmPzKzIWbWp+4RUdsiIpKFojoT/brYzx/UK3PgtIjaFxGRLBPV/UCGR9GOiIjkjkgSiJlNb6S4CngvdoiuiIi0MVFNYV1PcBb6b2PPLwR+D4wys79390cj6kdERLJEVAmkFjjD3XdCcIdC4D7gHGA5oAQiItLGRHUUVmFd8ojZBYxy973ELm8iIiJtS1QjkNfN7EXgydjzGcDy2Bnmn0fUh4iIZJGoRiA/ILgi7wRgIsFl2H/g7tXuflFEfUgbUF4OhYXQoUPws7w80xGJSFhRHcbrZlYBVLn7K7H7g/QguNugCABnngnr1x97vmULXHstPPoo/PrXmYtLRMKJ6oZSc4AlwL/HigYBz0bRtrQdH354YlltLbz5ZvpjEZHkRTmFdT6wD8DdP6CJG0FJ+/WnPzVe/keNU1tt6lQwO/7RtStMm5bpyKQ9iiqB1Lj7obonZtaJ2L1BROrk5zde3rVravprLzvbmhpYtkzrSZJ+USWQ35nZHUA3M5tKcDTWCxG1LW3EffdBXt7xZXl58OCD6Ysh13e2L78Mw4adWH7kCNx5Z/rjkfYtqgRyG7AbeA/4HvAr4G8jalvaiOJiKCsLdoBmwc+ysqA8Fdriznbu3ODgg8Zs3Zp8+02N2s44I+hbpL5IEoi71xIsmv+lu89w9wfcXVNYcoLiYti8OVg837w5dckDUr+zbShdhyh36dJ4+dChqemvpgY2boT33w9Xv71MJbZHSSUQC9xlZnuA94FKM9ttZv87mvBEkpOOnW3dDvKaa4KE5R78LCmJPonMnw8LFjQ+FThvXvLtNzVqq60Nn0Aak+tTiRJIdgQyl+Doqy+6e19370Nw/avzzeyvkg1O2qA0nkmY6p1tS1I1VZbqqcCtW+FqyvmYQo7SgY8p5GrKQ4/a2uJUosS4e+gHsAbo10h5f2BNC3WHEFy9dwOwnuA+6gB3Af8NvBN7XNZSHJMnT3bJAePGuQdf0I89OnRw/+pXU9rt6zcs9m0dh/lRzLd1HOav37A48j7MTnxrEJTnkveHXNLoGzlCB/+1hfs73Xxz0MzVLPaPCf4OHzPMr2Zxzn0+bQ1Q4UnkgGTPRO/s7nsaSUq7zaxzC3WPAD9099Vmlg+sMrOXY6/d4+7/nGRskm3qn4Zep7YWli5NTX9Tp8Irr/DlekWDj25h8AMlwbg5oq/sc+fCSScF0zINpWpdIt06Usv5Fu6Mzxuensp8XjmurJAtPEwJ/foApHAhTFIq2SmsQyFfw90/cffVsd//SDASGZRkPCItS8HcyfDh8J0G0z7foTx1U2UpmgocPX1ck6/1qA13xufo0Y2Xd+YI/wfNYeWyZEcgZ5nZvkbKDWj16WFmVkhwEca3Cb4b3mhm1wIVBKOUz5KMU7LBsGGNHxbV2AR5FMaNg1deafy1CA/Dmr9+Krx/4jfsRzuUxL6hRfgNOzaqOk7dij1EM6rq0qXx4VTYMz6b+Tv02JuCw+EkbZIagbh7R3fv2cgj391bmsICwMx6AE8Bc919H8GNqEYQXNn3E+DuJuqVmlmFmVXs3r07mbch6TJvXvpXtNN9zGs9HWrTuEoc1aiquSMPkjnjM4N/B0mhZBZQkn0AnYGlwF838XohsK6ldrSInkMWL3YfNixYXR42LHie6v7y8o5fFM7Li7bfulXidKyip6uvqP9O6fg7SMLI8CJ6aGZmwAJgg7v/S73yU9z9k9jTbwLrMhGfpEhxcWrPHmysPwi+nW/dGnzjnTcv+hiamvZJxTfsdPQV9d8pXX8HSSsLklAGOjb7MvA6weVPamPFdwBXE0xfObAZ+F69hNKooqIir6ioSFmsIi0qL4fSUjhw4FhZXl5qrtWSzr6kTTOzVe5eFLZ+xkYg7v4GwWJ7Q79KdywiSUvnN2x9m5cskbERSJQ0AhERSVyyI5CorsYrIiLtjBKIiIiEogQiIiKhKIGIiEgoSiAiIhKKEoiIiISiBCIiIqEogYiISChKICIiEooSiIiIhKIEIiIioSiBiIhIKEogIiISihKIiIiEogQiIiKhKIGIiEgoSiAiIhKKEoiIiISSlQnEzKaZWaWZbTKz2zIdj4iInCjrEoiZdQT+FfgaMBa42szGZjYqERFpKOsSCHA2sMndP3L3Q8AvgSsyHJOIiDTQKdMBNGIQsK3e8+3AOQ03MrNSoDT2dL+ZVUYYQwFQlcE2wtZNpF4/YE+IPtq7KP430i3TMaej/1T0kYv7gUTrjE6w/eO5e1Y9gG8BD9Z7Pgv4RZpjKMtkG2HrJlIPqMj03zoXH1H8b7S3mNPRfyr6yMX9QKJ1kt0PZOMU1nZgSL3ng4EdaY7hhQy3EbZuFHFL83LxM850zOnoPxV95OJ+IK1/a4tloaxhZp2AjcDFwH8DK4HvuPv6jAbWxphZhbsXZToOEcmcZPcDWbcG4u5HzOxGYCnQEXhIySMlyjIdgIhkXFL7gawbgYiISG7IxjUQERHJAUogIiISihKIiIiEogQiIiKhKIEIAGb2DTN7wMyeM7NLMx2PiKSXmZ1hZveb2RIzu6E1dZRA2jAze8jMdpnZugblJ1zt2N2fdfc5QAkwMwPhikjEEtwHbHD37wNXAa06N0QJpG1bBEyrX9CKqx3/bex1Ecl9i0hgH2BmlwNvAMta07gSSBvm7suBvQ2KG73asQX+EXjJ3VenO1YRiV4i+4DY9s+7+5eA4ta0n3VnokvKNXW145uAS4ACMxvp7vdnIjgRSblG9wFmdiEwHegC/Ko1DSmBtD/WSJm7+8+Bn6c7GBFJu6b2Aa8BryXSkKaw2p9suNqxiGROZPsAJZD2ZyVwupkNN7OTgG8Dz2c4JhFJn8j2AUogbZiZPQ68BYw2s+1mdr27HwHqrna8AXhCVzsWaZtSvQ/Q1XhFRCQUjUBERCQUJRAREQlFCUREREJRAhERkVCUQEREJBQlEBERCUUJRAQws6Nm9o6ZrTOzJ80sL4G6p5rZkgT7e83MGr1kdux+DKc1U/efzezPEulPJBWUQEQCB919grufCRwCvt+aSmbWyd13uPuMKIIws3FAR3f/qJnNfgHcFkV/IslQAhE50evASDPrHrshz0ozW2NmVwCYWUlslPIC8BszK6y7YY+ZdTWzhWb2XqzORbHybmb2SzNba2b/AXRrou9i4LlYnY5mtig2KnrPzP4KwN23AH3NbGBqPwaR5ulqvCL1mFknghvt/Bq4E3jV3a8zs17Af5nZK7FNzwO+4O57zaywXhM/AHD38WY2hiDBjAJuAA64+xfM7AtAU/dcOR94PPb7BGBQbFRELIY6q2PbPpXE2xVJikYgIoFuZvYOUAFsBRYAlwK3xcpfA7oCQ2Pbv+zuDW/UA/Bl4FEAd38f2AKMAr4CLI6VrwXWNhHHKcDu2O8fAaeZ2S/MbBqwr952u4BTE32TIlHSCEQkcNDdJ9QvMDMDrnT3ygbl5wDVTbTT2L0W6rTmwnMHCRIV7v6ZmZ0FfJVgZHMVcF1su66xbUUyRiMQkaYtBW6KJRLMbGIr6iwndjvQ2NTVUKCyQfmZwBeaqL8BGBnbrh/Qwd2fAv4OmFRvu1HAugTfj0iklEBEmvYPQGdgbWyR/B9aUeffgI5m9h7wH0CJu9cA9wE9zGwt8DfAfzVR/z+BC2O/DwJei02hLQJuBzCzzgRJpiLxtyQSHV3OXSSLmFk34LfA+e5+tIltvglMcve/S2twIg1oBCKSRdz9IPBjgtFHUzoBd6cnIpGmaQQiIiKhaAQiIiKhKIGIiEgoSiAiIhKKEoiIiISiBCIiIqH8f0LauaxMfFiKAAAAAElFTkSuQmCC\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-10-15 18:25:22,474 [line 753] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing 8P_CAS04_CAV07_NVR11_REV06.h5\n", - "2022-10-15 18:25:22,785 [line 753] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing 8P_CAS04_CAV07_NVR11_REV06.h5\n" - ] - } - ], - "source": [ - "show_plot = True\n", - "tf_cls = process_mth5(config,\n", - " kernel_dataset,\n", - " units=\"MT\",\n", - " show_plot=show_plot,\n", - " z_file_path=None,\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "py37", - "language": "python", - "name": "py37" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.10" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/notebooks/aurora/04a_process_cas04_multiple_station.ipynb b/notebooks/aurora/04_process_cas04_multiple_station.ipynb similarity index 100% rename from notebooks/aurora/04a_process_cas04_multiple_station.ipynb rename to notebooks/aurora/04_process_cas04_multiple_station.ipynb