diff --git a/docs/examples/notebooks/USMTArray.CAS04.2020.xml b/docs/examples/notebooks/USMTArray.CAS04.2020.xml new file mode 100644 index 00000000..ac49eac2 --- /dev/null +++ b/docs/examples/notebooks/USMTArray.CAS04.2020.xml @@ -0,0 +1,1741 @@ + + + Magnetotelluric Transfer Functions + USMTArray.CAS04.2020 + MT_TF + + impedance,tipper + + IRIS DMC MetaData + http://www.iris.edu/mda/8P/CAS04 + + + CAS04-CAS04bcd_REV06-CAS04bcd_NVR08.png + + + CAS04-CAS04bcd_REV06-CAS04bcd_NVR08.zmm + The original used to produce the XML + + + 2021-09-23T19:45:02 + EMTF File Conversion Utilities 4.0 + + Jade Crosbie, Paul Bedrosian and Anna Kelbert + pbedrosian@usgs.gov + U.S. Geological Survey + https://www.usgs.gov/natural-hazards/geomagnetism + + + Anna Kelbert + akelbert@usgs.gov + U.S. Geological Survey, Geomagnetism Program + https://www.usgs.gov/natural-hazards/geomagnetism + + + + + USMTArray South Magnetotelluric Transfer Functions + Schultz, A., Pellerin, L., Bedrosian, P., Kelbert, A., Crosbie, J. + 2020-2023 + doi:10.17611/DP/EMTF/USMTARRAY/SOUTH + + The USMTArray-CONUS South campaign was carried out through a cooperative agreement between +the U.S. Geological Survey (USGS) and Oregon State University (OSU). A subset of 40 stations +in the SW US were funded through NASA grant 80NSSC19K0232. +Land permitting, data acquisition, quality control and field processing were +carried out by Green Geophysics with project management and instrument/engineering +support from OSU and Chaytus Engineering, respectively. +Program oversight, definitive data processing and data archiving were provided +by the USGS Geomagnetism Program and the Geology, Geophysics and Geochemistry Science Centers. +We thank the U.S. Forest Service, the Bureau of Land Management, the National Park Service, +the Department of Defense, numerous state land offices and the many private landowners +who permitted land access to acquire the USMTArray data. + Unrestricted Release + All data and metadata for this survey are available free of charge and may be copied freely, duplicated and further distributed provided that this data set is cited as the reference, and that the author(s) contributions are acknowledged as detailed in the Acknowledgements. Any papers cited in this file are only for reference. There is no requirement to cite these papers when the data are used. Whenever possible, we ask that the author(s) are notified prior to any publication that makes use of these data. + While the author(s) strive to provide data and metadata of best possible quality, neither the author(s) of this data set, nor IRIS make any claims, promises, or guarantees about the accuracy, completeness, or adequacy of this information, and expressly disclaim liability for errors and omissions in the contents of this file. Guidelines about the quality or limitations of the data and metadata, as obtained from the author(s), are included for informational purposes only. + + + USMTArray + CONUS South + 2020 + USA + CAS04 + Corral Hollow, CA, USA + + 37.633351 + -121.468382 + 329.387 + 13.175 + + orthogonal + National Geoelectromagnetic Facility + 2020-06-02T18:41:43 + 2020-07-13T21:46:12 + CAS04a CAS04b CAS04c CAS04d + + 4 + 20.000 + 10000.000 + good TF from 10 to 10000 secs + + + 0 + + + + + + Barry Narod + NIMS + 2106-02 + + + + Barry Narod + NIMS + 2612-19 + + + + Oregon State University + 92.000 + 13.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 92.000 + 103.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + X Array at 0 deg rotation. Hillside valley. 46m line in each direction. Dry friable soil. 2 track 200m SW. Lines trenched. Hot sunny day. NIMS ID unreadabl + NIMS file declination 14.9 replaced with IGRF declination 13.1746. + 1.000 + 2020-06-02T18:41:43 + 2020-06-02T22:07:46 + + + + Barry Narod + NIMS + 2106-02 + + + + Barry Narod + NIMS + 2612-19 + + + + Oregon State University + 92.000 + 13.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 92.000 + 103.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + X Array at 0 deg rotation. AHillside valley. 46m line in each direction. Dry friable soil. 2 + NIMS file declination 14.9 replaced with IGRF declination 13.1746. + 1.000 + 2020-06-02T22:24:55 + 2020-06-12T17:52:23 + + + + Barry Narod + NIMS + 2106-02 + + + + Barry Narod + NIMS + 2612-19 + + + + Oregon State University + 92.000 + 13.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 92.000 + 103.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + X Array at 0 deg rotation. Hillside valley. 46m line in each direction. Dry friable soil. 2 track 200m SW. Lines trenched. Russian buckets used. Hot sunny + NIMS file declination 14.9 replaced with IGRF declination 13.1746. + 1.000 + 2020-06-12T18:32:17 + 2020-07-01T17:32:59 + + + + Barry Narod + NIMS + 2106-02 + + + + Barry Narod + NIMS + 2612-19 + + + + Oregon State University + 92.000 + 13.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 92.000 + 103.175 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + X Array at 0 deg rotation. Hillside valley. 46m line in each direction. Dry friable soil. 2 + NIMS file declination 14.9 replaced with IGRF declination 13.1746. + 1.000 + 2020-07-01T19:36:55 + 2020-07-13T21:46:12 + + + exp(+ i\omega t) + + + + USMTArray + CONUS South + 2020 + USA + REV06 + Poso Creek, CA, USA + + 35.712621 + -119.466414 + 61.050 + + + + Jade Crosbie, Paul Bedrosian and Anna Kelbert + + EMTF + 2015-08-26 + Gary Egbert + + CAS04-CAS04bcd_REV06-CAS04bcd_NVR08 + + + + Variance + http://www.iris.edu/dms/products/emtf/variance.html + error estimate + variance + + + Full covariance between each two TF components + http://www.iris.edu/dms/products/emtf/covariance.html + error estimate + covariance + + + Inverse Coherent Signal Power Matrix (S) + http://www.iris.edu/dms/products/emtf/inverse_signal_covariance.html + signal power estimate + inverse_signal_covariance + + + Residual Covariance (N) + http://www.iris.edu/dms/products/emtf/residual_covariance.html + error estimate + residual_covariance + + + Coherence + http://www.iris.edu/dms/products/emtf/coherence.html + signal coherence + coherence + + + Multiple Coherence + http://www.iris.edu/dms/products/emtf/multiple_coherence.html + signal coherence + multiple_coherence + + + Signal Amplitude + http://www.iris.edu/dms/products/emtf/signal_amplitude.html + signal power estimate + signal_amplitude + + + Signal Noise + http://www.iris.edu/dms/products/emtf/signal_noise.html + error estimate + signal_noise + + + + + MT impedance + http://www.iris.edu/dms/products/emtf/impedance.html + primary data type + impedance + + + Vertical Field Transfer Functions (Tipper) + http://www.iris.edu/dms/products/emtf/tipper.html + primary data type + tipper + + + + + + + + + + + + + + + + + 5.218971e-2 -4.937870e-1 + 1.004782e0 1.873659e0 + -8.261183e-1 1.226159e0 + 1.361610e0 -1.376113e0 + + + 1.073565e-2 + 3.300742e-3 + 2.555772e-2 + 7.857884e-3 + + + 2.733552e3 -3.930972e-5 + -4.851918e2 7.702000e2 + -4.851918e2 -7.702000e2 + 8.404479e2 -2.066028e-5 + + + 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+ -1.419307e-2 -3.934453e-2 + + + 8.215788e-4 + 4.156218e-4 + 2.303512e-3 + 1.165305e-3 + + + 2.495680e-7 -3.914230e-15 + 1.116381e-7 8.269000e-8 + 1.116381e-7 -8.269000e-8 + 1.262520e-7 2.768304e-16 + + + 3.292003e3 -5.684342e-14 + -1.950100e3 -2.293000e3 + -1.950100e3 2.293000e3 + 9.229997e3 -5.684342e-14 + + + -2.102757e-2 -6.664169e-2 + 5.568553e-1 1.630035e-1 + + + 2.375638e-2 + 1.201792e-2 + + + 2.495680e-7 -3.914230e-15 + 1.116381e-7 8.269000e-8 + 1.116381e-7 -8.269000e-8 + 1.262520e-7 2.768304e-16 + + + 9.519000e4 0.000000e0 + + + + + diff --git a/docs/examples/notebooks/USMTArray.NVR08.2020.xml b/docs/examples/notebooks/USMTArray.NVR08.2020.xml new file mode 100644 index 00000000..74cfd24b --- /dev/null +++ b/docs/examples/notebooks/USMTArray.NVR08.2020.xml @@ -0,0 +1,1693 @@ + + + Magnetotelluric Transfer Functions + USMTArray.NVR08.2020 + MT_TF + + impedance,tipper + + IRIS DMC MetaData + http://www.iris.edu/mda/8P/NVR08 + + + NVR08-R08_NVS09_NVR09_NVR08-R08_NVS11_NVR09_NVR08.png + + + NVR08-R08_NVS09_NVR09_NVR08-R08_NVS11_NVR09_NVR08.zmm + The original used to produce the XML + + + 2021-09-23T19:40:01 + EMTF File Conversion Utilities 4.0 + + Jade Crosbie, Paul Bedrosian and Anna Kelbert + pbedrosian@usgs.gov + U.S. Geological Survey + https://www.usgs.gov/natural-hazards/geomagnetism + + + Anna Kelbert + akelbert@usgs.gov + U.S. Geological Survey, Geomagnetism Program + https://www.usgs.gov/natural-hazards/geomagnetism + + + + + USMTArray South Magnetotelluric Transfer Functions + Schultz, A., Pellerin, L., Bedrosian, P., Kelbert, A., Crosbie, J. + 2020-2023 + doi:10.17611/DP/EMTF/USMTARRAY/SOUTH + + The USMTArray-CONUS South campaign was carried out through a cooperative agreement between +the U.S. Geological Survey (USGS) and Oregon State University (OSU). A subset of 40 stations +in the SW US were funded through NASA grant 80NSSC19K0232. +Land permitting, data acquisition, quality control and field processing were +carried out by Green Geophysics with project management and instrument/engineering +support from OSU and Chaytus Engineering, respectively. +Program oversight, definitive data processing and data archiving were provided +by the USGS Geomagnetism Program and the Geology, Geophysics and Geochemistry Science Centers. +We thank the U.S. Forest Service, the Bureau of Land Management, the National Park Service, +the Department of Defense, numerous state land offices and the many private landowners +who permitted land access to acquire the USMTArray data. + Unrestricted Release + All data and metadata for this survey are available free of charge and may be copied freely, duplicated and further distributed provided that this data set is cited as the reference, and that the author(s) contributions are acknowledged as detailed in the Acknowledgements. Any papers cited in this file are only for reference. There is no requirement to cite these papers when the data are used. Whenever possible, we ask that the author(s) are notified prior to any publication that makes use of these data. + While the author(s) strive to provide data and metadata of best possible quality, neither the author(s) of this data set, nor IRIS make any claims, promises, or guarantees about the accuracy, completeness, or adequacy of this information, and expressly disclaim liability for errors and omissions in the contents of this file. Guidelines about the quality or limitations of the data and metadata, as obtained from the author(s), are included for informational purposes only. + + + USMTArray + CONUS South + 2020 + USA + NVR08 + Rhodes Salt Marsh, NV, USA + + 38.326630 + -118.082382 + 1375.425 + 12.641 + + orthogonal + National Geoelectromagnetic Facility + 2020-06-03T19:10:11 + 2020-06-24T15:55:46 + NVR08a NVR08b NVR08c + + 3 + 5.000 + 3000.000 + long periods compromised in one or both modes + + + 0 + + + + + + Barry Narod + NIMS + 2106-10 + + + + Barry Narod + NIMS + 2612-02 + + + + Oregon State University + 94.000 + 12.641 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 94.000 + 102.641 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + x-array to 0 deg. Dry sand. Hot sunny day. Powerline + NIMS file declination 14.5 replaced with IGRF declination 12.6411. + 1.000 + 2020-06-03T19:10:11 + 2020-06-03T19:57:51 + + + + Barry Narod + NIMS + 2106-10 + + + + Barry Narod + NIMS + 2612-02 + + + + Oregon State University + 94.000 + 12.641 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 94.000 + 102.641 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + x-array to 0 deg. Dry sand. Hot sunny day. Powerline + NIMS file declination 14.5 replaced with IGRF declination 12.6411. + 1.000 + 2020-06-03T20:14:13 + 2020-06-14T16:56:02 + + + + Barry Narod + NIMS + 2106-10 + + + + Barry Narod + NIMS + 2612-02 + + + + Oregon State University + 94.000 + 12.641 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + + Oregon State University + 94.000 + 102.641 + Pb-PbCl2 kaolin gel Petiau 2 chamber type + Pb-PbCl2 kaolin gel Petiau 2 chamber type + + X-array t 0 deg. Dry sanod. Hot sunny day. Powerline + NIMS file declination 14.5 replaced with IGRF declination 12.6411. + 1.000 + 2020-06-14T18:00:44 + 2020-06-24T15:55:46 + + + exp(+ i\omega t) + + Jade Crosbie, Paul Bedrosian and Anna Kelbert + + EMTF + 2015-08-26 + Gary Egbert + + NVR08-R08_NVS09_NVR09_NVR08-R08_NVS11_NVR09_NVR08 + + + + Variance + http://www.iris.edu/dms/products/emtf/variance.html + error estimate + variance + + + Full covariance between each two TF components + http://www.iris.edu/dms/products/emtf/covariance.html + error estimate + covariance + + + Inverse Coherent Signal Power Matrix (S) + http://www.iris.edu/dms/products/emtf/inverse_signal_covariance.html + signal power estimate + inverse_signal_covariance + + + Residual Covariance (N) + http://www.iris.edu/dms/products/emtf/residual_covariance.html + error estimate + residual_covariance + + + Coherence + http://www.iris.edu/dms/products/emtf/coherence.html + signal coherence + coherence + + + Multiple Coherence + http://www.iris.edu/dms/products/emtf/multiple_coherence.html + signal coherence + multiple_coherence + + + Signal Amplitude + http://www.iris.edu/dms/products/emtf/signal_amplitude.html + signal power estimate + signal_amplitude + + + Signal Noise + http://www.iris.edu/dms/products/emtf/signal_noise.html + error estimate + signal_noise + + + + + MT impedance + http://www.iris.edu/dms/products/emtf/impedance.html + primary data type + impedance + + + Vertical Field Transfer Functions (Tipper) + http://www.iris.edu/dms/products/emtf/tipper.html + primary data type + tipper + + + + + + + + + + + + + + + + + -4.648010e-1 -4.197427e-1 + 5.548629e0 1.219884e0 + -9.853714e-1 -1.670116e0 + -3.154990e-1 5.195427e-1 + + + 8.941785e-2 + 2.972618e-2 + 1.816899e-2 + 6.040121e-3 + + + 8.600755e0 -1.043334e-7 + -3.577696e0 1.193000e0 + -3.577696e0 -1.193000e0 + 2.859245e0 1.065334e-7 + + + 1.039651e-2 -6.776264e-21 + -6.482694e-4 -2.595000e-4 + -6.482694e-4 2.595000e-4 + 2.112488e-3 6.776264e-21 + + 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-4,EM,CAY10,,LQN,2019-10-07T00:00:00,2019-10-30T00:00:00 -5,ZU,CAS04,,LQE,2020-06-02T19:00:00,2020-07-13T19:00:00 -6,ZU,CAS04,,LQN,2020-06-02T19:00:00,2020-07-13T19:00:00 -7,ZU,CAS04,,LFE,2020-06-02T19:00:00,2020-07-13T19:00:00 -8,ZU,CAS04,,LFN,2020-06-02T19:00:00,2020-07-13T19:00:00 -9,ZU,CAS04,,LFZ,2020-06-02T19:00:00,2020-07-13T19:00:00 -10,ZU,NVR08,,LQE,2020-06-02T19:00:00,2020-07-13T19:00:00 -11,ZU,NVR08,,LQN,2020-06-02T19:00:00,2020-07-13T19:00:00 -12,ZU,NVR08,,LFE,2020-06-02T19:00:00,2020-07-13T19:00:00 -13,ZU,NVR08,,LFN,2020-06-02T19:00:00,2020-07-13T19:00:00 -14,ZU,NVR08,,LFZ,2020-06-02T19:00:00,2020-07-13T19:00:00 +0,8P,CAS04,,LQE,2020-06-02T19:00:00,2020-07-13T19:00:00 +1,8P,CAS04,,LQN,2020-06-02T19:00:00,2020-07-13T19:00:00 +2,8P,CAS04,,LFE,2020-06-02T19:00:00,2020-07-13T19:00:00 +3,8P,CAS04,,LFN,2020-06-02T19:00:00,2020-07-13T19:00:00 +4,8P,CAS04,,LFZ,2020-06-02T19:00:00,2020-07-13T19:00:00 +5,8P,NVR08,,LQE,2020-06-02T19:00:00,2020-07-13T19:00:00 +6,8P,NVR08,,LQN,2020-06-02T19:00:00,2020-07-13T19:00:00 +7,8P,NVR08,,LFE,2020-06-02T19:00:00,2020-07-13T19:00:00 +8,8P,NVR08,,LFN,2020-06-02T19:00:00,2020-07-13T19:00:00 +9,8P,NVR08,,LFZ,2020-06-02T19:00:00,2020-07-13T19:00:00 diff --git a/docs/examples/notebooks/make_mth5_driver.ipynb b/docs/examples/notebooks/make_mth5_driver.ipynb index bef3a001..9cc1245c 100644 --- a/docs/examples/notebooks/make_mth5_driver.ipynb +++ b/docs/examples/notebooks/make_mth5_driver.ipynb @@ -70,16 +70,16 @@ "metadata": {}, "outputs": [], "source": [ - "ZUCAS04LQ1 = ['ZU', 'CAS04', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04LQ2 = ['ZU', 'CAS04', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04BF1 = ['ZU', 'CAS04', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04BF2 = ['ZU', 'CAS04', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04BF3 = ['ZU', 'CAS04', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08LQ1 = ['ZU', 'NVR08', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08LQ2 = ['ZU', 'NVR08', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08BF1 = ['ZU', 'NVR08', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08BF2 = ['ZU', 'NVR08', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08BF3 = ['ZU', 'NVR08', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04LQ1 = ['8P', 'CAS04', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04LQ2 = ['8P', 'CAS04', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04BF1 = ['8P', 'CAS04', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04BF2 = ['8P', 'CAS04', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04BF3 = ['8P', 'CAS04', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08LQ1 = ['8P', 'NVR08', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08LQ2 = ['8P', 'NVR08', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08BF1 = ['8P', 'NVR08', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08BF2 = ['8P', 'NVR08', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08BF3 = ['8P', 'NVR08', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", "\n", "request_list = [\n", " ZUCAS04LQ1, ZUCAS04LQ2, ZUCAS04BF1, ZUCAS04BF2, ZUCAS04BF3,\n", diff --git a/docs/examples/notebooks/make_mth5_driver_v0.2.0.ipynb b/docs/examples/notebooks/make_mth5_driver_v0.2.0.ipynb index ef3dc0d7..cbfb26d5 100644 --- a/docs/examples/notebooks/make_mth5_driver_v0.2.0.ipynb +++ b/docs/examples/notebooks/make_mth5_driver_v0.2.0.ipynb @@ -18,15 +18,20 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 18:05:10,341 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" + "2022-04-13 12:59:21,202 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" ] } ], "source": [ "from pathlib import Path\n", "\n", + "import numpy as np\n", "import pandas as pd\n", - "from mth5.clients.make_mth5 import MakeMTH5" + "from mth5.mth5 import MTH5\n", + "from mth5.clients.make_mth5 import MakeMTH5\n", + "\n", + "from matplotlib import pyplot as plt\n", + "%matplotlib widget" ] }, { @@ -90,7 +95,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -125,52 +130,7 @@ " \n", " \n", " 0\n", - " EM\n", - " CAY10\n", - " \n", - " LFE\n", - " 2019-10-07T00:00:00\n", - " 2019-10-30T00:00:00\n", - " \n", - " \n", - " 1\n", - " EM\n", - " CAY10\n", - " \n", - " LFN\n", - " 2019-10-07T00:00:00\n", - " 2019-10-30T00:00:00\n", - " \n", - " \n", - " 2\n", - " EM\n", - " CAY10\n", - " \n", - " LFZ\n", - " 2019-10-07T00:00:00\n", - " 2019-10-30T00:00:00\n", - " \n", - " \n", - " 3\n", - " EM\n", - " CAY10\n", - " \n", - " LQE\n", - " 2019-10-07T00:00:00\n", - " 2019-10-30T00:00:00\n", - " \n", - " \n", - " 4\n", - " EM\n", - " CAY10\n", - " \n", - " LQN\n", - " 2019-10-07T00:00:00\n", - " 2019-10-30T00:00:00\n", - " \n", - " \n", - " 5\n", - " ZU\n", + " 8P\n", " CAS04\n", " \n", " LQE\n", @@ -178,8 +138,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 6\n", - " ZU\n", + " 1\n", + " 8P\n", " CAS04\n", " \n", " LQN\n", @@ -187,8 +147,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 7\n", - " ZU\n", + " 2\n", + " 8P\n", " CAS04\n", " \n", " LFE\n", @@ -196,8 +156,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 8\n", - " ZU\n", + " 3\n", + " 8P\n", " CAS04\n", " \n", " LFN\n", @@ -205,8 +165,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 9\n", - " ZU\n", + " 4\n", + " 8P\n", " CAS04\n", " \n", " LFZ\n", @@ -214,8 +174,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 10\n", - " ZU\n", + " 5\n", + " 8P\n", " NVR08\n", " \n", " LQE\n", @@ -223,8 +183,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 11\n", - " ZU\n", + " 6\n", + " 8P\n", " NVR08\n", " \n", " LQN\n", @@ -232,8 +192,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 12\n", - " ZU\n", + " 7\n", + " 8P\n", " NVR08\n", " \n", " LFE\n", @@ -241,8 +201,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 13\n", - " ZU\n", + " 8\n", + " 8P\n", " NVR08\n", " \n", " LFN\n", @@ -250,8 +210,8 @@ " 2020-07-13T19:00:00\n", " \n", " \n", - " 14\n", - " ZU\n", + " 9\n", + " 8P\n", " NVR08\n", " \n", " LFZ\n", @@ -263,47 +223,36 @@ "" ], "text/plain": [ - " network station location channel start end\n", - "0 EM CAY10 LFE 2019-10-07T00:00:00 2019-10-30T00:00:00\n", - "1 EM CAY10 LFN 2019-10-07T00:00:00 2019-10-30T00:00:00\n", - "2 EM CAY10 LFZ 2019-10-07T00:00:00 2019-10-30T00:00:00\n", - "3 EM CAY10 LQE 2019-10-07T00:00:00 2019-10-30T00:00:00\n", - "4 EM CAY10 LQN 2019-10-07T00:00:00 2019-10-30T00:00:00\n", - "5 ZU CAS04 LQE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "6 ZU CAS04 LQN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "7 ZU CAS04 LFE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "8 ZU CAS04 LFN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "9 ZU CAS04 LFZ 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "10 ZU NVR08 LQE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "11 ZU NVR08 LQN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "12 ZU NVR08 LFE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "13 ZU NVR08 LFN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", - "14 ZU NVR08 LFZ 2020-06-02T19:00:00 2020-07-13T19:00:00" + " network station location channel start end\n", + "0 8P CAS04 LQE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "1 8P CAS04 LQN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "2 8P CAS04 LFE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "3 8P CAS04 LFN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "4 8P CAS04 LFZ 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "5 8P NVR08 LQE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "6 8P NVR08 LQN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "7 8P NVR08 LFE 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "8 8P NVR08 LFN 2020-06-02T19:00:00 2020-07-13T19:00:00\n", + "9 8P NVR08 LFZ 2020-06-02T19:00:00 2020-07-13T19:00:00" ] }, - "execution_count": 4, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "EMCAY10LFE = ['EM', 'CAY10', '', 'LFE', '2019-10-07T00:00:00', '2019-10-30T00:00:00'] \n", - "EMCAY10LFN = ['EM', 'CAY10', '', 'LFN', '2019-10-07T00:00:00', '2019-10-30T00:00:00'] \n", - "EMCAY10LFZ = ['EM', 'CAY10', '', 'LFZ', '2019-10-07T00:00:00', '2019-10-30T00:00:00'] \n", - "EMCAY10LQE = ['EM', 'CAY10', '', 'LQE', '2019-10-07T00:00:00', '2019-10-30T00:00:00'] \n", - "EMCAY10LQN = ['EM', 'CAY10', '', 'LQN', '2019-10-07T00:00:00', '2019-10-30T00:00:00'] \n", - "ZUCAS04LQ1 = ['ZU', 'CAS04', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04LQ2 = ['ZU', 'CAS04', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04BF1 = ['ZU', 'CAS04', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04BF2 = ['ZU', 'CAS04', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUCAS04BF3 = ['ZU', 'CAS04', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08LQ1 = ['ZU', 'NVR08', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08LQ2 = ['ZU', 'NVR08', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08BF1 = ['ZU', 'NVR08', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08BF2 = ['ZU', 'NVR08', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", - "ZUNRV08BF3 = ['ZU', 'NVR08', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + " ZUCAS04LQ1 = ['8P', 'CAS04', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04LQ2 = ['8P', 'CAS04', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04BF1 = ['8P', 'CAS04', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04BF2 = ['8P', 'CAS04', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUCAS04BF3 = ['8P', 'CAS04', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08LQ1 = ['8P', 'NVR08', '', 'LQE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08LQ2 = ['8P', 'NVR08', '', 'LQN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08BF1 = ['8P', 'NVR08', '', 'LFE', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08BF2 = ['8P', 'NVR08', '', 'LFN', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "ZUNRV08BF3 = ['8P', 'NVR08', '', 'LFZ', '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", "request_list = [\n", - " EMCAY10LFE, EMCAY10LFN, EMCAY10LFZ, EMCAY10LQE, EMCAY10LQN,\n", " ZUCAS04LQ1, ZUCAS04LQ2, ZUCAS04BF1, ZUCAS04BF2, ZUCAS04BF3,\n", " ZUNRV08LQ1, ZUNRV08LQ2, ZUNRV08BF1, ZUNRV08BF2, ZUNRV08BF3\n", "]\n", @@ -324,7 +273,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -337,30 +286,14 @@ "source": [ "## Get only the metadata from IRIS\n", "\n", - "It can be helpful to make sure that your request is what you would expect. For that you can request only the metadata from IRIS. The request is quick and light so shouldn't need to worry about the speed. " + "It can be helpful to make sure that your request is what you would expect. For that you can request only the metadata from IRIS. The request is quick and light so shouldn't need to worry about the speed. This returns a StationXML file and is loaded into an `obspy.Inventory` object." ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, - "outputs": [ - { - "ename": "FDSNNoDataException", - "evalue": "No data available for request.\nDetailed response of server:\n\n", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mFDSNNoDataException\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m~\\AppData\\Local\\Temp\\1/ipykernel_22416/663466057.py\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0minventory\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_inventory_from_df\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrequest_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[1;32m~\\Documents\\GitHub\\mth5\\mth5\\clients\\make_mth5.py\u001b[0m in \u001b[0;36mget_inventory_from_df\u001b[1;34m(self, df, client, data)\u001b[0m\n\u001b[0;32m 371\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mrow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnetwork\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mused_network\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 372\u001b[0m net_inv = client.get_stations(\n\u001b[1;32m--> 373\u001b[1;33m \u001b[0mrow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mend\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnetwork\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mrow\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnetwork\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"network\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 374\u001b[0m )\n\u001b[0;32m 375\u001b[0m \u001b[0mreturned_network\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnet_inv\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnetworks\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\Anaconda3\\envs\\mt\\lib\\site-packages\\obspy\\clients\\fdsn\\client.py\u001b[0m in \u001b[0;36mget_stations\u001b[1;34m(self, starttime, endtime, startbefore, startafter, endbefore, endafter, network, station, location, channel, minlatitude, maxlatitude, minlongitude, maxlongitude, latitude, longitude, minradius, maxradius, level, includerestricted, includeavailability, updatedafter, matchtimeseries, filename, format, **kwargs)\u001b[0m\n\u001b[0;32m 723\u001b[0m \"station\", DEFAULT_PARAMETERS['station'], kwargs)\n\u001b[0;32m 724\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 725\u001b[1;33m \u001b[0mdata_stream\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_download\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 726\u001b[0m \u001b[0mdata_stream\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mseek\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 727\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfilename\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\Anaconda3\\envs\\mt\\lib\\site-packages\\obspy\\clients\\fdsn\\client.py\u001b[0m in \u001b[0;36m_download\u001b[1;34m(self, url, return_string, data, use_gzip)\u001b[0m\n\u001b[0;32m 1395\u001b[0m \u001b[0mdebug\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreturn_string\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mreturn_string\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1396\u001b[0m timeout=self.timeout, use_gzip=use_gzip)\n\u001b[1;32m-> 1397\u001b[1;33m \u001b[0mraise_on_error\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1398\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1399\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32m~\\Anaconda3\\envs\\mt\\lib\\site-packages\\obspy\\clients\\fdsn\\client.py\u001b[0m in \u001b[0;36mraise_on_error\u001b[1;34m(code, data)\u001b[0m\n\u001b[0;32m 1721\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mcode\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m204\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1722\u001b[0m raise FDSNNoDataException(\"No data available for request.\",\n\u001b[1;32m-> 1723\u001b[1;33m server_info)\n\u001b[0m\u001b[0;32m 1724\u001b[0m \u001b[1;32melif\u001b[0m \u001b[0mcode\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m400\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1725\u001b[0m msg = (\"Bad request. If you think your request was valid \"\n", - "\u001b[1;31mFDSNNoDataException\u001b[0m: No data available for request.\nDetailed response of server:\n\n" - ] - } - ], + "outputs": [], "source": [ "inventory, data = m.get_inventory_from_df(request_df, data=False)" ] @@ -374,9 +307,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Inventory created at 2022-04-12T23:04:28.609255Z\n", + "\tCreated by: ObsPy 1.2.2\n", + "\t\t https://www.obspy.org\n", + "\tSending institution: MTH5\n", + "\tContains:\n", + "\t\tNetworks (1):\n", + "\t\t\t8P\n", + "\t\tStations (2):\n", + "\t\t\t8P.CAS04 (Corral Hollow, CA, USA)\n", + "\t\t\t8P.NVR08 (Rhodes Salt Marsh, NV, USA)\n", + "\t\tChannels (10):\n", + "\t\t\t8P.CAS04..LFZ, 8P.CAS04..LFN, 8P.CAS04..LFE, 8P.CAS04..LQN, \n", + "\t\t\t8P.CAS04..LQE, 8P.NVR08..LFZ, 8P.NVR08..LFN, 8P.NVR08..LFE, \n", + "\t\t\t8P.NVR08..LQN, 8P.NVR08..LQE" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "inventory" ] @@ -391,22 +348,81 @@ "\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=True` so we can interrogate the file when its complete. If you want to just write a file leave `interact=False` the default. " + "**Note:** we are setting `interact=False`. If you want to just to keep the file open to interogat it set `interact=True`. " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-04-12 16:05:24,284 [line 656] mth5.mth5.MTH5._initialize_file - INFO: Initialized MTH5 0.2.0 file C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\docs\\examples\\notebooks\\8P_CAS04_NVR08.h5 in mode w\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2022-04-12T16:06:10 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_si_units to a CoefficientFilter\n", + "2022-04-12T16:06:10 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_dipole_92.000 to a CoefficientFilter\n", + "2022-04-12T16:06:10 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_si_units to a CoefficientFilter\n", + "2022-04-12T16:06:10 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_dipole_92.000 to a CoefficientFilter\n", + "2022-04-12T16:06:10 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_si_units to a CoefficientFilter\n", + "2022-04-12T16:06:11 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_dipole_94.000 to a CoefficientFilter\n", + "2022-04-12T16:06:11 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_si_units to a CoefficientFilter\n", + "2022-04-12T16:06:11 [line 136] obspy_stages.create_filter_from_stage - INFO: Converting PoleZerosResponseStage electric_dipole_94.000 to a CoefficientFilter\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-04-12 16:06:13,053 [line 746] mth5.groups.base.Station.add_run - INFO: run a already exists, returning existing group.\n", + "2022-04-12 16:06:13,351 [line 224] mth5.timeseries.run_ts.RunTS.validate_metadata - WARNING: start time of dataset 2020-06-02T19:00:00+00:00 does not match metadata start 2020-06-02T18:41:43+00:00 updating metatdata value to 2020-06-02T19:00:00+00:00\n", + "2022-04-12 16:06:18,915 [line 746] mth5.groups.base.Station.add_run - INFO: run b already exists, returning existing group.\n", + "2022-04-12 16:06:26,568 [line 746] mth5.groups.base.Station.add_run - INFO: run c already exists, returning existing group.\n", + "2022-04-12 16:06:27,470 [line 462] mth5.timeseries.run_ts.RunTS.from_obspy_stream - WARNING: could not find ey\n", + "2022-04-12 16:06:36,701 [line 746] mth5.groups.base.Station.add_run - INFO: run d already exists, returning existing group.\n", + "2022-04-12 16:06:37,255 [line 462] mth5.timeseries.run_ts.RunTS.from_obspy_stream - WARNING: could not find ex\n", + "2022-04-12 16:06:37,377 [line 462] mth5.timeseries.run_ts.RunTS.from_obspy_stream - WARNING: could not find ey\n", + "2022-04-12 16:06:37,947 [line 235] mth5.timeseries.run_ts.RunTS.validate_metadata - WARNING: end time of dataset 2020-07-13T19:00:00+00:00 does not match metadata end 2020-07-13T21:46:12+00:00 updating metatdata value to 2020-07-13T19:00:00+00:00\n", + "2022-04-12 16:06:46,637 [line 746] mth5.groups.base.Station.add_run - INFO: run a already exists, returning existing group.\n", + "2022-04-12 16:06:53,707 [line 746] mth5.groups.base.Station.add_run - INFO: run b already exists, returning existing group.\n", + "2022-04-12 16:07:02,683 [line 746] mth5.groups.base.Station.add_run - INFO: run c already exists, returning existing group.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Created C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\docs\\examples\\notebooks\\8P_CAS04_NVR08.h5\n", + "Wall time: 1min 46s\n" + ] + } + ], "source": [ "%%time\n", "\n", - "mth5_object = m.make_mth5_from_fdsnclient(request_df, interact=True)\n", + "mth5_object = m.make_mth5_from_fdsnclient(request_df, interact=False)\n", "\n", "print(f\"Created {mth5_object.filename}\")" ] }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# open file already created\n", + "mth5_object = MTH5()\n", + "mth5_object.open_mth5(\"8P_CAS04_NVR08.h5\")" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -427,19 +443,358 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Create a DataFrame that summarizes each channel dataset\n", + "## Channel Summary\n", + "\n", + "A convenience table is supplied with an MTH5 file. This table provides some information about each channel that is present in the file. It also provides columns `hdf5_reference`, `run_hdf5_reference`, and `station_hdf5_reference`, these are internal references within an HDF5 file and can be used to directly access a group or dataset by using `mth5_object.from_reference` method. \n", "\n", - "**Note:** This is quite slow because attribute access is not optimized for speed. And the MTH5 code used for this summary table is not optimized. You should only do this once for a given file. Also, note the `hdf5_reference` column. This is an internal reference for an open HDF5 file and can be used to directly access a group or dataset. " + "**Note:** When a MTH5 file is close the table is resummarized so when you open the file next the `channel_summary` will be up to date. Same with the `tf_summary`." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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surveystationrunlatitudelongitudeelevationcomponentstartendn_samplessample_ratemeasurement_typeazimuthtiltunitshdf5_referencerun_hdf5_referencestation_hdf5_reference
0CONUS SoCalCAS04a37.633351-121.468382329.3875ex2020-06-02 19:00:00+00:002020-06-02 22:07:46+00:00112671.0electric13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
1CONUS SoCalCAS04a37.633351-121.468382329.3875ey2020-06-02 19:00:00+00:002020-06-02 22:07:46+00:00112671.0electric103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
2CONUS SoCalCAS04a37.633351-121.468382329.3875hx2020-06-02 19:00:00+00:002020-06-02 22:07:46+00:00112671.0magnetic13.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
3CONUS SoCalCAS04a37.633351-121.468382329.3875hy2020-06-02 19:00:00+00:002020-06-02 22:07:46+00:00112671.0magnetic103.20.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
4CONUS SoCalCAS04a37.633351-121.468382329.3875hz2020-06-02 19:00:00+00:002020-06-02 22:07:46+00:00112671.0magnetic0.090.0digital counts<HDF5 object reference><HDF5 object reference><HDF5 object reference>
.........................................................
65CONUS SouthNVR08NVR08c38.326630-118.0823821375.4250ex1980-01-01 00:00:00+00:001980-01-01 00:00:00+00:0010.0electric12.60.0none<HDF5 object reference><HDF5 object reference><HDF5 object reference>
66CONUS SouthNVR08NVR08c38.326630-118.0823821375.4250ey1980-01-01 00:00:00+00:001980-01-01 00:00:00+00:0010.0electric102.60.0none<HDF5 object reference><HDF5 object reference><HDF5 object reference>
67CONUS SouthNVR08NVR08c38.326630-118.0823821375.4250hx1980-01-01 00:00:00+00:001980-01-01 00:00:00+00:0010.0magnetic12.60.0none<HDF5 object reference><HDF5 object reference><HDF5 object reference>
68CONUS SouthNVR08NVR08c38.326630-118.0823821375.4250hy1980-01-01 00:00:00+00:001980-01-01 00:00:00+00:0010.0magnetic102.60.0none<HDF5 object reference><HDF5 object reference><HDF5 object reference>
69CONUS SouthNVR08NVR08c38.326630-118.0823821375.4250hz1980-01-01 00:00:00+00:001980-01-01 00:00:00+00:0010.0magnetic12.60.0none<HDF5 object reference><HDF5 object reference><HDF5 object reference>
\n", + "

70 rows × 18 columns

\n", + "
" + ], + "text/plain": [ + " survey station run latitude longitude elevation component \\\n", + "0 CONUS SoCal CAS04 a 37.633351 -121.468382 329.3875 ex \n", + "1 CONUS SoCal CAS04 a 37.633351 -121.468382 329.3875 ey \n", + "2 CONUS SoCal CAS04 a 37.633351 -121.468382 329.3875 hx \n", + "3 CONUS SoCal CAS04 a 37.633351 -121.468382 329.3875 hy \n", + "4 CONUS SoCal CAS04 a 37.633351 -121.468382 329.3875 hz \n", + ".. ... ... ... ... ... ... ... \n", + "65 CONUS South NVR08 NVR08c 38.326630 -118.082382 1375.4250 ex \n", + "66 CONUS South NVR08 NVR08c 38.326630 -118.082382 1375.4250 ey \n", + "67 CONUS South NVR08 NVR08c 38.326630 -118.082382 1375.4250 hx \n", + "68 CONUS South NVR08 NVR08c 38.326630 -118.082382 1375.4250 hy \n", + "69 CONUS South NVR08 NVR08c 38.326630 -118.082382 1375.4250 hz \n", + "\n", + " start end n_samples \\\n", + "0 2020-06-02 19:00:00+00:00 2020-06-02 22:07:46+00:00 11267 \n", + "1 2020-06-02 19:00:00+00:00 2020-06-02 22:07:46+00:00 11267 \n", + "2 2020-06-02 19:00:00+00:00 2020-06-02 22:07:46+00:00 11267 \n", + "3 2020-06-02 19:00:00+00:00 2020-06-02 22:07:46+00:00 11267 \n", + "4 2020-06-02 19:00:00+00:00 2020-06-02 22:07:46+00:00 11267 \n", + ".. ... ... ... \n", + "65 1980-01-01 00:00:00+00:00 1980-01-01 00:00:00+00:00 1 \n", + "66 1980-01-01 00:00:00+00:00 1980-01-01 00:00:00+00:00 1 \n", + "67 1980-01-01 00:00:00+00:00 1980-01-01 00:00:00+00:00 1 \n", + "68 1980-01-01 00:00:00+00:00 1980-01-01 00:00:00+00:00 1 \n", + "69 1980-01-01 00:00:00+00:00 1980-01-01 00:00:00+00:00 1 \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", + ".. ... ... ... ... ... \n", + "65 0.0 electric 12.6 0.0 none \n", + "66 0.0 electric 102.6 0.0 none \n", + "67 0.0 magnetic 12.6 0.0 none \n", + "68 0.0 magnetic 102.6 0.0 none \n", + "69 0.0 magnetic 12.6 0.0 none \n", + "\n", + " hdf5_reference run_hdf5_reference station_hdf5_reference \n", + "0 \n", + "1 \n", + "2 \n", + "3 \n", + "4 \n", + ".. ... ... ... \n", + "65 \n", + "66 \n", + "67 \n", + "68 \n", + "69 \n", + "\n", + "[70 rows x 18 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "%time\n", - "\n", "mth5_object.channel_summary.clear_table()\n", "mth5_object.channel_summary.summarize()\n", "\n", @@ -447,20 +802,785 @@ "ch_df" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Have a look at a station\n", + "\n", + "Lets grab one station `CAS04` and have a look at its metadata and contents.\n", + "Here we will grab it from the `mth5_object`." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{\n", + " \"station\": {\n", + " \"acquired_by.name\": null,\n", + " \"channels_recorded\": [\n", + " \"ex\",\n", + " \"ey\",\n", + " \"hx\",\n", + " \"hy\",\n", + " \"hz\"\n", + " ],\n", + " \"data_type\": \"BBMT\",\n", + " \"fdsn.id\": \"CAS04\",\n", + " \"geographic_name\": \"Corral Hollow, CA, USA\",\n", + " \"hdf5_reference\": \"\",\n", + " \"id\": \"CAS04\",\n", + " \"location.declination.model\": \"WMM\",\n", + " \"location.declination.value\": -13.5,\n", + " \"location.elevation\": 329.3875,\n", + " \"location.latitude\": 37.633351,\n", + " \"location.longitude\": -121.468382,\n", + " \"mth5_type\": \"Station\",\n", + " \"orientation.method\": null,\n", + " \"orientation.reference_frame\": \"geographic\",\n", + " \"provenance.creation_time\": \"1980-01-01T00:00:00+00:00\",\n", + " \"provenance.software.author\": \"none\",\n", + " \"provenance.software.name\": null,\n", + " \"provenance.software.version\": null,\n", + " \"provenance.submitter.email\": null,\n", + " \"provenance.submitter.organization\": null,\n", + " \"run_list\": [\n", + " \"a\",\n", + " \"b\",\n", + " \"c\",\n", + " \"d\"\n", + " ],\n", + " \"time_period.end\": \"2020-07-13T21:46:12+00:00\",\n", + " \"time_period.start\": \"2020-06-02T18:41:43+00:00\"\n", + " }\n", + "}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cas04 = mth5_object.get_station(\"CAS04\", survey=\"CONUS_SoCal\")\n", + "cas04.metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Changing Metadata\n", + "If you want to change the metadata of any group, be sure to use the `write_metadata` method. Here's an example:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "declination:\n", + "\tmodel = WMM\n", + "\tvalue = -13.5\n" + ] + } + ], + "source": [ + "cas04.metadata.location.declination.value = -13.5\n", + "cas04.write_metadata()\n", + "print(cas04.metadata.location.declination)" + ] + }, { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ - "## When you are finished be sure to close the file" + "## Have a look at a single channel\n", + "\n", + "Let's pick out a channel and interogate it. There are a couple ways\n", + "1. Get a channel the first will be from the `hdf5_reference` [*demonstrated here*]\n", + "2. Get a channel from `mth5_object`\n", + "3. Get a station first then get a channel\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Channel Summary:\n", + "\tStation: CAS04\n", + "\tRun: a\n", + "\tChannel Type: electric\n", + "\tComponent: ex\n", + "\tSample Rate: 1.0\n", + "\tStart: 2020-06-02T19:00:00+00:00\n", + "\tEnd: 2020-06-02T22:07:46+00:00\n", + "\tN Samples: 11267\n" + ] + } + ], + "source": [ + "ex = mth5_object.from_reference(ch_df.iloc[0].hdf5_reference).to_channel_ts()\n", + "print(ex)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{\n", + " \"electric\": {\n", + " \"channel_number\": 0,\n", + " \"comments\": \", mt: c, mt: b, mt: a, run_ids: []\",\n", + " \"component\": \"ex\",\n", + " \"data_quality.rating.value\": 0,\n", + " \"dipole_length\": 92.0,\n", + " \"filter.applied\": [\n", + " false,\n", + " false,\n", + " false,\n", + " false,\n", + " false,\n", + " false\n", + " ],\n", + " \"filter.name\": [\n", + " \"electric_si_units\",\n", + " \"electric_dipole_92.000\",\n", + " \"electric_butterworth_low_pass\",\n", + " \"electric_butterworth_high_pass\",\n", + " \"electric_analog_to_digital\",\n", + " \"electric_time_offset\"\n", + " ],\n", + " \"hdf5_reference\": \"\",\n", + " \"measurement_azimuth\": 13.2,\n", + " \"measurement_tilt\": 0.0,\n", + " \"mth5_type\": \"Electric\",\n", + " \"negative.elevation\": 329.4,\n", + " \"negative.id\": \"200406D\",\n", + " \"negative.latitude\": 37.633351,\n", + " \"negative.longitude\": -121.468382,\n", + " \"negative.manufacturer\": \"Oregon State University\",\n", + " \"negative.model\": \"Pb-PbCl2 kaolin gel Petiau 2 chamber type\",\n", + " \"negative.type\": \"electrode\",\n", + " \"positive.elevation\": 329.4,\n", + " \"positive.id\": \"200406B\",\n", + " \"positive.latitude\": 37.633351,\n", + " \"positive.longitude\": -121.468382,\n", + " \"positive.manufacturer\": \"Oregon State University\",\n", + " \"positive.model\": \"Pb-PbCl2 kaolin gel Petiau 2 chamber type\",\n", + " \"positive.type\": \"electrode\",\n", + " \"sample_rate\": 1.0,\n", + " \"time_period.end\": \"2020-06-02T22:07:46+00:00\",\n", + " \"time_period.start\": \"2020-06-02T19:00:00+00:00\",\n", + " \"type\": \"electric\",\n", + " \"units\": \"digital counts\"\n", + " }\n", + "}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ex.channel_metadata" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calibrate time series data\n", + "Most data loggers output data in digital counts. Then a series of filters that represent the various instrument responses are applied to get the data into physical units. The data can then be analyzed and processed. Commonly this is done during the processing step, but it is important to be able to look at time series data in physical units. Here we provide a `remove_instrument_response` method in the `ChananelTS` object. Here's an example: " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filters Included:\n", + "=========================\n", + "coefficient_filter:\n", + "\tcalibration_date = 1980-01-01\n", + "\tcomments = practical to SI unit conversion\n", + "\tgain = 1e-06\n", + "\tname = electric_si_units\n", + "\ttype = coefficient\n", + "\tunits_in = mV/km\n", + "\tunits_out = V/m\n", + "--------------------\n", + "coefficient_filter:\n", + "\tcalibration_date = 1980-01-01\n", + "\tcomments = electric dipole for electric field\n", + "\tgain = 92.0\n", + "\tname = electric_dipole_92.000\n", + "\ttype = coefficient\n", + "\tunits_in = V/m\n", + "\tunits_out = V\n", + "--------------------\n", + "pole_zero_filter:\n", + "\tcalibration_date = 1980-01-01\n", + "\tcomments = NIMS electric field 5 pole Butterworth 0.5 low pass (analog)\n", + "\tgain = 1.0\n", + "\tname = electric_butterworth_low_pass\n", + "\tnormalization_factor = 313383.493219835\n", + "\tpoles = [ -3.883009+11.951875j -3.883009-11.951875j -10.166194 +7.386513j\n", + " -10.166194 -7.386513j -12.566371 +0.j ]\n", + "\ttype = zpk\n", + "\tunits_in = V\n", + "\tunits_out = V\n", + "\tzeros = []\n", + "--------------------\n", + "pole_zero_filter:\n", + "\tcalibration_date = 1980-01-01\n", + "\tcomments = NIMS electric field 1 pole Butterworth high pass (analog)\n", + "\tgain = 1.0\n", + "\tname = electric_butterworth_high_pass\n", + "\tnormalization_factor = 1.00000000378188\n", + "\tpoles = [-0.000167+0.j]\n", + "\ttype = zpk\n", + "\tunits_in = V\n", + "\tunits_out = V\n", + "\tzeros = [ 0.+0.j]\n", + "--------------------\n", + "coefficient_filter:\n", + "\tcalibration_date = 1980-01-01\n", + "\tcomments = analog to digital conversion (electric)\n", + "\tgain = 409600000.0\n", + "\tname = electric_analog_to_digital\n", + "\ttype = coefficient\n", + "\tunits_in = V\n", + "\tunits_out = count\n", + "--------------------\n", + "time_delay_filter:\n", + "\tcalibration_date = 1980-01-01\n", + "\tcomments = time offset in seconds (digital)\n", + "\tdelay = -0.285\n", + "\tgain = 1.0\n", + "\tname = electric_time_offset\n", + "\ttype = time delay\n", + "\tunits_in = count\n", + "\tunits_out = count\n", + "--------------------\n", + "\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bafc68c4ecd14e7fa9fb3f8738f8538e", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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\n", + " \n", + "
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mth5.timeseries.ts_filters.RemoveInstrumentResponse.remove_instrument_response - INFO: Step 2: Removing Mean\n", + "2022-04-13 13:00:16,322 [line 483] mth5.timeseries.ts_filters.RemoveInstrumentResponse.remove_instrument_response - INFO: Step 3: Applying Zero Padding\n", + "2022-04-13 13:00:16,351 [line 510] mth5.timeseries.ts_filters.RemoveInstrumentResponse.remove_instrument_response - INFO: Step 4: Removing Calibration\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "79a4e43b3d13421ca781cd3959869f11", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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\n", + " Figure\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "array([-0.92496459, -0.86883736, -0.80189187, ..., 0.28510908,\n", + " 0.35069378, 0.51318662])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ex.remove_instrument_response(plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Have a look at a run\n", + "\n", + "Let's pick out a run, take a slice of it, and interogate it. There are a couple ways\n", + "1. Get a run the first will be from the `run_hdf5_reference` [*demonstrated here*]\n", + "2. Get a run from `mth5_object`\n", + "3. Get a station first then get a run" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "RunTS Summary:\n", + "\tStation: CAS04\n", + "\tRun: a\n", + "\tStart: 2020-06-02T19:00:00+00:00\n", + "\tEnd: 2020-06-02T19:06:00+00:00\n", + "\tSample Rate: 1.0\n", + "\tComponents: ['ex', 'ey', 'hx', 'hy', 'hz']\n" + ] + } + ], + "source": [ + "run_from_reference = mth5_object.from_reference(ch_df.iloc[0].run_hdf5_reference).to_runts(start=ch_df.iloc[0].start.isoformat(), n_samples=360)\n", + "print(run_from_reference)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c43faa6ddbb545d7ad645f84f7e2c436", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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stationsurveylatitudelongitudeelevationtf_idunitshas_impedancehas_tipperhas_covarianceperiod_minperiod_maxhdf5_referencestation_hdf5_reference
0CAS04CONUS_South37.633351-121.468382329.387CAS04noneTrueTrueTrue4.6545529127.11<HDF5 object reference><HDF5 object reference>
1NVR08CONUS_South38.326630-118.0823821375.425NVR08noneTrueTrueTrue4.6545529127.11<HDF5 object reference><HDF5 object reference>
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" + ], + "text/plain": [ + " station survey latitude longitude elevation tf_id units \\\n", + "0 CAS04 CONUS_South 37.633351 -121.468382 329.387 CAS04 none \n", + "1 NVR08 CONUS_South 38.326630 -118.082382 1375.425 NVR08 none \n", + "\n", + " has_impedance has_tipper has_covariance period_min period_max \\\n", + "0 True True True 4.65455 29127.11 \n", + "1 True True True 4.65455 29127.11 \n", + "\n", + " hdf5_reference station_hdf5_reference \n", + "0 \n", + "1 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mth5_object.tf_summary.summarize()\n", + "tf_df = mth5_object.tf_summary.to_dataframe()\n", + "tf_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot the transfer functions using MTpy\n", + "\n", + "**Note:** This currently works on branch `mtpy/v2_plots`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from mtpy import MTCollection" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "mc = MTCollection()\n", + "mc.open_collection(r\"8P_CAS04_NVR08\")" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\jpeacock\\Documents\\GitHub\\mtpy\\mtpy\\imaging\\plot_mt_response.py:420: UserWarning: Attempted to set non-positive left xlim on a log-scaled axis.\n", + "Invalid limit will be ignored.\n", + " self.fig.clf()\n", + "C:\\Users\\jpeacock\\Documents\\GitHub\\mtpy\\mtpy\\imaging\\plot_mt_response.py:420: UserWarning: Attempting to set identical left == right == 1.0 results in singular transformations; automatically expanding.\n", + " self.fig.clf()\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a3db1789f3fb46b3bfba0cd259278620", + "version_major": 2, + "version_minor": 0 + }, + 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", 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", + "text/html": [ + "\n", + "
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\n", + " Figure 2\n", + "
\n", + " \n", + "
\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pmr = mc.plot_mt_response([\"CAS04\", \"NVR08\"], plot_style=\"1\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot Station locations\n", + "\n", + "Here we can plot station locations for all stations in the file, or we can give it a bounding box. If you have internet access a basemap will be plotted using [Contextily](https://contextily.readthedocs.io/en/latest/). " + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "586c6e8d5dcf4ef89fda59e344f6b454", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", + "text/html": [ + "\n", + "
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8c9bf644..e6e51680 100644 --- a/docs/examples/notebooks/make_mth5_example_iris.ipynb +++ b/docs/examples/notebooks/make_mth5_example_iris.ipynb @@ -61,12 +61,11 @@ "outputs": [], "source": [ "channels = [\"LFE\", \"LFN\", \"LFZ\", \"LQE\", \"LQN\"]\n", - "CAY10 = [\"EM\",\"CAY10\", '2019-10-07T00:00:00', '2019-10-30T00:00:00']\n", - "CAS04 = [\"ZU\", \"CAS04\", '2020-06-02T19:00:00', '2020-07-13T19:00:00'] \n", - "NVR08 = [\"ZU\", \"NVR08\", '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", + "CAS04 = [\"8P\", \"CAS04\", '2020-06-02T19:00:00', '2020-07-13T19:00:00'] \n", + "NVR08 = [\"8P\", \"NVR08\", '2020-06-02T19:00:00', '2020-07-13T19:00:00']\n", "\n", "request_list = []\n", - "for entry in [CAY10, CAS04, NVR08]:\n", + "for entry in [CAS04, NVR08]:\n", " for channel in channels:\n", " request_list.append(\n", " [entry[0], entry[1], \"\", channel, entry[2], entry[3]]\n", diff --git a/docs/examples/notebooks/remove_instrument_response_example.ipynb b/docs/examples/notebooks/remove_instrument_response_example.ipynb index 08f5f540..9a7d7c8d 100644 --- a/docs/examples/notebooks/remove_instrument_response_example.ipynb +++ b/docs/examples/notebooks/remove_instrument_response_example.ipynb @@ -24,14 +24,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "2022-04-06T11:48:52 [line 157] numexpr.utils._init_num_threads - INFO: NumExpr defaulting to 8 threads.\n" + "2022-04-11T17:14:37 [line 157] numexpr.utils._init_num_threads - INFO: NumExpr defaulting to 8 threads.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2022-04-06 11:48:55,443 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" + "2022-04-11 17:14:39,983 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" ] } ], @@ -190,6 +190,27 @@ "ch_df" ] }, + { + "cell_type": "markdown", + "id": "d236875c-d23e-4ece-bbb0-6f7a78e039f7", + "metadata": {}, + "source": [ + "## Get observatory data\n", + "\n", + "https://geomag.usgs.gov/ws/data/?id=FRN&type=adjusted&elements=H&sampling_period=1&format=json&starttime=2020-06-02T19:00:00Z&endtime=2020-06-02T22:07:46Z" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "134ea085-8b2d-4cc9-9351-b84329108d9c", + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "frn_json = 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+ ] + }, { "cell_type": "markdown", "id": "9ed278c9-fca5-436c-9308-645350dc0d33", @@ -204,7 +225,7 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 5, "id": "09268f20-47fb-420b-aafc-023704f42a83", "metadata": {}, "outputs": [], @@ -214,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 6, "id": "1b7170cc-095d-4e3c-9738-1e8327cff696", "metadata": {}, "outputs": [ @@ -232,7 +253,7 @@ "\tsample rate: 1.0" ] }, - "execution_count": 95, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -253,7 +274,7 @@ }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 7, "id": "52f91525-5eb6-4e6c-8865-4aee81c77795", "metadata": {}, "outputs": [], @@ -273,7 +294,7 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 8, "id": "7b4bf97e-5d14-4519-a6a8-b774f5506624", "metadata": {}, "outputs": [ @@ -315,7 +336,7 @@ "--------------------" ] }, - "execution_count": 97, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -336,33 +357,20 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 9, "id": "d85d92a2-bf38-462d-9097-6c4e988ac919", "metadata": {}, "outputs": [ { "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "5b0c118d55c3418d9acb511b97754c11", - "version_major": 2, - "version_minor": 0 - }, - "image/png": 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\n", "text/plain": [ - "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -384,19 +392,20 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 10, "id": "dc49433f-a00f-4f1d-b85f-611313f05d71", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from scipy import signal\n", - "from matplotlib import pyplot as plt" + "from matplotlib import pyplot as plt\n", + "from matplotlib.lines import Line2D" ] }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 11, "id": "08ec859d-0026-46c4-9358-0b7f799f12b3", "metadata": {}, "outputs": [], @@ -406,7 +415,7 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 12, "id": "e0c3740d-9b6f-4143-ae9e-f2af712826d4", "metadata": {}, "outputs": [], @@ -457,7 +466,7 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 13, "id": "61105c61-071f-4086-94ad-cc3008456087", "metadata": {}, "outputs": [], @@ -496,12 +505,150 @@ }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 23, "id": "d4bd9be9-aa51-44a3-8035-fcd3ef48510a", "metadata": {}, "outputs": [], "source": [ - "def remove_instrument_response(channel_obj, zero_pad=False, window=None, window_params={}):\n", + "def _subplots(x, y, fig, sample_rate, color, nrows, num, label):\n", + " ax_t = fig.get_axes()[0]\n", + " ax_f = fig.get_axes()[1]\n", + " ax = fig.add_subplot(nrows, 2, num, sharex=ax_t)\n", + " ax2 = fig.add_subplot(nrows, 2, num+1, sharex=ax_f)\n", + "\n", + " # plot time series\n", + " line = Line2D([0], [0], color=color)\n", + " ax.plot(x, y, color=color)\n", + " f = np.fft.rfftfreq(x.size, d=sample_rate)\n", + " #plot spectra\n", + " data = np.fft.rfft(y)\n", + " ax2.loglog(f, abs(data), color=color)\n", + " ax.legend([line], [label], loc=\"upper left\", borderaxespad=.01, borderpad=.1, markerscale=.02).set_zorder(1000)\n", + "\n", + "def get_window(window, window_params, size):\n", + " return getattr(signal.windows, window)(size, **window_params)\n", + "\n", + "def apply_t_window(ts, window, window_params, plot=True, time_array=None, fig=None, sample_rate=1, subplot_dict=None):\n", + " \"\"\"\n", + " apply a time domain window\n", + " \"\"\"\n", + " w = get_window(window, window_params, ts.size)\n", + " ts = ts * w\n", + " \n", + " if plot:\n", + " if time_array is None:\n", + " time_array = np.arange(ts.size)\n", + " _subplots(time_array, ts, fig, sample_rate, (.7, .1, .25), subplot_dict[\"nrows\"], subplot_dict[\"t_window\"], f\"t_window {window.capitalize()}\")\n", + "\n", + " return ts\n", + "\n", + "def apply_f_window(data, window, window_params, plot=True, fig=None, time_array=None, sample_interval=1, subplot_dict=None):\n", + " \"\"\"\n", + " apply a frequency domain window\n", + " \n", + " Need to create a window twice the size of the input because we are only taking the rfft which gives just half the spectra\n", + " and then take only half the window\n", + " \"\"\"\n", + " w = get_window(window, window_params, 2 * data.size)[data.size:]\n", + " data = data * w\n", + " if plot:\n", + " f = np.fft.rfftfreq(2 * data.size, d=sample_interval)[1:]\n", + " ax_t = fig.get_axes()[0]\n", + " ax_f = fig.get_axes()[1]\n", + " ax = fig.add_subplot(subplot_dict[\"nrows\"], 2, subplot_dict[\"f_window\"], sharex=ax_t)\n", + " ax2 = fig.add_subplot(subplot_dict[\"nrows\"], 2, subplot_dict[\"f_window\"] + 1, sharex=ax_f)\n", + " \n", + " ax.plot(time_array, abs(np.fft.irfft(data)[0:time_array.size]), color=(.85, .1, .15)) \n", + " ax2.loglog(f, abs(data), color=(.85, .1, .15))\n", + " axt2 = ax2.twinx()\n", + " axt2.semilogx(f, w, color=(.5, .5, .5), zorder=0)\n", + " line = Line2D([0], [0], color=(.85, .1, .15))\n", + " ax.legend([line], [f\"Freq Window {window.capitalize()}\"], loc=\"upper left\", borderaxespad=.01, borderpad=.1)\n", + " return data\n", + " \n", + "def apply_detrend(ts, plot=True, time_array=None, fig=None, sample_rate=1, subplot_dict=None):\n", + " \"\"\"\n", + " detrend data with scipy.detrend\n", + " \"\"\"\n", + " ts = signal.detrend(ts, type=\"linear\")\n", + " \n", + " if plot:\n", + " if time_array is None:\n", + " time_array = np.arange(ts.size)\n", + " _subplots(time_array, ts, fig, sample_rate, (.45, .1, .5), subplot_dict[\"nrows\"], subplot_dict[\"detrend\"], \"Detrended\") \n", + " return ts\n", + "\n", + "def apply_zero_mean(ts, plot=True, time_array=None, fig=None, sample_rate=1, subplot_dict=None):\n", + " \"\"\"\n", + " remove mean\n", + " \"\"\"\n", + " ts = ts - ts.mean()\n", + " \n", + " if plot:\n", + " if time_array is None:\n", + " time_array = np.arange(ts.size)\n", + " _subplots(time_array, ts, fig, sample_rate, (.55, .1, .4), subplot_dict[\"nrows\"], subplot_dict[\"zero_mean\"], \"Zero Mean\") \n", + " return ts\n", + " \n", + "def apply_zero_pad(ts, plot=True, time_array=None, fig=None, sample_rate=1, subplot_dict=None):\n", + " \"\"\"\n", + " zero pad to power of 2, at the end of the time series\n", + " \"\"\"\n", + " \n", + " pad_ts = zero_pad(ts)\n", + "\n", + " if plot:\n", + " if time_array is None:\n", + " time_array = np.arange(pad_ts.size)\n", + " else:\n", + " dt = int(1./sample_rate * 1000000000)\n", + " diff = int(((pad_ts.size - ts.size)+ 1) * dt)\n", + " time_array = np.arange(time_array[0], time_array[-1] + np.timedelta64(diff), np.timedelta64(dt), dtype='datetime64[ns]')\n", + " _subplots(time_array, pad_ts, fig, sample_rate, (.7, .1, .25), subplot_dict[\"nrows\"], subplot_dict[\"pad\"], \"Zero Pad\") \n", + " \n", + " return pad_ts\n", + "\n", + "def apply_bandpass(ts, bandpass, plot=True, time_array=None, fig=None, sample_interval=1, subplot_dict=None):\n", + " \"\"\"\n", + " apply a bandpass filter\n", + " \"\"\"\n", + " ts = butter_bandpass_filter(ts, bandpass[\"low\"], bandpass[\"high\"], sample_interval, order=bandpass[\"order\"])\n", + " \n", + " if plot:\n", + " if time_array is None:\n", + " time_array = np.arange(ts.size)\n", + " _subplots(time_array, ts, fig, sample_interval, (.875, .1, .1), subplot_dict[\"nrows\"], subplot_dict[\"bandpass\"], \"Band Pass\") \n", + " \n", + " return ts\n", + " \n", + " \n", + "def get_subplot_count(pad, zero_mean, detrend, t_window, f_window, bandpass):\n", + " order = [\"detrend\", \"zero_mean\", \"t_window\", \"pad\", \"f_window\", \"bandpass\"]\n", + " pdict = {\"pad\": pad, \"zero_mean\": zero_mean, \"detrend\": detrend, \"t_window\": t_window, \"f_window\":f_window, \"bandpass\": bandpass}\n", + " subplot_dict = {}\n", + " count = 3\n", + " nrows = 2\n", + " for key in order:\n", + " value = pdict[key]\n", + " if value:\n", + " subplot_dict[key] = count\n", + " count += 2\n", + " nrows += 1\n", + " subplot_dict[\"nrows\"] = nrows\n", + " \n", + " return subplot_dict\n", + " \n", + "def remove_instrument_response(\n", + " channel_obj, \n", + " pad=False, \n", + " zero_mean=True, \n", + " detrend=False,\n", + " t_window=None, \n", + " t_window_params={}, \n", + " f_window=None, \n", + " f_window_params={}, \n", + " plot=True,\n", + " bandpass={}):\n", " \"\"\"\n", " Arguments\n", " -----------\n", @@ -517,18 +664,51 @@ " for a working example with seismic data see https://github.com/obspy/obspy/blob/master/obspy/core/trace.py `remove_response`\n", " \n", " \"\"\"\n", - " if zero_pad:\n", - " # pad the time series to a power of 2, this may be overkill, especially for long time series\n", - " npow_ts = zero_pad(channel_obj.ts)\n", - " else:\n", - " if channel_obj.ts.size % 2 == 1:\n", - " npow_ts = np.zeros(channel_obj.ts.size + 1)\n", - " npow_ts[0:channel_obj.ts.size] = channel_obj.ts\n", - " else:\n", - " npow_ts = channel_obj.ts\n", + " ts = np.copy(channel_obj.ts)\n", + " sr = channel_obj.sample_interval\n", + " f = np.fft.rfftfreq(ts.size, d=sr)\n", + " step = 1\n", + " if plot:\n", + " subplot_dict = get_subplot_count(pad, zero_mean, detrend, t_window, f_window, bandpass)\n", + " fig = plt.figure(1, figsize=[10,12])\n", + " fig.clf()\n", + " ax = fig.add_subplot(subplot_dict[\"nrows\"], 2, 1)\n", + " ax2 = fig.add_subplot(subplot_dict[\"nrows\"], 2, 2)\n", + " t = channel_obj._ts.time.to_numpy()\n", + " l1, = ax.plot(t, ts, color=\"k\", lw=2)\n", + " ax.set_xlim((t[0], t[-1]))\n", + " l2, = ax2.loglog(f, abs(np.fft.rfft(ts)), \"k\", lw=2)\n", + " ax2.set_xlim((f[0], f[-1]))\n", + " ax.legend([l1], [\"Original\"], loc=\"upper left\", borderaxespad=.01, borderpad=.1)\n", " \n", + " # detrend\n", + " if detrend:\n", + " ts = apply_detrend(ts, plot, t, fig, sr, subplot_dict)\n", + " print(f\"Step {step}: Applying Linear Detrend\")\n", + " step += 1\n", + " # zero mean\n", + " if zero_mean:\n", + " ts = apply_zero_mean(ts, plot, t, fig, sr, subplot_dict)\n", + " print(f\"Step {step}: Removing Mean\")\n", + " step += 1\n", + " \n", + " # filter in time domain\n", + " if t_window is not None:\n", + " ts = apply_t_window(ts, t_window, t_window_params, plot, t, fig, sr, subplot_dict)\n", + " print(f\"Step {step}: Applying {t_window} Time Window\")\n", + " step += 1\n", + " if plot:\n", + " wax = fig.get_axes()[subplot_dict[\"t_window\"] - 1].twinx() \n", + " tw, = wax.plot(t, get_window(t_window, t_window_params, ts.size), color=(.75, .75, .75), zorder=0)\n", + " \n", + " if pad:\n", + " # pad the time series to a power of 2, this may be overkill, especially for long time series\n", + " ts = apply_zero_pad(ts, plot, t, fig, sr, subplot_dict)\n", + " print(f\"Step {step}: Applying Zero Padding\")\n", + " step += 1\n", + "\n", " # get the real frequencies of the FFT\n", - " f = np.fft.rfftfreq(npow_ts.size, d=channel_obj.sample_interval)\n", + " f = np.fft.rfftfreq(ts.size, d=channel_obj.sample_interval)\n", " \n", " if channel_obj.channel_response_filter.filters_list is []:\n", " raise ValueError(\"There are no filters in channel_response to remove\")\n", @@ -540,21 +720,44 @@ " # remove the DC term at frequency == 0\n", " cr[-1] = abs(cr[-2]) + 0.0j\n", " \n", - " data = np.fft.rfft(npow_ts)\n", + " data = np.fft.rfft(ts)\n", " # remove DC term\n", " data[-1] = abs(data[-1]) + 0.0j\n", " \n", " # if a window is requested then create it here and mulitply by the data\n", " # the windows are designed to be symmetrical about frequency = 0\n", " # here we are taking only the real part of the FFT so we cut the window in half\n", - " if window is not None:\n", - " w = getattr(signal.windows, window)(data.size * 2, **window_params)[0: int(data.size)]\n", - " data = data * w\n", + " if f_window is not None:\n", + " data = apply_f_window(data, f_window, f_window_params, plot=plot, fig=fig, time_array=t, sample_interval=sr, subplot_dict=subplot_dict)\n", + " print(f\"Step {step}: Applying {f_window} Frequency Window\")\n", + " step += 1\n", " \n", " # calibrate the time series, compute real part of fft, divide out channel response, inverse fft\n", - " calibrated_ts = np.fft.irfft(data / cr)\n", + " calibrated_ts = np.fft.irfft(data / cr)[0:channel_obj.ts.size]\n", + " print(f\"Step {step}: Removing Calibration\")\n", + " step += 1\n", " \n", - " return calibrated_ts[0:channel_obj.ts.size]" + " # If a time window was applied, need to un-apply it to reconstruct the signal.\n", + " if t_window is not None:\n", + " w = get_window(t_window, t_window_params, calibrated_ts.size)\n", + " calibrated_ts = calibrated_ts / w\n", + " print(f\"Step {step}: Un-applying Time Window\")\n", + " step += 1\n", + " \n", + " if bandpass:\n", + " calibrated_ts = apply_bandpass(calibrated_ts, bandpass, plot, t, fig, sr, subplot_dict) \n", + " print(f\"Step {step}: Applying Bandpass Filter\")\n", + " step += 1\n", + " if plot:\n", + " _subplots(t[0:calibrated_ts.size], calibrated_ts, fig, sr, (1, .1, .1), subplot_dict[\"nrows\"], subplot_dict[\"nrows\"] * 2 -1, \"Calibrated\")\n", + " fig.get_axes()[-2].set_ylabel(channel_obj.channel_response_filter.units_in)\n", + " if t_window is not None:\n", + " wax = fig.get_axes()[-2].twinx() \n", + " tw, = wax.plot(t, 1./w, color=(.5, .5, .5), zorder=0)\n", + " fig.tight_layout()\n", + " plt.show()\n", + "\n", + " return calibrated_ts" ] }, { @@ -567,69 +770,47 @@ }, { "cell_type": "code", - "execution_count": 104, + "execution_count": 30, "id": "9147e87d-2a46-4b8b-aa9c-0a290847de70", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\jpeacock\\Anaconda3\\envs\\mt\\lib\\site-packages\\ipykernel_launcher.py:162: UserWarning: Attempted to set non-positive left xlim on a log-scaled axis.\n", + "Invalid limit will be ignored.\n", + "C:\\Users\\jpeacock\\Anaconda3\\envs\\mt\\lib\\site-packages\\ipykernel_launcher.py:169: UserWarning: Attempted to set non-positive left xlim on a log-scaled axis.\n", + "Invalid limit will be ignored.\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "(11267,)\n" + "Step 1: Applying Linear Detrend\n", + "Step 2: Removing Mean\n", + "Step 3: Applying hamming Time Window\n", + "Step 4: Applying Zero Padding\n", + "Step 5: Removing Calibration\n", + "Step 6: Un-applying Time Window\n" ] - } - ], - "source": [ - "calibrated_ex = remove_instrument_response(exts, window=\"kaiser\", window_params={\"beta\":5})\n", - "print(calibrated_ex.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "id": "e5786d2b-7653-4331-8c6f-b7274c0860aa", - "metadata": {}, - "outputs": [], - "source": [ - "# apply a bandpass otherwise low frequencies get blown up\n", - "bp_calibrated_ts = butter_bandpass_filter(calibrated_ex, .35, None, exts.sample_rate, order=3)" - ] - }, - { - "cell_type": "markdown", - "id": "6aacdfae-cd0b-4d39-a3c3-bed30f1f6eaa", - "metadata": {}, - "source": [ - "## Plot response and look at the differences\n", - "\n", - "The big difference are at the ends of the time series which have to do with the window applied and the calibration. Need to figure out a good scheme to reduce those effects. \n", - "\n", - "- Better window\n", - "- Better padding\n", - "- Better removal scheme" - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "id": "a4e792af-c98c-4ad2-84b0-1c2135d0703a", - "metadata": {}, - "outputs": [ + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0226d41ba72f49c3a441c81bbfcfc11a", + "model_id": "23573f8620ec492cbae78e9d41229c95", "version_major": 2, "version_minor": 0 }, - "image/png": 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"text/html": [ "\n", "
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\n", - " Figure\n", + " Figure 1\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -639,64 +820,29 @@ }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "plt.rcParams[\"figure.subplot.hspace\"] = .45\n", - "\n", - "f = np.fft.rfftfreq(calibrated_ex.size, d=exts.sample_interval)\n", - "\n", - "fig = plt.figure(figsize=[12, 8])\n", - "ax_original = fig.add_subplot(3, 2, 1)\n", - "l1, = ax_original.plot(exts._ts.time, exts.ts, color=(0, 0, 0))\n", - "ax_original.set_ylabel(f\"Original [{exts.channel_response_filter.units_out}]\")\n", - "\n", - "ax_original_fft = fig.add_subplot(3, 2, 2)\n", - "l1, = ax_original_fft.loglog(f, abs(np.fft.rfft(exts.ts)), color=(0, 0, 0))\n", - "ax_original_fft.loglog(f, abs(exts.channel_response_filter.complex_response(f)[::-1]), color=(.1, .75, .2))\n", - "\n", - "ax_calibrated = fig.add_subplot(3, 2, 3, sharex=ax_original)\n", - "l2, = ax_calibrated.plot(exts._ts.time, calibrated_ex, color=(.75, .1, .2))\n", - "ax_calibrated.set_ylabel(f\"Calibrated [{exts.channel_response_filter.units_in}]\")\n", - "\n", - "ax_calibrated_fft = fig.add_subplot(3, 2, 4, sharex=ax_original_fft)\n", - "l2, = ax_calibrated_fft.loglog(f, abs(np.fft.rfft(calibrated_ex)), color=(.75, .1, .2))\n", - "\n", - "ax_bandpassed = fig.add_subplot(3, 2, 5, sharex=ax_original)\n", - "l3, = ax_bandpassed.plot(exts._ts.time, bp_calibrated_ts, color=(.2, .1, .75))\n", - "ax_bandpassed.set_ylabel(f\"Bandpassed [{exts.channel_response_filter.units_in}]\")\n", - "\n", - "ax_bandpassed_fft = fig.add_subplot(3, 2, 6, sharex=ax_original_fft)\n", - "l3, = ax_bandpassed_fft.loglog(f, abs(np.fft.rfft(bp_calibrated_ts)), color=(.2, .1, .75))\n", - "\n", - "fig.canvas.toolbar_visible = True\n", - "fig.canvas.header_visible = True\n", - "fig.canvas.resizable = True\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 116, - "id": "e15cd94e-52e2-430c-b9eb-fe947c7046c9", - "metadata": {}, - "outputs": [ + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\jpeacock\\Anaconda3\\envs\\mt\\lib\\site-packages\\ipykernel_launcher.py:26: DeprecationWarning: parsing timezone aware datetimes is deprecated; this will raise an error in the future\n" + ] + }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e39a8b5f39c44cf39c360f9bc82866ae", + "model_id": "4c6bb8499c364928986d33a514715b94", "version_major": 2, "version_minor": 0 }, - "image/png": 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\n", - " Figure\n", + " Figure 2\n", "
\n", - " \n", + " \n", "
\n", " " ], @@ -709,93 +855,65 @@ } ], "source": [ - "fig = plt.figure(figsize=[12, 6])\n", + "calibrated_ex = remove_instrument_response(\n", + " exts, \n", + " zero_mean=True,\n", + " detrend=True,\n", + " pad=True,\n", + " t_window=\"hamming\",\n", + " t_window_params={},\n", + " #f_window=\"tukey\",\n", + " #f_window_params={\"alpha\":.1},\n", + " #bandpass={\"low\": .0001, \"high\": .4, \"order\":2},\n", + " plot=True)\n", + "\n", + "# plot normalized version of original and calibrated\n", + "fig = plt.figure(2, figsize=[5,4])\n", + "fig.clf()\n", "ax_original = fig.add_subplot(1, 2, 1)\n", - "l1, = ax_original.plot(exts._ts.time, (exts.ts / exts.ts.max()) - (exts.ts / exts.ts.max()).mean(), color=(0, 0, 0))\n", - "l2, = ax_original.plot(exts._ts.time, (calibrated_ex / calibrated_ex.max()) - (calibrated_ex / calibrated_ex.max()).mean(), color=(.75, .1, .2))\n", - "l3, = ax_original.plot(exts._ts.time, (bp_calibrated_ts / bp_calibrated_ts.max()) - (bp_calibrated_ts / bp_calibrated_ts.max()).mean(), color=(.2, .1, .75))\n", - "ax_original.set_ylabel(\"Normalized\")\n", + "original_ts = exts.ts.copy()\n", + "original_ts = original_ts - original_ts.mean()\n", + "original_ts = original_ts / original_ts.max()\n", + "frn_ts = np.array(frn_json[\"values\"][0][\"values\"], dtype=float)\n", + "frn_ts = signal.detrend(frn_ts, type=\"linear\")\n", + "frn_ts = frn_ts - frn_ts.mean()\n", + "#frn_ts = frn_ts / frn_ts.max()\n", + "l1, = ax_original.twinx().plot(exts._ts.time, original_ts, color=(0, 0, 0))\n", + "l2, = ax_original.plot(exts._ts.time, calibrated_ex, color=(.75, .1, .1))\n", + "l3, = ax_original.plot(np.array(frn_json[\"times\"], dtype=np.datetime64), frn_ts, color=(.2, .1, .75))\n", + "ax_original.set_ylabel(\"nT\")\n", + "\n", "\n", "ax_original_fft = fig.add_subplot(1, 2, 2)\n", - "original = abs(np.fft.rfft(exts.ts))\n", + "f = np.fft.rfftfreq(original_ts.size, d=1)\n", + "original_fft = abs(np.fft.rfft(original_ts))\n", "calibrated = abs(np.fft.rfft(calibrated_ex))\n", "response = abs(exts.channel_response_filter.complex_response(f))[::-1]\n", "response[-1] = response[-2]\n", - "bp = abs(np.fft.rfft(bp_calibrated_ts))\n", - "l1, = ax_original_fft.loglog(f, original / original.max(), color=(0, 0, 0))\n", + "frn_spectra = abs(np.fft.rfft(frn_ts))\n", + "f_frn = np.fft.rfftfreq(frn_ts.size, d=1)\n", + "l1, = ax_original_fft.loglog(f, original_fft / original_fft.max(), color=(0, 0, 0))\n", "l2, = ax_original_fft.loglog(f, calibrated / calibrated.max(), color=(.75, .1, .2))\n", - "l2, = ax_original_fft.loglog(f, bp / bp.max(), color=(.2, .1, .75))\n", - "l4, = ax_original_fft.loglog(f, response / response.max(), color=(.1, .75, .2))\n", + "l3, = ax_original_fft.loglog(f, response / response.max(), color=(.1, .75, .2))\n", + "l4, = ax_original_fft.loglog(f_frn, frn_spectra / frn_spectra.max(), color=(.2, .1, .75))\n", + "\n", + "ax_original.legend([l1, l2, l4], [\"Original\", \"Calibrated\", \"Observatory\"], ncol=1, loc=\"upper left\")\n", "\n", "fig.canvas.toolbar_visible = True\n", "fig.canvas.header_visible = True\n", "fig.canvas.resizable = True\n", "\n", + "fig.tight_layout()\n", + "\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 108, - "id": "8e949dfb-f8c3-4782-a76d-418ee7e05b91", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-04-06 12:55:04,156 [line 310] mt_metadata.base.metadata.pole_zero_filter.pass_band - WARNING: No pass band could be found within the given frequency range. Returning None\n", - "2022-04-06 12:55:04,191 [line 310] mt_metadata.base.metadata.coefficient_filter.pass_band - WARNING: No pass band could be found within the given frequency range. Returning None\n", - "2022-04-06 12:55:04,234 [line 310] mt_metadata.base.metadata.pole_zero_filter.pass_band - WARNING: No pass band could be found within the given frequency range. Returning None\n", - "2022-04-06 12:55:04,281 [line 310] mt_metadata.base.metadata.coefficient_filter.pass_band - WARNING: No pass band could be found within the given frequency range. Returning None\n", - "2022-04-06 12:55:04,322 [line 310] mt_metadata.base.metadata.pole_zero_filter.pass_band - WARNING: No pass band could be found within the given frequency range. Returning None\n", - "2022-04-06 12:55:04,369 [line 310] mt_metadata.base.metadata.coefficient_filter.pass_band - WARNING: No pass band could be found within the given frequency range. Returning None\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "7f167ecef8f9466386f06d053f442884", - "version_major": 2, - "version_minor": 0 - }, - "image/png": 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\n", - " " - ], - "text/plain": [ - "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exts.channel_response_filter.plot_response(f[::-2])" - ] - }, - { - "cell_type": "code", - "execution_count": 117, - "id": "f5da15d5-c328-4b66-9603-ee32d900ce66", + "execution_count": null, + "id": "b5f462de-03a7-47b0-beba-26793146e159", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-04-06 13:05:09,701 [line 726] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing c:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\docs\\examples\\notebooks\\ZU_CAS04_NVR08_small.h5\n" - ] - } - ], + "outputs": [], "source": [ "m.close_mth5()" ] @@ -803,7 +921,7 @@ { "cell_type": "code", "execution_count": null, - "id": "5f88b732-1f9b-4c2f-b8ee-b2ceb6f281c8", + "id": "72f6bf11-9211-4a23-a41a-0f413ecd4e91", "metadata": {}, "outputs": [], "source": [] diff --git a/docs/examples/notebooks/transfer_function_example.ipynb b/docs/examples/notebooks/transfer_function_example.ipynb index 584ced96..85ef79da 100644 --- a/docs/examples/notebooks/transfer_function_example.ipynb +++ b/docs/examples/notebooks/transfer_function_example.ipynb @@ -27,14 +27,6 @@ "This examples demonstrates how transfer functions can be added to an MTH5 file. " ] }, - { - "cell_type": "code", - "execution_count": null, - "id": "d43ea04c-cec6-419c-9926-bb0d2c1b34b2", - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "markdown", "id": "a6ad495f-36cc-437b-9214-e4a503985720", @@ -67,14 +59,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "2022-03-24T17:56:29 [line 157] numexpr.utils._init_num_threads - INFO: NumExpr defaulting to 8 threads.\n" + "2022-04-12T00:47:38 [line 157] numexpr.utils._init_num_threads - INFO: NumExpr defaulting to 8 threads.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 17:56:31,539 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" + "2022-04-12 00:47:40,386 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" ] } ], @@ -95,8 +87,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 17:56:31,642 [line 604] mth5.mth5.MTH5.open_mth5 - WARNING: transfer_function_example.h5 will be overwritten in 'w' mode\n", - "2022-03-24 17:56:31,944 [line 687] mth5.mth5.MTH5._initialize_file - INFO: Initialized MTH5 0.2.0 file transfer_function_example.h5 in mode w\n" + "2022-04-12 00:47:40,818 [line 591] mth5.mth5.MTH5.open_mth5 - WARNING: transfer_function_example.h5 will be overwritten in 'w' mode\n", + "2022-04-12 00:47:41,119 [line 656] mth5.mth5.MTH5._initialize_file - INFO: Initialized MTH5 0.2.0 file transfer_function_example.h5 in mode w\n" ] } ], @@ -153,7 +145,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 17:56:32,663 [line 981] mth5.mth5.MTH5.get_survey - WARNING: /Experiment/Surveys/CONUS_South does not exist, check survey_list for existing names\n" + "2022-04-12 00:47:41,846 [line 982] mth5.mth5.MTH5.get_survey - WARNING: /Experiment/Surveys/CONUS_South does not exist, check survey_list for existing names\n" ] }, { @@ -205,14 +197,6 @@ "tf_group_01.has_estimate(\"covariance\")" ] }, - { - "cell_type": "code", - "execution_count": null, - "id": "7bbb7ae9-351c-4d1f-84c1-084f99ecc215", - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "markdown", "id": "d0fb6f89-d4da-4b78-94e0-4db46dcb892e", @@ -223,104 +207,6 @@ "Note that an EMTF XML has comprehensive metadata which can be used to populate the MTH5 as necessary, including `Runs` and `Channels`" ] }, - { - "cell_type": "code", - "execution_count": 6, - "id": "620bbe7c-1f3f-4d14-af49-efe2b63f50e8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "/:\n", - "====================\n", - " |- Group: Experiment\n", - " --------------------\n", - " |- Group: Reports\n", - " -----------------\n", - " |- Group: Standards\n", - " -------------------\n", - " --> Dataset: summary\n", - " ......................\n", - " |- Group: Surveys\n", - " -----------------\n", - " |- Group: CONUS_South\n", - " ---------------------\n", - " |- Group: Filters\n", - " -----------------\n", - " |- Group: coefficient\n", - " ---------------------\n", - " |- Group: fap\n", - " -------------\n", - " |- Group: fir\n", - " -------------\n", - " |- Group: time_delay\n", - " --------------------\n", - " |- Group: zpk\n", - " -------------\n", - " |- Group: Reports\n", - " -----------------\n", - " |- Group: Standards\n", - " -------------------\n", - " --> Dataset: summary\n", - " ......................\n", - " |- Group: Stations\n", - " ------------------\n", - " |- Group: NMX20\n", - " ---------------\n", - " |- Group: NMX20a\n", - " ----------------\n", - " --> Dataset: ex\n", - " .................\n", - " --> Dataset: ey\n", - " .................\n", - " --> Dataset: hx\n", - " .................\n", - " --> Dataset: hy\n", - " .................\n", - " --> Dataset: hz\n", - " .................\n", - " |- Group: NMX20b\n", - " ----------------\n", - " --> Dataset: ex\n", - " .................\n", - " --> Dataset: ey\n", - " .................\n", - " --> Dataset: hx\n", - " .................\n", - " --> Dataset: hy\n", - " .................\n", - " --> Dataset: hz\n", - " .................\n", - " |- Group: Transfer_Functions\n", - " ----------------------------\n", - " |- Group: NMX20\n", - " ---------------\n", - " --> Dataset: inverse_signal_power\n", - " ...................................\n", - " --> Dataset: period\n", - " .....................\n", - " --> Dataset: residual_covariance\n", - " ..................................\n", - " --> Dataset: transfer_function\n", - " ................................\n", - " --> Dataset: transfer_function_error\n", - " ......................................\n", - " --> Dataset: channel_summary\n", - " ..............................\n", - " --> Dataset: tf_summary\n", - " ........................." - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "m" - ] - }, { "cell_type": "markdown", "id": "ca68ec41-7013-41b2-80aa-8fd85c270380", @@ -333,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "ced41eda-b1f7-40f2-8783-6d7f4aba9858", "metadata": {}, "outputs": [], @@ -351,7 +237,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "b12a3baa-bebf-4020-9c24-46dc34845b89", "metadata": {}, "outputs": [ @@ -359,7 +245,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 17:56:33,181 [line 981] mth5.mth5.MTH5.get_survey - WARNING: /Experiment/Surveys/unknown_survey does not exist, check survey_list for existing names\n" + "2022-04-12 00:47:42,315 [line 982] mth5.mth5.MTH5.get_survey - WARNING: /Experiment/Surveys/unknown_survey does not exist, check survey_list for existing names\n" ] }, { @@ -376,39 +262,6 @@ "print(tf_group_02.has_estimate(\"covariance\"))" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "85fe42d2-ef18-42ea-85a8-e88a89c4706c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "/Experiment/Surveys/unknown_survey/Stations/SAGE_2005/Transfer_Functions/SAGE_2005:\n", - "====================\n", - " --> Dataset: inverse_signal_power\n", - " ...................................\n", - " --> Dataset: period\n", - " .....................\n", - " --> Dataset: residual_covariance\n", - " ..................................\n", - " --> Dataset: transfer_function\n", - " ................................\n", - " --> Dataset: transfer_function_error\n", - " ......................................" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tg = m.from_reference(tf_group_02.tf_entry[\"hdf5_reference\"][0])\n", - "tg" - ] - }, { "cell_type": "markdown", "id": "3c8ee84e-7bcf-4ec2-9c39-73a925d38535", @@ -421,7 +274,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "9e87dc23-6f76-461d-abd8-ffce1256d549", "metadata": {}, "outputs": [ @@ -429,9 +282,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 17:56:33,711 [line 397] mth5.groups.base.TransferFunction.from_tf_object - WARNING: Did not find inverse_signal_power in TF. Skipping\n", - "2022-03-24 17:56:33,713 [line 397] mth5.groups.base.TransferFunction.from_tf_object - WARNING: Did not find residual_covariance in TF. Skipping\n", - "2022-03-24 17:56:33,714 [line 269] mth5.groups.base.TransferFunction.get_estimate - ERROR: residual_covariance does not exist, check groups_list for existing names\n" + "2022-04-12 00:48:07,067 [line 214] mth5.groups.base.TransferFunction.get_estimate - ERROR: residual_covariance does not exist, check groups_list for existing names\n" ] }, { @@ -440,7 +291,7 @@ "False" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -463,7 +314,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "b18a925f-be0d-4499-8833-820ae4c2a09f", "metadata": {}, "outputs": [ @@ -502,7 +353,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "464966c3-1d72-4ff6-9ab5-cecfb1d08c3d", "metadata": {}, "outputs": [ @@ -512,7 +363,7 @@ "True" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -535,7 +386,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "ca6de2e4-7548-4dc6-8ab5-c6305c5b4460", "metadata": {}, "outputs": [ @@ -638,10 +489,10 @@ " ......................\n", " |- Group: Stations\n", " ------------------\n", - " |- Group: 300\n", - " -------------\n", - " |- Group: 300a\n", - " --------------\n", + " |- Group: SAGE_2005\n", + " -------------------\n", + " |- Group: SAGE_2005a\n", + " --------------------\n", " --> Dataset: ex\n", " .................\n", " --> Dataset: ey\n", @@ -654,8 +505,8 @@ " .................\n", " |- Group: Transfer_Functions\n", " ----------------------------\n", - " |- Group: 300\n", - " -------------\n", + " |- Group: SAGE_2005\n", + " -------------------\n", " --> Dataset: inverse_signal_power\n", " ...................................\n", " --> Dataset: period\n", @@ -666,10 +517,32 @@ " ................................\n", " --> Dataset: transfer_function_error\n", " ......................................\n", - " |- Group: SAGE_2005\n", - " -------------------\n", - " |- Group: SAGE_2005a\n", - " --------------------\n", + " |- Group: unknown_survey_001\n", + " ----------------------------\n", + " |- Group: Filters\n", + " -----------------\n", + " |- Group: coefficient\n", + " ---------------------\n", + " |- Group: fap\n", + " -------------\n", + " |- Group: fir\n", + " -------------\n", + " |- Group: time_delay\n", + " --------------------\n", + " |- Group: zpk\n", + " -------------\n", + " |- Group: Reports\n", + " -----------------\n", + " |- Group: Standards\n", + " -------------------\n", + " --> Dataset: summary\n", + " ......................\n", + " |- Group: Stations\n", + " ------------------\n", + " |- Group: TEST01\n", + " ----------------\n", + " |- Group: TEST01a\n", + " -----------------\n", " --> Dataset: ex\n", " .................\n", " --> Dataset: ey\n", @@ -682,22 +555,40 @@ " .................\n", " |- Group: Transfer_Functions\n", " ----------------------------\n", - " |- Group: SAGE_2005\n", - " -------------------\n", - " --> Dataset: inverse_signal_power\n", - " ...................................\n", + " |- Group: TEST01\n", + " ----------------\n", " --> Dataset: period\n", " .....................\n", - " --> Dataset: residual_covariance\n", - " ..................................\n", " --> Dataset: transfer_function\n", " ................................\n", " --> Dataset: transfer_function_error\n", " ......................................\n", - " |- Group: TEST01\n", - " ----------------\n", - " |- Group: TEST01a\n", - " -----------------\n", + " |- Group: unknown_survey_002\n", + " ----------------------------\n", + " |- Group: Filters\n", + " -----------------\n", + " |- Group: coefficient\n", + " ---------------------\n", + " |- Group: fap\n", + " -------------\n", + " |- Group: fir\n", + " -------------\n", + " |- Group: time_delay\n", + " --------------------\n", + " |- Group: zpk\n", + " -------------\n", + " |- Group: Reports\n", + " -----------------\n", + " |- Group: Standards\n", + " -------------------\n", + " --> Dataset: summary\n", + " ......................\n", + " |- Group: Stations\n", + " ------------------\n", + " |- Group: 300\n", + " -------------\n", + " |- Group: 300a\n", + " --------------\n", " --> Dataset: ex\n", " .................\n", " --> Dataset: ey\n", @@ -710,10 +601,14 @@ " .................\n", " |- Group: Transfer_Functions\n", " ----------------------------\n", - " |- Group: TEST01\n", - " ----------------\n", + " |- Group: 300\n", + " -------------\n", + " --> Dataset: inverse_signal_power\n", + " ...................................\n", " --> Dataset: period\n", " .....................\n", + " --> Dataset: residual_covariance\n", + " ..................................\n", " --> Dataset: transfer_function\n", " ................................\n", " --> Dataset: transfer_function_error\n", @@ -724,7 +619,7 @@ " ........................." ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -745,7 +640,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "c5f3ee5b-784e-4ba9-a480-a36c13b2a09c", "metadata": {}, "outputs": [], @@ -755,7 +650,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "535ebb46-db7a-436f-a7e6-e2e2e500d17c", "metadata": {}, "outputs": [ @@ -827,7 +722,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "4a63b5d4-207b-4c4a-be5a-621242501289", "metadata": {}, "outputs": [ @@ -853,6 +748,7 @@ " \n", " \n", " station\n", + " survey\n", " latitude\n", " longitude\n", " elevation\n", @@ -871,6 +767,7 @@ " \n", " 0\n", " NMX20\n", + " CONUS_South\n", " 34.470528\n", " -108.712288\n", " 1940.05\n", @@ -886,23 +783,8 @@ " \n", " \n", " 1\n", - " 300\n", - " 34.727000\n", - " -115.735000\n", - " 0.00\n", - " 300\n", - " none\n", - " True\n", - " True\n", - " True\n", - " 1.163640\n", - " 10922.666990\n", - " <HDF5 object reference>\n", - " <HDF5 object reference>\n", - " \n", - " \n", - " 2\n", " SAGE_2005\n", + " unknown_survey\n", " 35.550000\n", " -106.283333\n", " 0.00\n", @@ -917,8 +799,9 @@ " <HDF5 object reference>\n", " \n", " \n", - " 3\n", + " 2\n", " TEST01\n", + " unknown_survey_001\n", " -30.930285\n", " 127.229230\n", " 175.27\n", @@ -932,22 +815,39 @@ " <HDF5 object reference>\n", " <HDF5 object reference>\n", " \n", + " \n", + " 3\n", + " 300\n", + " unknown_survey_002\n", + " 34.727000\n", + " -115.735000\n", + " 0.00\n", + " 300\n", + " none\n", + " True\n", + " True\n", + " True\n", + " 1.163640\n", + " 10922.666990\n", + " <HDF5 object reference>\n", + " <HDF5 object reference>\n", + " \n", " \n", "\n", "" ], "text/plain": [ - " station latitude longitude elevation tf_id units \\\n", - "0 NMX20 34.470528 -108.712288 1940.05 NMX20 none \n", - "1 300 34.727000 -115.735000 0.00 300 none \n", - "2 SAGE_2005 35.550000 -106.283333 0.00 SAGE_2005 none \n", - "3 TEST01 -30.930285 127.229230 175.27 TEST01 none \n", + " station survey latitude longitude elevation tf_id \\\n", + "0 NMX20 CONUS_South 34.470528 -108.712288 1940.05 NMX20 \n", + "1 SAGE_2005 unknown_survey 35.550000 -106.283333 0.00 SAGE_2005 \n", + "2 TEST01 unknown_survey_001 -30.930285 127.229230 175.27 TEST01 \n", + "3 300 unknown_survey_002 34.727000 -115.735000 0.00 300 \n", "\n", - " has_impedance has_tipper has_covariance period_min period_max \\\n", - "0 True True True 4.654550 29127.110000 \n", - "1 True True True 1.163640 10922.666990 \n", - "2 True True True 0.004196 209.731544 \n", - "3 True True False 0.001212 1211.527490 \n", + " units has_impedance has_tipper has_covariance period_min period_max \\\n", + "0 none True True True 4.654550 29127.110000 \n", + "1 none True True True 0.004196 209.731544 \n", + "2 none True True False 0.001212 1211.527490 \n", + "3 none True True True 1.163640 10922.666990 \n", "\n", " hdf5_reference station_hdf5_reference \n", "0 \n", @@ -956,7 +856,7 @@ "3 " ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1012,8 +912,8 @@ } ], "source": [ - "tf_from_reference = m.from_reference(tf_df.iloc[0].hdf5_reference)\n", - "tf_object = tf_from_reference.to_tf_object()\n", + "tf_object = m.from_reference(tf_df.iloc[0].hdf5_reference)\n", + "\n", "print(tf_object)" ] }, @@ -1029,20 +929,12 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "55c38861-3605-4e33-bc39-99325549f10f", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-03-24 17:59:51,369 [line 747] mth5.mth5.MTH5.close_mth5 - INFO: Flushing and closing transfer_function_example.h5\n" - ] - } - ], + "outputs": [], "source": [ - "m.close_mth5()" + "#m.close_mth5()" ] }, { diff --git a/docs/examples/notebooks/v0.2.0_example.ipynb b/docs/examples/notebooks/v0.2.0_example.ipynb index 3c161f68..e15e136e 100644 --- a/docs/examples/notebooks/v0.2.0_example.ipynb +++ b/docs/examples/notebooks/v0.2.0_example.ipynb @@ -18,14 +18,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "2022-03-24T18:10:56 [line 157] numexpr.utils._init_num_threads - INFO: NumExpr defaulting to 8 threads.\n" + "2022-04-12T21:21:46 [line 157] numexpr.utils._init_num_threads - INFO: NumExpr defaulting to 8 threads.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 18:10:58,269 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" + "2022-04-12 21:21:47,999 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" ] } ], @@ -71,8 +71,8 @@ "{'file.type': 'MTH5',\n", " 'file.version': '0.2.0',\n", " 'file.access.platform': 'Windows-10-10.0.19041-SP0',\n", - " 'file.access.time': '2022-03-25T01:10:58.410369+00:00',\n", - " 'mth5.software.version': '0.2.4',\n", + " 'file.access.time': '2022-04-13T04:21:53.788393+00:00',\n", + " 'mth5.software.version': '0.2.5',\n", " 'mth5.software.name': 'mth5',\n", " 'data_level': 1}" ] @@ -166,7 +166,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 18:10:58,747 [line 687] mth5.mth5.MTH5._initialize_file - INFO: Initialized MTH5 0.2.0 file example.h5 in mode w\n" + "2022-04-12 21:22:02,707 [line 591] mth5.mth5.MTH5.open_mth5 - WARNING: example.h5 will be overwritten in 'w' mode\n", + "2022-04-12 21:22:03,000 [line 656] mth5.mth5.MTH5._initialize_file - INFO: Initialized MTH5 0.2.0 file example.h5 in mode w\n" ] } ], @@ -184,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 20, "id": "e7b9de3c-1c4d-4055-ba95-05012cc2bb59", "metadata": {}, "outputs": [ @@ -203,13 +204,51 @@ " ......................\n", " |- Group: Surveys\n", " -----------------\n", + " |- Group: example\n", + " -----------------\n", + " |- Group: Filters\n", + " -----------------\n", + " |- Group: coefficient\n", + " ---------------------\n", + " |- Group: fap\n", + " -------------\n", + " |- Group: fir\n", + " -------------\n", + " |- Group: time_delay\n", + " --------------------\n", + " |- Group: zpk\n", + " -------------\n", + " |- Group: Reports\n", + " -----------------\n", + " |- Group: Standards\n", + " -------------------\n", + " --> Dataset: summary\n", + " ......................\n", + " |- Group: Stations\n", + " ------------------\n", + " |- Group: mt001\n", + " ---------------\n", + " |- Group: Transfer_Functions\n", + " ----------------------------\n", + " |- Group: mt002\n", + " ---------------\n", + " |- Group: 001\n", + " -------------\n", + " --> Dataset: ex\n", + " .................\n", + " --> Dataset: hy\n", + " .................\n", + " |- Group: 002\n", + " -------------\n", + " |- Group: Transfer_Functions\n", + " ----------------------------\n", " --> Dataset: channel_summary\n", " ..............................\n", " --> Dataset: tf_summary\n", " ........................." ] }, - "execution_count": 7, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -236,9 +275,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-03-24 18:10:58,776 [line 530] mth5.mth5.MTH5.filters_group - INFO: File version 0.2.0 does not have a FiltersGroup at the experiment level\n", - "2022-03-24 18:10:58,781 [line 552] mth5.mth5.MTH5.stations_group - INFO: File version 0.2.0 does not have a Stations. try surveys_group.\n", - "2022-03-24 18:10:58,783 [line 489] mth5.mth5.MTH5.survey_group - INFO: File version 0.2.0 does not have a survey_group, try surveys_group\n" + "2022-04-12 21:22:11,930 [line 519] mth5.mth5.MTH5.filters_group - INFO: File version 0.2.0 does not have a FiltersGroup at the experiment level\n", + "2022-04-12 21:22:11,932 [line 541] mth5.mth5.MTH5.stations_group - INFO: File version 0.2.0 does not have a Stations. try surveys_group.\n", + "2022-04-12 21:22:11,934 [line 479] mth5.mth5.MTH5.survey_group - INFO: File version 0.2.0 does not have a survey_group, try surveys_group\n" ] }, { @@ -351,7 +390,7 @@ "text/plain": [ "{\n", " \"station\": {\n", - " \"acquired_by.author\": \"me\",\n", + " \"acquired_by.name\": \"me\",\n", " \"channels_recorded\": [],\n", " \"data_type\": \"BBMT\",\n", " \"geographic_name\": null,\n", @@ -579,7 +618,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "id": "a4bac97a-b386-4bd5-adcf-893f9db4ab67", "metadata": {}, "outputs": [ @@ -696,7 +735,7 @@ "1 " ] }, - "execution_count": 19, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -722,7 +761,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "67311be2-88bb-4cd9-9bd7-7b4811238190", "metadata": {}, "outputs": [ @@ -740,7 +779,7 @@ "\tsample rate: 0.0" ] }, - "execution_count": 20, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } diff --git a/examples/notebooks/Untitled.ipynb b/examples/notebooks/Untitled.ipynb new file mode 100644 index 00000000..9e9d4561 --- /dev/null +++ b/examples/notebooks/Untitled.ipynb @@ -0,0 +1,33 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "10bb46de-0e5e-41c1-a2bd-49e14264aaf9", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/notebooks/remove_instrument_response.ipynb b/examples/notebooks/remove_instrument_response.ipynb new file mode 100644 index 00000000..46114b3d --- /dev/null +++ b/examples/notebooks/remove_instrument_response.ipynb @@ -0,0 +1,384 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "540dc674-f1bd-45e4-8173-48015aadf009", + "metadata": {}, + "source": [ + "# Remove instrument response\n", + "\n", + "This notebook will explore different ways to remove the instrument response from the data" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f4c38a58-8251-4c2a-8c04-0b00de60a404", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2021-12-01 17:31:15,182 [line 135] mth5.setup_logger - INFO: Logging file can be found C:\\Users\\jpeacock\\Documents\\GitHub\\mth5\\logs\\mth5_debug.log\n" + ] + } + ], + "source": [ + "%matplotlib widget\n", + "\n", + "import numpy as np\n", + "from scipy import signal as sps\n", + "\n", + "from mt_metadata.timeseries.filters import PoleZeroFilter, FrequencyResponseTableFilter\n", + "from mth5.timeseries import ChannelTS\n", + "from mth5.timeseries import ts_filters\n", + "from mth5.utils.exceptions import MTTSError\n", + "\n", + "from matplotlib import pyplot as plt\n", + "\n", + "window = False" + ] + }, + { + "cell_type": "markdown", + "id": "aaf6975f-9242-4817-b75b-d9d316025e79", + "metadata": {}, + "source": [ + "## Create a channel" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e1ef67d3-268d-4ea8-ae3b-ecf13c096def", + "metadata": {}, + "outputs": [], + "source": [ + "c = ChannelTS()\n", + "c.sample_rate = 256\n", + "\n", + "n_samples = 50000\n", + "t = np.arange(n_samples) * c.sample_interval\n", + "c.ts = np.sum([np.cos(2*np.pi*w*t + phi) for w, phi in zip(np.logspace(-3, 2, 20), np.random.rand(20))], axis=0)" + ] + }, + { + "cell_type": "markdown", + "id": "68b12306-20a7-47ae-93ee-7513a28f5705", + "metadata": {}, + "source": [ + "### Add a filter as an instrument response" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a2e5d059-2d02-46f6-bee8-c401936ebcaf", + "metadata": {}, + "outputs": [], + "source": [ + "#pz = PoleZeroFilter(units_in=\"volts\", units_out=\"nanotesla\", name=\"instrument_response\")\n", + "#pz.poles = [(-6.283185+10.882477j), (-6.283185-10.882477j), (-12.566371+0j)]\n", + "#pz.zeros = []\n", + "#pz.normalization_factor = 2002.269 \n", + "\n", + "#c.channel_response_filter.filters_list.append(pz)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "82f19965-c234-4550-9678-31caeb9da89b", + "metadata": {}, + "outputs": [], + "source": [ + "fap = FrequencyResponseTableFilter(units_in=\"volts\", units_out=\"nanotesla\", name=\"example_fap\")\n", + "\n", + "fap.frequencies = [\n", + " 1.95312000e-03, 2.76214000e-03, 3.90625000e-03,\n", + " 5.52427000e-03, 7.81250000e-03, 1.10485000e-02,\n", + " 1.56250000e-02, 2.20971000e-02, 3.12500000e-02,\n", + " 4.41942000e-02, 6.25000000e-02, 8.83883000e-02,\n", + " 1.25000000e-01, 1.76780000e-01, 2.50000000e-01,\n", + " 3.53550000e-01, 5.00000000e-01, 7.07110000e-01,\n", + " 1.00000000e+00, 1.41420000e+00, 2.00000000e+00,\n", + " 2.82840000e+00, 4.00000000e+00, 5.65690000e+00,\n", + " 8.00000000e+00, 1.13140000e+01, 1.60000000e+01,\n", + " 2.26270000e+01, 3.20000000e+01, 4.52550000e+01,\n", + " 6.40000000e+01, 9.05100000e+01, 1.28000000e+02,\n", + " 1.81020000e+02, 2.56000000e+02, 3.62040000e+02,\n", + " 5.12000000e+02, 7.24080000e+02, 1.02400000e+03,\n", + " 1.44820000e+03, 2.04800000e+03, 2.89630000e+03,\n", + " 4.09600000e+03, 5.79260000e+03, 8.19200000e+03,\n", + " 1.15850000e+04]\n", + "\n", + "fap.amplitudes = [\n", + " 1.59009000e-03, 3.07497000e-03, 5.52793000e-03,\n", + " 9.47448000e-03, 1.54565000e-02, 2.49498000e-02,\n", + " 3.96462000e-02, 7.87192000e-02, 1.57134000e-01,\n", + " 3.09639000e-01, 5.94224000e-01, 1.12698000e+00,\n", + " 2.01092000e+00, 3.33953000e+00, 5.00280000e+00,\n", + " 6.62396000e+00, 7.97545000e+00, 8.82872000e+00,\n", + " 9.36883000e+00, 9.64102000e+00, 9.79664000e+00,\n", + " 9.87183000e+00, 9.90666000e+00, 9.92845000e+00,\n", + " 9.93559000e+00, 9.93982000e+00, 9.94300000e+00,\n", + " 9.93546000e+00, 9.93002000e+00, 9.90873000e+00,\n", + " 9.86383000e+00, 9.78129000e+00, 9.61814000e+00,\n", + " 9.26461000e+00, 8.60175000e+00, 7.18337000e+00,\n", + " 4.46123000e+00, -8.72600000e-01, -5.15684000e+00,\n", + " -2.95111000e+00, -9.28512000e-01, -2.49850000e-01,\n", + " -5.75682000e-02, -1.34293000e-02, -1.02708000e-03,\n", + " 1.09577000e-03]\n", + "\n", + "fap.phases = [\n", + " 7.60824000e-02, 1.09174000e-01, 1.56106000e-01,\n", + " 2.22371000e-01, 3.12020000e-01, 4.41080000e-01,\n", + " 6.23548000e-01, 8.77188000e-01, 1.23360000e+00,\n", + " 1.71519000e+00, 2.35172000e+00, 3.13360000e+00,\n", + " 3.98940000e+00, 4.67269000e+00, 4.96593000e+00,\n", + " 4.65875000e+00, 3.95441000e+00, 3.11098000e+00,\n", + " 2.30960000e+00, 1.68210000e+00, 1.17928000e+00,\n", + " 8.20015000e-01, 5.36474000e-01, 3.26955000e-01,\n", + " 1.48051000e-01, -8.24275000e-03, -1.66064000e-01,\n", + " -3.48852000e-01, -5.66625000e-01, -8.62435000e-01,\n", + " -1.25347000e+00, -1.81065000e+00, -2.55245000e+00,\n", + " -3.61512000e+00, -5.00185000e+00, -6.86158000e+00,\n", + " -8.78698000e+00, -9.08920000e+00, -4.22925000e+00,\n", + " 2.15533000e-01, 6.00661000e-01, 3.12368000e-01,\n", + " 1.31660000e-01, 5.01553000e-02, 1.87239000e-02,\n", + " 6.68243000e-03]\n", + "\n", + "c.channel_response_filter.filters_list.append(fap)" + ] + }, + { + "cell_type": "markdown", + "id": "4097c71f-946c-4f8e-8b29-80c45f60f486", + "metadata": {}, + "source": [ + "## Estimate the response and remove\n", + "This will be done in the frequency domain, so there are some tricks that we will need to use to be sure that the calibrated response is \"clean\"" + ] + }, + { + "cell_type": "markdown", + "id": "74f50b4a-c8a0-4ee3-96a2-2a198faf795c", + "metadata": {}, + "source": [ + "1. Pad the data to a power of 2 to make the FFT more efficient\n", + "2. Apply a window ?\n", + "3. Compute frequencies, the complex response of the filters, and FFT. Here we will use rfft which computes uses the real signal and computes one side of the symmetric spectrum and is quicker\n", + "4. Compute iFFT and trim to the original number of samples\n", + "5. Bandpass if desired to remove effects of the response filter, this is important for broadband instruments " + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "499aceac-452b-4d4e-bfd9-55d5e16a951b", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2021-12-01 17:32:12,884 [line 192] mt_metadata.base.metadata.frequency_response_table_filter.complex_response - WARNING: Extrapolating, use values outside calibration frequencies with caution\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "65536\n" + ] + } + ], + "source": [ + "# 1\n", + "ts_npow = ts_filters.zero_pad(c.ts)\n", + "print(ts_npow.size)\n", + "\n", + "# 2\n", + "if window:\n", + " ts_npow *= sps.windows.nuttall(ts_npow.size)\n", + "\n", + "# 3\n", + "f = np.fft.rfftfreq(ts_npow.size, c.sample_interval)\n", + "ts_fft = np.fft.rfft(ts_npow)\n", + "cr = c.channel_response_filter.complex_response(f)\n", + "ts_remove_response = ts_fft / cr\n", + "\n", + "# 4\n", + "ts_calibrated = np.fft.irfft(ts_remove_response)\n", + "\n", + "# 5\n", + "highcut = 100\n", + "lowcut = .05\n", + "order = 3\n", + "ts_bp = ts_filters.butter_bandpass_filter(ts_calibrated, lowcut, highcut, c.sample_rate, order=order)\n", + "bp = ts_filters.butter_bandpass(lowcut, highcut, c.sample_rate, order=order)" + ] + }, + { + "cell_type": "markdown", + "id": "c4e7add7-8b28-4413-8583-b7795627818b", + "metadata": {}, + "source": [ + "## Plot some results" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a4cdf7c0-509a-4e0a-9576-d6cf80203c62", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\jpeacock\\AppData\\Local\\Temp\\1/ipykernel_23108/2839787752.py:2: UserWarning: Attempted to set non-positive left xlim on a log-scaled axis.\n", + "Invalid limit will be ignored.\n", + " fig.clf()\n", + "C:\\Users\\jpeacock\\AppData\\Local\\Temp\\1/ipykernel_23108/2839787752.py:29: RuntimeWarning: divide by zero encountered in log10\n", + " ax6.semilogx((c.sample_rate * 0.5 / np.pi) * w, 20*np.log10(abs(h)))\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "82601e1c2e83439784c3f8146dd97d59", + "version_major": 2, + "version_minor": 0 + }, + "text/html": [ + "\n", + "
\n", + "
\n", + " Figure 1\n", + "
\n", + " \n", + "
\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(1)\n", + "fig.clf()\n", + "\n", + "ax1 = fig.add_subplot(3, 2, 1)\n", + "ax1.plot(t, c.ts)\n", + "ax1.set_ylabel(\"original\")\n", + "\n", + "ax2 = fig.add_subplot(3, 2, 2)\n", + "ax2.semilogx(f, 20*np.log10(np.abs(ts_fft))) \n", + "ax2.semilogx(f, 20*np.log10(np.abs(cr)))\n", + "ax2.set_ylabel(\"dB\")\n", + "\n", + "ax3 = fig.add_subplot(3, 2, 3, sharex=ax1)\n", + "ax3.plot(t, ts_calibrated[0:n_samples])\n", + "ax3.set_ylabel(\"calibrated\")\n", + "\n", + "ax4 = fig.add_subplot(3, 2, 4, sharex=ax2)\n", + "ax4.semilogx(f, 20*np.log10(np.abs(np.fft.rfft(ts_calibrated))))\n", + "ax4.semilogx(f, 20*np.log10(np.abs(cr)))\n", + "ax4.set_ylabel(\"dB\")\n", + "\n", + "ax5 = fig.add_subplot(3, 2, 5, sharex=ax1)\n", + "ax5.plot(t, ts_bp[0:n_samples])\n", + "ax3.set_ylabel(\"bandpassed\")\n", + "\n", + "ax6 = fig.add_subplot(3, 2, 6, sharex=ax2)\n", + "ax6.semilogx(f, 20*np.log10(np.abs(np.fft.rfft(ts_bp))))\n", + "w, h = sps.sosfreqz(bp, worN=n_samples)\n", + "ax6.semilogx((c.sample_rate * 0.5 / np.pi) * w, 20*np.log10(abs(h)))\n", + "ax6.set_ylabel(\"dB\")\n", + "\n", + "fig.tight_layout()\n", + "\n", + "fig.canvas.toolbar_visible = True\n", + "fig.canvas.resizable = True\n", + "display(fig.canvas)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d0600652-3893-438b-8a5a-f543fa080c57", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(65536,)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ts_bp.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9c76d1a5-86b5-47dc-849d-071b8e9fee26", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2.1072099696478683" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log10(128)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8b06aff-2514-40f2-a492-2d3786fbfad0", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/mth5/groups/master_station_run_channel.py b/mth5/groups/master_station_run_channel.py index 80341e80..1c440715 100644 --- a/mth5/groups/master_station_run_channel.py +++ b/mth5/groups/master_station_run_channel.py @@ -38,6 +38,7 @@ inherit_doc_string, validate_name, ) + from mth5.timeseries import ChannelTS, RunTS from mth5.timeseries.channel_ts import make_dt_coordinates from mth5.utils.mth5_logger import setup_logger @@ -271,6 +272,7 @@ def add_station(self, station_name, station_metadata=None): """ if station_name is None: raise Exception("station name is None, do not know what to name it") + station_name = validate_name(station_name) try: station_group = self.hdf5_group.create_group(station_name) diff --git a/mth5/groups/survey.py b/mth5/groups/survey.py index ac6176cc..abe6b68b 100644 --- a/mth5/groups/survey.py +++ b/mth5/groups/survey.py @@ -270,7 +270,7 @@ def add_survey(self, survey_name, survey_metadata=None): if validate_name(survey_metadata.id) != survey_name: msg = ( f"survey group name {survey_name} must be same as " - + f"survey id {survey_metadata.id}" + + f"survey id {survey_metadata.id.replace(' ', '_')}" ) self.logger.error(msg) raise MTH5Error(msg) @@ -309,7 +309,9 @@ def get_survey(self, survey_name): MTH5Error: MT001 does not exist, check survey_list for existing names """ + survey_name = validate_name(survey_name) + try: return SurveyGroup(self.hdf5_group[survey_name], **self.dataset_options) except KeyError: @@ -343,7 +345,9 @@ def remove_survey(self, survey_name): >>> mth5_obj.surveys_group.remove_survey('MT001') """ + survey_name = validate_name(survey_name) + try: del self.hdf5_group[survey_name] self.logger.info( diff --git a/mth5/helpers.py b/mth5/helpers.py index c9812688..85b5cb7a 100644 --- a/mth5/helpers.py +++ b/mth5/helpers.py @@ -201,6 +201,19 @@ def to_numpy_type(value): raise TypeError("Type {0} not understood".format(type(value))) +def validate_name(name): + """ + make sure the name has no spaces or slashes + + :param name: DESCRIPTION + :type name: TYPE + :return: DESCRIPTION + :rtype: TYPE + + """ + + return name.replace(" ", "_").replace("/", "_") + def from_numpy_type(value): """ Need to make the attributes friendly with Numpy and HDF5. diff --git a/mth5/mth5.py b/mth5/mth5.py index f44ca31e..999ea855 100644 --- a/mth5/mth5.py +++ b/mth5/mth5.py @@ -621,6 +621,8 @@ def open_mth5(self, filename=None, mode="a"): self.logger.error(msg) raise MTH5Error(msg) # TODO need to add a validation step to check for version and legit file + if not "channel_summary" in self.__hdf5_obj[self._root_path].keys(): + self._initialize_summary() def _initialize_file(self, mode="w"): """ @@ -648,6 +650,13 @@ def _initialize_file(self, mode="w"): pass m5_grp = getattr(self, f"{group_name.lower()}_group") m5_grp.initialize_group() + self._initialize_summary() + + self.logger.info( + f"Initialized MTH5 {self.file_version} file {self.filename} in mode {mode}" + ) + + def _initialize_summary(self): # initiate channel and tf summary datasets self.__hdf5_obj[self._default_root_name].create_dataset( "channel_summary", @@ -665,10 +674,6 @@ def _initialize_file(self, mode="w"): **self.dataset_options, ) - self.logger.info( - f"Initialized MTH5 {self.file_version} file {self.filename} in mode {mode}" - ) - def validate_file(self): """ Validate an open mth5 file @@ -1082,6 +1087,7 @@ def get_station(self, station_name, survey=None): MTH5Error: MT001 does not exist, check station_list for existing names """ + station_name = helpers.validate_name(station_name) if self.file_version in ["0.1.0"]: return self.stations_group.get_station(station_name) elif self.file_version in ["0.2.0"]: @@ -1089,6 +1095,7 @@ def get_station(self, station_name, survey=None): msg = "Need to input 'survey' for file version %s" self.logger.error(msg, self.file_version) raise ValueError(msg % self.file_version) + survey = helpers.validate_name(survey) sg = self.get_survey(survey) return sg.stations_group.get_station(station_name) @@ -1113,7 +1120,7 @@ def remove_station(self, station_name, survey=None): >>> mth5_obj.remove_station('MT001') """ - + station_name = helpers.validate_name(station_name) if self.file_version in ["0.1.0"]: return self.stations_group.remove_station(station_name) elif self.file_version in ["0.2.0"]: @@ -1121,6 +1128,7 @@ def remove_station(self, station_name, survey=None): msg = "Need to input 'survey' for file version %s" self.logger.error(msg, self.file_version) raise ValueError(msg % self.file_version) + survey = helpers.validate_name(survey) sg = self.get_survey(survey) return sg.stations_group.remove_station(station_name) @@ -1174,7 +1182,8 @@ def get_run(self, station_name, run_name, survey=None): >>> existing_run = mth5_obj.get_run('MT001', 'MT001a') """ - + station_name = helpers.validate_name(station_name) + run_name = helpers.validate_name(run_name) if self.file_version in ["0.1.0"]: run_path = f"{self._root_path}/Stations/{station_name}/{run_name}" elif self.file_version in ["0.2.0"]: @@ -1182,6 +1191,8 @@ def get_run(self, station_name, run_name, survey=None): msg = "Need to input 'survey' for file version %s" self.logger.error(msg, self.file_version) raise ValueError(msg % self.file_version) + + survey = helpers.validate_name(survey) run_path = ( f"{self._root_path}/Surveys/{survey}/Stations/{station_name}/{run_name}" ) @@ -1316,6 +1327,9 @@ def get_channel(self, station_name, run_name, channel_name, survey=None): sample rate: 4096 """ + station_name = helpers.validate_name(station_name) + run_name = helpers.validate_name(run_name) + channel_name = helpers.validate_name(channel_name) # ch = f"Survey/Stations/{station_name}/{run_name}/{channel_name}" # return groups.ChannelDataset(self.__hdf5_obj[ch]) return ( @@ -1350,7 +1364,9 @@ def remove_channel(self, station_name, run_name, channel_name, survey=None): >>> mth5_obj.remove_channel('MT001', 'MT001a', 'Ex') """ - + station_name = helpers.validate_name(station_name) + run_name = helpers.validate_name(run_name) + channel_name = helpers.validate_name(channel_name) return ( self.get_station(station_name, survey=survey) .get_run(run_name) diff --git a/mth5/timeseries/channel_ts.py b/mth5/timeseries/channel_ts.py index 80c1219b..419ed0fc 100644 --- a/mth5/timeseries/channel_ts.py +++ b/mth5/timeseries/channel_ts.py @@ -31,6 +31,7 @@ from mth5.utils.exceptions import MTTSError from mth5.utils.mth5_logger import setup_logger from mth5.utils import fdsn_tools +from mth5.timeseries.ts_filters import RemoveInstrumentResponse from obspy.core import Trace @@ -60,7 +61,6 @@ def make_dt_coordinates(start_time, sample_rate, n_samples, logger): ) logger.warning(msg) sample_rate = 1 - if start_time is None: msg = ( f"Need to input a start time. Not {start_time}, " @@ -69,15 +69,12 @@ def make_dt_coordinates(start_time, sample_rate, n_samples, logger): ) logger.warning(msg) start_time = "1980-01-01T00:00:00" - if n_samples < 1: msg = f"Need to input a valid n_samples. Not {n_samples}" logger.error(msg) raise ValueError(msg) - if not isinstance(start_time, MTime): start_time = MTime(start_time) - dt_freq = "{0:.0f}N".format(1.0e9 / (sample_rate)) dt_index = pd.date_range( @@ -180,7 +177,6 @@ def __init__( ) self.logger.error(msg) raise ValueError(msg) - if channel_metadata is not None: if isinstance(channel_metadata, type(self.channel_metadata)): self.channel_metadata.update(channel_metadata) @@ -194,7 +190,6 @@ def __init__( channel_metadata = {channel_type: channel_metadata} self.channel_metadata.from_dict(channel_metadata) self.logger.debug("Loading from metadata dict") - else: msg = "input metadata must be type %s or dict, not %s" self.logger.error( @@ -203,47 +198,39 @@ def __init__( raise MTTSError( msg % (type(self.channel_metadata), type(channel_metadata)) ) - # add station metadata, this will be important when propogating a single # channel such that it can stand alone. if station_metadata is not None: if isinstance(station_metadata, metadata.Station): self.station_metadata.update(station_metadata) - elif isinstance(station_metadata, dict): if not "station" in [cc.lower() for cc in station_metadata.keys()]: station_metadata = {"Station": station_metadata} self.station_metadata.from_dict(station_metadata) self.logger.debug("Loading from metadata dict") - else: msg = "input metadata must be type {0} or dict, not {1}".format( type(self.station_metadata), type(station_metadata) ) self.logger.error(msg) raise MTTSError(msg) - # add run metadata, this will be important when propogating a single # channel such that it can stand alone. if run_metadata is not None: if isinstance(run_metadata, metadata.Run): self.run_metadata.update(run_metadata) - elif isinstance(run_metadata, dict): if not "run" in [cc.lower() for cc in run_metadata.keys()]: run_metadata = {"Run": run_metadata} self.run_metadata.from_dict(run_metadata) self.logger.debug("Loading from metadata dict") - else: msg = "input metadata must be type %s or dict, not %s" self.logger.error(msg, type(self.run_metadata), type(run_metadata)) raise MTTSError(msg % (type(self.run_metadata), type(run_metadata))) - # input data if data is not None: self.ts = data - self._update_xarray_metadata() for key in list(kwargs.keys()): @@ -270,15 +257,12 @@ def __eq__(self, other): if not isinstance(other, ChannelTS): raise ValueError(f"Cannot compare ChannelTS with {type(other)}") - if not other.metadata == self.channel_metadata: return False - if self.ts.equals(other.ts) is False: msg = "timeseries are not equal" self.logger.info(msg) return False - return True def __ne__(self, other): @@ -287,7 +271,6 @@ def __ne__(self, other): def __lt__(self, other): if not isinstance(other, ChannelTS): raise ValueError(f"Cannot compare ChannelTS with {type(other)}") - self.logger.info("Only testing start time") if other.start < self.start and other.sample_rate == self.sample_rate: return True @@ -311,7 +294,6 @@ def ts(self, ts_arr): if isinstance(ts_arr, (np.ndarray, list, tuple)): if not isinstance(ts_arr, np.ndarray): ts_arr = np.array(ts_arr) - # Validate an input array to make sure its 1D if len(ts_arr.shape) == 2: if 1 in ts_arr.shape: @@ -320,13 +302,11 @@ def ts(self, ts_arr): msg = f"Input array must be 1-D array not {ts_arr.shape}" self.logger.error(msg) raise ValueError(msg) - dt = make_dt_coordinates( self.start, self.sample_rate, ts_arr.size, self.logger ) self._ts = xr.DataArray(ts_arr, coords=[("time", dt)], name="ts") self._update_xarray_metadata() - elif isinstance(ts_arr, pd.core.frame.DataFrame): if isinstance(ts_arr.index[0], pd._libs.tslibs.timestamps.Timestamp): dt = ts_arr.index @@ -339,7 +319,6 @@ def ts(self, ts_arr): ts_arr["data"], coords=[("time", dt)], name="ts" ) self._update_xarray_metadata() - except AttributeError: msg = ( "Data frame needs to have a column named `data` " @@ -347,7 +326,6 @@ def ts(self, ts_arr): ) self.logger.error(msg) raise MTTSError(msg) - elif isinstance(ts_arr, pd.core.series.Series): if isinstance(ts_arr.index[0], pd._libs.tslibs.timestamps.Timestamp): dt = ts_arr.index @@ -355,10 +333,8 @@ def ts(self, ts_arr): dt = make_dt_coordinates( self.start, self.sample_rate, ts_arr["data"].size, self.logger, ) - self._ts = xr.DataArray(ts_arr.values, coords=[("time", dt)], name="ts") self._update_xarray_metadata() - elif isinstance(ts_arr, xr.DataArray): # TODO: need to validate the input xarray self._ts = ts_arr @@ -374,13 +350,11 @@ def ts(self, ts_arr): station_dict[key.split("station.")[-1]] = meta_dict.pop(key) for key in run_keys: run_dict[key.split("run.")[-1]] = meta_dict.pop(key) - self.channel_metadata.from_dict({meta_dict["type"]: meta_dict}) self.station_metadata.from_dict({"station": station_dict}) self.run_metadata.from_dict({"run": run_dict}) # need to run this incase things are different. self._update_xarray_metadata() - else: msg = ( "Data type {0} not supported".format(type(ts_arr)) @@ -389,6 +363,16 @@ def ts(self, ts_arr): ) raise MTTSError(msg) + @property + def time_index(self): + """ + time index as a numpy array dtype np.datetime[ns] + :return: DESCRIPTION + :rtype: TYPE + + """ + return self._ts.time.to_numpy() + @property def channel_type(self): """Channel Type""" @@ -413,7 +397,6 @@ def channel_type(self, value): + "[ Electrict | Magnetic | Auxiliary ]" ) self.logger.error(msg) - for key in self.channel_metadata.to_dict()[ self.channel_metadata._class_name ].keys(): @@ -466,7 +449,6 @@ def component(self, comp): ) self.logger.error(msg) raise MTTSError(msg) - elif self.channel_metadata.type == "magnetic": if comp[0].lower() not in ["h", "b"]: msg = ( @@ -475,7 +457,6 @@ def component(self, comp): ) self.logger.error(msg) raise MTTSError(msg) - if self.channel_metadata.type == "auxiliary": if comp[0].lower() in ["e", "h", "b"]: msg = ( @@ -484,7 +465,6 @@ def component(self, comp): ) self.logger.error(msg) raise MTTSError(msg) - self.channel_metadata.component = comp self._update_xarray_metadata() @@ -526,7 +506,6 @@ def sample_rate(self): / np.timedelta64(1, "s") ) ) - else: self.logger.debug("Data has not been set yet, sample rate is from metadata") sr = self.channel_metadata.sample_rate @@ -607,7 +586,6 @@ def start(self, start_time): if not isinstance(start_time, MTime): start_time = MTime(start_time) - self.channel_metadata.time_period.start = start_time.iso_str if self.has_data: if start_time == MTime(self._ts.coords.indexes["time"][0].isoformat()): @@ -617,11 +595,9 @@ def start(self, start_time): start_time, self.sample_rate, self.n_samples, self.logger ) self._ts.coords["time"] = new_dt - # make a time series that the data can be indexed by else: self.logger.debug("No data, just updating metadata start") - self._update_xarray_metadata() @property @@ -682,9 +658,65 @@ def channel_response_filter(self, value): ) self.logger.error(msg) raise TypeError(msg) - self._channel_response = value + def remove_instrument_response(self, **kwargs): + """ + Remove instrument response from the given channel response filter + + The order of operations is important (if applied): + + 1) detrend + 2) zero mean + 3) zero pad + 4) time window + 5) frequency window + 6) remove response + 7) undo time window + 8) bandpass + + **kwargs** + + :param plot: to plot the calibration process [ False | True ] + :type plot: boolean, default True + :param detrend: Remove linar trend of the time series + :type detrend: boolean, default True + :param zero_mean: Remove the mean of the time series + :type zero_mean: boolean, default True + :param zero_pad: pad the time series to the next power of 2 for efficiency + :type zero_pad: boolean, default True + :param t_window: Time domain windown name see `scipy.signal.windows` for options + :type t_window: string, default None + :param t_window_params: Time domain window parameters, parameters can be + found in `scipy.signal.windows` + :type t_window_params: dictionary + :param f_window: Frequency domain windown name see `scipy.signal.windows` for options + :type f_window: string, defualt None + :param f_window_params: Frequency window parameters, parameters can be + found in `scipy.signal.windows` + :type f_window_params: dictionary + :param bandpass: bandpass freequency and order {"low":, "high":, "order":,} + :type bandpass: dictionary + + """ + + remover = RemoveInstrumentResponse( + self.ts, + self.time_index, + self.sample_interval, + self.channel_response_filter, + **kwargs, + ) + + calibrated_ts = ChannelTS() + calibrated_ts.__dict__.update(self.__dict__) + calibrated_ts.ts = remover.remove_instrument_response() + calibrated_ts.channel_metadata.filter.applied = [True] * len( + self.channel_metadata.filter.applied + ) + + return calibrated_ts + def get_slice(self, start, end=None, n_samples=None): """ Get a slice from the time series given a start and end time. @@ -706,23 +738,18 @@ def get_slice(self, start, end=None, n_samples=None): msg = "Must input either end_time or n_samples." self.logger.error(msg) raise ValueError(msg) - if n_samples is not None and end is not None: msg = "Must input either end_time or n_samples, not both." self.logger.error(msg) raise ValueError(msg) - if not isinstance(start, MTime): start = MTime(start) - if n_samples is not None: n_samples = int(n_samples) end = start + n_samples / self.sample_rate - if end is not None: if not isinstance(end, MTime): end = MTime(end) - new_ts = self._ts.loc[ (self._ts.indexes["time"] >= start.iso_no_tz) & (self._ts.indexes["time"] < end.iso_no_tz) @@ -758,7 +785,6 @@ def resample(self, dec_factor=1, inplace=False): if inplace: self.ts = new_ts - else: new_ts.attrs.update( self.channel_metadata.to_dict()[self.channel_metadata._class_name] @@ -821,14 +847,12 @@ def from_obspy_trace(self, obspy_trace): msg = f"Input must be obspy.core.Trace, not {type(obspy_trace)}" self.logger.error(msg) raise MTTSError(msg) - if obspy_trace.stats.channel[1].lower() in ["e", "q"]: self.channel_metadata = metadata.Electric() elif obspy_trace.stats.channel[1].lower() in ["h", "b", "f"]: self.channel_metadata = metadata.Magnetic() else: self.channel_metadata = metadata.Auxiliary() - mt_code = fdsn_tools.make_mt_channel( fdsn_tools.read_channel_code(obspy_trace.stats.channel) ) diff --git a/mth5/timeseries/ts_filters.py b/mth5/timeseries/ts_filters.py new file mode 100644 index 00000000..89277741 --- /dev/null +++ b/mth5/timeseries/ts_filters.py @@ -0,0 +1,674 @@ +#!/usr/bin/env python + +""" +time series filters + +""" + +# ================================================================= +import numpy as np +from scipy import signal + +from matplotlib import pyplot as plt +from matplotlib.lines import Line2D +from mth5.utils.mth5_logger import setup_logger + +logger = setup_logger(__file__) +# ================================================================= + + +def butter_bandpass(lowcut, highcut, fs, order=5): + nyq = 0.5 * fs + + if lowcut is not None: + low = lowcut / nyq + if highcut is not None: + high = highcut / nyq + if lowcut and highcut: + sos = signal.butter( + order, [low, high], analog=False, btype="band", output="sos" + ) + elif highcut is None: + sos = signal.butter(order, low, analog=False, btype="low", output="sos") + elif lowcut is None: + sos = signal.butter(order, high, analog=False, btype="high", output="sos") + return sos + + +def butter_bandpass_filter(data, lowcut, highcut, fs, order=5): + sos = butter_bandpass(lowcut, highcut, fs, order=order) + y = signal.sosfiltfilt(sos, data) + return y + + +def low_pass(f, low_pass_freq, cutoff_freq, sampling_rate): + nyq = 0.5 * sampling_rate + filt_order, wn = signal.buttord(low_pass_freq / nyq, cutoff_freq / nyq, 3, 40) + + b, a = signal.butter(filt_order, wn, btype="low") + f_filt = signal.filtfilt(b, a, f) + + return f_filt + + +def zero_pad(input_array, power=2, pad_fill=0): + """ + pad the input array with pad_fill to the next power of power. + + For faster fft computation pad the array to the next power of 2 with zeros + + Arguments: + ----------- + **input_array** : np.ndarray (only 1-d arrays are supported at the + moment) + + **power** : [ 2 | 10 ] + power look for + + **pad_fill** : float or int + pad the array with this + + Output: + -------- + **pad_array** : np.ndarray padded with pad_fill + + """ + + len_array = input_array.shape[0] + if power == 2: + npow = int(np.ceil(np.log2(len_array))) + if power == 10: + npow = int(np.ceil(np.log10(len_array))) + if npow > 32: + logger.warning( + "Exceeding memory allocation inherent in your computer 2**32. " + "Limiting the zero pad to 2**32" + ) + pad_array = np.zeros(power ** npow) + if pad_fill != 0: + pad_array[:] = pad_fill + pad_array[0:len_array] = input_array + + return pad_array + + +class RemoveInstrumentResponse: + """ + Remove instrument response from the given channel response filter + + The order of operations is important (if applied): + + 1) detrend + 2) zero mean + 3) zero pad + 4) time window + 5) frequency window + 6) remove response + 7) undo time window + 8) bandpass + + :param ts: time series data to remove response from + :type ts: np.ndarray((N,) , dtype=float) + :param time_array: time index that corresponds to the time series + :type time_array: np.ndarray((N,) , dtype=np.datetime[ns]) + :param sample_interval: seconds per sample (time interval between samples) + :type sample_interval: float + :param channel_response_filter: Channel response filter with all filters + included to convert from counts to physical units + :type channel_response_filter: `class`:mt_metadata.timeseries.filters.ChannelResponseFilter` + + **kwargs** + + :param plot: to plot the calibration process [ False | True ] + :type plot: boolean, default True + :param detrend: Remove linar trend of the time series + :type detrend: boolean, default True + :param zero_mean: Remove the mean of the time series + :type zero_mean: boolean, default True + :param zero_pad: pad the time series to the next power of 2 for efficiency + :type zero_pad: boolean, default True + :param t_window: Time domain windown name see `scipy.signal.windows` for options + :type t_window: string, default None + :param t_window_params: Time domain window parameters, parameters can be + found in `scipy.signal.windows` + :type t_window_params: dictionary + :param f_window: Frequency domain windown name see `scipy.signal.windows` for options + :type f_window: string, defualt None + :param f_window_params: Frequency window parameters, parameters can be + found in `scipy.signal.windows` + :type f_window_params: dictionary + :param bandpass: bandpass freequency and order {"low":, "high":, "order":,} + :type bandpass: dictionary + + + """ + + def __init__( + self, ts, time_array, sample_interval, channel_response_filter, **kwargs + ): + self.logger = setup_logger(f"{__name__}.{self.__class__.__name__}") + self.ts = ts + self.time_array = time_array + self.sample_interval = sample_interval + self.channel_response_filter = channel_response_filter + self.plot = False + self.detrend = True + self.zero_mean = True + self.zero_pad = True + self.t_window = None + self.t_window_params = {} + self.f_window = None + self.f_window_params = {} + self.bandpass = {} + self.fig = None + self.nrows = None + self.subplot_dict = {} + + for key, value in kwargs.items(): + setattr(self, key, value) + + def _subplots(self, x, y, color, num, label): + """ + helper function to make subplots for if plotting is desired + + :param x: x array + :type x: np.ndarray + :param y: y array + :type y: np.ndarray + :param color: color of the line + :type color: tuple + :param num: subplot number + :type num: integer + :param label: legend label + :type label: string + + """ + ax_t = self.fig.get_axes()[0] + ax_f = self.fig.get_axes()[1] + ax = self.fig.add_subplot(self.nrows, 2, num, sharex=ax_t) + ax2 = self.fig.add_subplot(self.nrows, 2, num + 1, sharex=ax_f) + + # plot time series + line = Line2D([0], [0], color=color) + ax.plot(x, y, color=color) + f = np.fft.rfftfreq(x.size, d=self.sample_interval) + + # plot spectra + data = np.fft.rfft(y) + ax2.loglog(f, abs(data), color=color) + ax.legend( + [line], + [label], + loc="upper left", + borderaxespad=0.01, + borderpad=0.1, + markerscale=0.02, + ).set_zorder(1000) + + @staticmethod + def get_window(window, window_params, size): + """ + Get window from scipy.signal + + :param window: name of the window + :type window: string + :param window_params: dictionary of window parameters + :type window_params: dictionary + :param size: number of points in the window + :type size: integer + :return: window function + :rtype: class:`scipy.signal` + + """ + return getattr(signal.windows, window)(size, **window_params) + + def apply_detrend(self, ts): + """ + Detrend time series using scipy.detrend('linear') + + :param ts: input time series + :type ts: np.ndarray + :return: detrended time series + :rtype: np.ndarray + + """ + ts = signal.detrend(ts, type="linear") + + if self.plot: + self._subplots( + self.time_array, + ts, + (0.45, 0.1, 0.5), + self.subplot_dict["detrend"], + "Detrended", + ) + return ts + + def apply_zero_mean(self, ts): + """ + Remove the mean from the time series + + :param ts: input time series + :type ts: np.ndarray + :return: zero mean time series + :rtype: np.ndarray + + """ + ts = ts - ts.mean() + + if self.plot: + self._subplots( + self.time_array, + ts, + (0.55, 0.1, 0.4), + self.subplot_dict["zero_mean"], + "Zero Mean", + ) + return ts + + def apply_zero_pad(self, ts): + """ + zero pad to power of 2, at the end of the time series to make the + FFT more efficient + + :param ts: input time series + :type ts: np.ndarray + :return: zero padded time series + :rtype: np.ndarray + + """ + + pad_ts = zero_pad(ts) + + if self.plot: + dt = int(1.0 / self.sample_interval * 1000000000) + diff = int(((pad_ts.size - ts.size) + 1) * dt) + time_array = np.arange( + self.time_array[0], + self.time_array[-1] + np.timedelta64(diff), + np.timedelta64(dt), + dtype="datetime64[ns]", + ) + self._subplots( + time_array, + pad_ts, + (0.7, 0.1, 0.25), + self.subplot_dict["pad"], + "Zero Pad", + ) + return pad_ts + + def apply_t_window(self, ts): + """ + Apply a window in the time domain. Get the available windows from + `scipy.signal.windows` + + :param ts: input time series + :type ts: np.ndarray + :return: windowed time series + :rtype: np.ndarray + + """ + w = self.get_window(self.t_window, self.t_window_params, self.ts.size) + ts = ts * w + + if self.plot: + self._subplots( + self.time_array, + ts, + (0.7, 0.1, 0.25), + self.subplot_dict["t_window"], + f"t_window {self.t_window.capitalize()}", + ) + return ts + + def apply_f_window(self, data): + """ + Apply a frequency domain window. Get the available windows from + `scipy.signal.windows` + + Need to create a window twice the size of the input because we are + only taking the rfft which gives just half the spectra + and then take only half the window + + :param data: input spectra + :type data: np.ndarray + :return: windowed spectra + :rtype: np.ndarray + + """ + + w = self.get_window(self.f_window, self.f_window_params, 2 * data.size)[ + data.size : + ] + data = data * w + if self.plot: + f = np.fft.rfftfreq(2 * data.size, d=self.sample_interval)[1:] + ax_t = self.fig.get_axes()[0] + ax_f = self.fig.get_axes()[1] + ax = self.fig.add_subplot( + self.nrows, 2, self.subplot_dict["f_window"], sharex=ax_t + ) + ax2 = self.fig.add_subplot( + self.nrows, 2, self.subplot_dict["f_window"] + 1, sharex=ax_f + ) + + ax.plot( + self.time_array, + abs(np.fft.irfft(data)[0 : self.time_array.size]), + color=(0.85, 0.1, 0.15), + ) + ax2.loglog(f, abs(data), color=(0.85, 0.1, 0.15)) + axt2 = ax2.twinx() + axt2.semilogx(f, w, color=(0.5, 0.5, 0.5), zorder=0) + line = Line2D([0], [0], color=(0.85, 0.1, 0.15)) + ax.legend( + [line], + [f"Freq Window {self.f_window.capitalize()}"], + loc="upper left", + borderaxespad=0.01, + borderpad=0.1, + ) + return data + + def apply_bandpass(self, ts): + """ + apply a bandpass filter to the calibrated data + + + :param ts: calibrated time series + :type ts: np.ndarray + :return: bandpassed time series + :rtype: np.ndarray + + """ + ts = butter_bandpass_filter( + ts, + self.bandpass["low"], + self.bandpass["high"], + self.sample_interval, + order=self.bandpass["order"], + ) + + if self.plot: + self._subplots( + self.time_array, + ts, + (0.875, 0.1, 0.1), + self.subplot_dict["bandpass"], + "Band Pass", + ) + return ts + + def _get_subplot_count(self): + """ + helper function to get subplot information + + :return: dictionary of subplot information + :rtype: dictionary + + """ + order = ["detrend", "zero_mean", "t_window", "pad", "f_window", "bandpass"] + pdict = { + "pad": self.zero_pad, + "zero_mean": self.zero_mean, + "detrend": self.detrend, + "t_window": self.t_window, + "f_window": self.f_window, + "bandpass": self.bandpass, + } + subplot_dict = {} + count = 3 + nrows = 2 + for key in order: + value = pdict[key] + if value: + subplot_dict[key] = count + count += 2 + nrows += 1 + self.nrows = nrows + + return subplot_dict + + def remove_instrument_response(self): + """ + Remove instrument response following the recipe provided + + :return: calibrated time series + :rtype: np.ndarray + + """ + ts = np.copy(self.ts) + f = np.fft.rfftfreq(ts.size, d=self.sample_interval) + step = 1 + if self.plot: + self.subplot_dict = self._get_subplot_count() + self.fig = plt.figure(figsize=[10, 12]) + self.fig.clf() + ax = self.fig.add_subplot(self.nrows, 2, 1) + ax2 = self.fig.add_subplot(self.nrows, 2, 2) + (l1,) = ax.plot(self.time_array, ts, color="k", lw=2) + ax.set_xlim((self.time_array[0], self.time_array[-1])) + (l2,) = ax2.loglog(f, abs(np.fft.rfft(ts)), "k", lw=2) + ax2.set_xlim((f[0], f[-1])) + ax.legend( + [l1], ["Original"], loc="upper left", borderaxespad=0.01, borderpad=0.1 + ) + # detrend + if self.detrend: + ts = self.apply_detrend(ts) + self.logger.debug(f"Step {step}: Applying Linear Detrend") + step += 1 + # zero mean + if self.zero_mean: + ts = self.apply_zero_mean(ts) + self.logger.debug(f"Step {step}: Removing Mean") + step += 1 + # filter in time domain + if self.t_window is not None: + ts = self.apply_t_window(ts) + self.logger.debug(f"Step {step}: Applying {self.t_window} Time Window") + step += 1 + if self.plot: + wax = self.fig.get_axes()[self.subplot_dict["t_window"] - 1].twinx() + (tw,) = wax.plot( + self.time_array, + self.get_window(self.t_window, self.t_window_params, ts.size), + color=(0.75, 0.75, 0.75), + zorder=0, + ) + if self.zero_pad: + # pad the time series to a power of 2, this may be overkill, especially for long time series + ts = self.apply_zero_pad(ts) + self.logger.debug(f"Step {step}: Applying Zero Padding") + step += 1 + # get the real frequencies of the FFT + f = np.fft.rfftfreq(ts.size, d=self.sample_interval) + + if self.channel_response_filter.filters_list is []: + raise ValueError("There are no filters in channel_response to remove") + # compute the complex response given the frequency range of the FFT + # the complex response assumes frequencies are in reverse order and flip them on input + # so we need to flip the complex reponse so it aligns with the fft. + cr = self.channel_response_filter.complex_response(f)[::-1] + # remove the DC term at frequency == 0 + cr[-1] = abs(cr[-2]) + 0.0j + + data = np.fft.rfft(ts) + # remove DC term + data[-1] = abs(data[-1]) + 0.0j + + # if a window is requested then create it here and mulitply by the data + # the windows are designed to be symmetrical about frequency = 0 + # here we are taking only the real part of the FFT so we cut the window in half + if self.f_window is not None: + data = self.apply_f_window(data) + self.logger.debug(f"Step {step}: Applying {self.f_window} Frequency Window") + step += 1 + # calibrate the time series, compute real part of fft, divide out channel response, inverse fft + calibrated_ts = np.fft.irfft(data / cr)[0 : self.ts.size] + self.logger.debug(f"Step {step}: Removing Calibration") + step += 1 + + # If a time window was applied, need to un-apply it to reconstruct the signal. + if self.t_window is not None: + w = self.get_window(self.t_window, self.t_window_params, calibrated_ts.size) + calibrated_ts = calibrated_ts / w + self.logger.debug(f"Step {step}: Un-applying Time Window") + step += 1 + if self.bandpass: + calibrated_ts = self.apply_bandpass(calibrated_ts) + self.logger.debug(f"Step {step}: Applying Bandpass Filter") + step += 1 + if self.plot: + self._subplots( + self.time_array[0 : calibrated_ts.size], + calibrated_ts, + (1, 0.1, 0.1), + self.nrows * 2 - 1, + "Calibrated", + ) + self.fig.get_axes()[-2].set_ylabel(self.channel_response_filter.units_in) + if self.t_window is not None: + wax = self.fig.get_axes()[-2].twinx() + (tw,) = wax.plot( + self.time_array, 1.0 / w, color=(0.5, 0.5, 0.5), zorder=0 + ) + self.fig.tight_layout() + plt.show() + return calibrated_ts + + +def adaptive_notch_filter( + bx, + df=100, + notches=[50, 100], + notchradius=0.5, + freqrad=0.9, + rp=0.1, + dbstop_limit=5.0, +): + """ + adaptive_notch_filter(bx, df, notches=[50,100], notchradius=.3, freqrad=.9) + will apply a notch filter to the array bx by finding the nearest peak + around the supplied notch locations. The filter is a zero-phase + Chebyshev type 1 bandstop filter with minimal ripples. + + Arguments: + ----------- + **bx** : np.ndarray(len_time_series) + time series to filter + + **df** : float + sampling frequency in Hz + + **notches** : list of frequencies (Hz) to filter + + **notchradius** : float + radius of the notch in frequency domain (Hz) + + **freqrad** : float + radius to searching for peak about notch from notches + + **rp** : float + ripple of Chebyshev type 1 filter, lower numbers means less + ripples + + **dbstop_limit** : float (in decibels) + limits the difference between the peak at the + notch and surrounding spectra. Any difference + above dbstop_limit will be filtered, anything + less will not + + Outputs: + --------- + + **bx** : np.ndarray(len_time_series) + filtered array + + **filtlst** : list + location of notches and power difference between peak of + notch and average power. + + ..Example: :: + + >>> import RemovePeriodicNoise_Kate as rmp + >>> # make a variable for the file to load in + >>> fn = r"/home/MT/mt01_20130101_000000.BX" + >>> # load in file, if the time series is not an ascii file + >>> # might need to add keywords to np.loadtxt or use another + >>> # method to read in the file + >>> bx = np.loadtxt(fn) + >>> # create a list of frequencies to filter out + >>> freq_notches = [50, 150, 200] + >>> # filter data + >>> bx_filt, filt_lst = rmp.adaptiveNotchFilter(bx, df=100. + >>> ... notches=freq_notches) + >>> #save the filtered data into a file + >>> np.savetxt(r"/home/MT/Filtered/mt01_20130101_000000.BX", bx_filt) + + Notes: + ------- + Most of the time the default parameters work well, the only thing + you need to change is the notches and perhaps the radius. I would + test it out with a few time series to find the optimum parameters. + Then make a loop over all you time series data. Something like + + >>> import os + >>> dirpath = r"/home/MT" + >>> #make a director to save filtered time series + >>> save_path = r"/home/MT/Filtered" + >>> if not os.path.exists(save_path): + >>> os.mkdir(save_path) + >>> for fn in os.listdir(dirpath): + >>> bx = np.loadtxt(os.path.join(dirpath, fn) + >>> bx_filt, filt_lst = rmp.adaptiveNotchFilter(bx, df=100. + >>> ... notches=freq_notches) + >>> np.savetxt(os.path.join(save_path, fn), bx_filt) + + """ + + bx = np.array(bx) + + if type(notches) is list: + notches = np.array(notches) + elif type(notches) in [float, int]: + notches = np.array([notches], dtype=np.float) + df = float(df) # make sure df is a float + dt = 1.0 / df # sampling rate + + # transform data into frequency domain to find notches + BX = np.fft.fft(zero_pad(bx)) + n = len(BX) # length of array + dfn = df / n # frequency step + dfnn = int(freqrad / dfn) # radius of frequency search + fn = notchradius # filter radius + freq = np.fft.fftfreq(n, dt) + + filtlst = [] + for notch in notches: + if notch > freq.max(): + break + else: + fspot = int(round(notch / dfn)) + nspot = np.where( + abs(BX) == max(abs(BX[max([fspot - dfnn, 0]) : min([fspot + dfnn, n])])) + )[0][0] + + med_bx = np.median( + abs(BX[max([nspot - dfnn * 10, 0]) : min([nspot + dfnn * 10, n])]) ** 2 + ) + + # calculate difference between peak and surrounding spectra in dB + dbstop = 10 * np.log10(abs(BX[nspot]) ** 2 / med_bx) + if np.nan_to_num(dbstop) == 0.0 or dbstop < dbstop_limit: + filtlst.append("No need to filter \n") + pass + else: + filtlst.append([freq[nspot], dbstop]) + ws = 2 * np.array([freq[nspot] - fn, freq[nspot] + fn]) / df + wp = 2 * np.array([freq[nspot] - 2 * fn, freq[nspot] + 2 * fn]) / df + ford, wn = signal.cheb1ord(wp, ws, 1, dbstop) + b, a = signal.cheby1(1, 0.5, wn, btype="bandstop") + bx = signal.filtfilt(b, a, bx) + return bx, filtlst diff --git a/tests/timeseries/test_remove_response.py b/tests/timeseries/test_remove_response.py new file mode 100644 index 00000000..7aaf34a0 --- /dev/null +++ b/tests/timeseries/test_remove_response.py @@ -0,0 +1,97 @@ +# -*- coding: utf-8 -*- +""" +Created on Wed Dec 1 12:18:08 2021 + +@author: jpeacock +""" +# ============================================================================= +# Imports +# ============================================================================= +import unittest +import numpy as np + +from mt_metadata.timeseries.filters import PoleZeroFilter +from mth5.timeseries import ChannelTS + +# ============================================================================= +# +# ============================================================================= + + +class TestRemoveResponse(unittest.TestCase): + """ + Test remove response, make a fake signal add some trends, + """ + + def setUp(self): + # pole zero filter + pz = PoleZeroFilter( + units_in="volts", units_out="nanotesla", name="instrument_response" + ) + pz.poles = [ + (-6.283185 + 10.882477j), + (-6.283185 - 10.882477j), + (-12.566371 + 0j), + ] + pz.zeros = [] + pz.normalization_factor = 18244400 + + # channel properties + self.channel = ChannelTS() + self.channel.channel_metadata.filter.applied = [False] + self.channel.channel_metadata.filter.name = ["instrument_response"] + self.channel.channel_metadata.component = "hx" + self.channel.channel_response_filter.filters_list.append(pz) + self.channel.sample_rate = 1 + n_samples = 4096 + self.t = np.arange(n_samples) * self.channel.sample_interval + # make a random signal + self.example_ts = np.sum( + [ + np.cos(2 * np.pi * w * self.t + phi) + for w, phi in zip( + np.logspace(-4, self.channel.sample_rate / 2, 20), + np.random.rand(20), + ) + ], + axis=0, + ) + + # multiply by filter response + f = np.fft.rfftfreq(self.t.size, self.channel.sample_interval) + response_ts = np.fft.irfft( + np.fft.rfft(self.example_ts) * pz.complex_response(f)[::-1] + ) + + # add in a linear trend + self.channel.ts = (0.3 * self.t) + response_ts + + self.calibrated_ts = self.channel.remove_instrument_response() + + def test_return_type(self): + self.assertIsInstance(self.calibrated_ts, ChannelTS) + + def test_applied(self): + self.assertTrue( + (np.array(self.calibrated_ts.channel_metadata.filter.applied) == True).all() + ) + + def test_returned_metadata(self): + with self.subTest("component"): + self.assertEqual(self.channel.component, self.calibrated_ts.component) + with self.subTest("sample rate"): + self.assertEqual(self.channel.sample_rate, self.calibrated_ts.sample_rate) + + def test_calibration(self): + + original_ts = self.example_ts - self.example_ts.mean() + std = (self.calibrated_ts.ts - original_ts).std() / original_ts.max() + print(std) + self.assertLessEqual(std, 0.075) + + +# ============================================================================= +# run +# ============================================================================= +if __name__ == "__main__": + unittest.main() diff --git a/tests/version_1/expected.csv b/tests/version_1/expected.csv new file mode 100644 index 00000000..a12b7750 --- /dev/null +++ b/tests/version_1/expected.csv @@ -0,0 +1,36 @@ +,survey,station,run,latitude,longitude,elevation,component,start,end,n_samples,sample_rate,measurement_type,azimuth,tilt,units,hdf5_reference,run_hdf5_reference,station_hdf5_reference +0,CONUS SoCal,CAS04,a,37.633351,-121.468382,329.3875,ex,2020-06-02 18:41:43+00:00,2020-06-02 22:07:46+00:00,12364,1.0,electric,13.2,0.0,digital counts,,, +1,CONUS SoCal,CAS04,a,37.633351,-121.468382,329.3875,ey,2020-06-02 18:41:43+00:00,2020-06-02 22:07:46+00:00,12364,1.0,electric,103.2,0.0,digital counts,,, +2,CONUS SoCal,CAS04,a,37.633351,-121.468382,329.3875,hx,2020-06-02 18:41:43+00:00,2020-06-02 22:07:46+00:00,12364,1.0,magnetic,13.2,0.0,digital counts,,, +3,CONUS SoCal,CAS04,a,37.633351,-121.468382,329.3875,hy,2020-06-02 18:41:43+00:00,2020-06-02 22:07:46+00:00,12364,1.0,magnetic,103.2,0.0,digital counts,,, +4,CONUS SoCal,CAS04,a,37.633351,-121.468382,329.3875,hz,2020-06-02 18:41:43+00:00,2020-06-02 22:07:46+00:00,12364,1.0,magnetic,0.0,90.0,digital counts,,, +5,CONUS SoCal,CAS04,b,37.633351,-121.468382,329.3875,ex,2020-06-02 22:24:55+00:00,2020-06-12 17:52:23+00:00,847649,1.0,electric,13.2,0.0,digital counts,,, +6,CONUS SoCal,CAS04,b,37.633351,-121.468382,329.3875,ey,2020-06-02 22:24:55+00:00,2020-06-12 17:52:23+00:00,847649,1.0,electric,103.2,0.0,digital counts,,, +7,CONUS SoCal,CAS04,b,37.633351,-121.468382,329.3875,hx,2020-06-02 22:24:55+00:00,2020-06-12 17:52:23+00:00,847649,1.0,magnetic,13.2,0.0,digital counts,,, +8,CONUS SoCal,CAS04,b,37.633351,-121.468382,329.3875,hy,2020-06-02 22:24:55+00:00,2020-06-12 17:52:23+00:00,847649,1.0,magnetic,103.2,0.0,digital counts,,, +9,CONUS SoCal,CAS04,b,37.633351,-121.468382,329.3875,hz,2020-06-02 22:24:55+00:00,2020-06-12 17:52:23+00:00,847649,1.0,magnetic,0.0,90.0,digital counts,,, +10,CONUS SoCal,CAS04,c,37.633351,-121.468382,329.3875,ex,2020-06-12 18:32:17+00:00,2020-07-01 17:32:59+00:00,1638043,1.0,electric,13.2,0.0,digital counts,,, +11,CONUS SoCal,CAS04,c,37.633351,-121.468382,329.3875,ey,2020-06-12 18:32:17+00:00,2020-07-01 17:32:59+00:00,1638043,1.0,electric,0.0,0.0,counts,,, +12,CONUS SoCal,CAS04,c,37.633351,-121.468382,329.3875,hx,2020-06-12 18:32:17+00:00,2020-07-01 17:32:59+00:00,1638043,1.0,magnetic,13.2,0.0,digital counts,,, +13,CONUS SoCal,CAS04,c,37.633351,-121.468382,329.3875,hy,2020-06-12 18:32:17+00:00,2020-07-01 17:32:59+00:00,1638043,1.0,magnetic,103.2,0.0,digital counts,,, +14,CONUS SoCal,CAS04,c,37.633351,-121.468382,329.3875,hz,2020-06-12 18:32:17+00:00,2020-07-01 17:32:59+00:00,1638043,1.0,magnetic,0.0,90.0,digital counts,,, +15,CONUS SoCal,CAS04,d,37.633351,-121.468382,329.3875,ex,2020-07-01 19:36:55+00:00,2020-07-13 19:00:00+00:00,1034586,1.0,electric,0.0,0.0,counts,,, +16,CONUS SoCal,CAS04,d,37.633351,-121.468382,329.3875,ey,2020-07-01 19:36:55+00:00,2020-07-13 19:00:00+00:00,1034586,1.0,electric,0.0,0.0,counts,,, +17,CONUS SoCal,CAS04,d,37.633351,-121.468382,329.3875,hx,2020-07-01 19:36:55+00:00,2020-07-13 19:00:00+00:00,1034586,1.0,magnetic,13.2,0.0,digital counts,,, +18,CONUS SoCal,CAS04,d,37.633351,-121.468382,329.3875,hy,2020-07-01 19:36:55+00:00,2020-07-13 19:00:00+00:00,1034586,1.0,magnetic,103.2,0.0,digital counts,,, +19,CONUS SoCal,CAS04,d,37.633351,-121.468382,329.3875,hz,2020-07-01 19:36:55+00:00,2020-07-13 19:00:00+00:00,1034586,1.0,magnetic,0.0,90.0,digital counts,,, +20,CONUS SoCal,NVR08,a,38.32663,-118.082382,1375.425,ex,2020-06-03 19:10:11+00:00,2020-06-03 19:57:51+00:00,2861,1.0,electric,12.6,0.0,digital counts,,, +21,CONUS SoCal,NVR08,a,38.32663,-118.082382,1375.425,ey,2020-06-03 19:10:11+00:00,2020-06-03 19:57:51+00:00,2861,1.0,electric,102.6,0.0,digital counts,,, +22,CONUS SoCal,NVR08,a,38.32663,-118.082382,1375.425,hx,2020-06-03 19:10:11+00:00,2020-06-03 19:57:51+00:00,2861,1.0,magnetic,12.6,0.0,digital counts,,, +23,CONUS SoCal,NVR08,a,38.32663,-118.082382,1375.425,hy,2020-06-03 19:10:11+00:00,2020-06-03 19:57:51+00:00,2861,1.0,magnetic,102.6,0.0,digital counts,,, +24,CONUS SoCal,NVR08,a,38.32663,-118.082382,1375.425,hz,2020-06-03 19:10:11+00:00,2020-06-03 19:57:51+00:00,2861,1.0,magnetic,0.0,90.0,digital counts,,, +25,CONUS SoCal,NVR08,b,38.32663,-118.082382,1375.425,ex,2020-06-03 20:14:13+00:00,2020-06-14 16:56:02+00:00,938510,1.0,electric,12.6,0.0,digital counts,,, +26,CONUS SoCal,NVR08,b,38.32663,-118.082382,1375.425,ey,2020-06-03 20:14:13+00:00,2020-06-14 16:56:02+00:00,938510,1.0,electric,102.6,0.0,digital counts,,, +27,CONUS SoCal,NVR08,b,38.32663,-118.082382,1375.425,hx,2020-06-03 20:14:13+00:00,2020-06-14 16:56:02+00:00,938510,1.0,magnetic,12.6,0.0,digital counts,,, +28,CONUS SoCal,NVR08,b,38.32663,-118.082382,1375.425,hy,2020-06-03 20:14:13+00:00,2020-06-14 16:56:02+00:00,938510,1.0,magnetic,102.6,0.0,digital counts,,, +29,CONUS SoCal,NVR08,b,38.32663,-118.082382,1375.425,hz,2020-06-03 20:14:13+00:00,2020-06-14 16:56:02+00:00,938510,1.0,magnetic,0.0,90.0,digital counts,,, +30,CONUS SoCal,NVR08,c,38.32663,-118.082382,1375.425,ex,2020-06-14 18:00:44+00:00,2020-06-24 15:55:46+00:00,856503,1.0,electric,12.6,0.0,digital counts,,, +31,CONUS SoCal,NVR08,c,38.32663,-118.082382,1375.425,ey,2020-06-14 18:00:44+00:00,2020-06-24 15:55:46+00:00,856503,1.0,electric,102.6,0.0,digital counts,,, +32,CONUS SoCal,NVR08,c,38.32663,-118.082382,1375.425,hx,2020-06-14 18:00:44+00:00,2020-06-24 15:55:46+00:00,856503,1.0,magnetic,12.6,0.0,digital counts,,, +33,CONUS SoCal,NVR08,c,38.32663,-118.082382,1375.425,hy,2020-06-14 18:00:44+00:00,2020-06-24 15:55:46+00:00,856503,1.0,magnetic,102.6,0.0,digital counts,,, +34,CONUS SoCal,NVR08,c,38.32663,-118.082382,1375.425,hz,2020-06-14 18:00:44+00:00,2020-06-24 15:55:46+00:00,856503,1.0,magnetic,0.0,90.0,digital counts,,, diff --git a/tests/version_1/test_from_stationxml.py b/tests/version_1/test_from_stationxml.py index a47fb5d9..d56afdc9 100644 --- a/tests/version_1/test_from_stationxml.py +++ b/tests/version_1/test_from_stationxml.py @@ -34,36 +34,38 @@ def setUp(self): self.m.from_experiment(self.experiment, 0) def test_groups(self): - with self.subTest(msg="Survey"): + + with self.subTest("has Survey"): self.assertEqual(self.m.has_group("Survey"), True) - with self.subTest(msg="Stations"): + with self.subTest("has SStations"): self.assertEqual(self.m.has_group("Survey/Stations"), True) - with self.subTest(msg="cas04"): + with self.subTest("has CAS04"): self.assertEqual(self.m.has_group("Survey/Stations/CAS04"), True) - with self.subTest(msg="run 001"): + with self.subTest("has run 001"): self.assertEqual(self.m.has_group("Survey/Stations/CAS04/001"), True) - with self.subTest(msg="ey"): + with self.subTest("has channel ey"): self.assertEqual(self.m.has_group("Survey/Stations/CAS04/001/ey"), True) - with self.subTest(msg="ex"): + with self.subTest("has channel hy"): self.assertEqual(self.m.has_group("Survey/Stations/CAS04/001/hy"), True) def test_survey_metadata(self): - with self.subTest(msg="id"): + with self.subTest("has network ZU"): self.assertEqual(self.m.survey_group.metadata.fdsn.network, "ZU") - with self.subTest(msg="start"): + with self.subTest("test start"): self.assertEqual( self.m.survey_group.metadata.time_period.start_date, "2020-01-01" ) - with self.subTest(msg="end"): + with self.subTest("test end"): self.assertEqual( self.m.survey_group.metadata.time_period.end_date, "2023-12-31" ) - with self.subTest(msg="summary"): + with self.subTest("survey summary"): + self.assertEqual( self.m.survey_group.metadata.summary, "USMTArray South Magnetotelluric Time Series (USMTArray CONUS South-USGS)", ) - with self.subTest(msg="doi"): + with self.subTest("doi"): self.assertEqual( self.m.survey_group.metadata.citation_dataset.doi, "10.7914/SN/ZU_2020" ) @@ -98,7 +100,7 @@ def test_station_metadata(self): m_station = self.m.get_station(station_dict["id"]).metadata for key, true_value in station_dict.items(): - with self.subTest(msg=key): + with self.subTest(key): self.assertEqual(true_value, m_station.get_attr_from_name(key)) def test_run_metadata(self): @@ -112,7 +114,7 @@ def test_run_metadata(self): m_run = self.m.get_run("CAS04", run_dict["id"]).metadata for key, true_value in run_dict.items(): - with self.subTest(msg=key): + with self.subTest(key): self.assertEqual(true_value, m_run.get_attr_from_name(key)) def test_ey_metadata(self): @@ -136,7 +138,7 @@ def test_ey_metadata(self): m_ch = self.m.get_channel("CAS04", "001", "ey").metadata for key, true_value in ch_dict.items(): - with self.subTest(msg=key): + with self.subTest(key): self.assertEqual(true_value, m_ch.get_attr_from_name(key)) def test_hy_metadata(self): diff --git a/tests/version_1/test_make_mth5.py b/tests/version_1/test_make_mth5.py index ac8ba3a0..5b41bc91 100644 --- a/tests/version_1/test_make_mth5.py +++ b/tests/version_1/test_make_mth5.py @@ -13,6 +13,8 @@ from obspy.clients.fdsn.header import FDSNNoDataException from mth5.utils.mth5_logger import setup_logger +expected_csv = Path(__file__).parent.joinpath("expected.csv") +expected_df = pd.read_csv(expected_csv) # ============================================================================= # Test various inputs for getting metadata # ============================================================================= @@ -26,99 +28,19 @@ class TestMakeMTH5(unittest.TestCase): def setUp(self): - ZUCAS04LQ1 = [ - "ZU", - "CAS04", - "", - "LQE", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUCAS04LQ2 = [ - "ZU", - "CAS04", - "", - "LQN", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUCAS04BF1 = [ - "ZU", - "CAS04", - "", - "LFE", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUCAS04BF2 = [ - "ZU", - "CAS04", - "", - "LFN", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUCAS04BF3 = [ - "ZU", - "CAS04", - "", - "LFZ", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUNRV08LQ1 = [ - "ZU", - "NVR08", - "", - "LQE", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUNRV08LQ2 = [ - "ZU", - "NVR08", - "", - "LQN", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUNRV08BF1 = [ - "ZU", - "NVR08", - "", - "LFE", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUNRV08BF2 = [ - "ZU", - "NVR08", - "", - "LFN", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - ZUNRV08BF3 = [ - "ZU", - "NVR08", - "", - "LFZ", - "2020-06-12T18:32:17", - "2020-07-13T19:00:00", - ] - metadata_list = [ - ZUCAS04LQ1, - ZUCAS04LQ2, - ZUCAS04BF1, - ZUCAS04BF2, - ZUCAS04BF3, - ZUNRV08LQ1, - ZUNRV08LQ2, - ZUNRV08BF1, - ZUNRV08BF2, - ZUNRV08BF3, - ] + self.make_mth5 = MakeMTH5(mth5_version="0.1.0") + self.make_mth5.client = "IRIS" + channels = ["LFE", "LFN", "LFZ", "LQE", "LQN"] + CAS04 = ["8P", "CAS04", "2020-06-02T18:00:00", "2020-07-13T19:00:00"] + NVR08 = ["8P", "NVR08", "2020-06-02T18:00:00", "2020-07-13T19:00:00"] + + request_list = [] + for entry in [CAS04, NVR08]: + for channel in channels: + request_list.append( + [entry[0], entry[1], "", channel, entry[2], entry[3]] + ) self.logger = setup_logger("test_make_mth5_v1") self.csv_fn = Path().cwd().joinpath("test_inventory.csv") self.mth5_path = Path().cwd() @@ -126,16 +48,15 @@ def setUp(self): self.stations = ["CAS04", "NVR08"] self.channels = ["LQE", "LQN", "LFE", "LFN", "LFZ"] - self.make_mth5 = MakeMTH5(mth5_version="0.1.0") - self.make_mth5.client = "IRIS" # Turn list into dataframe self.metadata_df = pd.DataFrame( - metadata_list, columns=self.make_mth5.column_names + request_list, columns=self.make_mth5.column_names ) + self.metadata_df.to_csv(self.csv_fn, index=False) self.metadata_df_fail = pd.DataFrame( - metadata_list, columns=["net", "sta", "loc", "chn", "startdate", "enddate"] + request_list, columns=["net", "sta", "loc", "chn", "startdate", "enddate"] ) def test_df_input_inventory(self): @@ -144,30 +65,36 @@ def test_df_input_inventory(self): ) with self.subTest(name="stations"): self.assertListEqual( - self.stations, [ss.code for ss in inv.networks[0].stations] + sorted(self.stations), + sorted([ss.code for ss in inv.networks[0].stations]), ) with self.subTest(name="channels_CAS04"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[0].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[0].channels]), ) with self.subTest(name="channels_NVR08"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[1].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[1].channels]), ) def test_csv_input_inventory(self): inv, streams = self.make_mth5.get_inventory_from_df(self.csv_fn, data=False) with self.subTest(name="stations"): self.assertListEqual( - self.stations, [ss.code for ss in inv.networks[0].stations] + sorted(self.stations), + sorted([ss.code for ss in inv.networks[0].stations]), ) with self.subTest(name="channels_CAS04"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[0].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[0].channels]), ) with self.subTest(name="channels_NVR08"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[1].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[1].channels]), ) def test_fail_csv_inventory(self): @@ -204,24 +131,23 @@ def test_make_mth5(self): ["Transfer_Functions", "a", "b", "c", "d"], self.m.get_station("CAS04").groups_list, ) - for run in ["a", "b"]: + for run in ["a", "b", "c", "d"]: for ch in ["ex", "ey", "hx", "hy", "hz"]: with self.subTest(name=f"has data CAS04.{run}.{ch}"): x = self.m.get_channel("CAS04", run, ch) - x_ts = x.to_channel_ts() - self.assertTrue(np.all((x_ts._ts.values == 0) == True)) - for run in ["c", "d"]: - for ch in ["ex", "ey", "hx", "hy", "hz"]: - with self.subTest(name=f"has data CAS04.{run}.{ch}"): - x = self.m.get_channel("CAS04", run, ch) - x_ts = x.to_channel_ts() - self.assertFalse(np.all(x.hdf5_dataset == 0)) - self.assertFalse(np.all((x_ts._ts.values == 0) == True)) + self.assertTrue(abs(x.hdf5_dataset[()].mean()) > 0) + with self.subTest(name="NVR08_runs"): + self.assertListEqual( + ["Transfer_Functions", "a", "b", "c"], + self.m.get_station("NVR08").groups_list, + ) for run in ["a", "b", "c"]: for ch in ["ex", "ey", "hx", "hy", "hz"]: with self.subTest(name=f"has data NVR08.{run}.{ch}"): x = self.m.get_channel("NVR08", run, ch) - self.assertFalse(np.all(x.hdf5_dataset == 0)) + self.assertTrue(abs(x.hdf5_dataset[()].mean()) > 0) + # with self.subTest("channel summary"): + self.m.close_mth5() self.m.filename.unlink() except FDSNNoDataException as error: diff --git a/tests/version_2/test_make_mth5.py b/tests/version_2/test_make_mth5.py index c4084237..48bd2e78 100644 --- a/tests/version_2/test_make_mth5.py +++ b/tests/version_2/test_make_mth5.py @@ -26,99 +26,19 @@ class TestMakeMTH5(unittest.TestCase): def setUp(self): - ZUCAS04LQ1 = [ - "ZU", - "CAS04", - "", - "LQE", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUCAS04LQ2 = [ - "ZU", - "CAS04", - "", - "LQN", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUCAS04BF1 = [ - "ZU", - "CAS04", - "", - "LFE", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUCAS04BF2 = [ - "ZU", - "CAS04", - "", - "LFN", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUCAS04BF3 = [ - "ZU", - "CAS04", - "", - "LFZ", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUNRV08LQ1 = [ - "ZU", - "NVR08", - "", - "LQE", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUNRV08LQ2 = [ - "ZU", - "NVR08", - "", - "LQN", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUNRV08BF1 = [ - "ZU", - "NVR08", - "", - "LFE", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUNRV08BF2 = [ - "ZU", - "NVR08", - "", - "LFN", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - ZUNRV08BF3 = [ - "ZU", - "NVR08", - "", - "LFZ", - "2020-06-02T19:00:00", - "2020-07-13T19:00:00", - ] - metadata_list = [ - ZUCAS04LQ1, - ZUCAS04LQ2, - ZUCAS04BF1, - ZUCAS04BF2, - ZUCAS04BF3, - ZUNRV08LQ1, - ZUNRV08LQ2, - ZUNRV08BF1, - ZUNRV08BF2, - ZUNRV08BF3, - ] + self.make_mth5 = MakeMTH5(mth5_version="0.2.0") + self.make_mth5.client = "IRIS" + + channels = ["LFE", "LFN", "LFZ", "LQE", "LQN"] + CAS04 = ["8P", "CAS04", "2020-06-02T18:00:00", "2020-07-13T19:00:00"] + NVR08 = ["8P", "NVR08", "2020-06-02T18:00:00", "2020-07-13T19:00:00"] + request_list = [] + for entry in [CAS04, NVR08]: + for channel in channels: + request_list.append( + [entry[0], entry[1], "", channel, entry[2], entry[3]] + ) self.logger = setup_logger("test_make_mth5_v2") self.csv_fn = Path().cwd().joinpath("test_inventory.csv") self.mth5_path = Path().cwd() @@ -126,16 +46,14 @@ def setUp(self): self.stations = ["CAS04", "NVR08"] self.channels = ["LQE", "LQN", "LFE", "LFN", "LFZ"] - self.make_mth5 = MakeMTH5(mth5_version="0.2.0") - self.make_mth5.client = "IRIS" # Turn list into dataframe self.metadata_df = pd.DataFrame( - metadata_list, columns=self.make_mth5.column_names + request_list, columns=self.make_mth5.column_names ) self.metadata_df.to_csv(self.csv_fn, index=False) self.metadata_df_fail = pd.DataFrame( - metadata_list, columns=["net", "sta", "loc", "chn", "startdate", "enddate"] + request_list, columns=["net", "sta", "loc", "chn", "startdate", "enddate"] ) def test_df_input_inventory(self): @@ -144,30 +62,36 @@ def test_df_input_inventory(self): ) with self.subTest(name="stations"): self.assertListEqual( - self.stations, [ss.code for ss in inv.networks[0].stations] + sorted(self.stations), + sorted([ss.code for ss in inv.networks[0].stations]), ) with self.subTest(name="channels_CAS04"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[0].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[0].channels]), ) with self.subTest(name="channels_NVR08"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[1].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[1].channels]), ) def test_csv_input_inventory(self): inv, streams = self.make_mth5.get_inventory_from_df(self.csv_fn, data=False) with self.subTest(name="stations"): self.assertListEqual( - self.stations, [ss.code for ss in inv.networks[0].stations] + sorted(self.stations), + sorted([ss.code for ss in inv.networks[0].stations]), ) with self.subTest(name="channels_CAS04"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[0].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[0].channels]), ) with self.subTest(name="channels_NVR08"): self.assertListEqual( - self.channels, [ss.code for ss in inv.networks[0].stations[1].channels] + sorted(self.channels), + sorted([ss.code for ss in inv.networks[0].stations[1].channels]), ) def test_fail_csv_inventory(self): @@ -197,24 +121,24 @@ def test_make_mth5(self): self.metadata_df, self.mth5_path, interact=True ) - sg = self.m.get_survey("CONUS_South") + sg = self.m.get_survey("CONUS_SoCal") with self.subTest(name="stations"): self.assertListEqual(self.stations, sg.stations_group.groups_list) with self.subTest(name="CAS04_runs"): self.assertListEqual( ["Transfer_Functions", "a", "b", "c", "d"], - self.m.get_station("CAS04", "CONUS_South").groups_list, + self.m.get_station("CAS04", "CONUS_SoCal").groups_list, ) for run in ["a", "b", "c", "d"]: for ch in ["ex", "ey", "hx", "hy", "hz"]: with self.subTest(name=f"has data CAS04.{run}.{ch}"): - x = self.m.get_channel("CAS04", run, ch, "CONUS_South") - self.assertFalse(np.all(x.hdf5_dataset == 0)) + x = self.m.get_channel("CAS04", run, ch, "CONUS_SoCal") + self.assertTrue(abs(x.hdf5_dataset[()].mean()) > 0) for run in ["a", "b", "c"]: for ch in ["ex", "ey", "hx", "hy", "hz"]: with self.subTest(name=f"has data NVR08.{run}.{ch}"): - x = self.m.get_channel("NVR08", run, ch, "CONUS_South") - self.assertFalse(np.all(x.hdf5_dataset == 0)) + x = self.m.get_channel("NVR08", run, ch, "CONUS_SoCal") + self.assertTrue(abs(x.hdf5_dataset[()].mean()) > 0) self.m.close_mth5() self.m.filename.unlink() except FDSNNoDataException as error: