{ "cells": [ { "cell_type": "markdown", "id": "4770c6c1-0d3b-45b3-9c41-57fad0025130", "metadata": {}, "source": [ "# Filters\n", "\n", "This section includes information about filters, which can be a very painful process and somewhat obtuse. \n", "\n", "Filters are basically anything that manipulates the time series data into something else. This includes scaling, removing instrument response, removing trends, notch filtering, passband filtering, etc. We want to work with data that is in physical units, but the data are often collected in digital counts. To transform between the two we need to apply or unapply certain filters. When going from physical units to digital counts we are applying filters, `channel_metadata.filter.applied = [True]`, whereas going from counts to physical units we are unapplying the filters `channel_metadata.filter.applied = [False]`. This may seem backwards, but this is the way most archived data is thought of. Then any filter applied to physical units for the purposes of cleaning the data are `channel_metadata.filter.applied = [True]`. \n", "\n", "**Note**: currently there are not tools to convert digital counts to physical units, this is a work in progress. Nevertheless all the information is there for you to do the transformation. \n", "\n", "Supported filters in `mt_metadata.timeseries.filters` are: \n", "\n", "| **Filter** | **Description** |\n", "|--------|-------------|\n", "| **CoefficientFilter** | A coefficient filter scales the data by a given factor, a real value. |\n", "| **FIRFilter** | A finite impulse response filter is commonly an anti-alias filter and is represented as a 1-D array of real valued coefficients.| \n", "| **PoleZeroFilter** | A pole-zero filter is often an type of bandpass filter. It is represented as symmetric complex poles and zeros with a scale factor |\n", "| **TimeDelayFilter** | A time delay filter delays the data by a real valued time delay. A negative value is a delay and a positive value is a prediction. | \n", "| **FrequencyResponseTableFilter** | A frequency, amplitude, phase look-up table, commonly in physical units and degrees. This is commonly how manufacturers provide instrument responses.|\n", "| **ChannelResponseFilter** | A comprehensive representation of all filters. Contains a list of all filters, should be the most commonly used filter object as it can compute the total response, and estimate the passband and normalization frequency. |\n" ] }, { "cell_type": "markdown", "id": "d8b1ebbb-f046-48d1-b60f-011aa5ad9659", "metadata": {}, "source": [ "## Filter Base\n", "\n", "All filters inherit from a `FilterBase` class, which has attributes and methods common to all filters. \n", "\n", "### Units\n", "\n", "The two common to all filters are `units_in` and `units_out`. These attributes are key as they describes how the filters are transforming the data. The units should be SI units and given as all lowercase full names. For example Volts would be `volts` and V/m would be `volts per meter`. All units are represented in short form. \n", "\n", "### Complex Response\n", "\n", "A method is provided to compute the complex response, this is slightly different for each filter and the method overwritten by the different filters. \n", "\n", "### Pass Band\n", "\n", "A method is also provided to compute the \"pass band\" of a given filter. This is the band where the response is flat, the estimation is only approximate and should be used with caution. It works well for simple filters, but more complex filters, it tries to pick the longest segment with a flat response. `CoefficientFilter` and `TimeDelayFilter` objects have an infinite pass band. `FrequencyResponseTableFilter` estimate the pass band within the given frequencies, unless told otherwise. If the frequency range is out of the range of the calibration frequencies extrapolation is applied. This should also be done with caution. " ] }, { "cell_type": "code", "execution_count": 1, "id": "eda77e78-a969-43b6-b8da-2a83ff71f8b5", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "\n", "# make a general frequency array to calculate complex response\n", "# note that these are linear frequencies and the complex response uses angular frequencies\n", "frequencies = np.logspace(-5, 5, 500)" ] }, { "cell_type": "markdown", "id": "529168cd-4680-4e78-8b89-461e0c90d2b9", "metadata": {}, "source": [ "## Coefficient Filter\n", "A coefficient filter is relatively simple. It includes a scale factor represented as `gain`." ] }, { "cell_type": "code", "execution_count": 2, "id": "890920a2-81c4-477b-9ea4-ccbb5ce2177d", "metadata": {}, "outputs": [], "source": [ "from mt_metadata.timeseries.filters import CoefficientFilter" ] }, { "cell_type": "code", "execution_count": 3, "id": "3c48531b-027e-4929-9f5c-7407715bfc1a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{\n", " \"coefficient_filter\": {\n", " \"calibration_date\": \"1980-01-01\",\n", " \"gain\": 100.0,\n", " \"name\": \"example_coefficient_filter\",\n", " \"type\": \"coefficient\",\n", " \"units_in\": \"V\",\n", " \"units_out\": \"V\"\n", " }\n", "}" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cf = CoefficientFilter(units_in=\"volts\", units_out=\"V\", gain=100.0, name=\"example_coefficient_filter\")\n", "cf" ] }, { "cell_type": "code", "execution_count": 4, "id": "f2bf6727-01d3-4df6-a1c4-ef1fee9373cc", "metadata": {}, "outputs": [ { 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cf.plot_response(frequencies, x_units=\"frequency\")" ] }, { "cell_type": "markdown", "id": "e65ac93b-d885-46bf-8321-fae06854875a", "metadata": {}, "source": [ "## FIR Filter\n", "An finite impulse response filter is commonly used as an anti-alias filter, and is represented as a 1-D array of real valued coefficients. " ] }, { "cell_type": "code", "execution_count": 5, "id": "caab02c5-edff-4128-bd99-86f931f79d15", "metadata": {}, "outputs": [], "source": [ "from mt_metadata.timeseries.filters import FIRFilter" ] }, { "cell_type": "code", "execution_count": 6, "id": "0b0a17e6-cf2c-4e3d-b9a7-3d89f17d8e5e", "metadata": {}, "outputs": [], "source": [ "fir = FIRFilter(\n", " units_in=\"volts\",\n", " units_out=\"volts\",\n", " name=\"example_fir\",\n", " decimation_input_sample_rate=32000,\n", " gain=0.999904,\n", " symmetry=\"EVEN\",\n", " decimation_factor=16,\n", ")\n", "\n", "fir.coefficients = [\n", " 1.0828314e-06, 1.7808272e-06, 3.2410387e-06, 5.4627321e-06, 8.682945e-06, 1.3240843e-05, 1.9565294e-05,\n", " 2.8185128e-05, 3.9656901e-05, 5.4688699e-05, 7.4153548e-05, 9.8989171e-05, 0.00013036761, 0.00016954952,\n", " 0.00021798223, 0.00027731725, 0.00034936491, 0.00043613836, 0.00053984317, 0.0006628664, 0.00080777059,\n", " 0.00097733398, 0.0011744311, 0.0014021378, 0.0016635987, 0.0019620692, 0.0023008469, 0.0026832493,\n", " 0.0031125348, 0.0035918986, 0.0041243695, 0.0047127693, 0.0053596641, 0.0060672448, 0.0068373145,\n", " 0.0076711699, 0.0085695535, 0.0095325625, 0.010559602, 0.01164928, 0.012799387, 0.014006814, 0.015267504,\n", " 0.016576445, 0.017927598, 0.019313928, 0.020727372, 0.022158878, 0.023598416, 0.025035053, 0.026456987,\n", " 0.027851671, 0.029205887, 0.030505868, 0.031737458, 0.032886244, 0.03393773, 0.034877509, 0.035691477,\n", " 0.036365997, 0.036888145, 0.037245877, 0.03742826, 0.037425674, 0.03723, 0.036834806, 0.036235519,\n", " 0.035429578, 0.034416564, 0.033198304, 0.031778947, 0.030165028, 0.028365461, 0.026391543, 0.024256891,\n", " 0.021977346, 0.019570865, 0.017057346, 0.014458441, 0.011797323, 0.009098433, 0.0063871844, 0.0036896705,\n", " 0.0010323179, -0.0015584482, -0.0040565561, -0.0064366534, -0.0086744577, -0.010747112, -0.012633516,\n", " -0.014314661, -0.0157739, -0.01699724, -0.017973563, -0.018694809, -0.019156145, -0.01935605, -0.019296378,\n", " -0.018982368, -0.018422581, -0.017628808, -0.016615927, -0.015401681, -0.014006456, -0.012452973,\n", " -0.010765962, -0.0089718029, -0.0070981304, -0.0051734182, -0.0032265538, -0.0012863991, 0.0006186511,\n", " 0.0024610918, 0.0042147399, 0.0058551184, 0.0073598339, 0.0087089101, 0.0098850802, 0.01087404, 0.011664648,\n", " 0.012249067, 0.012622863, 0.012785035, 0.012737988, 0.012487462, 0.01204238, 0.011414674, 0.010619033,\n", " 0.0096726287, 0.0085947802, 0.007406604, 0.006130626, 0.0047903718, 0.0034099557, 0.002013647, 0.00062545808,\n", " -0.0007312728, -0.0020342721, -0.0032627005, -0.0043974896, -0.0054216445, -0.0063205026, -0.0070819431,\n", " -0.0076965573, -0.0081577515, -0.0084618134, -0.0086079109, -0.0085980454, -0.0084369555, -0.0081319623,\n", " -0.0076927822, -0.0071312929, -0.0064612622, -0.005698049, -0.0048582871, -0.0039595389, -0.0030199524,\n", " -0.0020579058, -0.0010916605, -0.00013902181, 0.00078298012, 0.0016583927, 0.0024726097, 0.0032126096,\n", " 0.0038671608, 0.0044269804, 0.0048848582, 0.005235733, 0.0054767267, 0.0056071337, 0.0056283739,\n", " 0.0055438946, 0.0053590466, 0.0050809216, 0.0047181565, 0.0042807218, 0.0037796798, 0.0032269375,\n", " 0.0026349833, 0.0020166242, 0.001384723, 0.00075194426, 0.00013050952, -0.00046802824, -0.0010329896,\n", " -0.0015547526, -0.0020249044, -0.0024363673, -0.0027834927, -0.0030621202, -0.0032696081, -0.0034048304,\n", " -0.003468141, -0.0034613123, -0.003387446, -0.0032508562, -0.003056939, -0.0028120177, -0.0025231787,\n", " -0.0021980959, -0.0018448512, -0.001471751, -0.0010871479, -0.00069926586, -0.00031603608, 5.5052958e-05,\n", " 0.00040709358, 0.00073387625, 0.0010299878, 0.0012908906, 0.0015129783, 0.0016936094, 0.0018311206,\n", " 0.0019248178, 0.0019749457, 0.0019826426, 0.0019498726, 0.0018793481, 0.001774437, 0.0016390601,\n", " 0.0014775817, 0.0012946966, 0.0010953132, 0.00088443852, 0.00066706788, 0.00044807568, 0.00023212004,\n", " 2.3551687e-05, -0.00017366471, -0.00035601447, -0.00052048819, -0.00066461961, -0.0007865114, -0.00088484585,\n", " -0.00095888576, -0.0010084547, -0.0010339168, -0.0010361352, -0.0010164281, -0.00097651512, -0.0009184563,\n", " -0.00084458862, -0.00075745879, -0.00065975531, -0.0005542388, -0.00044368068, -0.00033079527, -0.00021818698,\n", " -0.0001082966, -3.3548122e-06, 9.4652831e-05, 0.00018401834, 0.00026333242, 0.00033149892, 0.00038773834,\n", " 0.00043159194, 0.00046290434, 0.0004818163, 0.0004887383, 0.00048432534, 0.00046944799, 0.00044515711,\n", " 0.0004126484, 0.0003732258, 0.00032826542, 0.0002791743, 0.00022736372, 0.0001742071, 0.00012101705,\n", " 6.9016627e-05, 1.9314915e-05, -2.7108661e-05, -6.9420195e-05, -0.00010694123, -0.00013915499, -0.00016570302,\n", " -0.00018639189, -0.00020117435, -0.00021015058, -0.00021354953, -0.00021171506, -0.00020509114, -0.00019420317,\n", " -0.00017963824, -0.00016202785, -0.00014203126, -0.00012030972, -9.7522447e-05, -7.4297881e-05, -5.1229126e-05,\n", " -2.8859566e-05, -7.6714587e-06, 1.191924e-05, 2.9567975e-05, 4.5006156e-05, 5.8043028e-05, 6.8557049e-05,\n", " 7.6507284e-05, 8.1911501e-05, 8.4854546e-05, 8.5473977e-05, 8.3953237e-05, 8.0514517e-05, 7.5410928e-05,\n", " 6.8914269e-05, 6.1308667e-05, 5.2886291e-05, 4.3926615e-05, 3.4708195e-05, 2.5484322e-05, 1.6489239e-05,\n", " 7.9309229e-06, -1.335887e-08, -7.1985955e-06, -1.3510014e-05, -1.8867066e-05, -2.32245e-05, -2.6558888e-05,\n", " -2.8887769e-05, -3.0242758e-05, -3.0684769e-05, -3.0291432e-05, -2.9154804e-05, -2.7376906e-05, -2.5070442e-05,\n", " -2.2347936e-05, -1.9321938e-05, -1.6109379e-05, -1.2808429e-05, -9.5234091e-06, -6.3382245e-06,\n", " -3.3291028e-06, -5.5987789e-07, 1.9187619e-06, 4.072373e-06, 5.8743913e-06, 7.312286e-06, 8.3905516e-06,\n", " 9.10975e-06, 9.4979405e-06, 9.5751602e-06, 9.3762619e-06, 8.9382884e-06, 8.301693e-06, 7.5045982e-06,\n", " 6.592431e-06, 5.6033018e-06, 4.5713236e-06, 3.5404175e-06, 2.5302468e-06, 1.5771827e-06, 6.9930724e-07,\n", " -8.6047464e-08, -7.6676685e-07, -1.3332562e-06, -1.7875625e-06, -2.1266892e-06, -2.35267e-06, -2.4824365e-06,\n", " -2.5098916e-06, -2.4598471e-06, -2.335345e-06, -2.1523615e-06, -1.9251499e-06, -1.6707684e-06, -1.3952398e-06,\n", " -1.1173763e-06, -8.4543007e-07, -5.7948262e-07, -3.444687e-07, -1.2505329e-07, 6.1743521e-08, 2.1873758e-07,\n", " 3.4424812e-07, 4.3748074e-07, 4.931357e-07, 5.2551894e-07, 5.344753e-07, 5.136161e-07, 4.9029785e-07,\n", " 4.3492003e-07, 3.8198567e-07, 3.2236682e-07, 2.6023093e-07, 1.9363162e-07, 1.3382508e-07, 6.8672463e-08,\n", " 2.1443693e-08, -1.9671351e-09, -4.7522178e-08, -6.2719053e-08, -1.0190665e-07, -1.2015286e-07, -1.103657e-07,\n", " -1.0294882e-07, -1.1965994e-07, -1.3612285e-07, -1.463918e-07, -1.4752351e-07, 3.9802276e-07]" ] }, { "cell_type": "code", "execution_count": 7, "id": "ba0cf7a9-cc69-47c2-ac1d-733a78ceacd9", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Pass Band frequency range estimation: [1.00000000e-05 1.18071285e+01]\n" ] } ], "source": [ "fir.plot_response(frequencies, x_units=\"frequency\", pb_tol=.5)\n", "print(f\"Pass Band frequency range estimation: {fir.pass_band(frequencies, tol=.5)}\") " ] }, { "cell_type": "markdown", "id": "9857ee3b-b428-4d8f-9b1f-d86fe2ccb9b1", "metadata": {}, "source": [ "## Pole Zero Filter\n", "\n", "A pole-zero filter is a mathematical way to represent a filter using complex valued poles and zeros and a scaling factor. The advantage of the pole-zero representation is that arbitrary frequency ranges can be computed without having to extrapolate. " ] }, { "cell_type": "code", "execution_count": 8, "id": "3736294e-a270-4ad1-a4cb-110ad29b5701", "metadata": {}, "outputs": [], "source": [ "from mt_metadata.timeseries.filters import PoleZeroFilter" ] }, { "cell_type": "code", "execution_count": 23, "id": "91729ac6-72f3-4e30-a69d-532444864f25", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{\n", " \"pole_zero_filter\": {\n", " \"calibration_date\": \"1980-01-01\",\n", " \"gain\": 1.0,\n", " \"name\": \"example_zpk_response\",\n", " \"normalization_factor\": 2002.269,\n", " \"poles\": {\n", " \"real\": [\n", " -6.283185,\n", " -6.283185,\n", " -12.566371\n", " ],\n", " \"imag\": [\n", " 10.882477,\n", " -10.882477,\n", " 0.0\n", " ]\n", " },\n", " \"type\": \"zpk\",\n", " \"units_in\": \"nT\",\n", " \"units_out\": \"V\",\n", " \"zeros\": {\n", " \"real\": [],\n", " \"imag\": []\n", " }\n", " }\n", "}" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pz = PoleZeroFilter(units_in=\"nanotesla\", units_out=\"volts\", name=\"example_zpk_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", "pz" ] }, { "cell_type": "code", "execution_count": 24, "id": "564b5c2a-8108-4607-bb1c-ea75d5a28551", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Pass Band frequency range estimation: [1.00000000e-05 5.36363132e-01]\n" ] } ], "source": [ "pz.plot_response(frequencies, x_units=\"frequency\", pb_tol=1e-2)\n", "print(f\"Pass Band frequency range estimation: {pz.pass_band(frequencies, tol=1e-2)}\") " ] }, { "cell_type": "markdown", "id": "a23e8bff-0748-4a17-9c53-b89bcd9b9aca", "metadata": {}, "source": [ "## Time Delay Filter\n", "\n", "A time delay filter are often incorporated in the AD converter that controls mulitple channels and creates a small time delay as it shifts between the channels. A positive value predicts time and a negative value delays time. For causality the value should always be negative. The delay is givne in seconds. " ] }, { "cell_type": "code", "execution_count": 25, "id": "d58ce2ae-0dca-4a0e-a055-a9fbd875d768", "metadata": {}, "outputs": [], "source": [ "from mt_metadata.timeseries.filters import TimeDelayFilter" ] }, { "cell_type": "code", "execution_count": 26, "id": "cca24908-2eb3-4fea-80f3-0f4cbe9415eb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1.e-05, 1.e+05])" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "td = TimeDelayFilter(units_in=\"volts\", units_out=\"volts\", name=\"example_time_delay\", delay=-.25)\n", "td.pass_band(frequencies)" ] }, { "cell_type": "code", "execution_count": 27, "id": "b00bee06-27c9-4c99-8317-0704b327bc39", "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "td.plot_response(frequencies, x_units=\"frequency\")" ] }, { "cell_type": "markdown", "id": "0d7773aa-c121-46fe-b4fa-9e6ea732384c", "metadata": {}, "source": [ "## FrequencyResponseTableFilter\n", "\n", "Commonly to calibrate the frequency response of an instrument a manufacturer will run a calibration taking measurements at discrete frequencies and then supplying a table of frequency, amplitude, and phase for the users. This is more accurate than pole-zero representation but has limitations in that extrapolation needs to be applied to frequencies outside of the calibrated frequencies and interpolation between calibrated frequencies. \n", "\n", "**Note**: phase is assumed to be in radians. " ] }, { "cell_type": "code", "execution_count": 28, "id": "b0ff2298-9428-4863-b969-d6e6c45a65a9", "metadata": {}, "outputs": [], "source": [ "from mt_metadata.timeseries.filters import FrequencyResponseTableFilter" ] }, { "cell_type": "code", "execution_count": 29, "id": "83130862-90c8-4bae-a1d7-4d193999688f", "metadata": {}, "outputs": [], "source": [ "fap = FrequencyResponseTableFilter(units_in=\"nanotesla\", units_out=\"volts\", 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]" ] }, { "cell_type": "code", "execution_count": 30, "id": "f2180686-40e5-40e7-b335-9b3a25cbb210", "metadata": {}, "outputs": [], "source": [ "from matplotlib import pyplot as plt" ] }, { "cell_type": "code", "execution_count": 31, "id": "d1c6f673-ce57-488a-89ff-73180cead414", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33m\u001b[1m2023-12-15T15:19:49.985222-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:19:49.987198-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Pass Band frequency range estimation: [ 2. 181.02]\n" ] } ], "source": [ "fap.plot_response(frequencies, x_units=\"frequency\", unwrap=True, pb_tol=1E-2, interpolation_method=\"slinear\")\n", "print(f\"Pass Band frequency range estimation: {fap.pass_band(fap.frequencies, tol=1e-2, interpolation_method='slinear')}\") " ] }, { "cell_type": "markdown", "id": "a2ed3316-a821-4c09-82c4-16d218a5ca5d", "metadata": {}, "source": [ "**IMPORTANT**: As you can see above extrapolation is unstable and will have change the data in unknown ways. If you need to extrapolate past the calibrated frequencies try to extrapolate using a different method than the one provided. Try using a different interpolation method, or a different curve fitting algorithm. " ] }, { "cell_type": "markdown", "id": "ea5b6390-be53-4582-b655-d2d933df8c54", "metadata": {}, "source": [ "## ChannelResponse\n", "\n", "These individual filters are useful, but the more practical use is combining all filters into a single filter and calculating the total response. The `mt_metadata.timeseries.filters.ChannelResponse` is provide for this purpose. " ] }, { "cell_type": "code", "execution_count": 32, "id": "4798fc87-d791-469d-9616-4ff4345a5a9d", "metadata": {}, "outputs": [], "source": [ "from mt_metadata.timeseries.filters import ChannelResponse" ] }, { "cell_type": "code", "execution_count": 34, "id": "2725625e-67f5-4f9f-a618-1683201186fa", "metadata": {}, "outputs": [], "source": [ "channel_response = ChannelResponse()\n", "channel_response.filters_list = [fap, fir, td]\n", "channel_response.frequencies = frequencies" ] }, { "cell_type": "code", "execution_count": 35, "id": "79c808d4-4108-4fab-8649-a1810d400eec", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33m\u001b[1m2023-12-15T15:20:19.893002-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:19.898653-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:19.903162-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:19.917270-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:19.930826-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "channel_response.plot_response(x_units=\"frequency\", pb_tol=1e-1, include_delay=True)" ] }, { "cell_type": "markdown", "id": "9019c701-329a-4410-be82-b0964afb8e4e", "metadata": {}, "source": [ "## Estimate Total Sensitivity\n", "If you want to do a quick calibration you can divide the time series by the total sensitivity and it will be accurate within the pass band." ] }, { "cell_type": "code", "execution_count": 36, "id": "6c497b3d-a629-4cee-981d-b9a6e058ca1b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33m\u001b[1m2023-12-15T15:20:26.677815-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.689788-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "Normalization Frequency: 1.097 Hz\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.705198-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "Pass Band: [ 0.1018629 11.80712847] Hz\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.717494-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.730959-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.745496-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.760097-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.778543-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "\u001b[33m\u001b[1m2023-12-15T15:20:26.804114-0800 | WARNING | mt_metadata.timeseries.filters.frequency_response_table_filter | complex_response | Extrapolating, use values outside calibration frequencies with caution\u001b[0m\n", "Total Sensitivity: 9.405\n" ] } ], "source": [ "print(f\"Normalization Frequency: {channel_response.normalization_frequency} Hz\") \n", "print(f\"Pass Band: {channel_response.pass_band} Hz\")\n", "print(f\"Total Sensitivity: {channel_response.compute_instrument_sensitivity(sig_figs=3)}\")" ] }, { "cell_type": "markdown", "id": "17ff821a-00fc-4342-9813-73a403ce456d", "metadata": {}, "source": [ "## Check if units are proper between filters\n", "The output units of the first filter must be the same units as the input units for the second filter. This is done when the filter list is set. Here you can see that the unit order is not correct." ] }, { "cell_type": "code", "execution_count": 37, "id": "6c79132f-a70a-4bf8-8ce4-17314d42e911", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[31m\u001b[1m2023-12-15T15:21:05.111062-0800 | ERROR | mt_metadata.timeseries.filters.channel_response | _check_consistency_of_units | Unit consistency is incorrect. The input units for example_fap should be V not nT\u001b[0m\n" ] }, { "ename": "ValueError", "evalue": "Unit consistency is incorrect. The input units for example_fap should be V not nT", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[37], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m channel_response \u001b[38;5;241m=\u001b[39m ChannelResponse()\n\u001b[0;32m----> 2\u001b[0m channel_response\u001b[38;5;241m.\u001b[39mfilters_list \u001b[38;5;241m=\u001b[39m [cf, fap, pz]\n", "File \u001b[0;32m~/software/irismt/mt_metadata/mt_metadata/base/metadata.py:371\u001b[0m, in \u001b[0;36mBase.__setattr__\u001b[0;34m(self, name, value)\u001b[0m\n\u001b[1;32m 337\u001b[0m skip_list \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 338\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlatitude\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 339\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlongitude\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 367\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfn\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 368\u001b[0m ]\n\u001b[1;32m 370\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m skip_list:\n\u001b[0;32m--> 371\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__setattr__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 372\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m 373\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m name\u001b[38;5;241m.\u001b[39mstartswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m 374\u001b[0m \u001b[38;5;66;03m# test if the attribute is a property first, if it is, then\u001b[39;00m\n\u001b[1;32m 375\u001b[0m \u001b[38;5;66;03m# it will have its own defined setter, so use that one and\u001b[39;00m\n\u001b[1;32m 376\u001b[0m \u001b[38;5;66;03m# skip validation.\u001b[39;00m\n", "File \u001b[0;32m~/software/irismt/mt_metadata/mt_metadata/timeseries/filters/channel_response.py:76\u001b[0m, in \u001b[0;36mChannelResponse.filters_list\u001b[0;34m(self, filters_list)\u001b[0m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"set the filters list and validate the list\"\"\"\u001b[39;00m\n\u001b[1;32m 75\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_filters_list \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_filters_list(filters_list)\n\u001b[0;32m---> 76\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_consistency_of_units\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/software/irismt/mt_metadata/mt_metadata/timeseries/filters/channel_response.py:371\u001b[0m, in \u001b[0;36mChannelResponse._check_consistency_of_units\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 365\u001b[0m msg \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 366\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnit consistency is incorrect. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 367\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe input units for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmt_filter\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m should be \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 368\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mprevious_units\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmt_filter\u001b[38;5;241m.\u001b[39munits_in\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 369\u001b[0m )\n\u001b[1;32m 370\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlogger\u001b[38;5;241m.\u001b[39merror(msg)\n\u001b[0;32m--> 371\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg)\n\u001b[1;32m 372\u001b[0m previous_units \u001b[38;5;241m=\u001b[39m mt_filter\u001b[38;5;241m.\u001b[39munits_out\n\u001b[1;32m 374\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n", "\u001b[0;31mValueError\u001b[0m: Unit consistency is incorrect. The input units for example_fap should be V not nT" ] } ], "source": [ "channel_response = ChannelResponse()\n", "channel_response.filters_list = [cf, fap, pz]" ] } ], "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": "3.10.10" } }, "nbformat": 4, "nbformat_minor": 5 }