.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/Inference_1D/plot_inference_1d_tempest.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_Inference_1D_plot_inference_1d_tempest.py: Running GeoBIPy to invert Tempest data ++++++++++++++++++++++++++++++++++++++ .. GENERATED FROM PYTHON SOURCE LINES 5-29 .. code-block:: Python import os import sys import pathlib from datetime import timedelta import time import numpy as np from geobipy import Inference3D from geobipy import user_parameters from geobipy import get_prng def checkCommandArguments(): """Check the users command line arguments. """ import argparse # warnings.filterwarnings('error') Parser = argparse.ArgumentParser(description="GeoBIPy", formatter_class=argparse.ArgumentDefaultsHelpFormatter) Parser.add_argument('--index', default=0, type=int, help='job array index 0-18') Parser.add_argument('--data', default=None, help="Data type. Choose from ['skytem_512', 'tempest', 'resolve']") Parser.add_argument('--model', default=None, help="Model type. Choose from ['glacial', 'saline_clay', 'resistive_dolomites', 'resistive_basement', 'coastal_salt_water', 'ice_over_salt_water']") return Parser.parse_args() .. GENERATED FROM PYTHON SOURCE LINES 30-40 .. code-block:: Python np.random.seed(0) args = checkCommandArguments() sys.path.append(os.getcwd()) models = ['glacial', 'saline_clay', 'resistive_dolomites', 'resistive_basement', 'coastal_salt_water', 'ice_over_salt_water'] data_type = "Tempest" model_type = models[args.index] .. GENERATED FROM PYTHON SOURCE LINES 41-43 The directory where HDF files will be stored %% .. GENERATED FROM PYTHON SOURCE LINES 43-91 .. code-block:: Python file_path = os.path.join(data_type, model_type) pathlib.Path(file_path).mkdir(parents=True, exist_ok=True) for filename in os.listdir(file_path): try: if os.path.isfile(file_path) or os.path.islink(file_path): os.unlink(file_path) except Exception as e: print('Failed to delete %s. Reason: %s' % (file_path, e)) output_directory = file_path data_filename = data_type + '_' + model_type supplementary = "..//..//supplementary//" parameter_file = supplementary + "//options_files//{}_options".format(data_type) inputFile = pathlib.Path(parameter_file) assert inputFile.exists(), Exception("Cannot find input file {}".format(inputFile)) output_directory = pathlib.Path(output_directory) assert output_directory.exists(), Exception("Make sure the output directory exists {}".format(output_directory)) print('Using user input file {}'.format(parameter_file)) print('Output files will be produced at {}'.format(output_directory)) kwargs = user_parameters.read(inputFile) kwargs['n_markov_chains'] = 5000 kwargs['data_filename'] = supplementary + '//data//' + data_filename + '.csv' kwargs['system_filename'] = supplementary + "//data//" + kwargs['system_filename'] # Everyone needs the system classes read in early. data = kwargs['data_type']._initialize_sequential_reading(kwargs['data_filename'], kwargs['system_filename']) # Start keeping track of time. t0 = time.time() seed = 146100583096709124601953385843316024947 prng = get_prng(seed=seed) inference3d = Inference3D(data, prng=prng) inference3d.create_hdf5(directory=output_directory, **kwargs) print("Created hdf5 files in {} h:m:s".format(str(timedelta(seconds=time.time()-t0)))) inference3d.infer(index=2, **kwargs) .. image-sg:: /examples/Inference_1D/images/sphx_glr_plot_inference_1d_tempest_001.png :alt: Fiducial [2.], Time Domain EM Data :srcset: /examples/Inference_1D/images/sphx_glr_plot_inference_1d_tempest_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none Using user input file ..//..//supplementary////options_files//Tempest_options Output files will be produced at Tempest/glacial self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) Creating HDF5 files, this may take a few minutes... Files are being created for data files ..//..//supplementary////data//Tempest_glacial.csv and system files ..//..//supplementary////data//..//data/tempest.stm self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) Created hdf5 file for line 0.0 with 79 data points Created hdf5 files 79 total data points self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) Created hdf5 files in 0:00:00.343917 h:m:s self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) self.n_components=2, self.nTimes=array([15]) i=5000, k=5, acc=*24.800, 0.013 s/Model, 67.241 s Elapsed, eta=--:--:-- h:m:s Remaining Points -2/1 || Elapsed Time: 0:01:08.886762 h:m:s || ETA 0:00:22.962254 h:m:s .. rst-class:: sphx-glr-timing **Total running time of the script:** (1 minutes 12.870 seconds) .. _sphx_glr_download_examples_Inference_1D_plot_inference_1d_tempest.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_inference_1d_tempest.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_inference_1d_tempest.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_inference_1d_tempest.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_