Hysteresis Processing#
Install and import packages#
Import local data in MagIC format#
In this demonstration we will be using local data.
The data is from the following publication:
Swanson-Hysell, N. L., Avery, M. S., Zhang, Y., Hodgin, E. B., Sherwood, R. J., Apen, F. E., et al. (2021). The paleogeography of Laurentia in its early years: New constraints from the Paleoproterozoic East-Central Minnesota Batholith. Tectonics, 40, e2021TC006751. https://doi.org/10.1029/2021TC006751
# set the dir_path to the directory where the measurements.txt file is located
dir_path = '../example_data/ECMB'
# set the name of the MagIC file
ipmag.unpack_magic('magic_contribution_20213.txt',
dir_path = dir_path,
input_dir_path = dir_path,
print_progress=False)
# create a contribution object from the tables in the directory
contribution = cb.Contribution(dir_path)
measurements = contribution.tables['measurements'].df
specimens = contribution.tables['specimens'].df
1 records written to file /Users/yimingzhang/Github/RockmagPy-notebooks/example_data/ECMB/contribution.txt
1 records written to file /Users/yimingzhang/Github/RockmagPy-notebooks/example_data/ECMB/locations.txt
90 records written to file /Users/yimingzhang/Github/RockmagPy-notebooks/example_data/ECMB/sites.txt
312 records written to file /Users/yimingzhang/Github/RockmagPy-notebooks/example_data/ECMB/samples.txt
1574 records written to file /Users/yimingzhang/Github/RockmagPy-notebooks/example_data/ECMB/specimens.txt
17428 records written to file /Users/yimingzhang/Github/RockmagPy-notebooks/example_data/ECMB/measurements.txt
-I- Using online data model
-I- Getting method codes from earthref.org
-I- Importing controlled vocabularies from https://earthref.org
Get hysteresis data using the method code#
The method codes relevant to hysteresis loops are:
LP-HYSfor regular hysteresis loopsLP-HYS-Ofor hysteresis loops as a function of orientationLP-HYS-Tfor hysteresis loops as a function of temperature
We can filter the data to only have data for LP-HYS.
hyst_measurements = measurements[measurements['method_codes'] == 'LP-HYS']
We can see what experimental hysteresis data are available in this dataset:
hyst_experiments = rmag.make_experiment_df(hyst_measurements)
hyst_experiments
| specimen | method_codes | experiment | |
|---|---|---|---|
| 0 | NED1-5c | LP-HYS | IRM-VSM3-LP-HYS-218845 |
| 1 | NED18-2c | LP-HYS | IRM-VSM3-LP-HYS-218847 |
| 2 | NED2-8c | LP-HYS | IRM-VSM3-LP-HYS-218849 |
| 3 | NED4-1c | LP-HYS | IRM-VSM3-LP-HYS-218853 |
| 4 | NED6-6c | LP-HYS | IRM-VSM3-LP-HYS-218855 |
Process hysteresis data for one experiment#
We can visualize that data from one of the experiments using the rmag.process_hyst_loop function. The details behind the function are detailed in the hysteresis_processing_walk_through.ipynb notebook.
#specify the experiment name and specimen name
experiment_name = 'IRM-VSM3-LP-HYS-218845'
specimen_name = 'NED1-5c'
experiment_hyst = measurements[measurements['experiment'] == experiment_name].reset_index(drop=True)
experiment_results = rmag.process_hyst_loop(experiment_hyst['meas_field_dc'].values, experiment_hyst['magn_mass'].values, specimen_name)
NED1_5c_hyst_process_result = experiment_results
Process hysteresis data for all experiments#
results = rmag.process_hyst_loops(hyst_experiments,measurements)
for i in hyst_experiments.index:
experiment = hyst_experiments['experiment'][i]
specimen = hyst_experiments['specimen'][i]
experiment_hyst = measurements[measurements['experiment'] == experiment].reset_index(drop=True)
experiment_hyst_result = rmag.process_hyst_loop(experiment_hyst['meas_field_dc'].values, experiment_hyst['magn_mass'].values, specimen)
experiment_hyst_result
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'loop_closure_test_results': {'SNR': -8.290556040314511,
'HAR': nan,
'loop_is_closed': True},
'loop_is_closed': True,
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'Brh': 0.07213917073117043,
'sigma': -0.785285332466001,
'chi_HF': 2.9999504736760194e-07,
'FNL60': 17.162713319279685,
'FNL70': 11.24212943818284,
'FNL80': 1.6222739928908756,
'Ms': 0.004094243626387143,
'Bc': 0.02326904798646487,
'M_sn_f': 184.9021345020286,
'Qf': 2.2669419246643217,
'Fnl_lin': None,
'plot': figure(id='p2631', ...)}
export hysteresis loop statistics into a MagIC specimens data table#
rmag.add_hyst_stats_to_specimens_table(specimens, 'IRM-VSM3-LP-HYS-218845', NED1_5c_hyst_process_result)
specimens
| citations | critical_temp | critical_temp_type | description | dir_comp | dir_dang | dir_dec | dir_inc | dir_mad_free | dir_n_comps | ... | rem_hirm_mass | rem_sratio | rem_sratio_back | rem_sratio_forward | result_quality | sample | software_packages | specimen | volume | weight | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| specimen name | |||||||||||||||||||||
| NED1-1b | This study | NaN | None | None | mc | 2.8 | 159.7 | 62.5 | 1.0 | 1.0 | ... | NaN | NaN | NaN | NaN | g | NED1-1 | pmagpy-4.2.25: demag_gui | NED1-1b | NaN | NaN |
| NED1-1b | This study | NaN | None | None | mc | 2.8 | 139.2 | 74.1 | 1.0 | 1.0 | ... | NaN | NaN | NaN | NaN | g | NED1-1 | pmagpy-4.2.25: demag_gui | NED1-1b | NaN | NaN |
| NED1-1b | This study | NaN | None | None | None | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | None | NED1-1 | None | NED1-1b | NaN | NaN |
| NED1-2b | This study | NaN | None | None | mc | 3.4 | 164.1 | 66.9 | 0.4 | 1.0 | ... | NaN | NaN | NaN | NaN | g | NED1-2 | pmagpy-4.2.25: demag_gui | NED1-2b | NaN | NaN |
| NED1-2b | This study | NaN | None | None | mc | 3.4 | 149.9 | 76.3 | 0.4 | 1.0 | ... | NaN | NaN | NaN | NaN | g | NED1-2 | pmagpy-4.2.25: demag_gui | NED1-2b | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| NED1-5c | This study | NaN | None | None | None | NaN | NaN | NaN | NaN | NaN | ... | -0.000007 | 0.931 | 0.1 | 1.0 | None | NED1-5 | None | NED1-5c | NaN | 0.000154 |
| NED18-2c | This study | NaN | None | None | None | NaN | NaN | NaN | NaN | NaN | ... | 0.000066 | 0.938 | 0.1 | 1.0 | None | NED18-2 | None | NED18-2c | NaN | 0.000254 |
| NED2-8c | This study | NaN | None | None | None | NaN | NaN | NaN | NaN | NaN | ... | 0.000074 | 0.846 | 0.1 | 1.0 | None | NED2-8 | None | NED2-8c | NaN | 0.000188 |
| NED18-2c | This study | 105.9 | Verwey | None | None | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | None | NED18-2 | None | NED18-2c | NaN | NaN |
| NED18-2c | This study | 106.3 | Verwey | None | None | NaN | NaN | NaN | NaN | NaN | ... | NaN | NaN | NaN | NaN | None | NED18-2 | None | NED18-2c | NaN | NaN |
1574 rows × 38 columns