Summary plots of hysteresis parameters

This notebook imports summary hysteresis parameters from a MagIC contribution and generates:

• a Day plot which is the remanence ratio (M_r/M_s; “squareness”) vs. the coercivity ratio (B_cr/B_c)

• a squareness-coercivity diagram (M_r/M_s) vs. the coercivity (B_c); also referred to as a Néel plot

Here, M_r is the remanent magnetization, M_s is the saturation magnetization, B_c is the coercivity, and B_cr is the coercivity of remanence.

import pmagpy.rockmag as rmag
import pmagpy.ipmag as ipmag
import pmagpy.contribution_builder as cb
import pandas as pd

import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'retina'

Import local data in MagIC format

We will start by downloading the MagIC data associated with this paper (MagIC ID of 16460):

• Jackson, M. and Swanson-Hysell, N.L. (2012), Rock Magnetism of Remagnetized Carbonate Rocks: Another Look, In: Elmore, R. D., Muxworthy, A. R., Aldana, M. M. and Mena, M., eds., Remagnetization and Chemical Alteration of Sedimentary Rocks, Geological Society of London Special Publication, 371, https://doi.org/10.1144/SP371.3.

# set the dir_path to the directory where the measurements.txt file is located
dir_path = '../example_data/Jackson2012'

# download the data from the MagIC database using my private contribution key 
result, magic_file = ipmag.download_magic_from_id('16460', directory=dir_path)
# unpack the MagIC file
ipmag.unpack_magic(magic_file, dir_path, print_progress=False)
# get the contribution object
contribution = cb.Contribution(dir_path)
# get the measurements table
measurements = contribution.tables['measurements'].df
measurements = measurements.dropna(axis=1, how='all')
specimens = contribution.tables['specimens'].df

Download successful. File saved to: ../example_data/Jackson2012/magic_contribution_16460.txt
1  records written to file  /Users/unimos/0000_Github/RockmagPy-notebooks/example_data/Jackson2012/contribution.txt
5  records written to file  /Users/unimos/0000_Github/RockmagPy-notebooks/example_data/Jackson2012/locations.txt
8  records written to file  /Users/unimos/0000_Github/RockmagPy-notebooks/example_data/Jackson2012/sites.txt
51  records written to file  /Users/unimos/0000_Github/RockmagPy-notebooks/example_data/Jackson2012/samples.txt
186  records written to file  /Users/unimos/0000_Github/RockmagPy-notebooks/example_data/Jackson2012/specimens.txt
4758  records written to file  /Users/unimos/0000_Github/RockmagPy-notebooks/example_data/Jackson2012/measurements.txt
-I- Using online data model
-I- Getting method codes from earthref.org
-I- Importing controlled vocabularies from https://earthref.org

specimens.head()

	citations	description	experiments	hyst_bc	hyst_bc_offset	hyst_mr_mass	hyst_ms_mass	hyst_xhf	instrument_codes	meas_orient_phi	...	rem_bcr	rem_hirm_mass	rem_mr_mass	rem_sratio	rem_sratio_back	result_quality	sample	specimen	volume	weight
specimen name
09-27	This study	None	IRM-VSM1-4231	NaN	NaN	NaN	NaN	NaN	IRM-VSM1	0.0	...	0.0448	0.0	0.003193	0.0	0.1	g	09-27	09-27	0.000004	0.00738
09-27	This study	None	IRM-VSM1-4231	0.01059	0.000015	0.003193	0.01086	6.732000e-08	IRM-VSM1	0.0	...	NaN	NaN	NaN	NaN	NaN	g	09-27	09-27	0.000004	0.00738
10-23	This study	None	IRM-VSM1-4232	NaN	NaN	NaN	NaN	NaN	IRM-VSM1	0.0	...	0.0399	0.0	0.004520	0.0	0.1	g	10-23	10-23	0.000004	0.00785
10-23	This study	None	IRM-VSM1-4232	0.00455	0.000046	0.004520	0.02597	-1.511000e-08	IRM-VSM1	0.0	...	NaN	NaN	NaN	NaN	NaN	g	10-23	10-23	0.000004	0.00785
11-29	This study	None	None	NaN	NaN	NaN	NaN	NaN	None	NaN	...	NaN	NaN	NaN	NaN	NaN	None	11-29	11-29	0.000005	0.00901

5 rows × 23 columns

Make Day Plot

Option 1: filter for individual specimen data and make a Day Plot

• One has more flexibility to make a custom plot

• However, the user has to specify the row numbers that contain each of the attributes

specimen_name = '09-27'
example_specimen_data = specimens[specimens['specimen'] == specimen_name].reset_index()
example_specimen_data

	specimen name	citations	description	experiments	hyst_bc	hyst_bc_offset	hyst_mr_mass	hyst_ms_mass	hyst_xhf	instrument_codes	...	rem_bcr	rem_hirm_mass	rem_mr_mass	rem_sratio	rem_sratio_back	result_quality	sample	specimen	volume	weight
0	09-27	This study	None	IRM-VSM1-4231	NaN	NaN	NaN	NaN	NaN	IRM-VSM1	...	0.0448	0.0	0.003193	0.0	0.1	g	09-27	09-27	0.000004	0.00738
1	09-27	This study	None	IRM-VSM1-4231	0.01059	0.000015	0.003193	0.01086	6.732000e-08	IRM-VSM1	...	NaN	NaN	NaN	NaN	NaN	g	09-27	09-27	0.000004	0.00738

2 rows × 24 columns

ax = rmag.day_plot(Mr = example_specimen_data['hyst_mr_mass'][1], 
                   Ms = example_specimen_data['hyst_ms_mass'][1],
                   Bcr = example_specimen_data['rem_bcr'][0],
                   Bc = example_specimen_data['hyst_bc'][1], 
                   color = 'red', 
                   marker = 'o', 
                   label = specimen_name, 
                   alpha=1, 
                   lc = 'black')

plt.show()

Option 2: Plot all specimen data in a MagIC specimens data table on a Day Plot

• Because Bcr is obtained from a backfield experiment whereas other values can be obtained from a hysteresis experiment, the data entry in the data tables are decoupled. In many cases there could be multiple entries for the same attribute for the same specimen.

• If one were to use the default approach to plot all data at once, bear in mind that the default function will simply take the average of all of the entries for the same attribute for the same specimen.

H_specimens = specimens[specimens['specimen'].str.contains('H')].reset_index()

# let's filter for the room temperature measurements
H_specimens = H_specimens[H_specimens['meas_temp'] == 300].reset_index()
H_specimens_RT = H_specimens[H_specimens['meas_temp'] == 300].reset_index()
H_specimens_RT.head()

	level_0	index	specimen name	citations	description	experiments	hyst_bc	hyst_bc_offset	hyst_mr_mass	hyst_ms_mass	...	rem_bcr	rem_hirm_mass	rem_mr_mass	rem_sratio	rem_sratio_back	result_quality	sample	specimen	volume	weight
0	0	2	H1-0.2C	This study	None	IRM-VSM3-66769	0.004854	-0.003742	0.000034	0.000189	...	NaN	NaN	NaN	NaN	NaN	g	H1-0.2	H1-0.2C	1.300000e-06	0.004169
1	1	6	H1-0.4D	This study	None	IRM-VSM3-66771	NaN	NaN	NaN	NaN	...	0.0320	0.000003	0.000052	0.764	0.1	g	H1-0.4	H1-0.4D	9.000000e-07	0.004291
2	2	7	H1-0.4D	This study	average of 10 runs	IRM-VSM3-66770	0.005400	-0.001158	0.000052	0.000298	...	NaN	NaN	NaN	NaN	NaN	g	H1-0.4	H1-0.4D	9.000000e-07	0.004291
3	3	9	H1-0.5B	This study	None	IRM-VSM3-66773	NaN	NaN	NaN	NaN	...	0.0368	0.000001	0.000061	0.673	0.1	g	H1-0.5	H1-0.5B	2.700000e-06	0.010243
4	4	10	H1-0.5B	This study	None	IRM-VSM3-66772	0.006065	0.000918	0.000065	0.000316	...	NaN	NaN	NaN	NaN	NaN	g	H1-0.5	H1-0.5B	2.700000e-06	0.010243

5 rows × 26 columns

ax=rmag.day_plot_MagIC(H_specimens_RT,
               by='specimen',
               Mr='hyst_mr_mass', 
               Ms='hyst_ms_mass', 
               Bcr='rem_bcr', 
               Bc='hyst_bc', 
               color = 'dodgerblue', 
               marker = 'o', 
               label = 'Jackson 2012 carbonates', 
               alpha=1, 
               lc = 'black')

Make squareness-coercivity diagram

ax = rmag.neel_plot_magic(H_specimens_RT,
            by='specimen',
            Mr='hyst_mr_mass', 
            Ms='hyst_ms_mass', 
            Bcr='rem_bcr', 
            Bc='hyst_bc', 
            color = 'dodgerblue', 
            marker = 'o', 
            label = 'Jackson 2012 carbonates', 
            alpha=1, 
            lc = 'black')
ax.set_xlim(0, 0.01)
ax.set_ylim(0, 0.4)
plt.show()