QDM magnetic microscopy dataset of a speleothem from Morocco

High-resolution magnetic map of a stalagmite sample from Wintimdouine Cave, Morocco, created using Quantum Diamond Microscope (QDM) measurements at Harvard University. The data were collected to explore the magnetic remanence properties of hematite and magnetite within the sample, providing insight into past geomagnetic field variations recorded in cave deposits.

Original source: Carmo, Janine; Fu, Roger; Trindade, Ricardo; Piascik, Samuel (2023). QDM magnetic microscopy dataset of a speleothem from Morocco. figshare. Dataset. 10.6084/m9.figshare.22965200.v1

Pre-processing: Source code for preparation of the original dataset for redistribution in Ensaio

import matplotlib.pyplot as plt
import xarray as xr

import ensaio

Download and cache the data and return the path to it on disk. We’ll use the netCDF version because it’s smaller and can be loaded with xarray easily.

fname = ensaio.fetch_morroco_speleothem_qdm(version=1, file_format="netcdf")
print(fname)

/home/runner/work/_temp/cache/ensaio/v1/morroco-speleothem-qdm.nc

Load the netCDF grid with xarray

data = xr.load_dataarray(fname)
data

<xarray.DataArray 'bz' (y: 600, x: 960)> Size: 2MB
array([[ 352.40588  ,   94.89138  ,   41.619244 , ...,  470.18835  ,
         129.20056  ,   18.50121  ],
       [ 525.0481   ,  624.8466   ,   53.45418  , ...,  450.42517  ,
         240.12456  ,  -73.61368  ],
       [ 105.09393  ,  638.7656   ,  307.60736  , ...,  236.91327  ,
         386.84982  ,  -86.442154 ],
       ...,
       [ -83.74368  ,   32.98078  , -411.75073  , ...,  745.9937   ,
        1036.2003   , -140.64317  ],
       [ 171.17114  , -214.47801  ,  159.23438  , ...,  124.58138  ,
         258.5433   ,  -90.33769  ],
       [  80.609505 ,  273.08368  ,  118.23499  , ...,   -4.1957254,
         -53.55728  ,    2.1033592]], shape=(600, 960), dtype=float32)
Coordinates:
  * x        (x) float64 8kB 0.0 2.35 4.7 7.05 ... 2.249e+03 2.251e+03 2.254e+03
  * y        (y) float64 5kB 0.0 2.35 4.7 7.05 ... 1.403e+03 1.405e+03 1.408e+03
    z        (y, x) float32 2MB 5.0 5.0 5.0 5.0 5.0 5.0 ... 5.0 5.0 5.0 5.0 5.0
Attributes:
    Conventions:   CF-1.8
    title:         QDM magnetic microscopy dataset of a speleothem from Morocco
    source:        Measured on a Quantum Diamond Microscope (QDM) at Harvard ...
    license:       CC0 1.0 Universal
    references:    Carmo, Janine; Fu, Roger; Trindade, Ricardo; Piascik, Samu...
    long_name:     vertical magnetic field
    units:         nT
    actual_range:  [-236933.  301265.]

xarray.DataArray

'bz'

• y: 600
• x: 960

• 352.4 94.89 41.62 288.4 404.5 ... 101.0 -186.6 -4.196 -53.56 2.103

  array([[ 352.40588  ,   94.89138  ,   41.619244 , ...,  470.18835  ,
           129.20056  ,   18.50121  ],
         [ 525.0481   ,  624.8466   ,   53.45418  , ...,  450.42517  ,
           240.12456  ,  -73.61368  ],
         [ 105.09393  ,  638.7656   ,  307.60736  , ...,  236.91327  ,
           386.84982  ,  -86.442154 ],
         ...,
         [ -83.74368  ,   32.98078  , -411.75073  , ...,  745.9937   ,
          1036.2003   , -140.64317  ],
         [ 171.17114  , -214.47801  ,  159.23438  , ...,  124.58138  ,
           258.5433   ,  -90.33769  ],
         [  80.609505 ,  273.08368  ,  118.23499  , ...,   -4.1957254,
           -53.55728  ,    2.1033592]], shape=(600, 960), dtype=float32)

• Coordinates: (3)
  • x
    (x)
    float64
    0.0 2.35 ... 2.251e+03 2.254e+03

    units :

    µm

    array([   0.  ,    2.35,    4.7 , ..., 2248.95, 2251.3 , 2253.65], shape=(960,))

  • y
    (y)
    float64
    0.0 2.35 ... 1.405e+03 1.408e+03

    units :

    µm

    array([   0.  ,    2.35,    4.7 , ..., 1402.95, 1405.3 , 1407.65], shape=(600,))

  • z
    (y, x)
    float32
    5.0 5.0 5.0 5.0 ... 5.0 5.0 5.0 5.0

    long_name :

    sensor sample distance

    units :

    µm

    array([[5., 5., 5., ..., 5., 5., 5.],
           [5., 5., 5., ..., 5., 5., 5.],
           [5., 5., 5., ..., 5., 5., 5.],
           ...,
           [5., 5., 5., ..., 5., 5., 5.],
           [5., 5., 5., ..., 5., 5., 5.],
           [5., 5., 5., ..., 5., 5., 5.]], shape=(600, 960), dtype=float32)

• Indexes: (2)
  • x
    PandasIndex

    PandasIndex(Index([               0.0,               2.35,                4.7,
            7.050000000000001,                9.4,              11.75,
           14.100000000000001,              16.45,               18.8,
           21.150000000000002,
           ...
                       2232.5,            2234.85, 2237.2000000000003,
                      2239.55,             2241.9,            2244.25,
                       2246.6, 2248.9500000000003,             2251.3,
                      2253.65],
          dtype='float64', name='x', length=960))

  • y
    PandasIndex

    PandasIndex(Index([               0.0,               2.35,                4.7,
            7.050000000000001,                9.4,              11.75,
           14.100000000000001,              16.45,               18.8,
           21.150000000000002,
           ...
                       1386.5, 1388.8500000000001,             1391.2,
                      1393.55,             1395.9,            1398.25,
           1400.6000000000001,            1402.95,             1405.3,
                      1407.65],
          dtype='float64', name='y', length=600))

• Attributes: (8)

  Conventions :

  CF-1.8

  title :

  QDM magnetic microscopy dataset of a speleothem from Morocco

  source :

  Measured on a Quantum Diamond Microscope (QDM) at Harvard University, using a stalagmite from Wintimdouine cave (Morroco).

  license :

  CC0 1.0 Universal

  references :

  Carmo, Janine; Fu, Roger; Trindade, Ricardo; Piascik, Samuel (2023). QDM magnetic microscopy dataset of a speleothem from Morocco. figshare. Dataset. https://doi.org/10.6084/m9.figshare.22965200.v1

  long_name :

  vertical magnetic field

  units :

  nT

  actual_range :

  [-236933. 301265.]

Make a pseudo-color map of the magnetic microscopy data and adjust the scale because of some very strong sources.

fig, ax = plt.subplots(1, 1, figsize=(9, 4.8), layout="constrained")
scale = 2500
data.plot.imshow(ax=ax, cmap="RdBu_r", vmin=-scale, vmax=scale)
ax.set_aspect("equal")
plt.show()