!pip install pandas matplotlib zarr fsspec s3fs intake intake_xarray intake_parquet

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import intake
import matplotlib.pyplot as plt

plt.rcParams["font.family"] = "sans"
plt.rcParams["font.size"] = 8

First let’s take a look at the top level shots. In this table we can find all of the metadata we have about particular shots.

catalog  = intake.open_catalog('https://mastapp.site/intake/catalog.yml')
shots_df = catalog.index.level1.shots().read()
shots_df

	url	preshot_description	postshot_description	campaign	current_range	divertor_config	plasma_shape	comissioner	facility	shot_id	...	cpf_vol_ipmax	cpf_vol_max	cpf_vol_truby	cpf_wmhd_ipmax	cpf_wmhd_max	cpf_wmhd_truby	cpf_zeff_ipmax	cpf_zeff_max	cpf_zeff_truby	cpf_zmag_efit
0	s3://mast/level1/shots/11695.zarr	\n0.1T TF SHOT\n	\nOK\n	M5	None	Conventional	None	None	MAST	11695	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	s3://mast/level1/shots/11696.zarr	\nSTANDARD 0.3T TF SHOT\n	\nOK\n	M5	None	Conventional	None	None	MAST	11696	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	s3://mast/level1/shots/11697.zarr	\nRAISE TO 0.5T\n	\nOK, ALARMS ARE LOWER\n	M5	None	Conventional	None	None	MAST	11697	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	s3://mast/level1/shots/11698.zarr	\nRAISE TO .56T\n	\nSTILL ALARMS BUT LOWER AGAIN\n	M5	None	Conventional	None	None	MAST	11698	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	s3://mast/level1/shots/11699.zarr	\nRAISE TO .58T\n	\nOK\n	M5	None	Conventional	None	None	MAST	11699	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
15916	s3://mast/level1/shots/30467.zarr	\nRepeat with new neutron camera position.\ncH...	\nTwo times lower DD neutron rate than referen...	M9	700 kA	Conventional	Connected Double Null	None	MAST	30467	...	9.029202	9.046394	0.0	49469.122469	52653.445	0.0	NaN	NaN	NaN	0.013202
15917	s3://mast/level1/shots/30468.zarr	\nRepeat with new neutron camera position.\ncH...	\nGood beam.\nGood repeat.\n	M9	700 kA	Conventional	Lower Single Null	None	MAST	30468	...	9.102411	9.107017	0.0	48516.962675	49382.133	0.0	NaN	NaN	NaN	0.012445
15918	s3://mast/level1/shots/30469.zarr	\nRepeat with increased beam power (74 kV)\ncH...	\nGood shot. Modes present.\n	M9	700 kA	Conventional	Connected Double Null	None	MAST	30469	...	8.988730	9.047923	0.0	47466.249616	49115.805	0.0	NaN	NaN	NaN	0.015299
15919	s3://mast/level1/shots/30470.zarr	\nRepeat last using hydrogen in outboard and c...	\nNo HF gas.\n	M9	700 kA	Conventional	None	None	MAST	30470	...	9.687049	10.055509	0.0	17290.432865	22310.516	0.0	NaN	NaN	NaN	0.015164
15920	s3://mast/level1/shots/30471.zarr	\nThe last plasma:\nConvert to i/b Helios 1724...	\nGood shot.\n	M9	700 kA	Conventional	Lower Single Null	None	MAST	30471	...	8.817559	9.283702	0.0	38063.582380	40906.090	0.0	NaN	NaN	NaN	0.014340

15921 rows × 283 columns

Thomson Scattering Data

This notebook contains some examples of loading and plotting Thomson scattering data.

First we can have a look at how many thompson scattering sources are in the database:

catalog  = intake.open_catalog('https://mastapp.site/intake/catalog.yml')
sources_df = catalog.index.level1.sources().read()

# Can also use name == 'aye' for thompson scattering edge data.
sources_df = sources_df.loc[(sources_df.name == 'ayc')]
sources_df

	description	quality	uuid	shot_id	name	url
163486	Core Thomson scattering data	Not Checked	a61fdefa-e7e9-57df-a7f3-a341f737bcdd	23001	ayc	s3://mast/level1/shots/23001.zarr/ayc
163689	Core Thomson scattering data	Not Checked	a654a084-97f5-52f5-99d6-4e726880b39a	23018	ayc	s3://mast/level1/shots/23018.zarr/ayc
164159	Core Thomson scattering data	Not Checked	3cca7bc2-9c91-5bd9-a1cd-939142a84cd2	23133	ayc	s3://mast/level1/shots/23133.zarr/ayc
164189	Core Thomson scattering data	Not Checked	6fd9ab2f-ca5f-57a2-ba81-589cf6efe7d5	23135	ayc	s3://mast/level1/shots/23135.zarr/ayc
164204	Core Thomson scattering data	Not Checked	5334374c-8f9a-5437-aa56-822448ea5d27	23136	ayc	s3://mast/level1/shots/23136.zarr/ayc
...	...	...	...	...	...	...
307980	Core Thomson scattering data	Not Checked	1d345219-99c7-5725-9d65-2c9d455b629c	30467	ayc	s3://mast/level1/shots/30467.zarr/ayc
308015	Core Thomson scattering data	Not Checked	9ac2f540-8845-5c5a-8932-7634b7834d40	30468	ayc	s3://mast/level1/shots/30468.zarr/ayc
308050	Core Thomson scattering data	Not Checked	d07dc339-1510-525c-9fa9-015900101656	30469	ayc	s3://mast/level1/shots/30469.zarr/ayc
308085	Core Thomson scattering data	Not Checked	fa9b2d5d-348b-5e00-a4d5-fc5e39d75452	30470	ayc	s3://mast/level1/shots/30470.zarr/ayc
308120	Core Thomson scattering data	Not Checked	113ec983-6e14-5e41-8111-aadb0f744471	30471	ayc	s3://mast/level1/shots/30471.zarr/ayc

4665 rows × 6 columns

Let’s look at the data for a particular shot. Here we are going to use shot 30420 as an example. Below we get the url for the ayc data.

shot_id = 30420
url = sources_df.loc[sources_df.shot_id == shot_id].iloc[0].url
url

's3://mast/level1/shots/30420.zarr/ayc'

Thomson Scattering Data

ayc source holds the Thomson Scattering data at the core. Thomson scattering diagnostics provide accurate measurements of electron temperature and density.

dataset = catalog.level1.sources(url=url)
dataset = dataset.to_dask()

dataset

<xarray.Dataset>
Dimensions:              (acqiris_time: 73, radial_index: 131, arb: 130,
                          time: 73, spectral_index: 4, instrument_time: 20,
                          time_segment: 73, xyc_time: 73)
Coordinates:
  * acqiris_time         (acqiris_time) float32 0.0 1.0 2.0 ... 70.0 71.0 72.0
  * arb                  (arb) float32 0.0 1.0 2.0 3.0 ... 127.0 128.0 129.0
  * instrument_time      (instrument_time) float32 1.0 2.0 3.0 ... 19.0 20.0
  * radial_index         (radial_index) float32 0.0 1.0 2.0 ... 129.0 130.0
  * spectral_index       (spectral_index) float32 1.0 2.0 3.0 4.0
  * time                 (time) float32 0.004166 0.008332 0.0125 ... 0.3 0.3042
  * xyc_time             (xyc_time) float32 0.0 1.0 2.0 3.0 ... 70.0 71.0 72.0
Dimensions without coordinates: time_segment
Data variables: (12/36)
    acqiris_time_        (acqiris_time) float32 dask.array<chunksize=(73,), meta=np.ndarray>
    angle                (radial_index) float32 dask.array<chunksize=(131,), meta=np.ndarray>
    aspectra             (time, radial_index, spectral_index) float32 dask.array<chunksize=(73, 131, 4), meta=np.ndarray>
    chi2                 (time, radial_index) float32 dask.array<chunksize=(73, 131), meta=np.ndarray>
    covariance_ne_te     (time, radial_index) float32 dask.array<chunksize=(73, 131), meta=np.ndarray>
    instrument_dr        (instrument_time, radial_index) float32 dask.array<chunksize=(20, 131), meta=np.ndarray>
    ...                   ...
    te_error             (time, radial_index) float32 dask.array<chunksize=(73, 131), meta=np.ndarray>
    version_fibre        float32 ...
    version_poly         float32 ...
    version_raman        float32 ...
    xyc_time_            (xyc_time) float32 dask.array<chunksize=(73,), meta=np.ndarray>
    yag_nelint           (time) float32 dask.array<chunksize=(73,), meta=np.ndarray>
Attributes:
    description:  Core Thomson scattering data
    file_name:    ayc0304.20
    format:       IDA3
    mds_name:     None
    name:         ayc
    quality:      Not Checked
    shot_id:      30420
    signal_type:  Analysed
    source:       ayc
    uda_name:     AYC
    uuid:         8d043ece-8bf8-5af8-87e4-d2a1b01716fa
    version:      0

xarray.Dataset

• Dimensions:
  • acqiris_time: 73
  • radial_index: 131
  • arb: 130
  • time: 73
  • spectral_index: 4
  • instrument_time: 20
  • time_segment: 73
  • xyc_time: 73
• Coordinates: (7)
  • acqiris_time
    (acqiris_time)
    float32
    0.0 1.0 2.0 3.0 ... 70.0 71.0 72.0

    units :

    s

    array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
           14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.,
           28., 29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41.,
           42., 43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55.,
           56., 57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69.,
           70., 71., 72.], dtype=float32)

  • arb
    (arb)
    float32
    0.0 1.0 2.0 ... 127.0 128.0 129.0

    units :

    arb

    array([  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,  11.,
            12.,  13.,  14.,  15.,  16.,  17.,  18.,  19.,  20.,  21.,  22.,  23.,
            24.,  25.,  26.,  27.,  28.,  29.,  30.,  31.,  32.,  33.,  34.,  35.,
            36.,  37.,  38.,  39.,  40.,  41.,  42.,  43.,  44.,  45.,  46.,  47.,
            48.,  49.,  50.,  51.,  52.,  53.,  54.,  55.,  56.,  57.,  58.,  59.,
            60.,  61.,  62.,  63.,  64.,  65.,  66.,  67.,  68.,  69.,  70.,  71.,
            72.,  73.,  74.,  75.,  76.,  77.,  78.,  79.,  80.,  81.,  82.,  83.,
            84.,  85.,  86.,  87.,  88.,  89.,  90.,  91.,  92.,  93.,  94.,  95.,
            96.,  97.,  98.,  99., 100., 101., 102., 103., 104., 105., 106., 107.,
           108., 109., 110., 111., 112., 113., 114., 115., 116., 117., 118., 119.,
           120., 121., 122., 123., 124., 125., 126., 127., 128., 129.],
          dtype=float32)

  • instrument_time
    (instrument_time)
    float32
    1.0 2.0 3.0 4.0 ... 18.0 19.0 20.0

    units :

    s

    array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,
           15., 16., 17., 18., 19., 20.], dtype=float32)

  • radial_index
    (radial_index)
    float32
    0.0 1.0 2.0 ... 128.0 129.0 130.0

    units :

    arb

    array([  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,  11.,
            12.,  13.,  14.,  15.,  16.,  17.,  18.,  19.,  20.,  21.,  22.,  23.,
            24.,  25.,  26.,  27.,  28.,  29.,  30.,  31.,  32.,  33.,  34.,  35.,
            36.,  37.,  38.,  39.,  40.,  41.,  42.,  43.,  44.,  45.,  46.,  47.,
            48.,  49.,  50.,  51.,  52.,  53.,  54.,  55.,  56.,  57.,  58.,  59.,
            60.,  61.,  62.,  63.,  64.,  65.,  66.,  67.,  68.,  69.,  70.,  71.,
            72.,  73.,  74.,  75.,  76.,  77.,  78.,  79.,  80.,  81.,  82.,  83.,
            84.,  85.,  86.,  87.,  88.,  89.,  90.,  91.,  92.,  93.,  94.,  95.,
            96.,  97.,  98.,  99., 100., 101., 102., 103., 104., 105., 106., 107.,
           108., 109., 110., 111., 112., 113., 114., 115., 116., 117., 118., 119.,
           120., 121., 122., 123., 124., 125., 126., 127., 128., 129., 130.],
          dtype=float32)

  • spectral_index
    (spectral_index)
    float32
    1.0 2.0 3.0 4.0

    units :

    array([1., 2., 3., 4.], dtype=float32)

  • time
    (time)
    float32
    0.004166 0.008332 ... 0.3 0.3042

    units :

    s

    array([0.004166, 0.008332, 0.012498, 0.016664, 0.02083 , 0.024996, 0.029162,
           0.033333, 0.037499, 0.041665, 0.045831, 0.049998, 0.054163, 0.058329,
           0.062495, 0.066667, 0.070833, 0.074998, 0.079165, 0.083331, 0.087496,
           0.091663, 0.095829, 0.1     , 0.104166, 0.108332, 0.112498, 0.116664,
           0.12083 , 0.124996, 0.129162, 0.133333, 0.137499, 0.141665, 0.145831,
           0.149998, 0.154163, 0.158329, 0.162495, 0.166667, 0.170833, 0.174999,
           0.179165, 0.183331, 0.187496, 0.191663, 0.195829, 0.2     , 0.204166,
           0.208332, 0.212498, 0.216664, 0.22083 , 0.224996, 0.229162, 0.233333,
           0.237499, 0.241665, 0.245831, 0.249998, 0.254163, 0.258329, 0.262495,
           0.266667, 0.270833, 0.274998, 0.279165, 0.283331, 0.287496, 0.291663,
           0.295829, 0.3     , 0.304166], dtype=float32)

  • xyc_time
    (xyc_time)
    float32
    0.0 1.0 2.0 3.0 ... 70.0 71.0 72.0

    units :

    s

    array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13.,
           14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.,
           28., 29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41.,
           42., 43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55.,
           56., 57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69.,
           70., 71., 72.], dtype=float32)

• Data variables: (36)
  • acqiris_time_
    (acqiris_time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['acqiris_time']

    file_name :

    None

    format :

    None

    label :

    time

    mds_name :

    \TOP.ANALYSED.AYC:ACQIRIS_TIME

    name :

    ayc/acqiris_time_

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_ACQIRIS_TIME

    units :

    s

    uuid :

    424fbc4e-f837-5997-b90d-27da7842ee34

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • angle
    (radial_index)
    float32
    dask.array<chunksize=(131,), meta=np.ndarray>

    description :

    dims :

    ['radial_index']

    file_name :

    None

    format :

    None

    label :

    scattering angle

    mds_name :

    \TOP.ANALYSED.AYC:ANGLE

    name :

    ayc/angle

    quality :

    Not Checked

    rank :

    2

    shape :

    [1, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_ANGLE

    units :

    uuid :

    9b6b5033-9c0b-53c6-b940-c4bc29e02421

    version :

    0

    Array Chunk Bytes 524 B 524 B Shape (131,) (131,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • aspectra
    (time, radial_index, spectral_index)
    float32
    dask.array<chunksize=(73, 131, 4), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index', 'spectral_index']

    file_name :

    None

    format :

    None

    label :

    Fitted spectra

    mds_name :

    \TOP.ANALYSED.AYC:ASPECTRA

    name :

    ayc/aspectra

    quality :

    Not Checked

    rank :

    3

    shape :

    [73, 130, 4]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_ASPECTRA

    units :

    V

    uuid :

    94fe4ec9-cd29-5fd5-b2e5-f5da3c3b2834

    version :

    0

    Array Chunk Bytes 149.42 kiB 149.42 kiB Shape (73, 131, 4) (73, 131, 4) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • chi2
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    fit chi^2 error

    mds_name :

    \TOP.ANALYSED.AYC:CHI2

    name :

    ayc/chi2

    quality :

    Not Checked

    rank :

    2

    shape :

    [73, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_CHI2

    units :

    uuid :

    5a43a5f1-e090-5e06-b441-658878563a88

    version :

    0

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • covariance_ne_te
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    fit covariance of ne Te

    mds_name :

    \TOP.ANALYSED.AYC.COVARIANCE:NE_TE

    name :

    ayc/covariance_ne_te

    quality :

    Not Checked

    rank :

    2

    shape :

    [73, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_COVARIANCE_NE_TE

    units :

    eV / m ** 3

    uuid :

    6c4c38dd-f19c-5af2-9254-334abf13f088

    version :

    0

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • instrument_dr
    (instrument_time, radial_index)
    float32
    dask.array<chunksize=(20, 131), meta=np.ndarray>

    description :

    dims :

    ['instrument_time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    instrument_dr

    mds_name :

    \TOP.ANALYSED.AYC.INSTRUMENT:DR

    name :

    ayc/instrument_dr

    quality :

    Not Checked

    rank :

    2

    shape :

    [20, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_INSTRUMENT_DR

    units :

    m

    uuid :

    aac29b54-4567-5a77-beae-c12bd3317588

    version :

    0

    Array Chunk Bytes 10.23 kiB 10.23 kiB Shape (20, 131) (20, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • interferometer_corr
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    Interferometer Correctio

    mds_name :

    \TOP.ANALYSED.AYC.TERFEROMETER:CORR

    name :

    ayc/interferometer_corr

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_INTERFEROMETER_CORR

    units :

    -

    uuid :

    f0b399ed-75aa-5443-9243-313f2293bd3e

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • laser_energy
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    laser energy

    mds_name :

    \TOP.ANALYSED.AYC:LASER_ENERGY

    name :

    ayc/laser_energy

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_LASER_ENERGY

    units :

    J

    uuid :

    b90679b3-0109-59fc-9e67-3f78444cb09c

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • laser_track
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    laser number

    mds_name :

    \TOP.ANALYSED.AYC:LASER_TRACK

    name :

    ayc/laser_track

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_LASER_TRACK

    units :

    uuid :

    cede67e8-3fef-5085-a585-2de2089c57e6

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • ne
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    description :

    Electron Density

    dims :

    ['time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    electron density

    mds_name :

    \TOP.ANALYSED.AYC:NE

    name :

    ayc/ne

    quality :

    Not Checked

    rank :

    2

    shape :

    [73, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_NE

    units :

    1 / m ** 3

    uuid :

    0141808d-ccda-5bce-917c-2eebd553f22f

    version :

    0

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • ne_core
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    Peak electron density (t)

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    core density

    mds_name :

    \TOP.ANALYSED.AYC:NE_CORE

    name :

    ayc/ne_core

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_NE_CORE

    units :

    1 / m ** 3

    uuid :

    3a040ddc-6f6f-55ae-ad2e-b0e9489701e1

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • ne_error
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    units :

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • passnumber
    ()
    float32
    ...

    description :

    dims :

    []

    file_name :

    None

    format :

    None

    label :

    mds_name :

    \TOP.ANALYSED.AYC:PASSNUMBER

    name :

    ayc/passnumber

    quality :

    Not Checked

    rank :

    1

    shape :

    [1]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_PASSNUMBER

    units :

    uuid :

    476690c4-d531-5a96-924c-d2aa75fd8b7c

    version :

    0

    [1 values with dtype=float32]

  • pe
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    description :

    Electron Pressure

    dims :

    ['time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    electron pressure

    mds_name :

    \TOP.ANALYSED.AYC:PE

    name :

    ayc/pe

    quality :

    Not Checked

    rank :

    2

    shape :

    [73, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_PE

    units :

    uuid :

    d724d9a7-97ad-59c5-99bd-00f2de46ddf1

    version :

    0

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • pe_error
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    units :

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • plasmalight_error
    (time, radial_index, spectral_index)
    float32
    dask.array<chunksize=(73, 131, 4), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index', 'spectral_index']

    file_name :

    None

    format :

    None

    label :

    Plasma light noise on sc

    mds_name :

    \TOP.ANALYSED.AYC.PLASMALIGHT:ERROR

    name :

    ayc/plasmalight_error

    quality :

    Not Checked

    rank :

    3

    shape :

    [73, 130, 4]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_PLASMALIGHT_ERROR

    units :

    V

    uuid :

    0d5b9970-df99-5547-9384-7e0a5eac6b20

    version :

    0

    Array Chunk Bytes 149.42 kiB 149.42 kiB Shape (73, 131, 4) (73, 131, 4) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • poisson_error
    (time, radial_index, spectral_index)
    float32
    dask.array<chunksize=(73, 131, 4), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index', 'spectral_index']

    file_name :

    None

    format :

    None

    label :

    Poisson error on scatter

    mds_name :

    \TOP.ANALYSED.AYC.POISSON:ERROR

    name :

    ayc/poisson_error

    quality :

    Not Checked

    rank :

    3

    shape :

    [73, 130, 4]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_POISSON_ERROR

    units :

    V

    uuid :

    f33b5dab-f048-51e9-bc27-8ae83ace825d

    version :

    0

    Array Chunk Bytes 149.42 kiB 149.42 kiB Shape (73, 131, 4) (73, 131, 4) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • polyname
    (arb)
    float32
    dask.array<chunksize=(130,), meta=np.ndarray>

    description :

    dims :

    ['arb']

    file_name :

    None

    format :

    None

    label :

    polychromator

    mds_name :

    \TOP.ANALYSED.AYC:POLYNAME

    name :

    ayc/polyname

    quality :

    Not Checked

    rank :

    2

    shape :

    [1, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_POLYNAME

    units :

    uuid :

    24a481c8-739e-54fd-ab1d-b2044b1e1679

    version :

    0

    Array Chunk Bytes 520 B 520 B Shape (130,) (130,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • pulse
    (arb)
    float32
    dask.array<chunksize=(130,), meta=np.ndarray>

    description :

    dims :

    ['arb']

    file_name :

    None

    format :

    None

    label :

    pulse

    mds_name :

    name :

    ayc/pulse

    quality :

    Not Checked

    rank :

    2

    shape :

    [1, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_PULSE

    units :

    uuid :

    5986d498-7a4f-56fd-9c1d-bd1f7fce9792

    version :

    0

    Array Chunk Bytes 520 B 520 B Shape (130,) (130,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • r_core
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    Peak position (t)

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    core radius

    mds_name :

    \TOP.ANALYSED.AYC:R_CORE

    name :

    ayc/r_core

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_R_CORE

    units :

    m

    uuid :

    aab4d505-2c5d-5425-9be8-811d64a8cfe7

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • r_error
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    units :

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • radius
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    description :

    Radial basis (x,t)

    dims :

    ['time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    major radius

    mds_name :

    \TOP.ANALYSED.AYC:R

    name :

    ayc/r

    quality :

    Not Checked

    rank :

    2

    shape :

    [73, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_R

    units :

    m

    uuid :

    30d2c0c2-39ee-5a8e-a321-9d87ace7b5b9

    version :

    0

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • scat_length
    (arb)
    float32
    dask.array<chunksize=(130,), meta=np.ndarray>

    description :

    dims :

    ['arb']

    file_name :

    None

    format :

    None

    label :

    scattering length

    mds_name :

    \TOP.ANALYSED.AYC:SCAT_LENGTH

    name :

    ayc/scat_length

    quality :

    Not Checked

    rank :

    2

    shape :

    [1, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_SCAT_LENGTH

    units :

    m

    uuid :

    3edcd54b-335d-56f6-b942-89cd09684d14

    version :

    0

    Array Chunk Bytes 520 B 520 B Shape (130,) (130,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • segment_number
    (time_segment)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['time_segment']

    file_name :

    None

    format :

    None

    label :

    segment number

    mds_name :

    \TOP.ANALYSED.AYC.SEGMENT:NUMBER

    name :

    ayc/segment_number

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_SEGMENT_NUMBER

    units :

    uuid :

    92c061ca-16ef-5736-a5e2-943f19dce455

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • spectra
    (time, radial_index, spectral_index)
    float32
    dask.array<chunksize=(73, 131, 4), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index', 'spectral_index']

    file_name :

    None

    format :

    None

    label :

    Raw spectra

    mds_name :

    \TOP.ANALYSED.AYC:SPECTRA

    name :

    ayc/spectra

    quality :

    Not Checked

    rank :

    3

    shape :

    [73, 130, 4]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_SPECTRA

    units :

    V

    uuid :

    f496ab0c-babf-5b4e-a328-82800dc62550

    version :

    0

    Array Chunk Bytes 149.42 kiB 149.42 kiB Shape (73, 131, 4) (73, 131, 4) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • spectra_error
    (time, radial_index, spectral_index)
    float32
    dask.array<chunksize=(73, 131, 4), meta=np.ndarray>

    units :

    Array Chunk Bytes 149.42 kiB 149.42 kiB Shape (73, 131, 4) (73, 131, 4) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • spectra_stray_light
    (time, radial_index, spectral_index)
    float32
    dask.array<chunksize=(73, 131, 4), meta=np.ndarray>

    description :

    dims :

    ['time', 'radial_index', 'spectral_index']

    file_name :

    None

    format :

    None

    label :

    Raw spectra

    mds_name :

    \TOP.ANALYSED.AYC.SPECTRA_:STRAY_LIGHT

    name :

    ayc/spectra_stray_light

    quality :

    Not Checked

    rank :

    3

    shape :

    [73, 130, 4]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_SPECTRA_STRAY_LIGHT

    units :

    V

    uuid :

    0cdfb1e6-1318-57c6-8947-2840b427b683

    version :

    0

    Array Chunk Bytes 149.42 kiB 149.42 kiB Shape (73, 131, 4) (73, 131, 4) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • status
    ()
    float32
    ...

    description :

    dims :

    []

    file_name :

    None

    format :

    None

    label :

    mds_name :

    \TOP.ANALYSED.AYC:STATUS

    name :

    ayc/status

    quality :

    Not Checked

    rank :

    1

    shape :

    [1]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_STATUS

    units :

    uuid :

    fc60b479-2d9a-56d3-a028-723152f978c9

    version :

    0

    [1 values with dtype=float32]

  • te
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    description :

    Electron Temperature

    dims :

    ['time', 'radial_index']

    file_name :

    None

    format :

    None

    label :

    electron temperature

    mds_name :

    \TOP.ANALYSED.AYC:TE

    name :

    ayc/te

    quality :

    Not Checked

    rank :

    2

    shape :

    [73, 130]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_TE

    units :

    eV

    uuid :

    54a16683-8517-5f0e-a242-f36d4fbfb9ba

    version :

    0

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • te_core
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    Peak electron temperature (t)

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    core temperature

    mds_name :

    \TOP.ANALYSED.AYC:TE_CORE

    name :

    ayc/te_core

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_TE_CORE

    units :

    eV

    uuid :

    f5ebb5d8-f799-5a58-816e-613ef60f6e44

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • te_error
    (time, radial_index)
    float32
    dask.array<chunksize=(73, 131), meta=np.ndarray>

    units :

    Array Chunk Bytes 37.36 kiB 37.36 kiB Shape (73, 131) (73, 131) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • version_fibre
    ()
    float32
    ...

    description :

    dims :

    []

    file_name :

    None

    format :

    None

    label :

    mds_name :

    \TOP.ANALYSED.AYC.VERSION:FIBRE

    name :

    ayc/version_fibre

    quality :

    Not Checked

    rank :

    1

    shape :

    [1]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_VERSION_FIBRE

    units :

    uuid :

    d3fc997f-62ab-5f15-8bc9-5968427f3fd7

    version :

    0

    [1 values with dtype=float32]

  • version_poly
    ()
    float32
    ...

    description :

    dims :

    []

    file_name :

    None

    format :

    None

    label :

    mds_name :

    \TOP.ANALYSED.AYC:VERSION_POLY

    name :

    ayc/version_poly

    quality :

    Not Checked

    rank :

    1

    shape :

    [1]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_VERSION_POLY

    units :

    uuid :

    9c215e48-c155-5343-8c29-a4b8d67f4a22

    version :

    0

    [1 values with dtype=float32]

  • version_raman
    ()
    float32
    ...

    description :

    dims :

    []

    file_name :

    None

    format :

    None

    label :

    mds_name :

    \TOP.ANALYSED.AYC.VERSION:RAMAN

    name :

    ayc/version_raman

    quality :

    Not Checked

    rank :

    1

    shape :

    [1]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_VERSION_RAMAN

    units :

    uuid :

    d371ccf9-2582-5f6b-81f6-3d6419e874ca

    version :

    0

    [1 values with dtype=float32]

  • xyc_time_
    (xyc_time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['xyc_time']

    file_name :

    None

    format :

    None

    label :

    xyc_time

    mds_name :

    \TOP.ANALYSED.AYC:XYC_TIME

    name :

    ayc/xyc_time_

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_XYC_TIME

    units :

    s

    uuid :

    8eebc9a7-a49b-57cd-8d1d-b94b6d98f329

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

  • yag_nelint
    (time)
    float32
    dask.array<chunksize=(73,), meta=np.ndarray>

    description :

    dims :

    ['time']

    file_name :

    None

    format :

    None

    label :

    yag line integral densit

    mds_name :

    \TOP.ANALYSED.AYC:YAG_NELINT

    name :

    ayc/yag_nelint

    quality :

    Not Checked

    rank :

    1

    shape :

    [73]

    shot_id :

    30420

    signal_type :

    Analysed

    source :

    ayc

    time_index :

    0

    uda_name :

    AYC_YAG_NELINT

    units :

    e- / m2

    uuid :

    b82681c6-08c5-5207-9343-9215a65b270f

    version :

    0

    Array Chunk Bytes 292 B 292 B Shape (73,) (73,) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray

• Indexes: (7)
  • acqiris_time
    PandasIndex

    PandasIndex(Index([ 0.0,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
           12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
           24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0,
           36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0,
           48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0,
           60.0, 61.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0,
           72.0],
          dtype='float32', name='acqiris_time'))

  • arb
    PandasIndex

    PandasIndex(Index([  0.0,   1.0,   2.0,   3.0,   4.0,   5.0,   6.0,   7.0,   8.0,   9.0,
           ...
           120.0, 121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0, 128.0, 129.0],
          dtype='float32', name='arb', length=130))

  • instrument_time
    PandasIndex

    PandasIndex(Index([ 1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0, 12.0,
           13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0],
          dtype='float32', name='instrument_time'))

  • radial_index
    PandasIndex

    PandasIndex(Index([  0.0,   1.0,   2.0,   3.0,   4.0,   5.0,   6.0,   7.0,   8.0,   9.0,
           ...
           121.0, 122.0, 123.0, 124.0, 125.0, 126.0, 127.0, 128.0, 129.0, 130.0],
          dtype='float32', name='radial_index', length=131))

  • spectral_index
    PandasIndex

    PandasIndex(Index([1.0, 2.0, 3.0, 4.0], dtype='float32', name='spectral_index'))

  • time
    PandasIndex

    PandasIndex(Index([0.004166000057011843, 0.008331900462508202,   0.0124981002882123,
           0.016664499416947365,  0.02082959935069084, 0.024995999410748482,
           0.029162200167775154,  0.03333339840173721,  0.03749940171837807,
           0.041665200144052505,  0.04583140090107918,  0.04999779909849167,
            0.05416300147771835, 0.058329299092292786,  0.06249549984931946,
            0.06666669994592667,  0.07083269953727722,  0.07499849796295166,
            0.07916469871997833,  0.08333110064268112,   0.0874963030219078,
               0.09166269749403,  0.09582880139350891,  0.10000000149011612,
            0.10416600108146667,  0.10833189636468887,  0.11249800026416779,
            0.11666440218687057,  0.12082959711551666,  0.12499599903821945,
            0.12916210293769836,  0.13333329558372498,  0.13749930262565613,
            0.14166520535945892,  0.14583130180835724,   0.1499978005886078,
            0.15416289865970612,   0.1583292931318283,  0.16249549388885498,
            0.16666670143604279,  0.17083260416984558,  0.17499850690364838,
            0.17916469275951385,  0.18333110213279724,  0.18749630451202393,
            0.19166259467601776,  0.19582879543304443,  0.20000000298023224,
             0.2041659951210022,  0.20833179354667664,   0.2124979943037033,
             0.2166644036769867,  0.22082960605621338,  0.22499600052833557,
             0.2291620969772339,   0.2333333045244217,  0.23749929666519165,
            0.24166519939899445,  0.24583129584789276,  0.24999770522117615,
            0.25416290760040283,    0.258329302072525,  0.26249539852142334,
            0.26666659116744995,   0.2708325982093811,   0.2749984860420227,
             0.2791646122932434,  0.28333109617233276,   0.2874962091445923,
             0.2916626036167145,  0.29582878947257996,   0.2999998927116394,
            0.30416589975357056],
          dtype='float32', name='time'))

  • xyc_time
    PandasIndex

    PandasIndex(Index([ 0.0,  1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0,
           12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0,
           24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0,
           36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0,
           48.0, 49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0,
           60.0, 61.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0,
           72.0],
          dtype='float32', name='xyc_time'))

• Attributes: (12)

  description :

  Core Thomson scattering data

  file_name :

  ayc0304.20

  format :

  IDA3

  mds_name :

  None

  name :

  ayc

  quality :

  Not Checked

  shot_id :

  30420

  signal_type :

  Analysed

  source :

  ayc

  uda_name :

  AYC

  uuid :

  8d043ece-8bf8-5af8-87e4-d2a1b01716fa

  version :

  0

fig, axes = plt.subplots(2,1)
ax1, ax2 = axes

ax1.plot(dataset['time'], dataset['te_core'])
ax1.set_xlabel('Time (s)')
ax1.set_ylabel('Core Temperature (eV)')

ax2.plot(dataset['time'], dataset['ne_core'])
ax2.set_xlabel('Time (s)')
ax2.set_ylabel('Peak Core Electron Density ($1 / m^3$)')

for ax in axes:
    ax.grid(alpha=0.3)

plt.tight_layout()

2D Thomson Profiles

The dataset also includes 2D Thomson scattering profles as a function of time and angle/distance.

fig, (ax1, ax2) = plt.subplots(2, 1)
dataset = catalog.level1.sources(url=url)
dataset = dataset.to_dask()

tmax = dataset['te_core'].dropna(dim='time').time.max()

ds = dataset.copy()

te = ds['te']
te = te.sel(time=te.time <= tmax)
te = te.fillna(0)
te.plot.imshow(ax=ax1, vmax=1000)
ax1.set_title('Temperature ($T_e$)')

ne = ds['ne']
ne = ne.sel(time=ne.time <= tmax)
ne = ne.fillna(0)
ne.plot.imshow(ax=ax2, vmax=1e20)
ax2.set_title('Density ($n_e$)')

ax1.grid(False)
ax2.grid(False)
plt.tight_layout()