cdasws Example Jupyter Notebook

Prerequisites

1. Install CDF.
2. pip install spacepy
3. pip install cdasws

Get Data Example

The following code demonstrates how to access magnetic field measurements from the ACE mission dataset using the cdasws package in a Jupyter notebook.

from cdasws import CdasWs
import matplotlib.pyplot as plt
cdas = CdasWs()
data = cdas.get_data('AC_H1_MFI', ['Magnitude', 'BGSEc'],
                     '2009-06-01T00:00:00Z', '2009-06-01T00:10:00Z')[1]
print(data)

{'Epoch': VarCopy([datetime.datetime(2009, 6, 1, 0, 0),
         datetime.datetime(2009, 6, 1, 0, 4),
         datetime.datetime(2009, 6, 1, 0, 8)], dtype=object), 'Magnitude': VarCopy([3.495, 3.474, 3.477], dtype=float32), 'BGSEc': VarCopy([[-0.106,  2.521, -2.391],
         [-0.412,  2.402, -2.449],
         [-0.094,  2.309, -2.587]], dtype=float32), 'cartesian': VarCopy(['x_component', 'y_component', 'z_component'], dtype='<U11'), 'metavar0': VarCopy(['Bx GSE', 'By GSE', 'Bz GSE'], dtype='<U6')}

Display Metadata

To display metadata for the Magnitude variable, do

print(data['Magnitude'].attrs)

{'FIELDNAM': 'B-field magnitude', 'VALIDMIN': 0.0, 'VALIDMAX': 500.0, 'SCALEMIN': 0.0, 'SCALEMAX': 10.0, 'UNITS': 'nT', 'FORMAT': 'F8.3', 'VAR_TYPE': 'data', 'DICT_KEY': 'magnetic_field>magnitude', 'FILLVAL': -1e+31, 'DEPEND_0': 'Epoch_bin', 'CATDESC': 'B-field magnitude', 'LABLAXIS': '<|B|>', 'DISPLAY_TYPE': 'time_series', 'DIM_SIZES': 0}

Plot Values

To plot the Magnitude values using the label values from the metadata, do

plt.plot(data['Epoch'], data['Magnitude'])
plt.xlabel(data['Epoch'].attrs['LABLAXIS'])
plt.ylabel(data['Magnitude'].attrs['LABLAXIS'] + ' ' +
           data['Magnitude'].attrs['UNITS'])
plt.show()

Binning Example

To have uniformly spaced (with respect to time) values computed (with optional spike removal), add the binData keyword paramter like this

    status, data = cdas.get_data('AC_H1_MFI', ['Magnitude', 'BGSEc'],
                                 '2009-06-01T00:00:00Z', '2009-06-01T00:10:00Z',
                                 binData={
                                     'interval': 60.0,
                                     'interpolateMissingValues': True,
                                     'sigmaMultiplier': 4
                                 })
    print(data)

{'Epoch_bin': VarCopy([datetime.datetime(2009, 6, 1, 0, 0, 30),
         datetime.datetime(2009, 6, 1, 0, 1, 30),
         datetime.datetime(2009, 6, 1, 0, 2, 30),
         datetime.datetime(2009, 6, 1, 0, 3, 30),
         datetime.datetime(2009, 6, 1, 0, 4, 30),
         datetime.datetime(2009, 6, 1, 0, 5, 30),
         datetime.datetime(2009, 6, 1, 0, 6, 30),
         datetime.datetime(2009, 6, 1, 0, 7, 30),
         datetime.datetime(2009, 6, 1, 0, 8, 30),
         datetime.datetime(2009, 6, 1, 0, 9, 30)], dtype=object), 'Epoch': VarCopy([datetime.datetime(2009, 6, 1, 0, 0),
         datetime.datetime(2009, 6, 1, 0, 4),
         datetime.datetime(2009, 6, 1, 0, 8)], dtype=object), 'Magnitude': VarCopy([3.495  , 3.48975, 3.4845 , 3.47925, 3.474  , 3.47475, 3.4755 ,
         3.47625, 3.477  , 3.477  ], dtype=float32), 'BGSEc': VarCopy([[-0.106    ,  2.521    , -2.391    ],
         [-0.1825   ,  2.49125  , -2.4055   ],
         [-0.259    ,  2.4615   , -2.42     ],
         [-0.3355   ,  2.4317498, -2.4345   ],
         [-0.412    ,  2.402    , -2.449    ],
         [-0.3325   ,  2.3787498, -2.4835   ],
         [-0.253    ,  2.3555   , -2.518    ],
         [-0.1735   ,  2.33225  , -2.5524998],
         [-0.094    ,  2.309    , -2.587    ],
         [-0.094    ,  2.309    , -2.587    ]], dtype=float32), 'MAGNITUDE_NBIN': VarCopy([1., 0., 0., 0., 1., 0., 0., 0., 1., 0.], dtype=float32), 'MAGNITUDE_BIN_DELTA_MINUS_VAR': VarCopy([-1.e+31, -1.e+31, -1.e+31, -1.e+31, -1.e+31, -1.e+31, -1.e+31,
         -1.e+31, -1.e+31, -1.e+31], dtype=float32), 'MAGNITUDE_BIN_DELTA_PLUS_VAR': VarCopy([-1.e+31, -1.e+31, -1.e+31, -1.e+31, -1.e+31, -1.e+31, -1.e+31,
         -1.e+31, -1.e+31, -1.e+31], dtype=float32), 'BGSEC_NBIN': VarCopy([[ 1.,  1.,  1.],
         [-0., -0., -0.],
         [-0., -0., -0.],
         [-0., -0., -0.],
         [ 1.,  1.,  1.],
         [-0., -0., -0.],
         [-0., -0., -0.],
         [-0., -0., -0.],
         [ 1.,  1.,  1.],
         [-0., -0., -0.]], dtype=float32), 'BGSEC_BIN_DELTA_MINUS_VAR': VarCopy([[-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31]], dtype=float32), 'BGSEC_BIN_DELTA_PLUS_VAR': VarCopy([[-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31],
         [-1.e+31, -1.e+31, -1.e+31]], dtype=float32), 'cartesian_bin': VarCopy(['x_component', 'y_component', 'z_component'], dtype='<U11'), 'cartesian': VarCopy(['x_component', 'y_component', 'z_component'], dtype='<U11'), 'metavar0': VarCopy(['Bx GSE', 'By GSE', 'Bz GSE'], dtype='<U6'), 'metavar1': VarCopy(['# of Bx GSE', '# of By GSE', '# of Bz GSE'], dtype='<U11'), 'metavar2': VarCopy('# of ', dtype='<U5')}

DOI Example

To get data from a dataset with a digital object identifier do the following:

status, data = cdas.get_data('10.21978/P8PG8V', ['BT'], '1987-09-24T00:00:00Z', '1987-09-25T00:00:00Z')
print(data.attrs['Descriptor'])
print(data)

['MFI>3-axis fluxgate magnetometer averages']
{'Epoch': VarCopy([datetime.datetime(1987, 9, 24, 0, 30, 1, 567000),
         datetime.datetime(1987, 9, 24, 0, 30, 5, 567000),
         datetime.datetime(1987, 9, 24, 0, 30, 9, 567000), ...,
         datetime.datetime(1987, 9, 24, 23, 59, 51, 368000),
         datetime.datetime(1987, 9, 24, 23, 59, 55, 369000),
         datetime.datetime(1987, 9, 24, 23, 59, 59, 369000)], dtype=object), 'BT': VarCopy([89.8591, 89.7978, 89.7269, ..., 18.5909, 18.6276, 18.5359],
        dtype=float32)}

Additional Documentation

View the cdasws API for additional functions.