irfpy.swim.wind

Module to handle WIND data

Simplest way of getting the data is using WindMoon.

If you want to take the average key parameter of the solar wind at the Moon position, use the following syntaxes. This sample is to get the average between 03:15 and 03:20 on 10 May 2009.

>>> t0 = datetime.datetime(2009, 5, 10, 3, 15, 0)
>>> t1 = datetime.datetime(2009, 5, 10, 3, 20, 0)
>>> tarr, ave, var = WindMoon.get_average(t0, t1)
>>> print(len(tarr))
4
>>> label = WindMoon.label_array()
>>> print('%s %.2f (%.2f)' % (label[0], ave[0], var[0]))
N 2.22 (0.07)
>>> print('%s %.2f (%.2f)' % (label[1], ave[1], var[1]))
V 433.35 (28.05)
>>> print('%s %.2f (%.2f)' % (label[2], ave[2], var[2]))
Vth 27.49 (5.75)

The data file location should be specified by the .irfpyrc file using the entry in swim section with a name of windmoonpath. The data file should be made beforehand using wind2moon.py script.

See also the document: ftp://space.mit.edu/pub/plasma/wind/kp_files/000_README_WIND_P_FILES.TXT

There is an interface for ACE spacecraft. See irfpy.swim.ace, while the usage is a little bit different.

class irfpy.swim.wind.WindRawDataTree

Bases: object

WIND’s raw data tree

class irfpy.swim.wind.WindMoon

Bases: object

An user interface.

windmoondatatree = None

classmethod get_average(t0, t1)

Get the average of the parameters.

An interface to the WindMoonDataTree.get_average_wind_data_between.

Returns

Tuple of three arrays. The returned is 0) the array of time used with shape of (N,) where N is the number of data in between the time range [t0 t1]; 1) the array of the average of the key parameters; and 2) the array of the variance of the key parameters.

The order of the key parameters can be referred to WindMoonData.label_array().

>>> t0 = datetime.datetime(2009, 5, 1, 23, 50)
>>> t1 = datetime.datetime(2009, 5, 2, 4, 30)
>>> tarr, average, variance = WindMoon.get_average(t0, t1)
>>> print('N %.1f' % average[0])
N 7.7
>>> print('V %.1f' % average[1])
V 298.2
>>> print('Vth %.1f' % average[2])
Vth 22.4

>>> t0 = datetime.datetime(2009, 6, 15, 23, 59, 59)
>>> t1 = datetime.datetime(2009, 6, 16, 0, 0, 1)
>>> tarr, average, variance = WindMoon.get_average(t0, t1)
>>> print(len(tarr))
0
>>> print(len(average))
7
>>> print(len(variance))
7
>>> print(average[0])
nan

classmethod label_array()

class irfpy.swim.wind.WindMoonDataTree

Bases: object

WIND’s Moon data tree

get_filename(t)

get_wind_data(filename)

Get the WIND data as dictionary. 1 day data returned.

get_average_wind_data_between(t0, t1)

Get the WIND averaged key parameters.

>>> winddata = WindMoonDataTree()
>>> t0 = datetime.datetime(2009, 4, 30, 23, 50)
>>> t1 = datetime.datetime(2009, 5, 2, 4, 30)
>>> tarr, average, variance = winddata.get_average_wind_data_between(t0, t1)

The returned is 0) the array of time used with shape of (N,) where N is the number of data in between the time range [t0 t1]; 1) the array of the average of the key parameters; and 2) the array of the variance of the key parameters.

The order of the key parameters can be referred to WindMoonData.label_array().

get_wind_data_between(t0, t1)

Get the WIND data in the interval between t0 and t1.

Return the time array and the data array. Time array is the datetime instance array and the data array is the WindMoonData instance array.

>>> winddata = WindMoonDataTree()
>>> t0 = datetime.datetime(2009, 4, 30, 23, 50)
>>> t1 = datetime.datetime(2009, 5, 2, 4, 30)
>>> tarr, darr = winddata.get_wind_data_between(t0, t1)

class irfpy.swim.wind.WindData

Bases: object

WIND data.

>>> str='2009  354  0.00208993      377.5    -0.9312     -1.351      3.646      19.75 -1.000e+31     -377.3     -6.133     -8.901      246.1     -64.36      20.02'
>>> data = WindData.parse_string(str)

The data is stored as a member in the class.

• yr, doy, dayfrac, t

• v, ewang, nsang

• n

• vth

• alpha

• vx, vy, vz

• gsex, gsey, gsez

classmethod parse_string(line)

class irfpy.swim.wind.WindMoonData

Bases: object

WIND data at the Moon. >>> str=’2009 354 0.00208993 377.5 -0.9312 -1.351 3.646 19.75 -1.000e+31 -377.3 -6.133 -8.901 246.1 -64.36 20.02 2009-01-27 00:15:30 2009-01-27 01:30:44’

>>> data = WindMoonData.parse_string(str)

The data is stored as a member in the class.

• yr, doy, dayfrac, t

• tmoon

• v, ewang, nsang

• n

• vth

• alpha

• vx, vy, vz

• gsex, gsey, gsez

as_array()

Return the data as numpy.array.

Return 1-D array of [n, v, vth, alpha%, vx, vy, vz].

classmethod label_array()

Return the label of the as_array().

Returns

A string array ['N', 'V', 'Vth', 'Alpha%', 'Vx', 'Vy', 'Vz']

classmethod parse_string(line)

class irfpy.swim.wind.Wind2Moon

Bases: object

moonpos = None

classmethod run()

Run the WIND time shift to the Moon position.