import os
import codecs
from os.path import basename
from collections import OrderedDict
import numpy as np
from pandas import DataFrame, to_datetime
from pandas.io.parsers import read_csv
import astropy.units as u
from astropy.time import TimeDelta
import sunpy.io
from sunpy.time import parse_time
from sunpy.timeseries.timeseriesbase import GenericTimeSeries
from sunpy.util.decorators import deprecate_positional_args_since
from sunpy.util.exceptions import warn_deprecated
from sunpy.util.metadata import MetaDict
from sunpy.visualization import peek_show
__all__ = ['EVESpWxTimeSeries', 'ESPTimeSeries']
[docs]
class ESPTimeSeries(GenericTimeSeries):
"""
SDO EVE/ESP Level 1 data.
The Extreme ultraviolet Spectro-Photometer (ESP) is an irradiance instrument
which is part of the Extreme ultraviolet Variability Experiment (EVE) on board
SDO. ESP provides high time cadence (0.25s) EUV irradiance measurements in five
channels, one soft X-ray and 4 EUV. The first four orders of the diffraction grating
gives measurements centered on 18nm, 26nm, 30nm and 36nm. The zeroth order (obtained
by 4 photodiodes) provides the soft X-ray measurements from 0.1-7nm.
The ESP level 1 fits files are fully calibrated. The TimeSeries object created from
an ESP fits file will contain 4 columns namely:
* 'QD' - sum of 4 quad diodes, this is the soft X-ray measurements 0.1-7nm
* 'CH_18' - EUV irradiance 18nm
* 'CH_26' - EUV irradiance 26nm
* 'CH_30' - EUV irradiance 30nm
* 'CH_36' - EUV irradiance 36nm
References
----------
* `SDO Mission Homepage <https://sdo.gsfc.nasa.gov/>`__
* `EVE Homepage <http://lasp.colorado.edu/home/eve/>`__
* `README ESP data <http://lasp.colorado.edu/eve/data_access/evewebdata/products/level1/esp/EVE_ESP_L1_V6_README.pdf>`__
* `ESP lvl1 data <http://lasp.colorado.edu/eve/data_access/evewebdata/misc/eve_calendars/calendar_level1_2018.html>`__
* `ESP instrument paper <https://doi.org/10.1007/s11207-009-9485-8>`__
Notes
-----
The 36nm channel demonstrates a significant noise and it is not recommended to be
used for short-time observations of solar irradiance.
"""
_source = 'esp'
_url = "http://lasp.colorado.edu/home/eve/"
[docs]
def plot(self, axes=None, columns=None, **kwargs):
"""
Plots the EVE ESP Level 1 timeseries data.
Parameters
----------
axes : numpy.ndarray of `matplotlib.axes.Axes`, optional
The axes on which to plot the TimeSeries.
columns : list[str], optional
If provided, only plot the specified columns.
**kwargs : `dict`
Additional plot keyword arguments that are handed to `pandas.DataFrame.plot`.
Returns
-------
array of `~matplotlib.axes.Axes`
The plot axes.
"""
axes, columns = self._setup_axes_columns(axes, columns, subplots=True)
column_names = {"QD": "Flux \n 0.1-7nm", "CH_18": "Flux \n 18nm",
"CH_26": "Flux \n 26nm", "CH_30": "Flux \n 30nm", "CH_36": "Flux \n 36nm"}
for i, name in enumerate(self.to_dataframe()[columns]):
axes[i].plot(self._data[name],
label=name)
axes[i].set_ylabel(column_names[name])
axes[i].legend(loc="upper right")
axes[-1].set_xlim(self._data.index[0], self._data.index[-1])
self._setup_x_axis(axes)
return axes
[docs]
@peek_show
@deprecate_positional_args_since("4.1")
def peek(self, *, title="EVE/ESP Level 1", columns=None, **kwargs):
"""
Displays the EVE ESP Level 1 timeseries data by calling
`~sunpy.timeseries.sources.eve.ESPTimeSeries.plot`.
Parameters
----------
title : `str`, optional
The title of the plot. Defaults to "EVE/ESP Level 1".
columns : list[str], optional
If provided, only plot the specified columns.
**kwargs : `dict`
Additional plot keyword arguments that are handed to `pandas.DataFrame.plot`.
"""
axes = self.plot(columns=columns, **kwargs)
axes[0].set_title(title)
fig = axes[0].get_figure()
fig.tight_layout()
fig.subplots_adjust(hspace=0.05)
return fig
@classmethod
def _parse_file(cls, filepath):
"""
Parses a EVE ESP level 1 data.
"""
hdus = sunpy.io.read_file(filepath)
return cls._parse_hdus(hdus)
@classmethod
def _parse_hdus(cls, hdulist):
header = MetaDict(OrderedDict(hdulist[0].header))
# Adding telescope to MetaData
header.update({'TELESCOP': hdulist[1].header['TELESCOP'].split()[0]})
start_time = parse_time(hdulist[1].header['T_OBS'])
times = start_time + TimeDelta(hdulist[1].data['SOD']*u.second)
colnames = ['QD', 'CH_18', 'CH_26', 'CH_30', 'CH_36']
all_data = [hdulist[1].data[x] for x in colnames]
data = DataFrame(np.array(all_data).T, index=times.isot.astype(
'datetime64'), columns=colnames)
data.sort_index(inplace=True)
units = OrderedDict([('QD', u.W/u.m**2),
('CH_18', u.W/u.m**2),
('CH_26', u.W/u.m**2),
('CH_30', u.W/u.m**2),
('CH_36', u.W/u.m**2)])
return data, header, units
[docs]
@classmethod
def is_datasource_for(cls, **kwargs):
"""
Determines if header corresponds to an EVE image.
"""
if kwargs.get('source', ''):
return kwargs.get('source', '').lower().startswith(cls._source)
if 'meta' in kwargs.keys():
return kwargs['meta'].get('TELESCOP', '').endswith('SDO/EVE')
[docs]
class EVESpWxTimeSeries(GenericTimeSeries):
"""
SDO EVE LightCurve for level 0CS data.
The Extreme Ultraviolet Variability Experiment (EVE) is an instrument on board the Solar Dynamics Observatory (SDO).
The EVE instrument is designed to measure the solar extreme ultraviolet (EUV) irradiance.
The EUV radiation includes the 0.1-105 nm range, which provides the majority
of the energy for heating Earth's thermosphere and creating Earth's ionosphere (charged plasma).
EVE includes several irradiance instruments:
* The Multiple EUV Grating Spectrographs (MEGS)-A is a grazing- incidence spectrograph
that measures the solar EUV irradiance in the 5 to 37 nm range with 0.1-nm resolution,
* The MEGS-B is a normal-incidence, dual-pass spectrograph that measures the solar EUV
irradiance in the 35 to 105 nm range with 0.1-nm resolution.
Level 0CS data is primarily used for space weather.
It is provided near real-time and is crudely calibrated 1-minute averaged broadband irradiances from ESP and MEGS-P broadband.
For other levels of EVE data, use `~sunpy.net.Fido`, with ``sunpy.net.attrs.Instrument('eve')``.
Data is available starting on 2010/03/01.
Examples
--------
>>> import sunpy.timeseries
>>> import sunpy.data.sample # doctest: +REMOTE_DATA
>>> eve = sunpy.timeseries.TimeSeries(sunpy.data.sample.EVE_TIMESERIES, source='EVE') # doctest: +REMOTE_DATA
>>> eve = sunpy.timeseries.TimeSeries("http://lasp.colorado.edu/eve/data_access/evewebdata/quicklook/L0CS/LATEST_EVE_L0CS_DIODES_1m.txt", source='EVE') # doctest: +SKIP
>>> eve.peek(subplots=True) # doctest: +SKIP
References
----------
* `SDO Mission Homepage <https://sdo.gsfc.nasa.gov/>`__
* `EVE Homepage <http://lasp.colorado.edu/home/eve/>`__
* `Level 0CS Definition <http://lasp.colorado.edu/home/eve/data/>`__
* `EVE Data Access <http://lasp.colorado.edu/home/eve/data/data-access/>`__
* `Instrument Paper <https://doi.org/10.1007/s11207-009-9487-6>`__
"""
# Class attribute used to specify the source class of the TimeSeries.
_source = 'eve'
_url = "http://lasp.colorado.edu/home/eve/"
[docs]
@peek_show
@deprecate_positional_args_since("4.1")
def peek(self, *, columns=None, **kwargs):
"""
Plots the time series in a new figure.
.. plot::
import sunpy.timeseries
from sunpy.data.sample import EVE_TIMESERIES
eve = sunpy.timeseries.TimeSeries(EVE_TIMESERIES, source='eve')
eve.peek(subplots=True, figsize=(22,11))
Parameters
----------
columns : list[str], optional
If provided, only plot the specified columns.
**kwargs : `dict`
Additional plot keyword arguments that are handed to
:meth:`pandas.DataFrame.plot`.
"""
# Check we have a timeseries valid for plotting
self._validate_data_for_plotting()
# Choose title if none was specified
if "title" not in kwargs and columns is None:
if len(self.to_dataframe().columns) > 1:
kwargs['title'] = 'EVE (1 minute data)'
else:
if self._filename is not None:
base = self._filename.replace('_', ' ')
kwargs['title'] = os.path.splitext(base)[0]
else:
kwargs['title'] = 'EVE Averages'
if columns is None:
axes = self.to_dataframe().plot(sharex=True, **kwargs)
else:
data = self.to_dataframe()[columns]
if "title" not in kwargs and len(columns) == 1:
kwargs['title'] = 'EVE ' + columns[0].replace('_', ' ')
else:
kwargs['title'] = 'EVE Averages'
axes = data.plot(sharex=True, **kwargs)
if "subplots" in kwargs:
fig = axes[0].get_figure()
else:
fig = axes.get_figure()
return fig
@classmethod
def _parse_file(cls, filepath):
"""
Parses an EVE CSV file.
"""
cls._filename = basename(filepath)
with codecs.open(filepath, mode='rb', encoding='ascii') as fp:
# Determine type of EVE CSV file and parse
line1 = fp.readline()
if line1.startswith("Date"):
return cls._parse_average_csv(filepath)
elif line1.startswith(";"):
return cls._parse_level_0cs(filepath)
@staticmethod
def _parse_average_csv(filepath):
"""
Parses an EVE Averages file.
"""
warn_deprecated(
"Parsing SDO/EVE level 0CS average files is deprecated, and will be removed in "
"sunpy 6.0. Parsing this data is untested, and we cannot find a file to test it with. "
"If you know where level 0CS 'averages' files can be found, please get in touch at "
"https://community.openastronomy.org/c/sunpy/5."
)
return "", read_csv(filepath, sep=",", index_col=0, parse_dates=True)
@staticmethod
def _parse_level_0cs(filepath):
"""
Parses and EVE Level 0CS file.
"""
is_missing_data = False # boolean to check for missing data
missing_data_val = np.nan
header = []
fields = []
with codecs.open(filepath, mode='rb', encoding='ascii') as fp:
line = fp.readline()
# Read header at top of file
while line.startswith(";"):
header.append(line)
if '; Missing data:' in line:
is_missing_data = True
missing_data_val = line.split(':')[1].strip()
line = fp.readline()
meta = MetaDict()
for hline in header:
if hline == '; Format:\n' or hline == '; Column descriptions:\n':
continue
elif ('Created' in hline) or ('Source' in hline):
meta[hline.split(':',
1)[0].replace(';',
' ').strip()] = hline.split(':', 1)[1].strip()
elif ':' in hline:
meta[hline.split(':')[0].replace(';', ' ').strip()] = hline.split(':')[1].strip()
fieldnames_start = False
for hline in header:
if hline.startswith("; Format:"):
fieldnames_start = False
if fieldnames_start:
fields.append(hline.split(":")[0].replace(';', ' ').strip())
if hline.startswith("; Column descriptions:"):
fieldnames_start = True
# Next line is YYYY DOY MM DD
date_parts = line.split(" ")
year = int(date_parts[0])
month = int(date_parts[2])
day = int(date_parts[3])
data = read_csv(filepath, sep=r'\s+', names=fields, comment=';', dtype={'HHMM': int})
# First line is YYYY DOY MM DD
data = data.iloc[1:, :]
data['Hour'] = data['HHMM'] // 100
data['Minute'] = data['HHMM'] % 100
data = data.drop(['HHMM'], axis=1)
data['Year'] = year
data['Month'] = month
data['Day'] = day
datecols = ['Year', 'Month', 'Day', 'Hour', 'Minute']
data['Time'] = to_datetime(data[datecols])
data = data.set_index('Time')
data = data.drop(datecols, axis=1)
if is_missing_data: # If missing data specified in header
data[data == float(missing_data_val)] = np.nan
# Add the units data
units = OrderedDict([('XRS-B proxy', u.W/u.m**2),
('XRS-A proxy', u.W/u.m**2),
('SEM proxy', u.W/u.m**2),
('0.1-7ESPquad', u.W/u.m**2),
('17.1ESP', u.W/u.m**2),
('25.7ESP', u.W/u.m**2),
('30.4ESP', u.W/u.m**2),
('36.6ESP', u.W/u.m**2),
('darkESP', u.ct),
('121.6MEGS-P', u.W/u.m**2),
('darkMEGS-P', u.ct),
('q0ESP', u.dimensionless_unscaled),
('q1ESP', u.dimensionless_unscaled),
('q2ESP', u.dimensionless_unscaled),
('q3ESP', u.dimensionless_unscaled),
('CMLat', u.deg),
('CMLon', u.deg)])
# Todo: check units used.
return data, meta, units
[docs]
@classmethod
def is_datasource_for(cls, **kwargs):
"""
Determines if header corresponds to an EVE image.
"""
if kwargs.get('source', ''):
return kwargs.get('source', '').lower().startswith(cls._source)
