def joinFileSRS(fileName):
try:
print(fileName)
srs_table = srs.read_srs(fileName)
# print(srs_table)
# print(srs_table.colnames)
print(srs_table.meta['issued'].date())
outF = open("Data set\\01-ALL_SRS.csv", "a")
for x in srs_table:
LatitudeNumber = re.search("\d+", str(x['Latitude']))
LongitudeNumber = re.search("\d+", str(x['Longitude']))
stringX = "{0};{1};{2};{3};{4};{5};{6};{7};{8};{9};{10}\n".format(
x['ID'], x['Number'], x['Carrington Longitude'], x['Area'],
x['Z'], x['Longitudinal Extent'], x['Number of Sunspots'],
x['Mag Type'],
LatitudeNumber.group(0) if LatitudeNumber else 0,
LongitudeNumber.group(0) if LongitudeNumber else 0,
srs_table.meta['issued'].date())
# print(stringX)
outF.write(stringX)
outF.close()
except KeyError as err:
print("KeyError: {0}".format(err))
# filename.
file_name = Fido.fetch(result)
##############################################################################
# Download the SRS file.
srs_results = Fido.search(a.Time(start_time, end_time),
a.Instrument('SRS_TABLE'))
srs_downloaded_files = Fido.fetch(srs_results)
##############################################################################
# We get one SRS file per day. To read this file, we pass the filename into
# the SRS reader. So now `srs_table` contains an astropy table.
srs_table = srs.read_srs(srs_downloaded_files[0])
print(srs_table)
##############################################################################
# We only need the rows which have 'ID' = 'I' or 'IA'.
if 'I' in srs_table['ID'] or 'IA' in srs_table['ID']:
srs_table = srs_table[np.logical_or(srs_table['ID'] == 'I',
srs_table['ID'] == 'IA')]
else:
print("Warning : No I or IA entries for this date.")
srs_table = None
##############################################################################
# Now we extract the latitudes, longitudes and the region numbers. We make an
# empty list if there are no ARs.
def test_number_of_rows(path, number_of_rows):
table = srs.read_srs(path)
assert len(table) == number_of_rows
# used indexing to get the first file of the day, the list contains one
# filename.
file_name = Fido.fetch(result)
##############################################################################
# Download the SRS file.
srs_results = Fido.search(a.Time(start_time, end_time), a.Instrument('SRS_TABLE'))
srs_downloaded_files = Fido.fetch(srs_results)
##############################################################################
# We get one SRS file per day. To read this file, we pass the filename into
# the SRS reader. So now `srs_table` contains an astropy table.
srs_table = srs.read_srs(srs_downloaded_files[0])
print(srs_table)
##############################################################################
# We only need the rows which have 'ID' = 'I' or 'IA'.
if 'I' in srs_table['ID'] or 'IA' in srs_table['ID']:
srs_table = srs_table[np.logical_or(srs_table['ID'] == 'I',
srs_table['ID'] == 'IA')]
else:
print("Warning : No I or IA entries for this date.")
srs_table = None
##############################################################################
# Now we extract the latitudes, longitudes and the region numbers. We make an
# empty list if there are no ARs.
import numpy as np
from astropy.coordinates import SkyCoord
import sunpy.coordinates
import sunpy.data.sample
import sunpy.map
from sunpy.io.special import srs
##############################################################################
# For this example, we will start with the sample data. We need an HMI file and
# use it to create a map, and the SRS table which contains a list of active
# regions. Both of these data can be downloaded with ``Fido``.
smap = sunpy.map.Map(sunpy.data.sample.HMI_LOS_IMAGE)
srs_table = srs.read_srs(sunpy.data.sample.SRS_TABLE)
##############################################################################
# We only need the rows which have 'ID' = 'I' or 'IA'.
srs_table = srs_table[np.logical_or(srs_table['ID'] == 'I',
srs_table['ID'] == 'IA')]
##############################################################################
# Now we extract the latitudes, longitudes and the region numbers.
# :meth:`~astropy.visualization.wcsaxes.WCSAxes.plot_coord` will error on some
# versions of Astropy if a coordinate component contains a mask, but since
# none of the masks in these arrays here actually mask any elements, we simply
# remove the masks.
lats = srs_table['Latitude']
def test_number_of_rows(path, number_of_rows):
table = srs.read_srs(path)
assert len(table) == number_of_rows
plt.figure() rhessi_map.plot() plt.show() ############################################################################## # NORH norh = sunpy.timeseries.TimeSeries(sample_data.NORH_TIMESERIES) fig = plt.figure() norh.plot() plt.show() #################################################################################### # NOAA overlaid with HMI noaa = srs.read_srs(sample_data.SRS_TABLE) smap = sunpy.map.Map(sample_data.HMI_LOS_IMAGE) noaa = noaa[np.logical_or(noaa['ID'] == 'I', noaa['ID'] == 'IA')] lats = noaa['Latitude'] lngs = noaa['Longitude'] numbers = noaa['Number'] fig = plt.figure() ax = fig.add_subplot(projection=smap) smap.plot_settings["norm"].vmin = -200 smap.plot_settings["norm"].vmax = 200 smap.plot(axes=ax) smap.draw_limb(axes=ax)
