def __init__(self):
self._view = QtWidgets.QWidget()
self._ui = Ui_DataManager()
self._ui.setupUi(self._view)
self._ui.refresh_button.setIcon(self._view.style().standardIcon(
QStyle.SP_BrowserReload))
self._ui.remove_button.setIcon(self._view.style().standardIcon(
QStyle.SP_DialogNoButton))
self._ui.add_button.setIcon(self._view.style().standardIcon(
QStyle.SP_DialogYesButton))
self.dlg = DataManagerFilterDialog()
db = QtSql.QSqlDatabase.addDatabase('QSQLITE')
db.setDatabaseName(
sunpy.config.get("database", "url").replace("sqlite:///", ""))
model = QtSql.QSqlTableModel()
model.setTable("data")
model.setEditStrategy(QtSql.QSqlTableModel.OnFieldChange)
model.select()
self._ui.data_table.setModel(model)
self.initTableHeader(model)
self._ui.add_button.clicked.connect(lambda x: self.onAdd())
self._ui.remove_button.clicked.connect(lambda x: self.onRemove())
self._ui.open_button.clicked.connect(lambda x: self.onOpen())
self._ui.refresh_button.clicked.connect(lambda x: self.model.select())
self._ui.filter_button.clicked.connect(lambda x: self.onFilter())
self.sunpy_db = Database()
self.model = model
def test_config_url(monkeypatch):
monkeypatch.setattr("sunpy.config", ConfigParser.SafeConfigParser())
url = 'sqlite:///'
sunpy.config.add_section('database')
sunpy.config.set('database', 'url', url)
database = Database()
assert database.url == url
def test_fetch_separate_filenames():
# Setup
db = Database('sqlite:///')
download_query = [
vso.attrs.Time('2012-08-05', '2012-08-05 00:00:05'),
vso.attrs.Instrument('AIA')
]
tmp_test_dir = os.path.join(sunpy.config.get('downloads', 'download_dir'),
'tmp_test_dir/')
if not os.path.isdir(tmp_test_dir):
os.mkdir(tmp_test_dir)
path = tmp_test_dir + '{file}'
db.fetch(*download_query, path=path)
# Test
assert len(db) == 4
dir_contents = os.listdir(tmp_test_dir)
assert 'aia_lev1_335a_2012_08_05t00_00_02_62z_image_lev1.fits' in dir_contents
assert 'aia_lev1_94a_2012_08_05t00_00_01_12z_image_lev1.fits' in dir_contents
assert os.path.isfile(
os.path.join(tmp_test_dir,
'aia_lev1_335a_2012_08_05t00_00_02_62z_image_lev1.fits'))
assert os.path.isfile(
os.path.join(tmp_test_dir,
'aia_lev1_94a_2012_08_05t00_00_01_12z_image_lev1.fits'))
# Teardown
shutil.rmtree(tmp_test_dir)
def filled_database():
database = Database('sqlite:///:memory:')
for i in xrange(1, 11):
entry = DatabaseEntry()
database.add(entry)
# every fourth entry gets the tag 'foo'
if i % 4 == 0:
database.tag(entry, 'foo')
# every fifth entry gets the tag 'bar'
if i % 5 == 0:
database.tag(entry, 'bar')
database.commit()
return database
def connect_db(self, conn_string=''):
'''
This function creates a database connection based on the parameters
specified in the GUI.
Parameters: conn_string (string of the connection for the object) Optional
'''
def_wavelength = self.default_wavelength.get_widget().currentText()
try:
if conn_string == '':
conn_string = sunpy.config.get('database', 'url')
global database
database = Database(conn_string, default_waveunit=def_wavelength)
except:
conn_string = self.get_conn_string()
global database
database = Database(conn_string, default_waveunit=def_wavelength)
if self.set_default_box.get_state():
self.set_default_db(conn_string)
self.set_info("Database Connected at %s" % conn_string)
return database
def __init__(self):
self._view = QtWidgets.QWidget()
self._ui = Ui_DownloadResult()
self._ui.setupUi(self._view)
self._ui.tabs.clear()
self._ui.tabs.tabCloseRequested.connect(self._onRemoveTab)
self.database = Database()
self.tabs = {}
self.queries = {}
self.query_id = 0
self.loading = []
self.loaded = {entry.fileid: entry.path for entry in list(self.database)}
self._ui.download_button.clicked.connect(lambda evt: self._onDownloadSelected())
self._ui.open_button.clicked.connect(lambda evt: self._onOpenSelected())
def split_function_database():
"""
Generates a custom database to test the split_database function
"""
database = Database('sqlite:///:memory:')
for i in range(1, 11):
entry = DatabaseEntry()
database.add(entry)
# every fourth entry gets the instrument 'EIA'
if i % 4 == 0:
database.edit(entry, instrument='EIA')
# every fifth entry gets the instrument 'AIA_3'
elif i % 5 == 0:
database.edit(entry, instrument='AIA_3')
# every other entry gets instrument 'RHESSI'
else:
database.edit(entry, instrument='RHESSI')
# all entries have provider 'xyz'
database.edit(entry, provider='xyz')
database.commit()
return database
def test_display_entries_empty_db():
with pytest.raises(TypeError):
display_entries(Database('sqlite:///'), ['id'])
def test_create_display_table_empty_db():
with pytest.raises(TypeError):
_create_display_table(Database('sqlite:///'), ['id'])
from sunpy.net import vso
from sunpy.database import Database
database = Database("sqlite:///")
database.download(vso.attrs.Time("2012-08-05", "2012-08-05 00:00:05"),
vso.attrs.Instrument('AIA'))
len(database)
from sunpy.database.tables import display_entries
print display_entries(database,
["id", "observation_time_start", "wavemin", "wavemax"])
def database():
return Database('sqlite:///:memory:')
def database_using_lfucache():
return Database('sqlite:///:memory:', LFUCache, cache_size=3)
def test_config_url_none(monkeypatch):
monkeypatch.setattr("sunpy.config", ConfigParser.SafeConfigParser())
with pytest.raises(ConfigParser.NoSectionError):
Database()
# This is how it would query sunpy the data mapped in 'gathering_data_information.txt'
# At this time the vso client seems unstable and sunpy integration could not be complete
from sunpy.database import Database
from sunpy.net import vso
#Sets the connection to database, in this case, it is in postgresql but it can be others too
database = Database('postgresql+psycopg2://user:password@host/dbname')
#downloads and add to database
def downloadData(q_provider, q_source, q_instrument, q_physobs):
client = vso.VSOClient()
qr = client.search(
vso.attrs.Time('2016-05-07 00:00:00', '2016-05-08 00:00:00'))
print(qr)
database.add_from_vso_query_result(qr)
database.commit()
#downloads MAgnetogram vector from vso client
def dl_MagnetogramVector():
q_provider = 'JSOC'
q_source = 'SDO'
q_instrument = 'HMI'
q_physobs = 'vector_magnetic_field'
downloadData(q_provider, q_source, q_instrument, q_physobs)
#downloads XRay data from vso client
def dl_XRay():
def default_waveunit_database():
unit_database = Database('sqlite:///:memory:',
default_waveunit=units.meter)
str_database = Database('sqlite:///:memory:', default_waveunit="m")
return unit_database, str_database
hmiC.plot(cmap=cmap, annotate=False)
plt.clim(0,300)
plt.show()
# Now compare your awesome image with the HMI Intensitygram on https://sdo.gsfc.nasa.gov/data/.
# Intensitygrams show how bright the sun is over it's surface. You'll also see a flattened version on the SDO website.
# The flattened image takes into account the fact that most of the light from the sides of the sun as we see it is not directed towards us.
# This makes the sun look darker near the edges like in our image. This effect is called limb darkening.
## Multiwavelength Images
# We know that the sun emits many wavelengths of electromagnetic radiation lets get some images for the different parts of the EM spectrum.
# We've already seen a continuum or white light image of the sun that we colourised at the begining of the Notebook.
# To store our new data we are going to start a database which wil help us manage the observations we download:
db = Database('sqlite:///sunpydata.sqlite')
db.default_waveunit = 'angstrom'
# You'll notice a file called sunpydata.sqlite has appeared in our directory.
# This is our database. Let's download something to fill it.
# Science ready data from spacecraft is not available instantly so we will have to get information from a while back.
result = Fido.search(a.Time('2019/05/06 12:00', '2019/05/06 12:01'),a.Instrument('aia'),a.vso.Sample(2*u.minute),a.Wavelength(94*u.angstrom)|a.Wavelength(131*u.angstrom)|a.Wavelength(171*u.angstrom)|a.Wavelength(193*u.angstrom)|a.Wavelength(211*u.angstrom)|a.Wavelength(304*u.angstrom)|a.Wavelength(335*u.angstrom)|a.Wavelength(1600*u.angstrom)|a.Wavelength(4500*u.angstrom))
print(result)
# You should see a load of tables with the results from our search.
# Each table is for a different wavelength we specified in Angstrom (10E-10 m).
# We searched images from the SDO instrument AIA, and set a.vso.Sample() greater than the time period we searched.
# This meant we only get one image for each wavelength in that time period (which is only 2 minutes to begin with!).
# We can now download the data.
