def _response_to_query(query, reply_to, subject=None, url=None):
"""
Takes a parsed query string fetches the forecast,
compresses it and replies to the sender.
Parameters
----------
query : dict
An dictionary query
reply_to : string
The email address of the sender. The compressed forecast is sent
to this person.
subject : string (optional)
The subject of the email that is sent. If none, a summary of
the query is used.
url : string (optional)
A path to the forecast that should be used. This is mostly used
for debugging and testing.
Returns
----------
forecast_attachment : file-like
A file-like object holding the forecast that was sent
"""
compressed_forecast = process_query(query, url=url)
logging.debug("Compressed Size: %d" % len(compressed_forecast))
# create a file-like forecast attachment
logging.debug('Obtained the forecast')
file_fmt = '%Y-%m-%d_%H%m'
filename = datetime.datetime.today().strftime(file_fmt)
filename = '_'.join([query['type'], query['model'], filename])
if query.get('send-image', False):
logging.debug('Sending an image of the forecast')
fcst = compress.decompress_dataset(compressed_forecast)
visualize.plot_spot(fcst)
import matplotlib.pyplot as plt
png = BytesIO()
plt.savefig(png)
png.seek(0)
attachments = {'%s.png' % filename: png}
else:
logging.debug('Sending the compressed forecasts')
forecast_attachment = BytesIO(compressed_forecast)
ext = decide_extension(reply_to)
attachment_name = '%s.%s' % (filename, ext)
logging.debug("Attaching forecast as %s" % attachment_name)
attachments = {attachment_name: forecast_attachment}
# Make sure the forecast file isn't too large for sailmail
if 'sailmail' in reply_to and len(compressed_forecast) > 25000:
raise utils.BadQuery("Forecast was too large (%d bytes) for sailmail!"
% len(compressed_forecast))
# creates the new mime email
weather_email = emaillib.create_email(reply_to, _query_email,
_email_body,
subject=subject or query_summary(query),
attachments=attachments)
return weather_email
def test_version_assert(self):
# create a forecast that looks like its from a newer version
# and make sure an assertion is raised.
ds = create_data()
original_version = compress._VERSION
compress._VERSION = np.array(compress._VERSION + 1, dtype=np.uint8)
beaufort = compress.compress_dataset(ds)
compress._VERSION = original_version
self.assertRaises(ValueError,
lambda: compress.decompress_dataset(beaufort))
def main():
fcst = test_data()
fcst = compress.decompress_dataset(compress.compress_dataset(fcst))
for vn in ['current', 'wind']:
variable = query_utils.get_variable(vn)
if isinstance(variable, schemes.VelocityVariable):
interactive.InteractiveVelocity(fcst, variable)
plt.show()
def test_compress_dataset(self):
ds = create_data()
compressed = compress.compress_dataset(ds)
actual = compress.decompress_dataset(compressed)
np.testing.assert_allclose(actual['x_wind'].values, ds['x_wind'].values,
atol=1e-4, rtol=1e-4)
np.testing.assert_allclose(actual['y_wind'].values, ds['y_wind'].values,
atol=1e-4, rtol=1e-4)
np.testing.assert_allclose(actual['air_pressure_at_sea_level'].values,
ds['air_pressure_at_sea_level'].values,
atol=1e-4, rtol=1e-4)
# pass it through the system again, it should be idempotent.
compressed = compress.compress_dataset(ds)
actual = compress.decompress_dataset(compressed)
np.testing.assert_allclose(actual['x_wind'].values, ds['x_wind'].values,
atol=1e-4, rtol=1e-4)
np.testing.assert_allclose(actual['y_wind'].values, ds['y_wind'].values,
atol=1e-4, rtol=1e-4)
np.testing.assert_allclose(actual['air_pressure_at_sea_level'].values,
ds['air_pressure_at_sea_level'].values,
atol=1e-4, rtol=1e-4)
def test_query(self):
some_email = "*****@*****.**"
msg = emaillib.create_email(
to="*****@*****.**", fr=some_email, body="send GFS:30s,35s,175e,175w|0.5,0.5|0,3..12|WIND"
)
emails = []
# use a mocked emaillib to make sure an email was sent
with self.get_request(emails) as request:
request.process_email(msg.as_string(), fail_hard=True)
assert len(emails) == 1
parser = Parser.Parser()
email = parser.parsestr(emails.pop().args[0].as_string())
# make sure we are sending responses from ensembleweather
self.assertEqual(email["From"], "*****@*****.**")
# make sure we are responding to the right person
self.assertEqual(email["To"], some_email)
# here we pull out the expected attachment
body, attach = email.get_payload()
bytes = attach.get_payload()
# inflate it back into an xray Dataset
fcst = compress.decompress_dataset(base64.b64decode(bytes))
# make sure we're actually compressing the file.
self.assertLessEqual(len(bytes), len(zlib.compress(fcst.to_netcdf())))
# make sure the lats are what we expect
expected_lats = np.linspace(-35.0, -30.0, 11)
np.testing.assert_array_equal(fcst["latitude"].values, expected_lats)
self.assertEqual(fcst["latitude"].attrs["units"].lower(), "degrees north")
# and the lons
expected_lons = np.mod(np.linspace(175.0, 185.0, 21) + 180, 360) - 180
np.testing.assert_array_equal(fcst["longitude"].values, expected_lons)
self.assertEqual(fcst["longitude"].attrs["units"].lower(), "degrees east")
# and the time
expected_time = np.linspace(0, 12, 5)
expected_time = xray.conventions.decode_cf_datetime(expected_time, fcst["time"].encoding["units"])
np.testing.assert_array_equal(fcst["time"].values, expected_time)
self.assertIn("hours", fcst["time"].encoding["units"])
def test_spot_forecast(self):
some_email = "*****@*****.**"
msg = emaillib.create_email(
to="*****@*****.**", fr=some_email, body="send spot:gefs:8.53S,115.54E|8,6|wind"
)
emails = []
# use a mocked emaillib to make sure an email was sent
with self.get_request(emails) as request:
request.process_email(msg.as_string(), fail_hard=True)
assert len(emails) == 1
parser = Parser.Parser()
email = parser.parsestr(emails.pop().args[0].as_string())
# make sure we are sending responses from ensembleweather
self.assertEqual(email["From"], "*****@*****.**")
# make sure we are responding to the right person
self.assertEqual(email["To"], some_email)
# here we pull out the expected attachment
body, attach = email.get_payload()
bytes = attach.get_payload()
# inflate it back into an xray Dataset
fcst = compress.decompress_dataset(base64.b64decode(bytes))
# make sure we're actually compressing the file.
self.assertLessEqual(len(bytes), len(zlib.compress(fcst.to_netcdf())))
# make sure the lats are what we expect
np.testing.assert_array_almost_equal(fcst["latitude"].values, np.array([-8.53]), 3)
self.assertEqual(fcst["latitude"].attrs["units"].lower(), "degrees north")
# and the lons
np.testing.assert_array_almost_equal(fcst["longitude"].values, np.array([115.54]), 3)
self.assertEqual(fcst["longitude"].attrs["units"].lower(), "degrees east")
# and the time
expected_time = np.linspace(0, 192, 33)
expected_time = xray.conventions.decode_cf_datetime(expected_time, fcst["time"].encoding["units"])
np.testing.assert_array_equal(fcst["time"].values, expected_time)
self.assertIn("hours", fcst["time"].encoding["units"])
def test_gfs(self):
query = {'hours': [0., 3., 9., 24.],
'model': 'gfs',
'domain': {'N': 39.,
'S': 35,
'E': -120,
'W': -124},
'grid_delta': (1., 1.),
'variables': ['wind']}
model = grads.GFS()
gfs = model.fetch(self.temporary_fcst_path)
expected = subset.subset_dataset(gfs, query)
compressed = request.process_query(query, url=self.temporary_fcst_path)
actual = compress.decompress_dataset(compressed)
np.testing.assert_array_almost_equal(actual['x_wind'].values,
expected['x_wind'].values,
4)
np.testing.assert_array_almost_equal(actual['y_wind'].values,
expected['y_wind'].values,
4)