def test_export2tiff_mask_tuple_string(self):
eop = EOPatch.load(self.PATCH_FILENAME)
dates = np.array(eop.timestamp)
mask = np.arange(len(dates) * 3 * 2 * 1).reshape(len(dates), 3, 2, 1)
eop.mask['mask'] = mask
indices = [2, 4]
# day time gets floored
times = (datetime_to_iso(dates[indices[0]]),
datetime_to_iso(dates[indices[1]]))
selection = np.nonzero(
np.where((dates >= iso_to_datetime(times[0])) &
(dates <= iso_to_datetime(times[1])), dates, 0))
subset = mask[selection].squeeze()
with tempfile.TemporaryDirectory() as tmp_dir_name:
tmp_file_name = 'temp_file.tiff'
task = ExportToTiff((FeatureType.MASK, 'mask'),
folder=tmp_dir_name,
date_indices=times)
task.execute(eop, filename=tmp_file_name)
# rasterio saves `bands` to the last dimension, move it up front
raster = read_data(os.path.join(tmp_dir_name, tmp_file_name))
raster = np.moveaxis(raster, -1, 0)
self.assertTrue(np.all(subset == raster))
def _build_payloads(self, bbox, size_x, size_y, timestamp, time_interval):
""" Build payloads for the requests to the service
"""
if self.single_scene:
dates = [(iso_to_datetime(time_interval[0]), iso_to_datetime(time_interval[1]))]
else:
dates = [(date - self.time_difference, date + self.time_difference) for date in timestamp]
return [self._request_payload(date1, date2, bbox, size_x, size_y) for date1, date2 in dates]
def _build_requests(self, bbox, size_x, size_y, timestamp, time_interval):
""" Build requests
"""
if self.single_scene:
dates = [(iso_to_datetime(time_interval[0]),
iso_to_datetime(time_interval[1]))]
else:
dates = [(date - self.time_difference, date + self.time_difference)
for date in timestamp]
return [
self._create_sh_request(date1, date2, bbox, size_x, size_y)
for date1, date2 in dates
]
def _add_meta_info(self, eopatch, request_params, service_type):
""" Adds any missing metadata info to EOPatch """
for param, eoparam in zip(
['time', 'time_difference', 'maxcc'],
['time_interval', 'time_difference', 'maxcc']):
if eoparam not in eopatch.meta_info:
if param == 'time':
value = request_params[param]
eopatch.meta_info[eoparam] = value if isinstance(
value, str) else [
iso_to_datetime(parse_time(x)) if isinstance(
x, str) else x for x in value
]
else:
eopatch.meta_info[eoparam] = request_params[param]
if 'service_type' not in eopatch.meta_info:
eopatch.meta_info['service_type'] = service_type.value
for param in ['size_x', 'size_y']:
if param not in eopatch.meta_info:
eopatch.meta_info[param] = getattr(self, param)
if eopatch.bbox is None:
eopatch.bbox = request_params['bbox']
def test_iso_to_datetime(self):
test_pairs = [
('2018-01-01', datetime.datetime(2018, 1, 1)),
('2017-02-28', datetime.datetime(2017, 2, 28))
]
for date_str, date_dt in test_pairs:
with self.subTest(msg=date_str):
res_dt = time_utils.iso_to_datetime(date_str)
self.assertEqual(res_dt, date_dt,
msg='Expected {}, got {}'.format(date_dt, res_dt))
def _update_other_data(self, eopatch):
if 'time_interval' in eopatch.meta_info:
start_time, end_time = [iso_to_datetime(x) if isinstance(x, str)
else x for x in eopatch.meta_info['time_interval']]
eopatch.meta_info['time_interval'] = (max(start_time, self.start_date),
min(end_time, self.end_date))
return eopatch
def _get_dates_subset(self, array, dates):
dates = np.array(dates)
if isinstance(self.date_indices, list):
if [
date for date in self.date_indices
if not isinstance(date, int)
]:
raise ValueError(
'Invalid format in {} list, expected integers'.format(
self.date_indices))
array_sub = array[np.array(self.date_indices)]
elif isinstance(self.date_indices, tuple):
if tuple(map(type, self.date_indices)) == (int, int):
start_date = dates[self.date_indices[0]]
end_date = dates[self.date_indices[1]]
elif tuple(map(type, self.date_indices)) == (str, str):
start_date = iso_to_datetime(self.date_indices[0])
end_date = iso_to_datetime(self.date_indices[1])
elif tuple(map(type, self.date_indices)) == (datetime.datetime,
datetime.datetime):
start_date = self.date_indices[0]
end_date = self.date_indices[1]
else:
raise ValueError(
'Invalid format in {} tuple, expected ints, strings, or datetimes'
.format(self.date_indices))
array_sub = array[np.nonzero(
np.where((dates >= start_date) & (dates <= end_date), dates,
0))[0]]
else:
raise ValueError(
'Invalid format in {}, expected tuple or list'.format(
self.date_indices))
return array_sub
def fis_data_to_df(fis_data):
"""Creates a pd.DataFrame from list of FIS responses"""
COLUMNS = ['channel', 'date', 'min', 'max', 'mean', 'stDev']
data = []
for fis_response in fis_data:
for channel, channel_stats in fis_response.items():
for stat in channel_stats:
row = [int(channel[1:]), iso_to_datetime(stat['date'])]
for column in COLUMNS[2:]:
row.append(stat['basicStats'][column])
data.append(row)
return pd.DataFrame(data, columns=COLUMNS).sort_values(['channel', 'date'])
def test_time_interval(self):
for task in self.task_cases:
with self.subTest(msg='Test case {}'.format(task.name)):
self.assertEqual(
task.eop.meta_info['time_interval'],
[iso_to_datetime(x) for x in ('2017-1-1', '2018-1-1')])
