def bbox(self, south_west, north_east, start='0001-01-01T00:00:00Z',
end=None, groundwater_type="GWmMSL"):
if not end:
self.end = jsdt.now_iso()
else:
self.end = end
self.start = start
self.ts.queries = {"name": groundwater_type}
self.locs.bbox(south_west, north_east)
self.ts.bbox(south_west=south_west, north_east=north_east,
start=start, end=self.end)
def bbox(self,
start='0001-01-01T00:00:00Z',
end=None):
if end:
self.end = end
else:
self.end = jsdt.now_iso()
self.start = start
self.locs.bbox()
self.ts.bbox(start=start,
end=self.end)
def uuid(self, uuid, start='0001-01-01T00:00:00Z', end=None):
"""
Returns time series for a location by location-UUID.
:param uuid: name of a location
:param start: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format
:return: a dictionary of with nested location, aquo quantities and
events.
"""
if not end:
end = jsdt.now_iso()
self.get(uuid=uuid, start=start, end=end)
def bbox(self,
start='0001-01-01T00:00:00Z',
end=None,
groundwater_type="GWmMSL"):
if end:
self.end = end
else:
self.end = jsdt.now_iso()
self.start = start
self.ts.queries = {"name": groundwater_type}
self.locs.bbox()
self.ts.bbox(start=start,
end=self.end)
def uuid(self, ts_uuid, start='0001-01-01T00:00:00Z', end=None,
organisation=None):
"""
Returns time series for a timeseries by timeseries-UUID.
:param ts_uuid: uuid of a timeseries
:param start: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format
:return: a dictionary of with nested location, aquo quantities and
events.
"""
if not end:
end = jsdt.now_iso()
old_base_url = self.base_url
self.base_url += ts_uuid + "/"
org_query = self.organisation_query(organisation)
self.get(start=start, end=end, **org_query)
self.base_url = old_base_url
def all_to_csv(self, start='0001-01-01T00:00:00Z', end=None,
organisation=None):
if not end:
end = jsdt.now_iso()
if isinstance(start, int):
start -= 10000
if isinstance(end, int):
end += 10000
org_query = self.organisation_query(organisation)
self.get(
start=start,
end=end,
**org_query
)
csv = (
[r['name'], r['uuid'], jsdt.js_to_datestring(e['timestamp']), e['max']] for r
in self.results for e in r['events']
)
loc = Locations(use_header=self.use_header)
extra_queries_ts = copy.deepcopy(self.extra_queries).items()
extra_queries = {
key if not key.startswith("location__") else key[10:]: value
for key, value in extra_queries_ts
}
org_query = self.organisation_query(organisation, '')
extra_queries.update(**org_query)
loc.get(**extra_queries)
coords = loc.coord_uuid_name()
headers = (
[
r['uuid'], r['name'], coords[r['location']['uuid']]['name'],
coords[r['location']['uuid']]['coordinates'][0],
coords[r['location']['uuid']]['coordinates'][1]
]
for r in self.results
)
return headers, csv
def bbox(self, south_west, north_east, statistic=None,
start='0001-01-01T00:00:00Z', end=None):
"""
Find all timeseries within a certain bounding box.
Returns records within bounding box using Bounding Box format (min Lon,
min Lat, max Lon, max Lat). Also returns features with overlapping
geometry.
:param south_west: lattitude and longtitude of the south-western point
:param north_east: lattitude and longtitude of the north-eastern point
:param start: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format
:return: a dictionary of the api-response.
"""
self.statistic = statistic
if statistic == 'mean':
statistic = ['count', 'sum']
if not statistic:
statistic = ['min', 'max', 'count', 'sum']
self.statistic = None
if not end:
end = jsdt.now_iso()
min_lat, min_lon = south_west
max_lat, max_lon = north_east
polygon_coordinates = [
[min_lon, min_lat],
[min_lon, max_lat],
[max_lon, max_lat],
[max_lon, min_lat],
[min_lon, min_lat],
]
points = ['%20'.join([str(x), str(y)]) for x, y in polygon_coordinates]
geom_within = 'POLYGON%20((' + ',%20'.join(points) + '))'
self.get(start=start, end=end, min_points=1, fields=statistic,
location__geom_within=geom_within)
def bbox(self, south_west, north_east, statistic=None,
start='0001-01-01T00:00:00Z', end=None, organisation=None):
"""
Find all timeseries within a certain bounding box.
Returns records within bounding box using Bounding Box format (min Lon,
min Lat, max Lon, max Lat). Also returns features with overlapping
geometry.
:param south_west: lattitude and longtitude of the south-western point
:param north_east: lattitude and longtitude of the north-eastern point
:param start_: start timestamp in ISO 8601 format
:param end: end timestamp in ISO 8601 format
:return: a dictionary of the api-response.
"""
if not end:
end = jsdt.now_iso()
if isinstance(start, int):
start -= 10000
if isinstance(end, int):
end += 10000
min_lat, min_lon = south_west
max_lat, max_lon = north_east
polygon_coordinates = [
[min_lon, min_lat],
[min_lon, max_lat],
[max_lon, max_lat],
[max_lon, min_lat],
[min_lon, min_lat],
]
points = [' '.join([str(x), str(y)]) for x, y in polygon_coordinates]
geom_within = {'a': 'POLYGON ((' + ', '.join(points) + '))'}
geom_within = urllib.parse.urlencode(geom_within).split('=')[1]
org_query = self.organisation_query(organisation)
self.statistic = statistic
if statistic == 'mean':
statistic = ['count', 'sum']
elif not statistic:
statistic = ['min', 'max', 'count', 'sum']
self.statistic = None
elif statistic == 'range (max - min)':
statistic = ['min', 'max']
elif statistic == 'difference (last - first)':
statistic = 'count'
elif statistic == 'difference (mean last - first year)':
year = dt.timedelta(days=366)
first_end = jsdt.datetime_to_js(jsdt.js_to_datetime(start) + year)
last_start = jsdt.datetime_to_js(jsdt.js_to_datetime(end) - year)
self.get(
start=start,
end=first_end,
min_points=1,
fields=['count', 'sum'],
location__geom_within=geom_within,
**org_query
)
first_year = {}
for r in self.results:
try:
first_year[r['location']['uuid']] = {
'first_value_timestamp': r['first_value_timestamp'],
'mean': r['events'][0]['sum'] / r['events'][0]['count']
}
except IndexError:
first_year[r['location']['uuid']] = {
'first_value_timestamp': np.nan,
'mean': np.nan
}
self.results = []
self.get(
start=last_start,
end=end,
min_points=1,
fields=['count', 'sum'],
location__geom_within=geom_within,
**org_query
)
for r in self.results:
try:
r['events'][0]['difference (mean last - first year)'] = \
r['events'][0]['sum'] / r['events'][0]['count'] - \
first_year[r['location']['uuid']]['mean']
r['first_value_timestamp'] = \
first_year[
r['location']['uuid']]['first_value_timestamp']
except IndexError:
r['events'] = [{
'difference (mean last - first year)': np.nan}]
r['first_value_timestamp'] = np.nan
r['last_value_timestamp'] = np.nan
return
self.get(
start=start,
end=end,
min_points=1,
fields=statistic,
location__geom_within=geom_within,
**org_query
)