def calc(self, request, **args):
min_lat, max_lat, min_lon, max_lon = request.get_min_lat(
), request.get_max_lat(), request.get_min_lon(), request.get_max_lon()
dataset1 = request.get_argument("ds1", None)
dataset2 = request.get_argument("ds2", None)
start_time = request.get_start_time()
end_time = request.get_end_time()
simple = request.get_argument("simple", None) is not None
averagebyday = self.get_daily_difference_average_for_box(
min_lat, max_lat, min_lon, max_lon, dataset1, dataset2, start_time,
end_time)
averagebyday = sorted(averagebyday, key=lambda dayavg: dayavg[0])
if simple:
import matplotlib.pyplot as plt
from matplotlib.dates import date2num
times = [
date2num(self.date_from_ms(dayavg[0]))
for dayavg in averagebyday
]
means = [dayavg[1] for dayavg in averagebyday]
plt.plot_date(times, means, ls='solid')
plt.xlabel('Date')
plt.xticks(rotation=70)
plt.ylabel(u'Difference from 5-Day mean (\u00B0C)')
plt.title('Sea Surface Temperature (SST) Anomalies')
plt.grid(True)
plt.tight_layout()
plt.savefig("test.png")
return averagebyday, None, None
else:
result = NexusResults(results=[[{
'time': dayms,
'mean': avg,
'ds': 0
}] for dayms, avg in averagebyday],
stats={},
meta=self.get_meta())
result.extendMeta(min_lat, max_lat, min_lon, max_lon, "",
start_time, end_time)
result.meta()['label'] = u'Difference from 5-Day mean (\u00B0C)'
return result
def calc(self, computeOptions, **args):
minLat = computeOptions.get_min_lat()
maxLat = computeOptions.get_max_lat()
minLon = computeOptions.get_min_lon()
maxLon = computeOptions.get_max_lon()
ds = computeOptions.get_dataset()[0]
startTime = computeOptions.get_start_time()
endTime = computeOptions.get_end_time()
res = self._tile_service.find_tiles_in_box(minLat,
maxLat,
minLon,
maxLon,
ds,
startTime,
endTime,
fetch_data=False)
res = NexusResults(results=res)
res.extendMeta(minLat, maxLat, minLon, maxLon, ds, startTime, endTime)
return res
def calc(self, compute_options, **args):
min_lat = compute_options.get_min_lat()
max_lat = compute_options.get_max_lat()
min_lon = compute_options.get_min_lon()
max_lon = compute_options.get_max_lon()
ds = compute_options.get_dataset()[0]
start_time = compute_options.get_start_time()
end_time = compute_options.get_end_time()
includemeta = compute_options.get_include_meta()
tiles = self._tile_service.get_tiles_bounded_by_box(
min_lat, max_lat, min_lon, max_lon, ds, start_time, end_time)
data = []
for tile in tiles:
for nexus_point in tile.nexus_point_generator():
data.append({
'latitude':
nexus_point.latitude,
'longitude':
nexus_point.longitude,
'time':
nexus_point.time,
'data': [{
'id': tile.tile_id,
'value': nexus_point.data_val
}]
})
if includemeta and len(tiles) > 0:
meta = [tile.get_summary() for tile in tiles]
else:
meta = None
result = NexusResults(results=data, stats={}, meta=meta)
result.extendMeta(min_lat, max_lat, min_lon, max_lon, "", start_time,
end_time)
return result
def calc(self, computeOptions, **args):
minLat = computeOptions.get_min_lat()
maxLat = computeOptions.get_max_lat()
minLon = computeOptions.get_min_lon()
maxLon = computeOptions.get_max_lon()
ds = computeOptions.get_dataset()[0]
startTime = computeOptions.get_start_time()
endTime = computeOptions.get_end_time()
# TODO update to expect tile objects back
res = [
tile.get_summary()
for tile in self._tile_service.find_tiles_in_box(minLat,
maxLat,
minLon,
maxLon,
ds,
startTime,
endTime,
fetch_data=False)
]
res = NexusResults(results=res)
res.extendMeta(minLat, maxLat, minLon, maxLon, ds, startTime, endTime)
return res
