def test(self):
s = self.session
dao = SA_Result_DAO(session = s)
# Drop/Create tables.
sa_metadata.metadata.drop_all(s.bind)
sa_metadata.metadata.create_all(s.bind)
s.commit()
# Generate test result set.
results = results_util.generate_results()
## Merge generated objects for testing.
for o_key, o in util_registry.object_registry.items():
try:
if not o_key[0] in ['Result']:
s.add(o)
except: pass
s.commit()
# Test DAO operations.
dao.save_results(results)
fetched_results = dao.get_results(filters=[
{
'field': 'tag',
'op': '==',
'value': 'a'
}
])
result_field = {
'field': 'a',
'aggregate_funcs': ['sum']
}
mapserver_data_string = dao.get_mapserver_data_string(result_field=result_field)
print mapserver_data_string
self.failUnless(True)
def main():
output_dir = '/home/adorsk/projects/sasi/sasi_model/outputs/shapefiles'
result_tag = 'gc30_all'
t = 1999
# Get result dao.
db_session = sa_session.get_session()
result_dao = SA_Result_DAO(session=db_session)
# Get values by time, cell, and field for results.
values_by_t_c_f = result_dao.get_values_by_t_c_f(filters=[
{'attr': 'tag', 'op': '==', 'value': result_tag},
{'attr': 'time', 'op': '==', 'value': t}
])
#
# Make fiona collection from result set.
#
# Define schema.
geometry_type = 'MultiPolygon'
schema = {
'geometry': geometry_type,
'properties': {
'type_id': 'str',
'hab_type': 'str'
}
}
generic_attrs = ['A', 'Y', 'X', 'Z', 'ZZ']
for generic_attr in generic_attrs: schema['properties'][generic_attr] = 'float'
# Write shpfile.
filename = "%s/%s.%s.shp" % (output_dir, result_tag, t)
driver = 'ESRI Shapefile'
crs = {'init': "epsg:4326"}
with collection(
filename, "w",
driver=driver,
schema=schema,
crs=crs
) as c:
record_counter = 1
for cell, cell_fields in values_by_t_c_f[t].items():
if (record_counter % 1000) == 0:
print >> sys.stderr, "%s" % record_counter
# Populate record properties.
habitat_types = set(["(%s)" % h.habitat_type.id for h in cell.habitats])
properties = {
'type_id': cell.type_id,
'hab_type': ' & '.join(habitat_types)
}
for generic_attr in generic_attrs:
properties[generic_attr] = cell_fields.get(generic_attr,0.0)
# Populate record geometry.
wkb_geom = "%s" % cell.geom.geom_wkb
geometry = GeomBuilder().build_wkb(wkb_geom)
# Assemble the record.
record = {
'id': record_counter,
'geometry': geometry,
'properties': properties
}
# Write the record.
c.write(record)
record_counter += 1
from datetime import datetime
import sys
import sasi.util.sasi_model as sasi_model_util
if __name__ == '__main__':
conf.conf['verbose'] = True
db_session = sa_session.get_session()
#db_session.bind.echo = True
result_dao = SA_Result_DAO(session=db_session)
effort_dao = SA_Effort_DAO(session=db_session)
#t0 = 1989
t0 = 2008
tf = 2010
dt = 1
times = range(t0,tf+1,dt)
#grid_model = StaticGridModel(cell_dao=SA_Cell_DAO(session=db_session), default_filters=[{'field': 'type','op': '==', 'value': 'km100' }, {'field': 'type_id', 'op': '==', 'value': '817'}])
grid_model = StaticGridModel(cell_dao=SA_Cell_DAO(session=db_session), default_filters=[{'field': 'type','op': '==', 'value': 'km100'} ])
# Filter domain for cells w/ depth less than 138 (for G3).
#grid_model = StaticGridModel(cell_dao=SA_Cell_DAO(session=db_session), default_filters=[{'field': 'type','value': ['km100'] }, {'field': 'depth', 'op': '>=', 'value': -138}])