def main(argv):
heat_d, h2o_d = get_climate_data()
irrigation_d = get_irrigation_data()
the_db.query(queries.starch_query)
data = the_db.store_result().fetch_row(how=1, maxrows=0)
data = [DO.StarchData(d.keys(), d.values()) for d in data]
golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
'sub_id')
dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
'sub_id')
field_data = [d for d in data if d.location_id in FIELD_TRIALS]
jki_gh_data = CD1.group_by([d for d in data if d.location_id == 6019],
'sub_id')
jki_sh_data = CD1.group_by([d for d in data if d.location_id == 6020],
'sub_id')
jki_gh_results = CD1.compute_starch_rel_ctrl(jki_gh_data, 6019,
[CD1.DROUGHT_ID])
jki_sh_results = CD1.compute_starch_rel_ctrl(jki_sh_data, 6020,
[CD1.DROUGHT_ID])
golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537,
[CD1.DROUGHT_ID])
dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
CD1.DETHLINGEN_DROUGHT_IDS)
field_results = CD1.compute_starch_rel_field(field_data,
FIELD_TRIALS, CD1.DROUGHT_ID)
all_results = [(jki_gh_results, 'JKI_CGW'),
(jki_sh_results, 'JKI_SHE'),
(golm_results, 'MPI_FIELD'),
(dethl_results, 'DET_FIELD'),
(field_results, 'ALL_FIELD')]
"""
compiled = {}
# compiled.update(golm_results)
compiled.update(dethl_results)
# compiled.update(field_results)
# compiled.update(jki_sh_results)
# compiled.update(jki_gh_results)
"""
for data, name in all_results:
print name
annotate_compiled_data(data, heat_d, h2o_d, irrigation_d)
WT.write_table(data, WT.FIELDS,
out=open('STARCH_REL_%s.csv' % name, 'w'))
return None
"""
def main(argv):
"""
Climate data
"""
the_db.query(queries.climate_query)
climate_data = the_db.store_result().fetch_row(how=1, maxrows=0)
climate_data = [DO.ClimateData(d.keys(), d.values())
for d in climate_data]
heat_d, h2o_d = CD1.compute_climate_data(climate_data)
# print heat_d
# return None
the_db.query(queries.starch_query)
data = the_db.store_result().fetch_row(how=1, maxrows=9999999)
data = [DO.StarchData(d.keys(), d.values()) for d in data]
golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
'sub_id')
dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
'sub_id')
field_data = [d for d in data if d.location_id in FIELD_TRIALS]
golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537,
[CD1.DROUGHT_ID])
dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
CD1.DETHLINGEN_DROUGHT_IDS)
field_results = CD1.compute_starch_rel_field(field_data,
FIELD_TRIALS, CD1.DROUGHT_ID)
# print field_results
compiled = {}
# compiled.update(golm_results)
# compiled.update(dethl_results)
compiled.update(field_results)
for k, v in sorted(compiled.items()):
if isinstance(k, str): continue
# print k
compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
compiled[k].limsloc = k[0]
compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]
# print v
# print heat_d
WT.write_table(compiled, WT.FIELDS)
return None
"""
def main(argv):
heat_d, h2o_d = get_climate_data()
irrigation_d = get_irrigation_data()
the_db.query(queries.starch_query)
data = the_db.store_result().fetch_row(how=1, maxrows=0)
data = [DO.StarchData(d.keys(), d.values()) for d in data]
golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
'sub_id')
dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
'sub_id')
field_data = [d for d in data if d.location_id in FIELD_TRIALS]
jki_gh_data = CD1.group_by([d for d in data if d.location_id == 6019],
'sub_id')
jki_sh_data = CD1.group_by([d for d in data if d.location_id == 6020],
'sub_id')
jki_gh_results = CD1.compute_starch_rel_ctrl(jki_gh_data, 6019,
[CD1.DROUGHT_ID])
jki_sh_results = CD1.compute_starch_rel_ctrl(jki_sh_data, 6020,
[CD1.DROUGHT_ID])
golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537,
[CD1.DROUGHT_ID])
dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
CD1.DETHLINGEN_DROUGHT_IDS)
field_results = CD1.compute_starch_rel_field(field_data, FIELD_TRIALS,
CD1.DROUGHT_ID)
all_results = [(jki_gh_results, 'JKI_CGW'), (jki_sh_results, 'JKI_SHE'),
(golm_results, 'MPI_FIELD'), (dethl_results, 'DET_FIELD'),
(field_results, 'ALL_FIELD')]
"""
compiled = {}
# compiled.update(golm_results)
compiled.update(dethl_results)
# compiled.update(field_results)
# compiled.update(jki_sh_results)
# compiled.update(jki_gh_results)
"""
for data, name in all_results:
print name
annotate_compiled_data(data, heat_d, h2o_d, irrigation_d)
WT.write_table(data,
WT.FIELDS,
out=open('STARCH_REL_%s.csv' % name, 'w'))
return None
"""
def main(argv):
"""
Climate data
"""
the_db.query(queries.climate_query)
climate_data = the_db.store_result().fetch_row(how=1, maxrows=0)
climate_data = [DO.ClimateData(d.keys(), d.values()) for d in climate_data]
heat_d, h2o_d = CD1.compute_climate_data(climate_data)
# print heat_d
# return None
the_db.query(queries.starch_query)
data = the_db.store_result().fetch_row(how=1, maxrows=9999999)
data = [DO.StarchData(d.keys(), d.values()) for d in data]
golm_data = CD1.group_by([d for d in data if d.location_id == 4537],
'sub_id')
dethl_data = CD1.group_by([d for d in data if d.location_id == 5519],
'sub_id')
field_data = [d for d in data if d.location_id in FIELD_TRIALS]
golm_results = CD1.compute_starch_rel_ctrl(golm_data, 4537,
[CD1.DROUGHT_ID])
dethl_results = CD1.compute_starch_rel_ctrl(dethl_data, 5519,
CD1.DETHLINGEN_DROUGHT_IDS)
field_results = CD1.compute_starch_rel_field(field_data, FIELD_TRIALS,
CD1.DROUGHT_ID)
# print field_results
compiled = {}
# compiled.update(golm_results)
# compiled.update(dethl_results)
compiled.update(field_results)
for k, v in sorted(compiled.items()):
if isinstance(k, str): continue
# print k
compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
compiled[k].limsloc = k[0]
compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]
# print v
# print heat_d
WT.write_table(compiled, WT.FIELDS)
return None
"""
def main(argv):
heat_d, h2o_d = CD2.get_climate_data()
the_db.query(daisy_query)
data = the_db.store_result().fetch_row(how=1, maxrows=0)
data = [DO.StarchData(d.keys(), d.values()) for d in data]
field_data = [d for d in data if d.location_id in CD2.FIELD_TRIALS]
# print field_data
field_results = CD1.compute_starch_rel_field(field_data,
CD2.FIELD_TRIALS, CD1.DROUGHT_ID)
compiled = {}
compiled.update(field_results)
for k, v in sorted(compiled.items()):
if isinstance(k, str): continue
compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
compiled[k].limsloc = k[0]
compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]
WT.write_table(compiled, WT.FIELDS)
return None
def main(argv):
heat_d, h2o_d = CD2.get_climate_data()
the_db.query(daisy_query)
data = the_db.store_result().fetch_row(how=1, maxrows=0)
data = [DO.StarchData(d.keys(), d.values()) for d in data]
field_data = [d for d in data if d.location_id in CD2.FIELD_TRIALS]
# print field_data
field_results = CD1.compute_starch_rel_field(field_data, CD2.FIELD_TRIALS,
CD1.DROUGHT_ID)
compiled = {}
compiled.update(field_results)
for k, v in sorted(compiled.items()):
if isinstance(k, str): continue
compiled[k].heat_sum, compiled[k].heat_nmeasures = heat_d[k[0]]
compiled[k].limsloc = k[0]
compiled[k].precipitation, compiled[k].prec_nmeasures = h2o_d[k[0]]
WT.write_table(compiled, WT.FIELDS)
return None