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both crop productions passing in py27 and py36. #BITBUCKET-3895

This commit is contained in:
David Fisher 2019-06-20 16:03:15 -07:00
parent 1eb651ee8c
commit 19fa82bac6
3 changed files with 15 additions and 15 deletions
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12
src/natcap/invest/crop_production_percentile.py
View File

@ -202,7 +202,7 @@ def execute(args):
crop_climate_percentile_table = utils.build_lookup_from_csv(
climate_percentile_yield_table_path, 'climate_bin', to_lower=True)
yield_percentile_headers = [
x for x in crop_climate_percentile_table.itervalues().next()
x for x in list(crop_climate_percentile_table.values())[0]
if x != 'climate_bin']
for yield_percentile_id in yield_percentile_headers:
@ -504,7 +504,7 @@ def tabulate_results(
for nutrient_id in _EXPECTED_NUTRIENT_TABLE_HEADERS
for yield_percentile_id in sorted(yield_percentile_headers) + [
'yield_observed']]
with open(target_table_path, 'wb') as result_table:
with open(target_table_path, 'w') as result_table:
result_table.write(
'crop,area (ha),' + 'production_observed,' +
','.join(production_percentile_headers) + ',' + ','.join(
@ -668,7 +668,7 @@ def aggregate_to_polygons(
nutrient_table[crop_name][nutrient_id])
# report everything to a table
with open(target_aggregate_table_path, 'wb') as aggregate_table:
with open(target_aggregate_table_path, 'w') as aggregate_table:
# write header
aggregate_table.write('FID,')
aggregate_table.write(','.join(sorted(total_yield_lookup)) + ',')
@ -677,11 +677,11 @@ def aggregate_to_polygons(
'%s_%s' % (nutrient_id, model_type)
for nutrient_id in _EXPECTED_NUTRIENT_TABLE_HEADERS
for model_type in sorted(
total_nutrient_table.itervalues().next())]))
list(total_nutrient_table.values())[0])]))
aggregate_table.write('\n')
# iterate by polygon index
for id_index in total_yield_lookup.itervalues().next():
for id_index in list(total_yield_lookup.values())[0]:
aggregate_table.write('%s,' % id_index)
aggregate_table.write(','.join([
str(total_yield_lookup[yield_header][id_index]['sum'])
@ -689,7 +689,7 @@ def aggregate_to_polygons(
for nutrient_id in _EXPECTED_NUTRIENT_TABLE_HEADERS:
for model_type in sorted(
total_nutrient_table.itervalues().next()):
list(total_nutrient_table.values())[0]):
aggregate_table.write(
',%s' % total_nutrient_table[
nutrient_id][model_type][id_index])

14
src/natcap/invest/crop_production_regression.py
View File

@ -192,7 +192,7 @@ def execute(args):
crop_lucodes = [
x[_EXPECTED_LUCODE_TABLE_HEADER]
for x in crop_to_landcover_table.itervalues()]
for x in crop_to_landcover_table.values()]
unique_lucodes = numpy.array([])
for _, lu_band_data in pygeoprocessing.iterblocks(
@ -280,7 +280,7 @@ def execute(args):
crop_regression_table[bin_id][header.lower()] = 0.0
yield_regression_headers = [
x for x in crop_regression_table.itervalues().next()
x for x in list(crop_regression_table.values())[0]
if x != 'climate_bin']
regression_parameter_raster_path_lookup = {}
@ -637,7 +637,7 @@ def tabulate_regression_results(
nutrient_id + '_' + mode
for nutrient_id in _EXPECTED_NUTRIENT_TABLE_HEADERS
for mode in ['modeled', 'observed']]
with open(target_table_path, 'wb') as result_table:
with open(target_table_path, 'w') as result_table:
result_table.write(
'crop,area (ha),' + 'production_observed,production_modeled,' +
','.join(nutrient_headers) + '\n')
@ -790,7 +790,7 @@ def aggregate_regression_results_to_polygons(
# report everything to a table
aggregate_table_path = os.path.join(
output_dir, _AGGREGATE_TABLE_FILE_PATTERN % file_suffix)
with open(aggregate_table_path, 'wb') as aggregate_table:
with open(aggregate_table_path, 'w') as aggregate_table:
# write header
aggregate_table.write('FID,')
aggregate_table.write(','.join(sorted(total_yield_lookup)) + ',')
@ -799,11 +799,11 @@ def aggregate_regression_results_to_polygons(
'%s_%s' % (nutrient_id, model_type)
for nutrient_id in _EXPECTED_NUTRIENT_TABLE_HEADERS
for model_type in sorted(
total_nutrient_table.itervalues().next())]))
list(total_nutrient_table.values())[0])]))
aggregate_table.write('\n')
# iterate by polygon index
for id_index in total_yield_lookup.itervalues().next():
for id_index in list(total_yield_lookup.values())[0]:
aggregate_table.write('%s,' % id_index)
aggregate_table.write(','.join([
str(total_yield_lookup[yield_header][id_index]['sum'])
@ -811,7 +811,7 @@ def aggregate_regression_results_to_polygons(
for nutrient_id in _EXPECTED_NUTRIENT_TABLE_HEADERS:
for model_type in sorted(
total_nutrient_table.itervalues().next()):
list(total_nutrient_table.values())[0]):
aggregate_table.write(
',%s' % total_nutrient_table[
nutrient_id][model_type][id_index])

4
tests/test_crop_production.py
View File

@ -150,7 +150,7 @@ class CropProductionTests(unittest.TestCase):
}
with open(args['landcover_to_crop_table_path'],
'wb') as landcover_crop_table:
'w') as landcover_crop_table:
landcover_crop_table.write(
'crop_name,lucode\nfakecrop,20\n')
@ -181,7 +181,7 @@ class CropProductionTests(unittest.TestCase):
}
with open(args['landcover_to_crop_table_path'],
'wb') as landcover_crop_table:
'w') as landcover_crop_table:
landcover_crop_table.write(
'crop_name,lucode\nfakecrop,20\n')