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comparing float equality with numpy.isclose, and other small changes. #BITBUCKET-3815.

This commit is contained in:
David Fisher 2018-11-13 15:40:53 -08:00
parent ec874ac288
commit f607ad5241
3 changed files with 21 additions and 23 deletions
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24
src/natcap/invest/crop_production_percentile.py
View File

@ -115,6 +115,7 @@ def execute(args):
Returns:
None.
"""
crop_to_landcover_table = utils.build_lookup_from_csv(
args['landcover_to_crop_table_path'], 'crop_name', to_lower=True)
@ -217,7 +218,8 @@ def execute(args):
crop_name, yield_percentile_id, file_suffix))
create_coarse_yield_percentile_task = graph.add_task(
func=pygeoprocessing.reclassify_raster,
args=((clipped_climate_bin_raster_path, 1), bin_to_percentile_yield,
args=((clipped_climate_bin_raster_path, 1),
bin_to_percentile_yield,
coarse_yield_percentile_raster_path, gdal.GDT_Float32,
_NODATA_YIELD),
target_path_list=[coarse_yield_percentile_raster_path],
@ -378,7 +380,7 @@ def _crop_production_op(
"""Mask in yields that overlap with `crop_lucode`."""
result = numpy.empty(lulc_array.shape, dtype=numpy.float32)
result[:] = _NODATA_YIELD
valid_mask = lulc_array != landcover_nodata
valid_mask = ~numpy.isclose(lulc_array, landcover_nodata)
lulc_mask = lulc_array == crop_lucode
result[valid_mask] = 0
result[lulc_mask] = (
@ -391,7 +393,7 @@ def _zero_observed_yield_op(observed_yield_array, observed_yield_nodata):
result = numpy.empty(
observed_yield_array.shape, dtype=numpy.float32)
result[:] = 0.0
valid_mask = observed_yield_array != observed_yield_nodata
valid_mask = ~numpy.isclose(observed_yield_array, observed_yield_nodata)
result[valid_mask] = observed_yield_array[valid_mask]
return result
@ -402,7 +404,7 @@ def _mask_observed_yield_op(
"""Mask total observed yield to crop lulc type."""
result = numpy.empty(lulc_array.shape, dtype=numpy.float32)
result[:] = observed_yield_nodata
valid_mask = lulc_array != landcover_nodata
valid_mask = ~numpy.isclose(lulc_array, landcover_nodata)
lulc_mask = lulc_array == crop_lucode
result[valid_mask] = 0
result[lulc_mask] = (
@ -450,9 +452,9 @@ def tabulate_results(
for _, yield_block in pygeoprocessing.iterblocks(
observed_production_raster_path):
production_pixel_count += numpy.count_nonzero(
(yield_block != observed_yield_nodata) & (yield_block > 0.0))
~numpy.isclose(yield_block, observed_yield_nodata) & (yield_block > 0.0))
yield_sum += numpy.sum(
yield_block[observed_yield_nodata != yield_block])
yield_block[~numpy.isclose(observed_yield_nodata, yield_block)])
production_area[crop_name] = production_pixel_count * pixel_area_ha
production_lookup['observed'] = yield_sum
result_table.write(',%f' % production_area[crop_name])
@ -467,7 +469,7 @@ def tabulate_results(
for _, yield_block in pygeoprocessing.iterblocks(
yield_percentile_raster_path):
yield_sum += numpy.sum(
yield_block[_NODATA_YIELD != yield_block])
yield_block[~numpy.isclose(yield_block, _NODATA_YIELD)])
production_lookup[yield_percentile_id] = yield_sum
result_table.write(",%f" % yield_sum)
@ -492,7 +494,7 @@ def tabulate_results(
for _, band_values in pygeoprocessing.iterblocks(
landcover_raster_path):
total_area += numpy.count_nonzero(
(band_values != landcover_nodata))
~numpy.isclose(band_values, landcover_nodata))
result_table.write(
'\n,total area (both crop and non-crop)\n,%f\n' % (
total_area * pixel_area_ha))
@ -658,13 +660,15 @@ def validate(args, limit_to=None):
([key], 'not found on disk'))
continue
if key_type == 'raster':
raster = gdal.OpenEx(args[key])
raster = gdal.OpenEx(
args[key], gdal.OF_RASTER | gdal.OF_READONLY)
if raster is None:
validation_error_list.append(
([key], 'not a raster'))
del raster
elif key_type == 'vector':
vector = gdal.OpenEx(args[key])
vector = gdal.OpenEx(
args[key], gdal.OF_VECTOR | gdal.OF_READONLY)
if vector is None:
validation_error_list.append(
([key], 'not a vector'))

18
src/natcap/invest/ui/crop_production.py
View File

@ -70,7 +70,7 @@ class CropProductionPercentile(model.InVESTModel):
u"sugarcane, sugarnes, sunflower, swedefor, "
u"sweetpotato, tangetc, taro, tea, tobacco, tomato, "
u"triticale, tropicalnes, tung, turnipfor, vanilla, "
u"vegetablenes, vegfor, vetch,walnut, watermelon, "
u"vegetablenes, vegfor, vetch, walnut, watermelon, "
u"wheat, yam, and yautia."),
label=u'Landcover to Crop Table (csv)',
validator=self.validator)
@ -78,11 +78,9 @@ class CropProductionPercentile(model.InVESTModel):
self.aggregate_polygon_path = inputs.File(
args_key=u'aggregate_polygon_path',
helptext=(
u"A polygon shapefile to aggregate/summarize final "
u"results. It is fine to have overlapping polygons. "
u"The attribute table must contain a keyfield for "
u"identifying polygons, be sure to indicate the name of "
u"this field in the Aggregate Polygon ID Field below."),
u"A polygon shapefile containing features with"
u"which to aggregate/summarize final results."
u"It is fine to have overlapping polygons."),
label=u'Aggregate results polygon (vector) (optional)',
validator=self.validator)
self.add_input(self.aggregate_polygon_path)
@ -156,11 +154,9 @@ class CropProductionRegression(model.InVESTModel):
self.aggregate_polygon_path = inputs.File(
args_key=u'aggregate_polygon_path',
helptext=(
u"A polygon shapefile to aggregate/summarize final "
u"results. It is fine to have overlapping polygons. "
u"The attribute table must contain a keyfield for "
u"identifying polygons, be sure to indicate the name of "
u"this field in the Aggregate Polygon ID Field below."),
u"A polygon shapefile containing features with"
u"which to aggregate/summarize final results."
u"It is fine to have overlapping polygons."),
label=u'Aggregate results polygon (vector) (optional)',
validator=self.validator)
self.add_input(self.aggregate_polygon_path)

2
tests/test_crop_production.py
View File

@ -43,7 +43,6 @@ class CropProductionTests(unittest.TestCase):
SAMPLE_DATA_PATH, 'landcover_to_crop_table.csv'),
'aggregate_polygon_path': os.path.join(
SAMPLE_DATA_PATH, 'aggregate_shape.shp'),
'aggregate_polygon_id': 'id',
'model_data_path': MODEL_DATA_PATH,
'n_workers': '-1'
}
@ -73,7 +72,6 @@ class CropProductionTests(unittest.TestCase):
self.workspace_dir, 'landcover_to_badcrop_table.csv'),
'aggregate_polygon_path': os.path.join(
SAMPLE_DATA_PATH, 'aggregate_shape.shp'),
'aggregate_polygon_id': 'id',
'model_data_path': MODEL_DATA_PATH,
'n_workers': '-1'
}