Flake 8 changes

Author: cgmorton

openet/core/api.py

@@ -1,4 +1,4 @@
-import sys
+# import sys
 
 import ee
 
@@ -22,7 +22,7 @@ def collection(
         t_interval,
         geometry,
         **kwargs
-    ):
+        ):
     """Generic OpenET Collection
 
     Parameters

openet/core/common.py

@@ -1,6 +1,3 @@
-import re
-import warnings
-
 import ee
 
 
@@ -547,4 +544,3 @@ def ged_emis(ged_col):
 
     return L8_LST.rename('surface_temperature')
     #     .set('system:time_start', image.get('system:time_start'))
-

openet/core/ensemble.py

@@ -1,9 +1,7 @@
-import pprint
-
 import ee
 
-from . import utils
-# import openet.core.utils as utils
+# from . import utils
+# # import openet.core.utils as utils
 
 model_index = {
     'disalexi': 1,

openet/core/interpolate.py

@@ -2,14 +2,20 @@
 import logging
 
 import ee
-from dateutil.relativedelta import *
+from dateutil.relativedelta import relativedelta
 
 from . import utils
 # import openet.core.utils as utils
 
 
-def daily(target_coll, source_coll, interp_days=32, interp_method='linear',
-          use_joins=False, compute_product=False):
+def daily(
+        target_coll,
+        source_coll,
+        interp_days=32,
+        interp_method='linear',
+        use_joins=False,
+        compute_product=False
+        ):
     """Interpolate non-daily source images to a daily target image collection
 
     Parameters
@@ -252,8 +258,12 @@ def aggregate_daily(image_coll, start_date=None, end_date=None,
     return aggregate_to_daily(image_coll, start_date, end_date, agg_type)
 
 
-def aggregate_to_daily(image_coll, start_date=None, end_date=None,
-                       agg_type='mean'):
+def aggregate_to_daily(
+        image_coll,
+        start_date=None,
+        end_date=None,
+        agg_type='mean'
+        ):
     """Aggregate images by day without using joins
 
     The primary purpose of this function is to join separate Landsat images
@@ -288,10 +298,12 @@ def aggregate_to_daily(image_coll, start_date=None, end_date=None,
         test_coll = image_coll.filterDate(ee.Date(start_date), ee.Date(end_date))
     elif start_date:
         test_coll = image_coll.filter(ee.Filter.greaterThanOrEquals(
-            'system:time_start', ee.Date(start_date).millis()))
+            'system:time_start', ee.Date(start_date).millis()
+        ))
     elif end_date:
         test_coll = image_coll.filter(ee.Filter.lessThan(
-            'system:time_start', ee.Date(end_date).millis()))
+            'system:time_start', ee.Date(end_date).millis()
+        ))
     else:
         test_coll = image_coll
 
@@ -321,10 +333,15 @@ def aggregate_func(date_str):
     return ee.ImageCollection(date_list.map(aggregate_func))
 
 
-def from_scene_et_fraction(scene_coll, start_date, end_date, variables,
-                           interp_args, model_args, t_interval,
-                           use_joins=False,
-                           ):
+def from_scene_et_fraction(
+        scene_coll,
+        start_date, end_date,
+        variables,
+        interp_args,
+        model_args,
+        t_interval,
+        use_joins=False,
+        ):
     """Interpolate from a precomputed collection of Landsat ET fraction scenes
 
     Parameters
@@ -521,8 +538,10 @@ def et_reference_adjust(input_img):
     # For count, compute the composite/mosaic image for the mask band only
     if 'count' in variables:
         aggregate_coll = aggregate_to_daily(
-            image_coll = scene_coll.select(['mask']),
-            start_date=start_date, end_date=end_date)
+            image_coll=scene_coll.select(['mask']),
+            start_date=start_date,
+            end_date=end_date,
+        )
 
         # The following is needed because the aggregate collection can be
         #   empty if there are no scenes in the target date range but there
@@ -531,13 +550,15 @@ def et_reference_adjust(input_img):
         #   bands will be which causes a non-homogeneous image collection.
         aggregate_coll = aggregate_coll.merge(
             ee.Image.constant(0).rename(['mask'])
-                .set({'system:time_start': ee.Date(start_date).millis()}))
+            .set({'system:time_start': ee.Date(start_date).millis()})
+        )
 
     # Interpolate to a daily time step
     daily_coll = daily(
         target_coll=daily_et_ref_coll,
         source_coll=scene_coll.select(interp_vars),
-        interp_method=interp_method, interp_days=interp_days,
+        interp_method=interp_method,
+        interp_days=interp_days,
         use_joins=use_joins,
         compute_product=False,
     )
@@ -554,8 +575,7 @@ def et_reference_adjust(input_img):
     # if 'et' in variables or 'et_fraction' in variables:
     def compute_et(img):
         """This function assumes ETr and ETf are present"""
-        et_img = img.select(['et_fraction']) \
-            .multiply(img.select(['et_reference']))
+        et_img = img.select(['et_fraction']).multiply(img.select(['et_reference']))
         return img.addBands(et_img.double().rename('et'))
     daily_coll = daily_coll.map(compute_et)
 
@@ -598,8 +618,8 @@ def aggregate_image(agg_start_date, agg_end_date, date_format):
         if 'et_fraction' in variables:
             # Compute average et fraction over the aggregation period
             image_list.append(
-                et_img.divide(et_reference_img).rename(
-                    ['et_fraction']).float())
+                et_img.divide(et_reference_img).rename(['et_fraction']).float()
+            )
         if 'ndvi' in variables:
             # Compute average ndvi over the aggregation period
             ndvi_img = daily_coll \
@@ -629,7 +649,8 @@ def agg_daily(daily_img):
             return aggregate_image(
                 agg_start_date=agg_start_date,
                 agg_end_date=ee.Date(agg_start_date).advance(1, 'day'),
-                date_format='YYYYMMdd')
+                date_format='YYYYMMdd',
+            )
 
         return ee.ImageCollection(daily_coll.map(agg_daily))
 
@@ -647,7 +668,8 @@ def agg_monthly(agg_start_date):
             return aggregate_image(
                 agg_start_date=agg_start_date,
                 agg_end_date=ee.Date(agg_start_date).advance(1, 'month'),
-                date_format='YYYYMM')
+                date_format='YYYYMM',
+            )
 
         return ee.ImageCollection(month_list.map(agg_monthly))
 
@@ -664,21 +686,30 @@ def agg_annual(agg_start_date):
             return aggregate_image(
                 agg_start_date=agg_start_date,
                 agg_end_date=ee.Date(agg_start_date).advance(1, 'year'),
-                date_format='YYYY')
+                date_format='YYYY',
+            )
 
         return ee.ImageCollection(year_list.map(agg_annual))
 
     elif t_interval.lower() == 'custom':
         # Returning an ImageCollection to be consistent
         return ee.ImageCollection(aggregate_image(
-            agg_start_date=start_date, agg_end_date=end_date,
-            date_format='YYYYMMdd'))
+            agg_start_date=start_date,
+            agg_end_date=end_date,
+            date_format='YYYYMMdd',
+        ))
 
 
-def from_scene_et_actual(scene_coll, start_date, end_date, variables,
-                         interp_args, model_args, t_interval,
-                         use_joins=False,
-                         ):
+def from_scene_et_actual(
+        scene_coll,
+        start_date,
+        end_date,
+        variables,
+        interp_args,
+        model_args,
+        t_interval,
+        use_joins=False,
+        ):
     """Interpolate from a precomputed collection of Landsat actual ET scenes
 
     Parameters

openet/core/tests/test_common.py

@@ -1,4 +1,4 @@
-import pprint
+# import pprint
 
 import ee
 import pytest
@@ -293,4 +293,4 @@ def test_landsat_c2_sr_lst_correct_values(image_id, xy, expected, tol=0.25):
     # original = utils.point_image_value(lst_img, xy, scale=30)['ST_B10']
     output_img = common.landsat_c2_sr_lst_correct(input_img, ndvi_img)
     corrected = utils.point_image_value(output_img, xy, scale=30)
-    assert abs(corrected['surface_temperature'] - expected) <= tol
+    assert abs(corrected['surface_temperature'] - expected) <= tol

openet/core/tests/test_ensemble.py

@@ -1,6 +1,6 @@
 # import datetime
-import logging
-import pprint
+# import logging
+# import pprint
 
 import ee
 import pytest
@@ -11,8 +11,6 @@
 # logging.basicConfig(level=logging.DEBUG, format='%(message)s')
 
 
-
-
 # TODO: Write a test to check that the output bandnames
 # def test_mad_bandname():
 #     assert False

openet/core/tests/test_interpolate.py

@@ -1,6 +1,6 @@
 import datetime
 import logging
-import pprint
+# import pprint
 
 import ee
 import pytest
@@ -23,6 +23,7 @@ def tgt_image(tgt_value, tgt_time):
               'system:index': datetime.datetime.utcfromtimestamp(
                   tgt_time / 1000.0).strftime('%Y%m%d')})
 
+
 def src_images(src_values, src_times):
     """Build constant source images from values and times"""
     src_images = []
@@ -82,22 +83,16 @@ def scene_coll(variables, et_fraction=[0.4, 0.4, 0.4], et=[5, 5, 5],
 
     # Mask and time bands currently get added on to the scene collection
     #   and images are unscaled just before interpolating in the export tool
-    scene_coll = ee.ImageCollection([
-        ee.Image([img.add(et_fraction[0]), img.add(et[0]), img.add(ndvi[0]),
-                  img.add(date1), mask])\
+    scene_coll = ee.ImageCollection.fromImages([
+        ee.Image([img.add(et_fraction[0]), img.add(et[0]), img.add(ndvi[0]), img.add(date1), mask])
             .rename(['et_fraction', 'et', 'ndvi', 'time', 'mask'])
-            .set({'system:index': 'LE07_044033_20170708',
-                  'system:time_start': time1}),
-        ee.Image([img.add(et_fraction[1]), img.add(et[1]), img.add(ndvi[1]),
-                  img.add(date2), mask])\
+            .set({'system:index': 'LE07_044033_20170708', 'system:time_start': time1}),
+        ee.Image([img.add(et_fraction[1]), img.add(et[1]), img.add(ndvi[1]), img.add(date2), mask])
             .rename(['et_fraction', 'et', 'ndvi', 'time', 'mask'])
-            .set({'system:index': 'LC08_044033_20170716',
-                  'system:time_start': time2}),
-        ee.Image([img.add(et_fraction[2]), img.add(et[2]), img.add(ndvi[2]),
-                  img.add(date3), mask])\
+            .set({'system:index': 'LC08_044033_20170716', 'system:time_start': time2}),
+        ee.Image([img.add(et_fraction[2]), img.add(et[2]), img.add(ndvi[2]), img.add(date3), mask])
             .rename(['et_fraction', 'et', 'ndvi', 'time', 'mask'])
-            .set({'system:index': 'LE07_044033_20170724',
-                  'system:time_start': time3}),
+            .set({'system:index': 'LE07_044033_20170724', 'system:time_start': time3}),
     ])
     return scene_coll.select(variables)
 
@@ -728,7 +723,7 @@ def test_from_scene_et_actual_daily_et_fraction_max(tol=0.0001):
 def test_from_scene_et_fraction_t_interval_bad_value():
     # Function should raise a ValueError if t_interval is not supported
     with pytest.raises(ValueError):
-        output_coll = interpolate.from_scene_et_fraction(
+        interpolate.from_scene_et_fraction(
             scene_coll(['et', 'time', 'mask']),
             start_date='2017-07-01', end_date='2017-08-01', variables=['et'],
             interp_args={'interp_method': 'linear', 'interp_days': 32},
@@ -742,7 +737,7 @@ def test_from_scene_et_fraction_t_interval_bad_value():
 def test_from_scene_et_fraction_t_interval_no_value():
     # Function should raise an Exception if t_interval is not set
     with pytest.raises(TypeError):
-        output_coll = interpolate.from_scene_et_fraction(
+        interpolate.from_scene_et_fraction(
             scene_coll(['et', 'time', 'mask']),
             start_date='2017-07-01', end_date='2017-08-01',
             variables=['et', 'et_reference', 'et_fraction', 'count'],
@@ -756,7 +751,7 @@ def test_from_scene_et_fraction_t_interval_no_value():
 def test_from_scene_et_actual_t_interval_bad_value():
     # Function should raise a ValueError if t_interval is not supported
     with pytest.raises(ValueError):
-        output_coll = interpolate.from_scene_et_actual(
+        interpolate.from_scene_et_actual(
             scene_coll(['et', 'time', 'mask']),
             start_date='2017-07-01', end_date='2017-08-01', variables=['et'],
             interp_args={'interp_method': 'linear', 'interp_days': 32,
@@ -772,7 +767,7 @@ def test_from_scene_et_actual_t_interval_bad_value():
 def test_from_scene_et_actual_t_interval_no_value():
     # Function should raise an Exception if t_interval is not set
     with pytest.raises(TypeError):
-        output_coll = interpolate.from_scene_et_actual(
+        interpolate.from_scene_et_actual(
             scene_coll(['et', 'time', 'mask']),
             start_date='2017-07-01', end_date='2017-08-01', variables=['et'],
             interp_args={'interp_method': 'linear', 'interp_days': 32,
@@ -787,7 +782,7 @@ def test_from_scene_et_actual_t_interval_no_value():
 
 """
 These tests were attempts at making "full" interpolation calls.
-They could be removed but are being left in case we want to explore this again 
+They could be removed but are being left in case we want to explore this again
 at some point in the future.
 """
 # def test_daily_values_collection_a():