def test_zonal_stats_mismatch_zones_values_shape():
zones = np.array([1, 2, 0])
values = np.array([1, 2, 0, np.nan])
with pytest.raises(Exception) as e_info:
zonal_stats(zones=zones, values=values)
assert e_info
def test_zonal_stats_invalid_values():
zones = np.array([1, 2, 0], dtype=np.int)
values = np.array(['apples', 'foobar', 'cowboy'])
with pytest.raises(Exception) as e_info:
zonal_stats(zones=zones, values=values)
assert e_info
def test_zonal_stats_invalid_zones():
zones = np.array([1, 2, 0.5])
values = np.array([1, 2, 0.5])
with pytest.raises(Exception) as e_info:
zonal_stats(zones=zones, values=values)
assert e_info
def test_zonal_stats_invalid_custom_stat():
cal_sum = lambda values, zones: values + zones
stats = {'sum': cal_sum}
# custom stat only takes 1 argument. Thus, raise error
with pytest.raises(Exception) as e_info:
zonal_stats(zones=zones, values=values, stats=stats)
assert e_info
def test_zonal_stats_custom_stat():
cal_sum = lambda values: values.sum()
def cal_double_sum(values):
return values.sum() * 2
zone_sums = [
cal_sum(zone_vals_1),
cal_sum(zone_vals_2),
cal_sum(zone_vals_3)
]
zone_double_sums = [
cal_double_sum(zone_vals_1),
cal_double_sum(zone_vals_2),
cal_double_sum(zone_vals_3)
]
stats = {'sum': cal_sum, 'double sum': cal_double_sum}
df = zonal_stats(zones=zones, values=values, stats=stats)
assert isinstance(df, pd.DataFrame)
# indices of the output DataFrame matches the unique values in `zones`
idx = df.index.tolist()
assert idx == unique_values
num_cols = len(df.columns)
# there are 2 statistics
assert num_cols == 2
assert zone_sums == df['sum'].tolist()
assert zone_double_sums == df['double sum'].tolist()
def test_zonal_stats_default():
# default stats=['mean', 'max', 'min', 'std', 'var']
df = zonal_stats(zones=zones, values=values)
assert isinstance(df, pd.DataFrame)
# indices of the output DataFrame matches the unique values in `zones`
idx = df.index.tolist()
assert idx == unique_values
num_cols = len(df.columns)
# there are 5 statistics in default setting
assert num_cols == 5
assert zone_means == df['mean'].tolist()
assert zone_maxes == df['max'].tolist()
assert zone_mins == df['min'].tolist()
assert zone_stds == df['std'].tolist()
assert zone_vars == df['var'].tolist()
def test_zonal_stats_invalid_stat_list():
stats = ['some_stat']
with pytest.raises(Exception) as e_info:
zonal_stats(zones=zones, values=values, stats=stats)
assert e_info
