[pre-commit.ci] auto fixes from pre-commit.com hooks

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Ouranosinc · Jul 16, 2024 · 8641c3b · 8641c3b
1 parent 0507d4c
commit 8641c3b
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Showing 3 changed files with 56 additions and 52 deletions.
diff --git a/tests/test_hydrology.py b/tests/test_hydrology.py
@@ -64,7 +64,7 @@ def test_simple(self, snw_series, pr_series):
 
         # 1 kg/ m2 /d of rain on day 11
         b = np.zeros(365)
-        b[11] = 1.0 / 60 ** 2 / 24
+        b[11] = 1.0 / 60**2 / 24
         pr = pr_series(b, start="1999-07-01")
 
         out = xci.melt_and_precip_max(snw, pr)
@@ -87,7 +87,7 @@ def test_simple(self, q_series):
         a[50:60] = 10
         a[200:210] = 20
         q = q_series(a)
-        out = xci.high_flow_frequency(q, 9, freq='YS')
+        out = xci.high_flow_frequency(q, 9, freq="YS")
         np.testing.assert_array_equal(out, 20)
 
 
@@ -97,6 +97,5 @@ def test_simple(self, q_series):
         a[50:60] = 1
         a[200:210] = 1
         q = q_series(a)
-        out = xci.low_flow_frequency(q, 0.2, freq='YS')
+        out = xci.low_flow_frequency(q, 0.2, freq="YS")
         np.testing.assert_array_equal(out, 20)
-
diff --git a/xclim/indices/_hydrology.py b/xclim/indices/_hydrology.py
@@ -7,22 +7,22 @@
 from xclim.core.calendar import get_calendar
 from xclim.core.missing import at_least_n_valid
 from xclim.core.units import declare_units, rate2amount
-from xclim.indices.generic import compare, threshold_count
+from xclim.indices.generic import compare
 
 from . import generic
 
 __all__ = [
     "base_flow_index",
+    "flow_index",
+    "high_flow_frequency",
+    "low_flow_frequency",
     "melt_and_precip_max",
     "rb_flashiness_index",
     "snd_max",
     "snd_max_doy",
     "snow_melt_we_max",
     "snw_max",
     "snw_max_doy",
-    "flow_index",
-    "high_flow_frequency",
-    "low_flow_frequency"
 ]
 
 
@@ -288,46 +288,46 @@ def melt_and_precip_max(
 @declare_units(q="[discharge]")
 def flow_index(q: xr.DataArray, p: float = 0.95) -> xr.DataArray:
     """
-    Calculate the Qp  (pth percentile of daily streamflow) normalized by the mean flow.
+        Calculate the Qp  (pth percentile of daily streamflow) normalized by the mean flow.
 
     Parameters
     ----------
-    q : xarray.DataArray
-        Daily streamflow data.
-    p : float
-        Percentile for
-args = (<xarray.DataArray 'q' ()> Size: 8B
-array(5.)
-Coordinates:
-    quantile  float64 8B 0.95
-Attributes:
-    units:    , 0.08202247191011236)
-kwds = {}
-
-    @wraps(func)
-    def inner(*args, **kwds):
-        with self._recreate_cm():
->           return func(*args, **kwds)
-E           AssertionError:
-E           Arrays are not almost equal to 7 decimals
-E            ACTUAL: <xarray.DataArray 'q' ()> Size: 8B
-E           array(5.)
-E           Coordinates:...
-E            DESIRED: 0.08202247191011236
-
-/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/contextlib.py:81: AssertionError
-
-Process finished with exit code 1
- calculating the flow index, between 0 and 1. Default of 0.95 is for high flows.
+        q : xarray.DataArray
+            Daily streamflow data.
+        p : float
+            Percentile for
+    args = (<xarray.DataArray 'q' ()> Size: 8B
+    array(5.)
+    Coordinates:
+        quantile  float64 8B 0.95
+    Attributes:
+        units:    , 0.08202247191011236)
+    kwds = {}
+
+        @wraps(func)
+        def inner(*args, **kwds):
+            with self._recreate_cm():
+    >           return func(*args, **kwds)
+    E           AssertionError:
+    E           Arrays are not almost equal to 7 decimals
+    E            ACTUAL: <xarray.DataArray 'q' ()> Size: 8B
+    E           array(5.)
+    E           Coordinates:...
+    E            DESIRED: 0.08202247191011236
+
+    /Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/contextlib.py:81: AssertionError
+
+    Process finished with exit code 1
+     calculating the flow index, between 0 and 1. Default of 0.95 is for high flows.
 
     Returns
     -------
-    xarray.DataArray
-    Normalized Qp, which is the p th percentile of daily streamflow normalized by the median flow.
+        xarray.DataArray
+        Normalized Qp, which is the p th percentile of daily streamflow normalized by the median flow.
 
-    Reference:
-    1. Addor, Nans & Nearing, Grey & Prieto, Cristina & Newman, A. & Le Vine, Nataliya & Clark, Martyn. (2018). A Ranking of Hydrological Signatures Based on Their Predictability in Space. Water Resources Research. 10.1029/2018WR022606.
-    2. Clausen, B., & Biggs, B. J. F. (2000). Flow variables for ecological studies in temperate streams: Groupings based on covariance. Journal of Hydrology, 237(3–4), 184–197. https://doi.org/10.1016/S0022-1694(00)00306-1
+        Reference:
+        1. Addor, Nans & Nearing, Grey & Prieto, Cristina & Newman, A. & Le Vine, Nataliya & Clark, Martyn. (2018). A Ranking of Hydrological Signatures Based on Their Predictability in Space. Water Resources Research. 10.1029/2018WR022606.
+        2. Clausen, B., & Biggs, B. J. F. (2000). Flow variables for ecological studies in temperate streams: Groupings based on covariance. Journal of Hydrology, 237(3–4), 184–197. https://doi.org/10.1016/S0022-1694(00)00306-1
 
     """
     qp = q.quantile(p, dim="time")
@@ -367,11 +367,12 @@ def high_flow_frequency(
     1. Addor, Nans & Nearing, Grey & Prieto, Cristina & Newman, A. & Le Vine, Nataliya & Clark, Martyn. (2018). A Ranking of Hydrological Signatures Based on Their Predictability in Space. Water Resources Research. 10.1029/2018WR022606.
     2. Clausen, B., & Biggs, B. J. F. (2000). Flow variables for ecological studies in temperate streams: Groupings based on covariance. Journal of Hydrology, 237(3–4), 184–197. https://doi.org/10.1016/S0022-1694(00)00306-1
     """
-
     median_flow = q.median(dim="time")
     with xr.set_options(keep_attrs=True):
         threshold = threshold_factor * median_flow
-    high_flow_days = compare(q, op=">", right=threshold).resample(time=freq).sum(dim="time")
+    high_flow_days = (
+        compare(q, op=">", right=threshold).resample(time=freq).sum(dim="time")
+    )
     out = high_flow_days.mean(dim="time")
     out.attrs["units"] = "days"
     return out
@@ -407,11 +408,12 @@ def low_flow_frequency(
     Olden, J. D., & Poff, N. L. (2003). Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Research and
     Applications, 19(2), 101–121. https://doi.org/10.1002/rra.700
     """
-
     mean_flow = q.mean(dim="time")
     with xr.set_options(keep_attrs=True):
         threshold = threshold_factor * mean_flow
-    low_flow_days = compare(q, op="<", right=threshold).resample(time=freq).sum(dim="time")
+    low_flow_days = (
+        compare(q, op="<", right=threshold).resample(time=freq).sum(dim="time")
+    )
     out = low_flow_days.mean(dim="time")
     out.attrs["units"] = "days"
     return out
diff --git a/xclim/indices/_streamflow_flow_indices.py b/xclim/indices/_streamflow_flow_indices.py
@@ -1,15 +1,17 @@
 from __future__ import annotations
+
 import xarray as xr
-import numpy as np
+
 from xclim.core.units import declare_units
-from xclim.indices.generic import compare, threshold_count
+from xclim.indices.generic import compare
 
 __all__ = [
     "flow_index",
     "high_flow_frequency",
     "low_flow_frequency",
 ]
 
+
 @declare_units(q="[discharge]")
 def flow_index(q: xr.DataArray, p: float = 0.95) -> xr.DataArray:
     """
@@ -69,11 +71,12 @@ def high_flow_frequency(
     1. Addor, Nans & Nearing, Grey & Prieto, Cristina & Newman, A. & Le Vine, Nataliya & Clark, Martyn. (2018). A Ranking of Hydrological Signatures Based on Their Predictability in Space. Water Resources Research. 10.1029/2018WR022606.
     2. Clausen, B., & Biggs, B. J. F. (2000). Flow variables for ecological studies in temperate streams: Groupings based on covariance. Journal of Hydrology, 237(3–4), 184–197. https://doi.org/10.1016/S0022-1694(00)00306-1
     """
-
     median_flow = q.median(dim="time")
     with xr.set_options(keep_attrs=True):
         threshold = threshold_factor * median_flow
-    high_flow_days = compare(q, op=">", right=threshold).resample(time=freq).sum(dim="time")
+    high_flow_days = (
+        compare(q, op=">", right=threshold).resample(time=freq).sum(dim="time")
+    )
     out = high_flow_days.mean(dim="time")
     out.attrs["units"] = "days/year"
     return out
@@ -109,12 +112,12 @@ def low_flow_frequency(
     Olden, J. D., & Poff, N. L. (2003). Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Research and
     Applications, 19(2), 101–121. https://doi.org/10.1002/rra.700
     """
-
     mean_flow = q.mean(dim="time")
     with xr.set_options(keep_attrs=True):
         threshold = threshold_factor * mean_flow
-    low_flow_days = compare(q, op="<", right=threshold).resample(time=freq).sum(dim="time")
+    low_flow_days = (
+        compare(q, op="<", right=threshold).resample(time=freq).sum(dim="time")
+    )
     out = low_flow_days.mean(dim="time")
     out.attrs["units"] = "days"
     return out
-