Remove use of kwarg.pop wherever possible

ChanJeunlam · Oct 21, 2019 · f7cb562 · f7cb562
1 parent e0bd6d9
commit f7cb562
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Showing 9 changed files with 32 additions and 81 deletions.
diff --git a/src/metpy/calc/indices.py b/src/metpy/calc/indices.py
@@ -69,7 +69,7 @@ def precipitable_water(dewpt, pressure, bottom=None, top=None):
 @exporter.export
 @preprocess_xarray
 @check_units('[pressure]')
-def mean_pressure_weighted(pressure, *args, **kwargs):
+def mean_pressure_weighted(pressure, *args, heights=None, bottom=None, depth=None):
     r"""Calculate pressure-weighted mean of an arbitrary variable through a layer.
 
     Layer top and bottom specified in height or pressure.
@@ -99,9 +99,6 @@ def mean_pressure_weighted(pressure, *args, **kwargs):
         v_mean: v-component of layer mean wind.
 
     """
-    heights = kwargs.pop('heights', None)
-    bottom = kwargs.pop('bottom', None)
-    depth = kwargs.pop('depth', None)
     ret = []  # Returned variable means in layer
     layer_arg = get_layer(pressure, *args, heights=heights,
                           bottom=bottom, depth=depth)

diff --git a/src/metpy/calc/kinematics.py b/src/metpy/calc/kinematics.py
@@ -45,9 +45,8 @@ def _check_and_flip(arr):
 def ensure_yx_order(func):
     """Wrap a function to ensure all array arguments are y, x ordered, based on kwarg."""
     @functools.wraps(func)
-    def wrapper(*args, **kwargs):
+    def wrapper(*args, dim_order=None, **kwargs):
         # Check what order we're given
-        dim_order = kwargs.pop('dim_order', None)
         x_first = _is_x_first_dim(dim_order)
 
         # If x is the first dimension, flip (transpose) every array within the function args.

diff --git a/src/metpy/calc/thermo.py b/src/metpy/calc/thermo.py
@@ -1586,7 +1586,9 @@ def most_unstable_parcel(pressure, temperature, dewpoint, heights=None,
 @exporter.export
 @preprocess_xarray
 @check_units('[temperature]', '[pressure]', '[temperature]')
-def isentropic_interpolation(theta_levels, pressure, temperature, *args, **kwargs):
+def isentropic_interpolation(theta_levels, pressure, temperature, *args, axis=0,
+                             temperature_out=False, max_iters=50, eps=1e-6,
+                             bottom_up_search=True, **kwargs):
     r"""Interpolate data in isobaric coordinates to isentropic coordinates.
 
     Parameters
@@ -1597,17 +1599,6 @@ def isentropic_interpolation(theta_levels, pressure, temperature, *args, **kwarg
         One-dimensional array of pressure levels
     temperature : array
         Array of temperature
-    args : array, optional
-        Any additional variables will be interpolated to each isentropic level.
-
-    Returns
-    -------
-    list
-        List with pressure at each isentropic level, followed by each additional
-        argument interpolated to isentropic coordinates.
-
-    Other Parameters
-    ----------------
     axis : int, optional
         The axis corresponding to the vertical in the temperature array, defaults to 0.
     temperature_out : bool, optional
@@ -1620,6 +1611,14 @@ def isentropic_interpolation(theta_levels, pressure, temperature, *args, **kwarg
     bottom_up_search : bool, optional
         Controls whether to search for theta levels bottom-up, or top-down. Defaults to
         True, which is bottom-up search.
+    args : array, optional
+        Any additional variables will be interpolated to each isentropic level.
+
+    Returns
+    -------
+    list
+        List with pressure at each isentropic level, followed by each additional
+        argument interpolated to isentropic coordinates.
 
     Notes
     -----
@@ -1648,17 +1647,11 @@ def _isen_iter(iter_log_p, isentlevs_nd, ka, a, b, pok):
         fp = exner * (ka * t - a)
         return iter_log_p - (f / fp)
 
-    # Change when Python 2.7 no longer supported
-    # Pull out keyword arguments
-    temperature_out = kwargs.get('tmpk_out')
-    if temperature_out is not None:
+    # Remove block when tmpk_out is removed in 1.0
+    if 'tmpk_out' in kwargs:
+        temperature_out = kwargs.get('tmpk_out')
         warnings.warn('The use of "tmpk_out" has been deprecated in favor of'
                       '"temperature_out",', metpyDeprecation)
-    temperature_out = kwargs.pop('temperature_out', temperature_out)
-    max_iters = kwargs.pop('max_iters', 50)
-    eps = kwargs.pop('eps', 1e-6)
-    axis = kwargs.pop('axis', 0)
-    bottom_up_search = kwargs.pop('bottom_up_search', True)
 
     # Get dimensions in temperature
     ndim = temperature.ndim
@@ -1895,7 +1888,7 @@ def mixed_parcel(p, temperature, dewpt, parcel_start_pressure=None,
 @exporter.export
 @preprocess_xarray
 @check_units('[pressure]')
-def mixed_layer(p, *args, **kwargs):
+def mixed_layer(p, *args, heights=None, bottom=None, depth=100 * units.hPa, interpolate=True):
     r"""Mix variable(s) over a layer, yielding a mass-weighted average.
 
     This function will integrate a data variable with respect to pressure and determine the
@@ -1916,20 +1909,14 @@ def mixed_layer(p, *args, **kwargs):
         The thickness of the layer as a pressure or height above the bottom of the layer
         (default 100 hPa)
     interpolate : bool, optional
-        Interpolate the top and bottom points if they are not in the given data
+        Interpolate the top and bottom points if they are not in the given data (default True)
 
     Returns
     -------
     `pint.Quantity`
         The mixed value of the data variable.
 
     """
-    # Pull out keyword arguments, remove when we drop Python 2.7
-    heights = kwargs.pop('heights', None)
-    bottom = kwargs.pop('bottom', None)
-    depth = kwargs.pop('depth', 100 * units.hPa)
-    interpolate = kwargs.pop('interpolate', True)
-
     layer = get_layer(p, *args, heights=heights, bottom=bottom,
                       depth=depth, interpolate=interpolate)
     p_layer = layer[0]
@@ -2014,7 +2001,8 @@ def moist_static_energy(heights, temperature, specific_humidity):
 @exporter.export
 @preprocess_xarray
 @check_units('[pressure]', '[temperature]')
-def thickness_hydrostatic(pressure, temperature, **kwargs):
+def thickness_hydrostatic(pressure, temperature, mixing=None,
+                          molecular_weight_ratio=mpconsts.epsilon, bottom=None, depth=None):
     r"""Calculate the thickness of a layer via the hypsometric equation.
 
     This thickness calculation uses the pressure and temperature profiles (and optionally
@@ -2057,11 +2045,6 @@ def thickness_hydrostatic(pressure, temperature, **kwargs):
     thickness_hydrostatic_from_relative_humidity, pressure_to_height_std, virtual_temperature
 
     """
-    mixing = kwargs.pop('mixing', None)
-    molecular_weight_ratio = kwargs.pop('molecular_weight_ratio', mpconsts.epsilon)
-    bottom = kwargs.pop('bottom', None)
-    depth = kwargs.pop('depth', None)
-
     # Get the data for the layer, conditional upon bottom/depth being specified and mixing
     # ratio being given
     if bottom is None and depth is None:
@@ -2088,7 +2071,7 @@ def thickness_hydrostatic(pressure, temperature, **kwargs):
 @preprocess_xarray
 @check_units('[pressure]', '[temperature]')
 def thickness_hydrostatic_from_relative_humidity(pressure, temperature, relative_humidity,
-                                                 **kwargs):
+                                                 bottom=None, depth=None):
     r"""Calculate the thickness of a layer given pressure, temperature and relative humidity.
 
     Similar to ``thickness_hydrostatic``, this thickness calculation uses the pressure,
@@ -2131,8 +2114,6 @@ def thickness_hydrostatic_from_relative_humidity(pressure, temperature, relative
     mixing_ratio_from_relative_humidity
 
     """
-    bottom = kwargs.pop('bottom', None)
-    depth = kwargs.pop('depth', None)
     mixing = mixing_ratio_from_relative_humidity(relative_humidity, temperature, pressure)
 
     return thickness_hydrostatic(pressure, temperature, mixing=mixing, bottom=bottom,

diff --git a/src/metpy/calc/tools.py b/src/metpy/calc/tools.py
@@ -418,7 +418,7 @@ def _get_bound_pressure_height(pressure, bound, heights=None, interpolate=True):
 @exporter.export
 @preprocess_xarray
 @check_units('[length]')
-def get_layer_heights(heights, depth, *args, **kwargs):
+def get_layer_heights(heights, depth, *args, bottom=None, interpolate=True, with_agl=False):
     """Return an atmospheric layer from upper air data with the requested bottom and depth.
 
     This function will subset an upper air dataset to contain only the specified layer using
@@ -447,10 +447,6 @@ def get_layer_heights(heights, depth, *args, **kwargs):
         The height and data variables of the layer
 
     """
-    bottom = kwargs.pop('bottom', None)
-    interpolate = kwargs.pop('interpolate', True)
-    with_agl = kwargs.pop('with_agl', False)
-
     # Make sure pressure and datavars are the same length
     for datavar in args:
         if len(heights) != len(datavar):
@@ -510,7 +506,8 @@ def get_layer_heights(heights, depth, *args, **kwargs):
 @exporter.export
 @preprocess_xarray
 @check_units('[pressure]')
-def get_layer(pressure, *args, **kwargs):
+def get_layer(pressure, *args, heights=None, bottom=None, depth=100 * units.hPa,
+              interpolate=True):
     r"""Return an atmospheric layer from upper air data with the requested bottom and depth.
 
     This function will subset an upper air dataset to contain only the specified layer. The
@@ -544,12 +541,6 @@ def get_layer(pressure, *args, **kwargs):
         The pressure and data variables of the layer
 
     """
-    # Pop off keyword arguments
-    heights = kwargs.pop('heights', None)
-    bottom = kwargs.pop('bottom', None)
-    depth = kwargs.pop('depth', 100 * units.hPa)
-    interpolate = kwargs.pop('interpolate', True)
-
     # If we get the depth kwarg, but it's None, set it to the default as well
     if depth is None:
         depth = 100 * units.hPa

diff --git a/src/metpy/interpolate/grid.py b/src/metpy/interpolate/grid.py
@@ -309,7 +309,7 @@ def interpolate_to_grid(x, y, z, interp_type='linear', hres=50000,
 
 @exporter.export
 @preprocess_pandas
-def interpolate_to_isosurface(level_var, interp_var, level, **kwargs):
+def interpolate_to_isosurface(level_var, interp_var, level, bottom_up_search=True):
     r"""Linear interpolation of a variable to a given vertical level from given values.
 
     This function assumes that highest vertical level (lowest pressure) is zeroth index.
@@ -326,9 +326,6 @@ def interpolate_to_isosurface(level_var, interp_var, level, **kwargs):
         given level (e.g., potential temperature on isobaric levels)
     level: int or float
         Desired interpolated level (e.g., 2 PVU surface)
-
-    Other Parameters
-    ----------------
     bottom_up_search : bool, optional
         Controls whether to search for levels bottom-up, or top-down. Defaults to
         True, which is bottom-up search.
@@ -346,10 +343,6 @@ def interpolate_to_isosurface(level_var, interp_var, level, **kwargs):
     tropopause (e.g., 2 PVU surface)
 
     """
-    # Change when Python 2.7 no longer supported
-    # Pull out keyword arguments
-    bottom_up_search = kwargs.pop('bottom_up_search', True)
-
     # Find index values above and below desired interpolated surface value
     above, below, good = metpy.calc.find_bounding_indices(level_var, [level], axis=0,
                                                           from_below=bottom_up_search)

diff --git a/src/metpy/interpolate/one_dimension.py b/src/metpy/interpolate/one_dimension.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2018 MetPy Developers.
+# Copyright (c) 2018,2019 MetPy Developers.
 # Distributed under the terms of the BSD 3-Clause License.
 # SPDX-License-Identifier: BSD-3-Clause
 """Interpolate data along a single axis."""
@@ -50,7 +50,7 @@ def interpolate_nans_1d(x, y, kind='linear'):
 
 @exporter.export
 @preprocess_xarray
-def interpolate_1d(x, xp, *args, **kwargs):
+def interpolate_1d(x, xp, *args, axis=0, fill_value=np.nan, return_list_always=False):
     r"""Interpolates data with any shape over a specified axis.
 
     Interpolation over a specified axis for arrays of any shape.
@@ -96,11 +96,6 @@ def interpolate_1d(x, xp, *args, **kwargs):
     xp and args must be the same shape.
 
     """
-    # Pull out keyword args
-    fill_value = kwargs.pop('fill_value', np.nan)
-    axis = kwargs.pop('axis', 0)
-    return_list_always = kwargs.pop('return_list_always', False)
-
     # Handle units
     x, xp = _strip_matching_units(x, xp)
 
@@ -180,7 +175,7 @@ def interpolate_1d(x, xp, *args, **kwargs):
 
 @exporter.export
 @preprocess_xarray
-def log_interpolate_1d(x, xp, *args, **kwargs):
+def log_interpolate_1d(x, xp, *args, axis=0, fill_value=np.nan):
     r"""Interpolates data with logarithmic x-scale over a specified axis.
 
     Interpolation on a logarithmic x-scale for interpolation values in pressure coordintates.
@@ -222,10 +217,6 @@ def log_interpolate_1d(x, xp, *args, **kwargs):
     xp and args must be the same shape.
 
     """
-    # Pull out kwargs
-    fill_value = kwargs.pop('fill_value', np.nan)
-    axis = kwargs.pop('axis', 0)
-
     # Handle units
     x, xp = _strip_matching_units(x, xp)
 

diff --git a/src/metpy/plots/skewt.py b/src/metpy/plots/skewt.py
@@ -909,9 +909,8 @@ def plot_colormapped(self, u, v, c, intervals=None, colors=None, **kwargs):
         This has been deprecated in 0.11 in favor of `intervals`.
 
         """
-        bounds = kwargs.pop('bounds', None)
-        if bounds is not None:
-            intervals = bounds
+        if 'bounds' in kwargs:
+            intervals = kwargs.pop('bounds')
             warnings.warn('The use of "bounds" as a parameter has been deprecated in '
                           'favor of "intervals",', metpyDeprecation)
 

diff --git a/tests/calc/test_calc_tools.py b/tests/calc/test_calc_tools.py
@@ -410,7 +410,7 @@ def test_get_layer_heights_agl_bottom_no_interp():
     heights_init = np.arange(300, 1200, 100) * units.m
     data = heights_init.m * 0.1 * units.degC
     heights, data = get_layer_heights(heights_init, 500 * units.m, data, with_agl=True,
-                                      interpolation=False, bottom=200 * units.m)
+                                      interpolate=False, bottom=200 * units.m)
     # Regression test for #789
     assert_array_equal(heights_init[0], 300 * units.m)
     heights_true = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7]) * units.km

diff --git a/tests/interpolate/test_grid.py b/tests/interpolate/test_grid.py
@@ -305,7 +305,7 @@ def test_interpolate_to_isosurface_from_below():
                       [340., 360., 380., 400., 420.],
                       [350., 370., 390., 410., 430.]]])
 
-    dt_thta = interpolate_to_isosurface(pv, thta, 2, from_below=False)
+    dt_thta = interpolate_to_isosurface(pv, thta, 2, bottom_up_search=False)
 
     truth = np.array([[330., 350., 370., 385., 400.],
                       [340., 359., 374., 389., 404.],