Add sa_ct_interp and tracer_ct_interp functions to GSW-Python

gsw/__init__.py

@@ -35,6 +35,7 @@
 from ._fixed_wrapped_ufuncs import *  # noqa
 from .conversions import t90_from_t68
 from .geostrophy import *  # noqa
+from .interpolation import *  # noqa
 from .stability import *  # noqa
 from .utility import *  # noqa
 

gsw/geostrophy.py

@@ -36,7 +36,7 @@ def geo_strf_dyn_height(SA, CT, p, p_ref=0, axis=0, max_dp=1.0,
         If any pressure interval in the input p exceeds max_dp, the dynamic
         height will be calculated after interpolating to a grid with this
         spacing.
-    interp_method : string {'pchip', 'linear'}
+    interp_method : string {'mrst', 'pchip', 'linear'}
         Interpolation algorithm.
 
     Returns
@@ -48,7 +48,7 @@ def geo_strf_dyn_height(SA, CT, p, p_ref=0, axis=0, max_dp=1.0,
         in an isobaric surface, relative to the reference surface.
 
     """
-    interp_methods = {'pchip' : 2, 'linear' : 1}
+    interp_methods = {'mrst' : 3, 'pchip' : 2, 'linear' : 1}
     if interp_method not in interp_methods:
         raise ValueError(f'interp_method must be one of {interp_methods.keys()}')
     if SA.shape != CT.shape:

gsw/interpolation.py

@@ -0,0 +1,177 @@
+"""
+Functions for vertical interpolation.
+"""
+
+import numpy as np
+
+from . import _gsw_ufuncs
+from ._utilities import indexer, match_args_return
+
+__all__ = ['sa_ct_interp',
+           'tracer_ct_interp',
+           ]
+
+@match_args_return
+def sa_ct_interp(SA, CT, p, p_i, axis=0):
+    """
+    Interpolates vertical casts of values of Absolute Salinity
+    and Conservative Temperature to the arbitrary pressures p_i.
+
+    Parameters
+    ----------
+    SA : array-like
+        Absolute Salinity, g/kg
+    CT : array-like
+        Conservative Temperature (ITS-90), degrees C
+    p : array-like
+        Sea pressure (absolute pressure minus 10.1325 dbar), dbar
+    p_i : array-like
+        Sea pressure to interpolate on, dbar
+    axis : int, optional, default is 0
+        The index of the pressure dimension in SA and CT.
+
+
+    Returns
+    -------
+    SA_i : array
+        Values of SA interpolated to p_i along the specified axis.
+    CT_i : array
+        Values of CT interpolated to p_i along the specified axis.
+
+    """
+    if SA.shape != CT.shape:
+        raise ValueError(f'Shapes of SA and CT must match; found {SA.shape} and {CT.shape}')
+    if p.ndim != p_i.ndim:
+        raise ValueError(f'p and p_i must have the same number of dimensions;\n'
+                         f' found {p.ndim} versus {p_i.ndim}')
+    if p.ndim == 1 and SA.ndim > 1:
+        if len(p) != SA.shape[axis]:
+            raise ValueError(
+                f'With 1-D p, len(p) must be SA.shape[axis];\n'
+                f' found {len(p)} versus {SA.shape[axis]} on specified axis, {axis}'
+                )
+        ind = [np.newaxis] * SA.ndim
+        ind[axis] = slice(None)
+        p = p[tuple(ind)]
+        p_i = p_i[tuple(ind)]
+    elif p.ndim > 1:
+        if p.shape != SA.shape:
+            raise ValueError(f'With {p.ndim}-D p, shapes of p and SA must match;\n'
+                             f'found {p.shape} and {SA.shape}')
+        if any([p.shape[i] != p_i.shape[i] for i in range(p.ndim) if i != axis]):
+            raise ValueError(f'With {p.ndim}-D p, p and p_i must have the same dimensions outside of axis {axis};\n'
+                             f' found {p.shape} versus {p_i.shape}')
+    with np.errstate(invalid='ignore'):
+        # The need for this context seems to be a bug in np.ma.any.
+        if np.ma.any(np.ma.diff(np.ma.masked_invalid(p_i), axis=axis) <= 0) \
+                or np.ma.any(np.ma.diff(np.ma.masked_invalid(p), axis=axis) <= 0):
+            raise ValueError('p and p_i must be increasing along the specified axis')
+    p = np.broadcast_to(p, SA.shape)
+    goodmask = ~(np.isnan(SA) | np.isnan(CT) | np.isnan(p))
+    SA_i = np.empty(p_i.shape, dtype=float)
+    CT_i = np.empty(p_i.shape, dtype=float)
+    SA_i.fill(np.nan)
+    CT_i.fill(np.nan)
+
+    try:
+        order = 'F' if SA.flags.fortran else 'C'
+    except AttributeError:
+        order = 'C'  # e.g., xarray DataArray doesn't have flags
+    for ind in indexer(SA.shape, axis, order=order):
+        # this is needed to support xarray inputs for numpy < 1.23
+        igood = np.asarray(goodmask[ind])
+        pgood = p[ind][igood]
+        pi = p_i[ind]
+        # There must be at least 2 non-NaN values for interpolation
+        if len(pgood) > 2:
+            sa = SA[ind][igood]
+            ct = CT[ind][igood]
+            sai, cti = _gsw_ufuncs.sa_ct_interp(sa, ct, pgood, pi)
+            SA_i[ind] = sai
+            CT_i[ind] = cti
+
+    return (SA_i, CT_i)
+
+@match_args_return
+def tracer_ct_interp(tracer, CT, p, p_i, factor=9., axis=0):
+    """
+    Interpolates vertical casts of values of a tracer
+    and Conservative Temperature to the arbitrary pressures p_i.
+
+    Parameters
+    ----------
+    tracer : array-like
+        tracer
+    CT : array-like
+        Conservative Temperature (ITS-90), degrees C
+    p : array-like
+        Sea pressure (absolute pressure minus 10.1325 dbar), dbar
+    p_i : array-like
+        Sea pressure to interpolate on, dbar
+    factor: float, optional, default is 9.
+        Ratio between the ranges of Conservative Temperature
+        and tracer in the world ocean.
+    axis : int, optional, default is 0
+        The index of the pressure dimension in tracer and CT.
+
+
+    Returns
+    -------
+    tracer_i : array
+        Values of tracer interpolated to p_i along the specified axis.
+    CT_i : array
+        Values of CT interpolated to p_i along the specified axis.
+
+    """
+    if tracer.shape != CT.shape:
+        raise ValueError(f'Shapes of tracer and CT must match; found {tracer.shape} and {CT.shape}')
+    if p.ndim != p_i.ndim:
+        raise ValueError(f'p and p_i must have the same number of dimensions;\n'
+                         f' found {p.ndim} versus {p_i.ndim}')
+    if p.ndim == 1 and tracer.ndim > 1:
+        if len(p) != tracer.shape[axis]:
+            raise ValueError(
+                f'With 1-D p, len(p) must be tracer.shape[axis];\n'
+                f' found {len(p)} versus {tracer.shape[axis]} on specified axis, {axis}'
+                )
+        ind = [np.newaxis] * tracer.ndim
+        ind[axis] = slice(None)
+        p = p[tuple(ind)]
+        p_i = p_i[tuple(ind)]
+    elif p.ndim > 1:
+        if p.shape != tracer.shape:
+            raise ValueError(f'With {p.ndim}-D p, shapes of p and tracer must match;\n'
+                             f'found {p.shape} and {tracer.shape}')
+        if any([p.shape[i] != p_i.shape[i] for i in range(p.ndim) if i != axis]):
+            raise ValueError(f'With {p.ndim}-D p, p and p_i must have the same dimensions outside of axis {axis};\n'
+                             f' found {p.shape} versus {p_i.shape}')
+    with np.errstate(invalid='ignore'):
+        # The need for this context seems to be a bug in np.ma.any.
+        if np.ma.any(np.ma.diff(np.ma.masked_invalid(p_i), axis=axis) <= 0) \
+                or np.ma.any(np.ma.diff(np.ma.masked_invalid(p), axis=axis) <= 0):
+            raise ValueError('p and p_i must be increasing along the specified axis')
+    p = np.broadcast_to(p, tracer.shape)
+    goodmask = ~(np.isnan(tracer) | np.isnan(CT) | np.isnan(p))
+    tracer_i = np.empty(p_i.shape, dtype=float)
+    CT_i = np.empty(p_i.shape, dtype=float)
+    tracer_i.fill(np.nan)
+    CT_i.fill(np.nan)
+
+    try:
+        order = 'F' if tracer.flags.fortran else 'C'
+    except AttributeError:
+        order = 'C'  # e.g., xarray DataArray doesn't have flags
+    for ind in indexer(tracer.shape, axis, order=order):
+        # this is needed to support xarray inputs for numpy < 1.23
+        igood = np.asarray(goodmask[ind])
+        pgood = p[ind][igood]
+        pi = p_i[ind]
+        # There must be at least 2 non-NaN values for interpolation
+        if len(pgood) > 2:
+            tr = tracer[ind][igood]
+            ct = CT[ind][igood]
+            tri, cti = _gsw_ufuncs.tracer_ct_interp(tr, ct, pgood, pi, factor)
+            tracer_i[ind] = tri
+            CT_i[ind] = cti
+
+    return (tracer_i, CT_i)

gsw/tests/test_geostrophy.py

@@ -1,7 +1,7 @@
 import os
 
 import numpy as np
-from numpy.testing import assert_almost_equal, assert_array_equal
+from numpy.testing import assert_almost_equal, assert_array_equal, assert_allclose
 
 import gsw
 from gsw._utilities import Bunch
@@ -102,3 +102,14 @@ def test_pz_roundtrip():
     zz = gsw.z_from_p(p, 30, 0.5, 0.25)
     assert_almost_equal(z, zz)
 
+def test_dyn_height_mrst():
+    """
+    Tests the MRST-PCHIP interpolation method.
+    """
+    p = cv.p_chck_cast
+    CT = cv.CT_chck_cast
+    SA = cv.SA_chck_cast
+    pr = cv.pr
+    strf = gsw.geo_strf_dyn_height(SA, CT, p, p_ref=pr, interp_method='mrst')
+
+    assert_allclose(strf, cv.geo_strf_dyn_height, rtol=0, atol=cv.geo_strf_dyn_height_ca)

gsw/tests/test_interpolation.py

@@ -0,0 +1,29 @@
+import os
+
+import numpy as np
+from numpy.testing import assert_allclose
+
+import gsw
+from gsw._utilities import Bunch
+
+root_path = os.path.abspath(os.path.dirname(__file__))
+
+cv = Bunch(np.load(os.path.join(root_path, 'gsw_cv_v3_0.npz')))
+
+def test_sa_ct_interp():
+    p = cv.p_chck_cast
+    CT = cv.CT_chck_cast
+    SA = cv.SA_chck_cast
+    p_i = np.repeat(cv.p_i[:, np.newaxis], p.shape[1], axis=1)
+    SA_i, CT_i = gsw.sa_ct_interp(SA, CT, p, p_i)
+    assert_allclose(SA_i, cv.SAi_SACTinterp, rtol=0, atol=cv.SAi_SACTinterp_ca)
+    assert_allclose(CT_i, cv.CTi_SACTinterp, rtol=0, atol=cv.CTi_SACTinterp_ca)
+
+def test_tracer_ct_interp():
+    p = cv.p_chck_cast
+    CT = cv.CT_chck_cast
+    tracer = cv.SA_chck_cast
+    p_i = np.repeat(cv.p_i[:, np.newaxis], p.shape[1], axis=1)
+    tracer_i, CT_i = gsw.tracer_ct_interp(tracer, CT, p, p_i)
+    assert_allclose(tracer_i, cv.traceri_tracerCTinterp, rtol=0, atol=cv.traceri_tracerCTinterp_ca)
+    assert_allclose(CT_i, cv.CTi_SACTinterp, rtol=0, atol=cv.CTi_SACTinterp_ca)