unpin gsw

Author: ocefpaf

ctd/plotting.py

@@ -198,6 +198,7 @@ def plot_section(self, reverse=False, filled=False, **kw):
         lat = lat[::-1]
         data = data.T[::-1].T
         h = h[::-1]
+    lon, lat = map(np.atleast_2d, (lon, lat))
     x = np.append(0, np.cumsum(gsw.distance(lon, lat)[0] / 1e3))
     z = self.index.values.astype(float)
 

ctd/processing.py

@@ -216,11 +216,11 @@ def barrier_layer_thickness(SA, CT):
 
     """
     import gsw
-    sigma_theta = gsw.sigma0_CT_exact(SA, CT)
+    sigma_theta = gsw.sigma0(SA, CT)
     mask = mixed_layer_depth(CT)
     mld = np.where(mask)[0][-1]
     sig_surface = sigma_theta[0]
-    sig_bottom_mld = gsw.sigma0_CT_exact(SA[0], CT[mld])
+    sig_bottom_mld = gsw.sigma0(SA[0], CT[mld])
     d_sig_t = sig_surface - sig_bottom_mld
     d_sig = sigma_theta - sig_bottom_mld
     mask = d_sig < d_sig_t  # Barrier layer.
@@ -241,8 +241,7 @@ def derive_cnv(self):
     cast['SR'] = gsw.SR_from_SP(cast['SP'].values)
     cast['CT'] = gsw.CT_from_t(cast['SA'].values, cast['t090C'].values, p)
     cast['z'] = -gsw.z_from_p(p, self.lat)
-    cast['sigma0_CT'] = gsw.sigma0_CT_exact(cast['SA'].values,
-                                            cast['CT'].values)
+    cast['sigma0_CT'] = gsw.sigma0(cast['SA'].values, cast['CT'].values)
     return cast
 
 

requirements.txt

@@ -2,4 +2,4 @@ numpy
 scipy
 matplotlib
 pandas
-gsw ==3.0.6
+gsw

tests/test_plotting.py

@@ -80,7 +80,7 @@ def proc_ctd(fname):
 def make_section(data_path=data_path, variable='t090C'):
     lon, lat = [], []
     section = OrderedDict()
-    pattern = '%s/CTD/g01mcan*c.cnv.gz' % data_path
+    pattern = '{}/CTD/g01mcan*c.cnv.gz'.format(data_path)
     fnames = sorted(glob(pattern), key=alphanum_key)
     for fname in fnames:
         cast = proc_ctd(fname)