Merge branch 'develop' of https://github.com/ssolson/MHKiT-Python int…

…o develop

mhkit/river/io/d3d.py

@@ -201,7 +201,6 @@ def get_layer_data(data, variable, layer_index=-1, time_index=-1):
     else:
         if type(var[0][0]) != np.float64:
             raise TypeError('data not recognized')
-
         dimensions = 2
         v = np.ma.getdata(var[time_index, :], False)
 

mhkit/tests/wave/test_contours.py

@@ -1,15 +1,24 @@
 from os.path import abspath, dirname, join, isfile, normpath, relpath
-import unittest
-import pickle
-import json
-import os
-
+from pandas.testing import assert_frame_equal
 from numpy.testing import assert_allclose
+from scipy.interpolate import interp1d
+from random import seed, randint
 import matplotlib.pylab as plt
+from datetime import datetime
+import xarray.testing as xrt
+import mhkit.wave as wave
+from io import StringIO
 import pandas as pd
 import numpy as np
-
-import mhkit.wave as wave
+import contextlib
+import unittest
+import netCDF4
+import inspect
+import pickle
+import time
+import json
+import sys
+import os
 
 
 testdir = dirname(abspath(__file__))
@@ -45,10 +54,6 @@ def setUpClass(self):
         self.wdrt_dt = 3600
         self.wdrt_period = 50
 
-        # `samples_contour`Example data
-        self.hs_contour = np.array([8.56637939, 9.27612515, 8.70427774])
-        self.te_contour = np.array([10, 15, 20])
-
     @classmethod
     def tearDownClass(self):
         pass
@@ -235,28 +240,7 @@ def test_kde_copulas(self):
                              self.wdrt_copulas['bivariate_KDE_log_x2'])]
         self.assertTrue(all(close))
 
-    def test_samples_contours_type_validation(self):
-        with self.assertRaises(TypeError):
-            wave.contours.samples_contour(
-                'not an array', self.te_contour, self.hs_contour)
-        with self.assertRaises(TypeError):
-            wave.contours.samples_contour(
-                self.te_contour, 'not an array', self.hs_contour)
-        with self.assertRaises(TypeError):
-            wave.contours.samples_contour(
-                self.te_contour, self.hs_contour, 'not an array')
-
-    def test_samples_contours_length_mismatch(self):
-        with self.assertRaises(ValueError):
-            wave.contours.samples_contour(
-                self.te_contour, self.hs_contour, np.array([1, 2]))
-
-    def test_samples_contours_range_validation(self):
-        with self.assertRaises(ValueError):
-            wave.contours.samples_contour(
-                np.array([5, 25]), self.te_contour, self.hs_contour)
-
-    def test_samples_contours_correct_interpolation(self):
+    def test_samples_contours(self):
         te_samples = np.array([10, 15, 20])
         hs_samples_0 = np.array([8.56637939, 9.27612515, 8.70427774])
         hs_contour = np.array(self.wdrt_copulas["gaussian_x1"])

mhkit/wave/contours.py

@@ -1792,51 +1792,28 @@ def samples_contour(t_samples, t_contour, hs_contour):
         raise TypeError(f't_contour must be of type np.ndarray. Got: {type(t_contour)}')
     if not isinstance(hs_contour, np.ndarray):
         raise TypeError(f'hs_contour must be of type np.ndarray. Got: {type(hs_contour)}')
-    if len(t_contour) != len(hs_contour):
-        raise ValueError(
-            "t_contour and hs_contour must be of the same length.")
-    if np.any(t_samples < np.min(t_contour)) or np.any(t_samples > np.max(t_contour)):
-        raise ValueError(
-            "All t_samples must be within the range of t_contour.")
-
-
 
-    # Find minimum and maximum energy period values
+    # finds minimum and maximum energy period values
     amin = np.argmin(t_contour)
     amax = np.argmax(t_contour)
     aamin = np.min([amin, amax])
     aamax = np.max([amin, amax])
-
-    # Separate points along the contour into upper & lower half
+    # finds points along the contour
     w1 = hs_contour[aamin:aamax]
     w2 = np.concatenate((hs_contour[aamax:], hs_contour[:aamin]))
-
-    # Get samples min and max
-    t_min, t_max = np.min(t_samples), np.max(t_samples)
-
-    # Choose the half of the contour with the largest wave height
-    if np.max(w1) > np.max(w2):
-        # Check if the max or min Tp values are within the contour half
-        include_aamax = t_max >= t_contour[aamax] or t_min <= t_contour[aamin]
-        # Set the x and y values for interpolation
-        x1 = t_contour[aamin:aamax + int(include_aamax)]
-        y1 = hs_contour[aamin:aamax + int(include_aamax)]
+    if (np.max(w1) > np.max(w2)):
+        x1 = t_contour[aamin:aamax]
+        y1 = hs_contour[aamin:aamax]
     else:
-        # Check if the max or min Tp values are within the contour half
-        include_aamin = t_max >= t_contour[aamin] or t_min <= t_contour[aamax]
-        # Set the x and y values for interpolation
-        x1 = np.concatenate(
-            (t_contour[aamax:], t_contour[:aamin + int(include_aamin)]))
-        y1 = np.concatenate(
-            (hs_contour[aamax:], hs_contour[:aamin + int(include_aamin)]))
-
-    # Sort data based on the max and min Tp values
+        x1 = np.concatenate((t_contour[aamax:], t_contour[:aamin]))
+        y1 = np.concatenate((hs_contour[aamax:], hs_contour[:aamin]))
+    # sorts data based on the max and min energy period values
     ms = np.argsort(x1)
     x = x1[ms]
     y = y1[ms]
-    # Interpolation function
+    # interpolates the sorted data
     si = interp.interp1d(x, y)
-    # Interpolate Tp samples values to get Hs values
+    # finds the wave height based on the user specified energy period values
     hs_samples = si(t_samples)
 
     return hs_samples