Merge pull request #337 from MHKiT-Software/develop

# MHKiT v0.8.1
MHKiT v0.8.1, includes bug fixes in the example notebooks and fixes the dependencies to requirements updates prior to Numpy 2.0.0.

Fixes MHKIT v0.8.0 installation issues (#334) by fixing the dependencies.
- #335

Fixes bugs in MHKiT example notebooks
- #327

Author: ssolson

environment.yml

@@ -3,10 +3,11 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python>=3.8
+  - python>=3.8,<3.12
+  - pip
   - pandas>=1.0.0
-  - numpy>=1.21.0
-  - scipy
+  - numpy>=1.21.0, <2.0.0
+  - scipy<=1.13.1
   - matplotlib
   - requests
   - lxml
@@ -16,10 +17,11 @@ dependencies:
   - beautifulsoup4
   - xarray
   - h5py>=3.6.0
-  - netcdf4>=1.5.8
+  - netcdf4>=1.5.8, <=1.6.5
   - pip:
       - pecos>=0.3.0
       - fatpack
       - NREL-rex>=0.2.63
       - h5pyd>=0.7.0
       - six>=1.13.0
+      - notebook

examples/ADCP_Delft3D_TRTS_example.ipynb

@@ -40,7 +40,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 1. Request Continuous Wind Data from NDBC\n",
+    "## 1. Request Continuous Wind Data from NDBC\n",
     "   \n",
     "MHKiT can be used to request historical data from the National Data Buoy Center ([NDBC](https://www.ndbc.noaa.gov/)). This process is split into the following steps:\n",
     "\n",
@@ -1098,7 +1098,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.9.17"
   }
  },
  "nbformat": 4,

examples/PacWave_resource_characterization_example.ipynb

@@ -17,7 +17,7 @@
 # Ignore future warnings
 _warn.simplefilter(action="ignore", category=FutureWarning)
 
-__version__ = "v0.8.0"
+__version__ = "v0.8.1"
 
 __copyright__ = """
 Copyright 2019, Alliance for Sustainable Energy, LLC under the terms of 

examples/cdip_example.ipynb

@@ -241,6 +241,7 @@ def short_term_extreme(
         short_term_extreme_dist = fit_maxima(maxima)
     else:
         print("Passed `method` not found.")
+        short_term_extreme_dist = None
     return short_term_extreme_dist
 
 

examples/metocean_example.ipynb

@@ -1,6 +1,4 @@
 """
-io.py
-
 This module provides functions to read and parse MoorDyn output files.
 
 The main function read_moordyn takes as input the path to a MoorDyn output file and optionally

examples/mooring_example.ipynb

@@ -107,6 +107,8 @@ def harmonics(
         hertz = np.arange(0, 3060, 5)
     elif grid_freq == 50:
         hertz = np.arange(0, 2570, 5)
+    else:
+        raise ValueError(f"grid_freq must be either 50 or 60. Got {grid_freq}")
 
     harmonic_amplitudes = harmonic_amplitudes.reindex(
         {"frequency": hertz}, method="nearest"
@@ -322,7 +324,11 @@ def interharmonics(
             + f"xr.DataArray, or xr.Dataset. Got {type(harmonic_amplitudes)}"
         )
 
-    if grid_freq not in [50, 60]:
+    if grid_freq == 60:
+        hertz = np.arange(0, 3060, 60)
+    elif grid_freq == 50:
+        hertz = np.arange(0, 2550, 50)
+    else:
         raise ValueError(f"grid_freq must be either 50 or 60. Got {grid_freq}")
 
     if not isinstance(to_pandas, bool):
@@ -340,11 +346,6 @@ def interharmonics(
             + f"of harmonic_amplitudes. Got {frequency_dimension}"
         )
 
-    if grid_freq == 60:
-        hertz = np.arange(0, 3060, 60)
-    elif grid_freq == 50:
-        hertz = np.arange(0, 2550, 50)
-
     # Sort input data index
     if frequency_dimension == "":
         frequency_dimension = list(harmonic_amplitudes.dims)[0]

examples/tidal_example.ipynb

@@ -86,7 +86,7 @@ def test_animate_2d_update(self):
         y_data = self.dsani[nodes_y[0]].isel(Time=frame).values
 
         # Manually set the data for the line object
-        line.set_data(x_data, y_data)
+        line.set_data([x_data], [y_data])
 
         # Extract updated data from the line object
         updated_x, updated_y = line.get_data()
@@ -126,7 +126,7 @@ def test_animate_3d_update(self):
         z_data = self.dsani[nodes_z[0]].isel(Time=frame).values
 
         # Manually set the data for the line object
-        line.set_data(x_data, y_data)
+        line.set_data([x_data], [y_data])
         line.set_3d_properties(z_data)
 
         # Extract updated data from the line object

mhkit/__init__.py

@@ -59,7 +59,12 @@ def test_load_noaa_data_xarray(self):
         """
         file_name = join(datadir, "s08010.json")
         data = tidal.io.noaa.read_noaa_json(file_name, to_pandas=False)
-        self.assertTrue(np.all(list(data.variables) == ["index", "s", "d", "b"]))
+        # Check if the variable sets are equal
+        data_variables = list(data.variables)
+        required_variables = ["index", "s", "d", "b"]
+        data_variables_set = set(data_variables)
+        required_variables_set = set(required_variables)
+        self.assertTrue(data_variables_set == required_variables_set)
         self.assertEqual(len(data["index"]), 18890)
         self.assertEqual(data.attrs["id"], "s08010")
 
@@ -96,7 +101,12 @@ def test_request_noaa_data_basic_xarray(self):
             write_json=None,
             to_pandas=False,
         )
-        self.assertTrue(np.all(list(data.variables) == ["index", "s", "d", "b"]))
+        # Check if the variable sets are equal
+        data_variables = list(data.variables)
+        required_variables = ["index", "s", "d", "b"]
+        data_variables_set = set(data_variables)
+        required_variables_set = set(required_variables)
+        self.assertTrue(data_variables_set == required_variables_set)
         self.assertEqual(len(data["index"]), 183)
         self.assertEqual(data.attrs["id"], "s08010")
 

mhkit/loads/extreme/extremes.py

@@ -71,11 +71,11 @@ def setUpClass(cls):
         cls.mp = pd.read_csv(
             join(datadir, "hindcast/multiparm.csv"),
             index_col="time_index",
-            names=["time_index", "energy_period_87", "mean_zero-crossing_period_87"],
+            names=["time_index", "energy_period_0", "mean_zero-crossing_period_0"],
             header=0,
             dtype={
-                "energy_period_87": "float32",
-                "mean_zero-crossing_period_87": "float32",
+                "energy_period_0": "float32",
+                "mean_zero-crossing_period_0": "float32",
             },
         )
         cls.mp.index = pd.to_datetime(cls.mp.index)

mhkit/mooring/io.py

@@ -331,7 +331,7 @@ def plot_current_timeseries(
 
     if not isinstance(principal_direction, (int, float)):
         raise TypeError("principal_direction must be of type int or float")
-    if (principal_direction < 0) and (principal_direction > 360):
+    if (principal_direction < 0) or (principal_direction > 360):
         raise ValueError("principal_direction must be between 0 and 360 degrees")
 
     # Rotate coordinate system by supplied principal_direction

mhkit/power/quality.py

@@ -3,7 +3,7 @@
 
 This module provides functions to fetch, process, and read NOAA (National
 Oceanic and Atmospheric Administration) current data directly from the
-NOAA Tides and Currents API (https://tidesandcurrents.noaa.gov/api/). It
+NOAA Tides and Currents API (https://api.tidesandcurrents.noaa.gov/api/prod/). It
 supports loading data into a pandas DataFrame, handling data in XML and 
 JSON formats, and writing data to a JSON file.
 
@@ -46,9 +46,9 @@ def request_noaa_data(
     to_pandas=True,
 ):
     """
-    Loads NOAA current data directly from https://tidesandcurrents.noaa.gov/api/
+    Loads NOAA current data directly from https://api.tidesandcurrents.noaa.gov/api/prod/
     into a pandas DataFrame. NOAA sets max of 31 days between start and end date.
-    See https://co-ops.nos.noaa.gov/api/ for options. All times are reported as
+    See https://api.tidesandcurrents.noaa.gov/api/prod/ for options. All times are reported as
     GMT and metric units are returned for data. Uses cached data if available.
 
     The request URL prints to the screen.

mhkit/tests/mooring/test_mooring.py

@@ -1,4 +1,4 @@
-from .time_utils import matlab_to_datetime, excel_to_datetime
+from .time_utils import matlab_to_datetime, excel_to_datetime, index_to_datetime
 from .stat_utils import (
     get_statistics,
     vector_statistics,

mhkit/tests/tidal/test_io.py

@@ -1,6 +1,7 @@
 import datetime as dt
 import pandas as pd
 import numpy as np
+from pecos.utils import index_to_datetime
 
 
 def matlab_to_datetime(matlab_datenum):

mhkit/tests/wave/io/hindcast/test_hindcast.py

@@ -239,7 +239,7 @@ def request_wpto_point_data(
                     gid = rex_waves.lat_lon_gid(lat_lon)
                     cols = temp_data.columns[:]
                     for i, col in zip(range(len(cols)), cols):
-                        temp = f"{param}_{gid}"
+                        temp = f"{param}_{i}"
                         temp_data = temp_data.rename(columns={col: temp})
 
                     data_list.append(temp_data)
@@ -263,7 +263,7 @@ def request_wpto_point_data(
                 data["time_index"] = pd.to_datetime(data.time_index)
 
                 if isinstance(parameter, list):
-                    param_coords = [f"{param}_{gid}" for param in parameter]
+                    param_coords = [f"{param}_{i}" for param in parameter]
                     data.coords["parameter"] = xr.DataArray(
                         param_coords, dims="parameter"
                     )
@@ -433,7 +433,7 @@ def request_wpto_directional_spectrum(
                 else:
                     break
 
-            ax1 = np.product(data_array.shape[:3])
+            ax1 = np.prod(data_array.shape[:3])
             ax2 = data_array.shape[-1] if len(data_array.shape) == 4 else 1
             datas[i] = pd.DataFrame(
                 data_array.reshape(ax1, ax2), columns=columns, index=idx

mhkit/tidal/graphics.py

@@ -167,7 +167,7 @@ def capture_length_matrix(Hm0, Te, L, statistic, Hm0_bins, Te_bins, to_pandas=Tr
     Te = convert_to_dataarray(Te)
     L = convert_to_dataarray(L)
 
-    if not isinstance(statistic, (str, types.FunctionType)):
+    if not (isinstance(statistic, str) or callable(statistic)):
         raise TypeError(
             f"statistic must be of type str or callable. Got: {type(statistic)}"
         )
@@ -219,7 +219,8 @@ def wave_energy_flux_matrix(Hm0, Te, J, statistic, Hm0_bins, Te_bins, to_pandas=
     Hm0 = convert_to_dataarray(Hm0)
     Te = convert_to_dataarray(Te)
     J = convert_to_dataarray(J)
-    if not isinstance(statistic, (str, callable)):
+
+    if not (isinstance(statistic, str) or callable(statistic)):
         raise TypeError(
             f"statistic must be of type str or callable. Got: {type(statistic)}"
         )

mhkit/tidal/io/noaa.py

@@ -1,6 +1,6 @@
 pandas>=1.0.0
-numpy>=1.21.0
-scipy
+numpy>=1.21.0, <2.0.0
+scipy<=1.13.1
 matplotlib
 requests
 pecos>=0.3.0
@@ -11,8 +11,9 @@ NREL-rex>=0.2.63
 six>=1.13.0
 h5py>=3.6.0
 h5pyd>=0.7.0
-netCDF4>=1.5.8
+netCDF4>=1.5.8, <=1.6.5
 xarray
 statsmodels
 bottleneck
 beautifulsoup4
+notebook

mhkit/utils/__init__.py

@@ -19,8 +19,8 @@
 ]
 DEPENDENCIES = [
     "pandas>=1.0.0",
-    "numpy>=1.21.0",
-    "scipy",
+    "numpy>=1.21.0, <2.0.0",
+    "scipy<=1.13.1",
     "matplotlib",
     "requests",
     "pecos>=0.3.0",
@@ -31,7 +31,7 @@
     "six>=1.13.0",
     "h5py>=3.6.0",
     "h5pyd >=0.7.0",
-    "netCDF4",
+    "netCDF4>=1.5.8, <=1.6.5",
     "xarray",
     "statsmodels",
     "pytz",
@@ -57,7 +57,7 @@
 
 Installation
 ------------------------
-MHKiT-Python requires Python (3.7, 3.8, or 3.9) along with several Python 
+MHKiT-Python requires Python (3.8, 3.9, 3.10, or 3.11) along with several Python 
 package dependencies.  MHKiT-Python can be installed from PyPI using the command ``pip install mhkit``.
 See [installation instructions](https://mhkit-software.github.io/MHKiT/installation.html) for more information.