want new version please

.github/workflows/docs.yml

@@ -12,10 +12,10 @@ jobs:
       uses: actions/checkout@v2
       with:
         persist-credentials: false
-    - name: Set up Python 3.x
+    - name: Set up Python 3.8
       uses: actions/setup-python@v2
       with:
-        python-version: '3.x'
+        python-version: '3.8'
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
@@ -25,7 +25,7 @@ jobs:
         pip install ipython
         pip install ipykernel
         pip install numpy
-        pip install matplotlib
+        pip install matplotlib==3.3.1
     - name: Build and test documentation
       run: |
         (cd docs && make docs)

docs/source/examples/HomogeneousField2D/HomogeneousField2D.rst

@@ -30,7 +30,8 @@ tidal-flow-calculator.
 
 To simulate passive particle transport we will use the Lagrangian-based
 transport model `dorado <https://github.com/passaH2O/dorado>`__. We can
-install dorado by typing ``pip install pydorado`` from the command line.
+install dorado by typing ``pip install pydorado`` from the command
+line.
 
 .. code:: ipython3
 

docs/source/examples/TidalFlow2ACO/TidalFlow2ACO_formatted_V2.rst

@@ -317,7 +317,7 @@ Plot final water depths
 
 
 Questions to think about
-========================
+------------------------
 
 1. Now you can see where there is high erosion occuring - why might this
    spot have erosion? What might change the pattern and location of

docs/source/examples/index.rst

@@ -6,6 +6,9 @@ Examples
 
 Examples using the tidal flood component. For the raw jupyter notebook files and other associated content, please refer to our `repository <https://github.com/espin-2020/CoastalTeam>`_.
 
+There is a Google Colab notebook associated with the "Tides on a randomly vegetated field" example, it is available `here <https://colab.research.google.com/drive/1x0ZiS6B5CVhyi5UPfKK0ooIkC5rV5Iod?usp=sharing>`_.
+
+
 .. toctree::
    :maxdepth: 1
 

passive_particles/particletransport.py

@@ -29,7 +29,7 @@ def init_particles(init_x, init_y, Np_tracer, grid_spacing, gridded_vals):
 
     """
     # create class
-    params = pt.params()
+    params = pt.modelParams()
     # populate with required parameters
     params.seed_xloc = init_y
     params.seed_yloc = init_x
@@ -72,7 +72,11 @@ def tidal_particles(params, tide_period, n_tide_periods, plot_grid=None):
 
     """
     # define the particle
-    particle = pt.Particle(params)
+    particle = pt.Particles(params)
+    # generate a set of particles to route around
+    particle.generate_particles(params.Np_tracer,
+                                params.seed_xloc,
+                                params.seed_yloc)
     # record each 1/2 tidal cycle so each ebb and flood
     for i in range(0, int(2*n_tide_periods)):
         if i == 0:
@@ -83,16 +87,18 @@ def tidal_particles(params, tide_period, n_tide_periods, plot_grid=None):
                 # ebb tide
                 params.u = params.ex
                 params.v = params.ey
-                particle = pt.Particle(params)
-                walk_data = particle.run_iteration(previous_walk_data=walk_data,
-                                                   target_time=tide_period/2*(i+1))
+                particle = pt.Particles(params)
+                particle.generate_particles(0, [], [],
+                                            previous_walk_data=walk_data)
+                walk_data = particle.run_iteration(target_time=tide_period/2*(i+1))
             else:
                 # flood tide
                 params.u = params.fx
                 params.v = params.fy
-                particle = pt.Particle(params)
-                walk_data = particle.run_iteration(previous_walk_data=walk_data,
-                                                   target_time=tide_period/2*(i+1))
+                particle = pt.Particles(params)
+                particle.generate_particles(0, [], [],
+                                            previous_walk_data=walk_data)
+                walk_data = particle.run_iteration(target_time=tide_period/2*(i+1))
 
         # plot and save particle locations
         if plot_grid is None: