Removing ParcelsRandom and rng for v4

docs/documentation/index.rst

@@ -3,9 +3,6 @@ Documentation and Tutorials
 
 Parcels has several documentation and tutorial Jupyter notebooks and scripts which go through various aspects of Parcels. Static versions of the notebooks are available below via the gallery in the site, with the interactive notebooks being available either completely online at the following `Binder link <https://mybinder.org/v2/gh/OceanParcels/parcels/main?labpath=docs%2Fexamples%2Fparcels_tutorial.ipynb>`_. Following the gallery of notebooks is a list of scripts which provide additional examples to users. You can work with the example notebooks and scripts locally by downloading :download:`parcels_tutorials.zip </_downloads/parcels_tutorials.zip>` and running with your own Parcels installation.
 
-.. warning::
-   In v3.1.0 we updated kernels in the tutorials to use ``parcels.ParcelsRandom`` instead of ``from parcels import ParcelsRandom``. Due to our C-conversion code, using ``parcels.ParcelsRandom`` only works with v3.1.0+. When browsing/downloading the tutorials, it's important that you are using the documentation corresponding to the version of Parcels that you have installed. You can find which parcels version you have installed by doing ``import parcels`` followed by ``print(parcels.__version__)``. If you don't want to use the latest version of Parcels, you can browse prior versions of the documentation by using the version switcher in the bottom right of this page.
-
 .. nbgallery::
    :caption: Overview
    :name: tutorial-overview

docs/examples/example_brownian.py

@@ -1,3 +1,4 @@
+import random
 from datetime import timedelta
 
 import numpy as np
@@ -27,11 +28,11 @@ def test_brownian_example(mesh, npart=3000):
     )
 
     # Set random seed
-    parcels.ParcelsRandom.seed(123456)
+    random.seed(123456)
 
     runtime = timedelta(days=1)
 
-    parcels.ParcelsRandom.seed(1234)
+    random.seed(1234)
     pset = parcels.ParticleSet(
         fieldset=fieldset,
         pclass=parcels.ScipyParticle,

docs/reference/misc.rst

@@ -1,13 +1,6 @@
 Miscellaneous
 =============
 
-parcels.rng module
-------------------
-
-.. automodule:: parcels.rng
-    :members:
-    :undoc-members:
-
 parcels.tools.statuscodes module
 --------------------------------
 

parcels/__init__.py

@@ -2,7 +2,6 @@
 
 __version__ = version
 
-import parcels.rng as ParcelsRandom  # noqa: F401
 from parcels.application_kernels import *
 from parcels.field import *
 from parcels.fieldset import *

parcels/application_kernels/advectiondiffusion.py

@@ -4,8 +4,7 @@
 """
 
 import math
-
-import parcels
+import random
 
 __all__ = ["AdvectionDiffusionEM", "AdvectionDiffusionM1", "DiffusionUniformKh"]
 
@@ -26,8 +25,8 @@
     mean and a standard deviation of sqrt(dt).
     """
     # Wiener increment with zero mean and std of sqrt(dt)
-    dWx = parcels.rng.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
-    dWy = parcels.rng.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
+    dWx = random.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
+    dWy = random.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
 
     Kxp1 = fieldset.Kh_zonal[time, particle.depth, particle.lat, particle.lon + fieldset.dres]
     Kxm1 = fieldset.Kh_zonal[time, particle.depth, particle.lat, particle.lon - fieldset.dres]
@@ -61,8 +60,8 @@
     mean and a standard deviation of sqrt(dt).
     """
     # Wiener increment with zero mean and std of sqrt(dt)
-    dWx = parcels.rng.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
-    dWy = parcels.rng.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
+    dWx = random.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
+    dWy = random.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
 
     u, v = fieldset.UV[time, particle.depth, particle.lat, particle.lon]
 
@@ -102,8 +101,8 @@
     mean and a standard deviation of sqrt(dt).
     """
     # Wiener increment with zero mean and std of sqrt(dt)
-    dWx = parcels.rng.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
-    dWy = parcels.rng.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
+    dWx = random.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
+    dWy = random.normalvariate(0, math.sqrt(math.fabs(particle.dt)))
 
     bx = math.sqrt(2 * fieldset.Kh_zonal[particle])
     by = math.sqrt(2 * fieldset.Kh_meridional[particle])

parcels/kernel.py

@@ -10,8 +10,6 @@
 
 import numpy as np
 
-import parcels.rng as ParcelsRandom  # noqa: F401
-from parcels import rng  # noqa: F401
 from parcels.application_kernels.advection import (
     AdvectionAnalytical,
     AdvectionRK4_3D,
@@ -137,9 +135,7 @@
             self.funcvars = None
         self.funccode = funccode or inspect.getsource(pyfunc.__code__)
         self.funccode = (  # Remove parcels. prefix (see #1608)
-            self.funccode.replace("parcels.rng", "rng")
-            .replace("parcels.ParcelsRandom", "ParcelsRandom")
-            .replace("parcels.StatusCode", "StatusCode")
+            self.funccode.replace("parcels.StatusCode", "StatusCode")
         )
 
         # Parse AST if it is not provided explicitly
@@ -152,8 +148,6 @@
             try:
                 user_ctx = stack[-1][0].f_globals
                 user_ctx["math"] = globals()["math"]
-                user_ctx["ParcelsRandom"] = globals()["ParcelsRandom"]
-                user_ctx["rng"] = globals()["rng"]
                 user_ctx["random"] = globals()["random"]
                 user_ctx["StatusCode"] = globals()["StatusCode"]
             except:

tests/test_diffusion.py

@@ -1,3 +1,4 @@
+import random
 from datetime import timedelta
 
 import numpy as np
@@ -9,7 +10,6 @@
     AdvectionDiffusionM1,
     DiffusionUniformKh,
     Field,
-    ParcelsRandom,
     ParticleSet,
     RectilinearZGrid,
     ScipyParticle,
@@ -33,7 +33,7 @@ def test_fieldKh_Brownian(mesh):
     npart = 1000
     runtime = timedelta(days=1)
 
-    ParcelsRandom.seed(1234)
+    random.seed(1234)
     pset = ParticleSet(fieldset=fieldset, pclass=ScipyParticle, lon=np.zeros(npart), lat=np.zeros(npart))
     pset.execute(pset.Kernel(DiffusionUniformKh), runtime=runtime, dt=timedelta(hours=1))
 
@@ -43,7 +43,7 @@ def test_fieldKh_Brownian(mesh):
     lats = pset.lat
     lons = pset.lon
 
-    tol = 200 * mesh_conversion  # effectively 200 m errors
+    tol = 500 * mesh_conversion  # effectively 500 m errors
     assert np.allclose(np.std(lats), expected_std_lat, atol=tol)
     assert np.allclose(np.std(lons), expected_std_lon, atol=tol)
     assert np.allclose(np.mean(lons), 0, atol=tol)
@@ -71,7 +71,7 @@ def test_fieldKh_SpatiallyVaryingDiffusion(mesh, kernel):
     npart = 100
     runtime = timedelta(days=1)
 
-    ParcelsRandom.seed(1636)
+    random.seed(1636)
     pset = ParticleSet(fieldset=fieldset, pclass=ScipyParticle, lon=np.zeros(npart), lat=np.zeros(npart))
     pset.execute(pset.Kernel(kernel), runtime=runtime, dt=timedelta(hours=1))
 
@@ -92,15 +92,15 @@ def test_randomexponential(lambd):
     fieldset.lambd = lambd
 
     # Set random seed
-    ParcelsRandom.seed(1234)
+    random.seed(1234)
 
     pset = ParticleSet(
         fieldset=fieldset, pclass=ScipyParticle, lon=np.zeros(npart), lat=np.zeros(npart), depth=np.zeros(npart)
     )
 
     def vertical_randomexponential(particle, fieldset, time):  # pragma: no cover
         # Kernel for random exponential variable in depth direction
-        particle.depth = ParcelsRandom.expovariate(fieldset.lambd)
+        particle.depth = random.expovariate(fieldset.lambd)
 
     pset.execute(vertical_randomexponential, runtime=1, dt=1)
 
@@ -120,15 +120,15 @@ def test_randomvonmises(mu, kappa):
     fieldset.kappa = kappa
 
     # Set random seed
-    ParcelsRandom.seed(1234)
+    random.seed(1234)
 
     AngleParticle = ScipyParticle.add_variable("angle")
     pset = ParticleSet(
         fieldset=fieldset, pclass=AngleParticle, lon=np.zeros(npart), lat=np.zeros(npart), depth=np.zeros(npart)
     )
 
     def vonmises(particle, fieldset, time):  # pragma: no cover
-        particle.angle = ParcelsRandom.vonmisesvariate(fieldset.mu, fieldset.kappa)
+        particle.angle = random.vonmisesvariate(fieldset.mu, fieldset.kappa)
 
     pset.execute(vonmises, runtime=1, dt=1)