diff --git a/lbmpy/macroscopic_value_kernels.py b/lbmpy/macroscopic_value_kernels.py
index bcfc9422c22fc3e353cc4bd73bb14eb6344823b5..4ec4f31ae4e44f0468ec58a191ea9843c8072a97 100644
--- a/lbmpy/macroscopic_value_kernels.py
+++ b/lbmpy/macroscopic_value_kernels.py
@@ -8,11 +8,11 @@ from lbmpy.advanced_streaming.utility import get_accessor, Timestep
def pdf_initialization_assignments(lb_method, density, velocity, pdfs,
- streaming_pattern='pull', timestep=Timestep.BOTH,
+ streaming_pattern='pull', previous_timestep=Timestep.BOTH,
set_pre_collision_pdfs=False):
"""Assignments to initialize the pdf field with equilibrium"""
if isinstance(pdfs, Field):
- accessor = get_accessor(streaming_pattern, timestep)
+ accessor = get_accessor(streaming_pattern, previous_timestep)
if set_pre_collision_pdfs:
field_accesses = accessor.read(pdfs, lb_method.stencil)
else:
@@ -32,10 +32,10 @@ def pdf_initialization_assignments(lb_method, density, velocity, pdfs,
def macroscopic_values_getter(lb_method, density, velocity, pdfs,
- streaming_pattern='pull', timestep=Timestep.BOTH,
+ streaming_pattern='pull', previous_timestep=Timestep.BOTH,
use_pre_collision_pdfs=False):
if isinstance(pdfs, Field):
- accessor = get_accessor(streaming_pattern, timestep)
+ accessor = get_accessor(streaming_pattern, previous_timestep)
if use_pre_collision_pdfs:
field_accesses = accessor.read(pdfs, lb_method.stencil)
else:
diff --git a/lbmpy_tests/advanced_streaming/test_fully_periodic_flow.py b/lbmpy_tests/advanced_streaming/test_fully_periodic_flow.py
index 4b52a17416ce505889cb1d085c815d38c173bfe8..4dc7b6b1a5fde034c49c59c3d82fcd22f8c89699 100644
--- a/lbmpy_tests/advanced_streaming/test_fully_periodic_flow.py
+++ b/lbmpy_tests/advanced_streaming/test_fully_periodic_flow.py
@@ -105,14 +105,14 @@ def test_fully_periodic_flow(target, stencil, streaming_pattern):
setter = macroscopic_values_setter(
lb_method, density, velocity, pdfs,
- streaming_pattern=streaming_pattern, timestep=zeroth_timestep)
+ streaming_pattern=streaming_pattern, previous_timestep=zeroth_timestep)
setter_kernel = create_kernel(setter, ghost_layers=1, target=target).compile()
getter_kernels = []
for t in timesteps:
getter = macroscopic_values_getter(
lb_method, density_field, velocity_field, pdfs,
- streaming_pattern=streaming_pattern, timestep=t)
+ streaming_pattern=streaming_pattern, previous_timestep=t)
getter_kernels.append(create_kernel(getter, ghost_layers=1, target=target).compile())
# Periodicity
diff --git a/lbmpy_tests/advanced_streaming/test_periodic_pipe_with_force.py b/lbmpy_tests/advanced_streaming/test_periodic_pipe_with_force.py
index 1cc3526386d1db65b6e5416e7bd02a06045139c2..cafd293b2ddb34e44fbe06f22aca35c05ac167b6 100644
--- a/lbmpy_tests/advanced_streaming/test_periodic_pipe_with_force.py
+++ b/lbmpy_tests/advanced_streaming/test_periodic_pipe_with_force.py
@@ -106,14 +106,14 @@ class PeriodicPipeFlow:
setter = macroscopic_values_setter(
self.lb_method, self.density, self.velocity, self.pdfs,
- streaming_pattern=self.streaming_pattern, timestep=self.zeroth_timestep)
+ streaming_pattern=self.streaming_pattern, previous_timestep=self.zeroth_timestep)
self.init_kernel = create_kernel(setter, ghost_layers=1, target=self.target).compile()
self.getter_kernels = []
for t in self.timesteps:
getter = macroscopic_values_getter(
self.lb_method, self.density_field, self.velocity_field, self.pdfs,
- streaming_pattern=self.streaming_pattern, timestep=t)
+ streaming_pattern=self.streaming_pattern, previous_timestep=t)
self.getter_kernels.append(create_kernel(getter, ghost_layers=1, target=self.target).compile())
# Periodicity
diff --git a/lbmpy_tests/centeredcumulant/test_flow_around_sphere.py b/lbmpy_tests/centeredcumulant/test_flow_around_sphere.py
index beb2d3db62db48ef7328815909913b449a9112fd..686eb0f60e14fc3c88098b30d143f910aab8c84f 100644
--- a/lbmpy_tests/centeredcumulant/test_flow_around_sphere.py
+++ b/lbmpy_tests/centeredcumulant/test_flow_around_sphere.py
@@ -104,7 +104,7 @@ def flow_around_sphere(stencil, galilean_correction, L_LU, total_steps):
init_eqs = pdf_initialization_assignments(lb_method, 1.0, initial_velocity, pdf_field,
streaming_pattern=streaming_pattern,
- timestep=timesteps[0])
+ previous_timestep=timesteps[0])
init_kernel = create_kernel(init_eqs, target=target).compile()
output = {
diff --git a/lbmpy_tests/centeredcumulant/test_periodic_pipe_flow.ipynb b/lbmpy_tests/centeredcumulant/test_periodic_pipe_flow.ipynb
index eb5562c460dd46558353b7bc7b43ebb485c9cab3..8076fdd2cdc9de4588dc54b8b8359bbfd234ebc6 100644
--- a/lbmpy_tests/centeredcumulant/test_periodic_pipe_flow.ipynb
+++ b/lbmpy_tests/centeredcumulant/test_periodic_pipe_flow.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 1,
"source": [
"import pytest\n",
"pytest.importorskip('pycuda')"
@@ -16,33 +16,24 @@
]
},
"metadata": {},
- "execution_count": 7
+ "execution_count": 1
}
],
"metadata": {}
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 2,
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
],
- "outputs": [
- {
- "output_type": "stream",
- "name": "stdout",
- "text": [
- "The autoreload extension is already loaded. To reload it, use:\n",
- " %reload_ext autoreload\n"
- ]
- }
- ],
+ "outputs": [],
"metadata": {}
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 3,
"source": [
"import sympy as sp\n",
"import numpy as np\n",
@@ -70,7 +61,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 4,
"source": [
"class PeriodicPipeFlow:\n",
" def __init__(self, method_params, optimization=dict()):\n",
@@ -132,14 +123,14 @@
"\n",
" setter = macroscopic_values_setter(\n",
" self.lb_method, self.density, self.velocity, self.pdfs,\n",
- " streaming_pattern=self.streaming_pattern, timestep=self.zeroth_timestep)\n",
+ " streaming_pattern=self.streaming_pattern, previous_timestep=self.zeroth_timestep)\n",
" self.init_kernel = create_kernel(setter, ghost_layers=1, target=self.target).compile()\n",
"\n",
" self.getter_kernels = []\n",
" for t in self.timesteps:\n",
" getter = macroscopic_values_getter(\n",
" self.lb_method, self.density_field, self.velocity_field, self.pdfs,\n",
- " streaming_pattern=self.streaming_pattern, timestep=t)\n",
+ " streaming_pattern=self.streaming_pattern, previous_timestep=t)\n",
" self.getter_kernels.append(create_kernel(getter, ghost_layers=1, target=self.target).compile())\n",
"\n",
" # Periodicity\n",
@@ -219,7 +210,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 5,
"source": [
"stencil = get_stencil('D3Q19')\n",
"dim = len(stencil[0])\n",
@@ -243,7 +234,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 6,
"source": [
"srt_params = {\n",
" 'stencil': stencil,\n",
@@ -263,7 +254,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 7,
"source": [
"srt_u = srt_flow.get_trimmed_velocity_array()\n",
"ps.plot.vector_field_magnitude(srt_u[30,:,:,:])\n",
@@ -274,11 +265,11 @@
"output_type": "execute_result",
"data": {
"text/plain": [
- "<matplotlib.colorbar.Colorbar at 0x7faa51244c40>"
+ "<matplotlib.colorbar.Colorbar at 0x7fd9a51311c0>"
]
},
"metadata": {},
- "execution_count": 13
+ "execution_count": 7
},
{
"output_type": "display_data",
@@ -310,7 +301,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 8,
"source": [
"cm_method_params = {\n",
" 'method' : 'monomial_cumulant',\n",
@@ -333,7 +324,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 9,
"source": [
"lb_method = cm_impl_f_flow.lb_method\n",
"assert all(rr == 2 for rr in lb_method.relaxation_rates[1:4])\n",
@@ -344,7 +335,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 10,
"source": [
"cm_impl_f_flow.init()\n",
"cm_impl_f_flow.run(400)"
@@ -354,7 +345,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 11,
"source": [
"cm_impl_f_u = cm_impl_f_flow.get_trimmed_velocity_array()\n",
"ps.plot.vector_field_magnitude(cm_impl_f_u[30,:,:,:])\n",
@@ -365,11 +356,11 @@
"output_type": "execute_result",
"data": {
"text/plain": [
- "<matplotlib.colorbar.Colorbar at 0x7faa5077ed30>"
+ "<matplotlib.colorbar.Colorbar at 0x7fd9a40bd5e0>"
]
},
"metadata": {},
- "execution_count": 17
+ "execution_count": 11
},
{
"output_type": "display_data",
@@ -388,7 +379,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 12,
"source": [
"assert_allclose(cm_impl_f_u, srt_u, rtol=1, atol=1e-4)"
],
@@ -404,7 +395,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 13,
"source": [
"from lbmpy.forcemodels import Simple\n",
"\n",
@@ -429,7 +420,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 14,
"source": [
"lb_method = cm_expl_f_flow.lb_method\n",
"assert all(rr == 0 for rr in lb_method.relaxation_rates[1:4])\n",
@@ -440,7 +431,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 15,
"source": [
"cm_expl_f_flow.init()\n",
"cm_expl_f_flow.run(400)"
@@ -450,7 +441,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 16,
"source": [
"cm_expl_f_u = cm_expl_f_flow.get_trimmed_velocity_array()\n",
"ps.plot.vector_field_magnitude(cm_expl_f_u[30,:,:,:])\n",
@@ -461,11 +452,11 @@
"output_type": "execute_result",
"data": {
"text/plain": [
- "<matplotlib.colorbar.Colorbar at 0x7faa506476a0>"
+ "<matplotlib.colorbar.Colorbar at 0x7fd99ddf0e20>"
]
},
"metadata": {},
- "execution_count": 22
+ "execution_count": 16
},
{
"output_type": "display_data",
@@ -484,7 +475,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 17,
"source": [
"assert_allclose(cm_expl_f_u, srt_u, rtol=1, atol=1e-4)\n",
"assert_allclose(cm_expl_f_u, cm_impl_f_u, rtol=1, atol=1e-4)"
diff --git a/lbmpy_tests/test_compiled_in_boundaries.ipynb b/lbmpy_tests/test_compiled_in_boundaries.ipynb
index 3ea3e793df5ad8b371c39515e4968d09369197b3..97a0cbfd822c08941b3f9ed6bd093c169391064a 100644
--- a/lbmpy_tests/test_compiled_in_boundaries.ipynb
+++ b/lbmpy_tests/test_compiled_in_boundaries.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 8,
"source": [
"from lbmpy.session import *\n",
"from lbmpy.boundaries.boundaries_in_kernel import update_rule_with_push_boundaries\n",
@@ -22,7 +22,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 9,
"source": [
"domain_size = (32, 32, 32)\n",
"relaxation_rate = 1.8\n",
@@ -34,7 +34,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 10,
"source": [
"dh = create_data_handling(domain_size, default_target='cpu')\n",
"pdfs = dh.add_array('pdfs', values_per_cell=19)\n",
@@ -46,7 +46,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 11,
"source": [
"boundaries = OrderedDict((\n",
" ((0, 1, 0), UBB([lid_velocity, 0, 0])), \n",
@@ -65,7 +65,7 @@
"getter_assignments = macroscopic_values_getter(update_rule_aa_even.method, velocity=u.center_vector,\n",
" pdfs=pdfs, density=None,\n",
" streaming_pattern=streaming_pattern, \n",
- " timestep=Timestep.EVEN)\n",
+ " previous_timestep=Timestep.EVEN)\n",
"\n",
"getter_kernel = ps.create_kernel(getter_assignments, target=dh.default_target).compile()\n",
"even_kernel = ps.create_kernel(update_rule_aa_even, target=dh.default_target, ghost_layers=1).compile()\n",
@@ -76,7 +76,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 12,
"source": [
"def init():\n",
" dh.fill(pdfs.name, 0, ghost_layers=True)\n",
@@ -95,7 +95,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 13,
"source": [
"init()\n",
"aa_time_loop(time_steps)\n",
@@ -108,11 +108,11 @@
"output_type": "execute_result",
"data": {
"text/plain": [
- "<matplotlib.colorbar.Colorbar at 0x7f7c316778e0>"
+ "<matplotlib.colorbar.Colorbar at 0x7f0cfc8f5b50>"
]
},
"metadata": {},
- "execution_count": 10
+ "execution_count": 13
},
{
"output_type": "display_data",
@@ -138,7 +138,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 14,
"source": [
"ldc = create_lid_driven_cavity(domain_size, relaxation_rate=relaxation_rate, lid_velocity=lid_velocity)\n",
"ldc.run(time_steps)\n",
@@ -152,11 +152,11 @@
"output_type": "execute_result",
"data": {
"text/plain": [
- "<matplotlib.colorbar.Colorbar at 0x7f7c30fd9d60>"
+ "<matplotlib.colorbar.Colorbar at 0x7f0cfca3ceb0>"
]
},
"metadata": {},
- "execution_count": 11
+ "execution_count": 14
},
{
"output_type": "display_data",