merge dev

.github/workflows/docker_deployment.yml

@@ -9,6 +9,7 @@ on:
   pull_request:
     branches:
       - 'main'
+      - 'dev'
 
 jobs:
   docker:

.github/workflows/ubuntu.yml

@@ -10,8 +10,8 @@ jobs:
     strategy:
       matrix:
         python: [ 3.8, 3.9, "3.10", "3.11" ]
-        os:  [ ubuntu-20.04 ]
-        compiler: [gcc, clang10]
+        os:  [ ubuntu-22.04 ]
+        compiler: [gcc, clang14]
         rust: [1.62.1]
     defaults:
       run:
@@ -55,19 +55,32 @@ jobs:
         run: |
           echo "$HOME/.local/bin" >> $GITHUB_PATH
 
+      - name: Set GCC as compiler
+        if: matrix.compiler == 'gcc'
+        run: |
+          echo "CC=gcc" >> $GITHUB_ENV
+          echo "CXX=g++" >> $GITHUB_ENV
+
+      - name: Install clang-14
+        if: matrix.compiler == 'clang14'
+        run: |
+          sudo apt-get install clang-14 clang++-14
+          echo "CC=clang-14" >> $GITHUB_ENV
+          echo "CXX=clang++-14" >> $GITHUB_ENV
+
       - name: Discover llvm-config
         run: |
           dpkg -S llvm-config
 
-      - name: Set LLVM_CONFIG on 20.04
-        if: matrix.os == 'ubuntu-20.04'
+      - name: Set LLVM_CONFIG on 22.04
+        if: matrix.os == 'ubuntu-22.04'
         run: |
-            echo "LLVM_CONFIG=/usr/bin/llvm-config-10" >> $GITHUB_ENV
+            echo "LLVM_CONFIG=/usr/bin/llvm-config" >> $GITHUB_ENV
 
-      - name: Set LLVM_CONFIG on 18.04
-        if: matrix.os == 'ubuntu-18.04'
-        run: |
-            echo "LLVM_CONFIG=/usr/lib/llvm-9/bin/llvm-config" >> $GITHUB_ENV
+      # - name: Set LLVM_CONFIG on 18.04
+      #   if: matrix.os == 'ubuntu-18.04'
+      #   run: |
+      #       echo "LLVM_CONFIG=/usr/lib/llvm-9/bin/llvm-config" >> $GITHUB_ENV
 
       - name: Python version
         run: |
@@ -91,20 +104,11 @@ jobs:
             # For sdist validation
             python -m pip install --user --upgrade twine
 
-      - name: Set GCC as compiler
-        if: matrix.compiler == 'gcc'
+      # Needed so that we don't affect building any pip dependencies with these flags
+      - name: Set CPPFLAGS for C++ builds
         run: |
-          echo "CC=gcc" >> $GITHUB_ENV
-          echo "CXX=g++" >> $GITHUB_ENV
           echo "CPPFLAGS=-Wextra -Weffc++ -Woverloaded-virtual -Wold-style-cast -Werror=effc++ -Werror=old-style-cast -Werror=overloaded-virtual -Werror=unused-parameter" >> $GITHUB_ENV
 
-      - name: Install clang-10
-        if: matrix.compiler == 'clang10'
-        run: |
-          sudo apt-get install clang-10 clang++-10
-          echo "CC=clang-10" >> $GITHUB_ENV
-          echo "CXX=clang++-10" >> $GITHUB_ENV
-
       - name: Build
         run: |
           cmake -E env CPPFLAGS="$CPPFLAGS" \

CMakeLists.txt

@@ -1,4 +1,7 @@
-cmake_minimum_required(VERSION 3.15)
+# Do not change this version range!
+# Doing so can break builds in unexpected ways.
+# The manylinux wheel build seem especially sensitive!
+cmake_minimum_required(VERSION 3.4...3.18)
 project(fwdpy11)
 
 set(CMAKE_CXX_EXTENSIONS OFF)
@@ -13,10 +16,12 @@ if (APPLE)
     set(CMAKE_MACOSX_RPATH 1)
 endif()
 
-find_package(pybind11)
+find_package(Python COMPONENTS Interpreter Development)
+find_package(pybind11 CONFIG)
+
 message(STATUS "Found pybind11: ${pybind11_VERSION}")
-if(${pybind11_VERSION} VERSION_LESS '2.10.0')
-    message(FATAL_ERROR "pybind11 version must be >= '2.10.0'")
+if(${pybind11_VERSION} VERSION_LESS '2.11.1')
+    message(FATAL_ERROR "pybind11 version must be >= '2.11.1'")
 endif()
 add_definitions(-DPYBIND11_VERSION="${pybind11_VERSION}")
 

cpp/CMakeLists.txt

@@ -54,6 +54,7 @@ set(GENETIC_VALUE_TO_FITNESS_SOURCES
     genetic_value_to_fitness/GeneticValueIsFitness.cc
     genetic_value_to_fitness/GeneticValueIsTrait.cc
     genetic_value_to_fitness/GSSmo.cc
+    genetic_value_to_fitness/GaussianStabilizingSelection.cc
     genetic_value_to_fitness/MultivariateGSSmo.cc
     genetic_value_to_fitness/Optimum.cc
     genetic_value_to_fitness/PleiotropicOptima.cc)

cpp/genetic_value_to_fitness/GaussianStabilizingSelection.cc

@@ -0,0 +1,19 @@
+#include <tuple>
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+#include <fwdpy11/genetic_value_to_fitness/GaussianStabilizingSelection.hpp>
+
+namespace py = pybind11;
+
+void
+init_GaussianStabilizingSelection(py::module& m)
+{
+    py::class_<fwdpy11::GaussianStabilizingSelection, fwdpy11::GeneticValueIsTrait>(
+        m, "_ll_GaussianStabilizingSelection")
+        .def(py::init([](const fwdpy11::GSSmo& single_trait) {
+            return fwdpy11::GaussianStabilizingSelection(single_trait);
+        }))
+        .def(py::init([](const fwdpy11::MultivariateGSSmo& pleiotropy) {
+            return fwdpy11::GaussianStabilizingSelection(pleiotropy);
+        }));
+}

cpp/genetic_value_to_fitness/init.cc

@@ -11,6 +11,7 @@ void init_GeneticValueToFitnessMap(py::module&);
 void init_GeneticValueIsTrait(py::module&);
 void init_GeneticValueIsFitness(py::module&);
 void init_GSSmo(py::module&);
+void init_GaussianStabilizingSelection(py::module&);
 
 // Multivariate classes
 void init_MultivariateGSSmo(py::module&);
@@ -25,6 +26,7 @@ initialize_genetic_value_to_fitness(py::module& m)
     init_GeneticValueIsTrait(m);
     init_GeneticValueIsFitness(m);
     init_GSSmo(m);
+    init_GaussianStabilizingSelection(m);
 
     init_MultivariateGSSmo(m);
 }

deployment/docker/Dockerfile

@@ -8,7 +8,7 @@ WORKDIR /app
 
 COPY . /app
 
-RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get -qq -y install cmake \
+RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get -qq -y install \
   gcc \
   git \
   g++ \

doc/long_vignettes/gss_vignette.md

@@ -38,7 +38,7 @@ class Recorder(object):
 ```
 
 Now, we will set up and simulate the model.
-We use {class}`fwdpy11.GSSmo` to specify when/how the optimum value shifts.
+We use {class}`fwdpy11.GaussianStabilizingSelection` to specify when/how the optimum value shifts.
 
 We will simulate the population for $10N$ generations around an optimum of zero.
 Then, we shift the optimum to 1 and evolve another 200 generations.
@@ -51,7 +51,7 @@ pop = fwdpy11.DiploidPopulation(500, 1.0)
 
 rng = fwdpy11.GSLrng(54321)
 
-GSSmo = fwdpy11.GSSmo(
+gssmo = fwdpy11.GaussianStabilizingSelection.single_trait(
     [
         fwdpy11.Optimum(when=0, optimum=0.0, VS=1.0),
         fwdpy11.Optimum(when=10 * pop.N - 200, optimum=1.0, VS=1.0),
@@ -62,7 +62,7 @@ rho = 1000.
 
 p = {
     "nregions": [],
-    "gvalue": fwdpy11.Additive(2.0, GSSmo),
+    "gvalue": fwdpy11.Additive(2.0, gssmo),
     "sregions": [fwdpy11.GaussianS(0, 1., 1, 0.1)],
     "recregions": [fwdpy11.PoissonInterval(0, 1., rho / float(4 * pop.N))],
     "rates": (0.0, 1e-3, None),

doc/long_vignettes/tskitconvert_vignette.md

@@ -138,11 +138,13 @@ assert "model_params" not in ts.metadata
 Here is an example of Gaussian stabilizing selection around an optimum trait value of `0.0`:
 
 ```{code-cell} python
+optimum = fwdpy11.Optimum(optimum=0.0, VS=10.0, when=0)
+gss = fwdpy11.GaussianStabilizingSelection.single_trait([optimum])
 pdict = {
     'nregions': [],
     'sregions': [fwdpy11.GaussianS(0, 1, 1, 0.10)],
     'recregions': [fwdpy11.PoissonInterval(0, 1, 1e-3)],
-    'gvalue': fwdpy11.Additive(2., fwdpy11.GSS(optimum=0.0, VS=10.0)),
+    'gvalue': fwdpy11.Additive(2., gss),
     'rates': (0.0, 1e-3, None),
     'simlen': 10 * pop.N,
     'prune_selected': False,
@@ -165,16 +167,18 @@ Imagine, for example, that we simulate the above model until equilibrium, and th
 The details are omitted here:
 
 1. This simulation requires two calls to {func}`fwdpy11.evolvets`
-2. It could have been done instead with a single call to {func}`fwdpy11.evolvets` and using
-   {class}`fwdpy11.GSSmo` and one `ModelParams` object instead of {class}`fwdpy11.GSS`
-   and two parameters objects.
+2. It could have been done instead with a single call to {func}`fwdpy11.evolvets` 
+   by passing a list of {class}`fwdpy11.Optimum` to {class}`fwdpy11.GaussianStabilizingSelection`.
+   This approach would have required one `ModelParams` instance.
 :::
 
 ```{code-cell} python
 import copy
 pdict2 = copy.deepcopy(pdict)
 
-pdict2['gvalue'] = fwdpy11.Additive(2., fwdpy11.GSS(optimum=5.0, VS=10.0)),
+optimum = fwdpy11.Optimum(optimum=5.0, VS=10.0, when=0)
+gss = fwdpy11.GaussianStabilizingSelection.single_trait([optimum])
+pdict2['gvalue'] = fwdpy11.Additive(2., gss),
 pdict2['simlen'] = 100
 
 params2 = fwdpy11.ModelParams(**pdict2)

doc/misc/changelog.md

@@ -3,6 +3,22 @@
 Major changes are listed below.  Each release likely contains fiddling with back-end code,
 updates to latest `fwdpp` version, etc.
 
+## Next release
+
+Deprecations
+
+The following are deprecated:
+
+* `fwdpy11.GSS`
+* `fwdpy11.GSSmo`
+* `fwdpy11.MutivariateGSS`
+* `fwdpy11.MutivariateGSSmo`
+
+Their functionality is replaced with {class}`fwdpy11.GaussianStabilizingSelection`.
+
+PR {pr}`1166`.
+Issue {issue}{`463`}.
+
 ## 0.21.0
 
 Breaking changes
@@ -643,12 +659,12 @@ Changes to `fwdpy11.conditional_models`:
 
 Bug fixes
 
-* Fixed bug in updating {class}`fwdpy11.MultivariateGSSmo`.
+* Fixed bug in updating `fwdpy11.MultivariateGSSmo`.
   PR {pr}`867`.
 
 Back end changes:
 
-* {class}`fwdpy11.GSSmo` and {class}`fwdpy11.MultivariateGSSmo` now handle cases where population start time is greater than zero.
+* `fwdpy11.GSSmo` and `fwdpy11.MultivariateGSSmo` now handle cases where population start time is greater than zero.
   PR {pr}`867`.
 
 Build system:
@@ -1260,7 +1276,7 @@ Maintenance release and one new feature:
 
 * Allow the first generation of a simulation to be preserved. PR {pr}`470`
   See {ref}`recapitation`.
-* Parameterizing classes like {class}`fwdpy11.GSSmo` is now more Pythonic,
+* Parameterizing classes like `fwdpy11.GSSmo` is now more Pythonic,
   and some existing `init` methods are deprecated in favor of the
   new approach. PR {pr}`461`.
 
@@ -1479,7 +1495,7 @@ Miscellaneous changes:
 The following bugs are fixed:
 
 * Mutations were not being recycled properly during simulations with tree sequences, resulting in excessive memory consumption. PR {pr}`317`
-* Several interface issues with {class}`fwdpy11.MultivariateGSSmo` are fixed. PR {pr}`313`
+* Several interface issues with `fwdpy11.MultivariateGSSmo` are fixed. PR {pr}`313`
 * Fix a bug that could lead to fixations with tree sequences not "pruning" selected fixations when that behavior is desired. {issue}`287`, fixed in PR {pr}`289`
 * A memory safety issue was fixed in the implementation of {attr}`fwdpy11.TreeIterator.samples_below`. PR {pr}`300`.  {issue}`299`
 

doc/pages/advancedtopics.md

@@ -560,7 +560,8 @@ class MyGeneticValueToFitness(fwdpy11.GeneticValueIsTrait):
 ```
 
 Two complete examples come from the test suite.  The first example reimplements
-{class}`fwdpy11.GSS` in Python.  The second example implements a model
+{class}`fwdpy11.GaussianStabilizingSelection` in Python for a single trait.
+The second example implements a model
 where the optimum changes to a new value each generation. (Note that
 the second model requires that {func}`numpy.random.seed` be called elsewhere
 so that results are reproducible.)

doc/pages/gvalue_to_fitness.md

@@ -13,16 +13,6 @@
 .. autoclass:: fwdpy11.GeneticValueIsFitness
 ```
 
-```{eval-rst}
-.. autoclass:: fwdpy11.GSS
-    :members: asdict, fromdict, asblack
-```
-
-```{eval-rst}
-.. autoclass:: fwdpy11.GSSmo
-    :members: asdict, fromdict, asblack
-```
-
 ```{eval-rst}
 .. autoclass:: fwdpy11.Optimum
     :members: asdict, fromdict, asblack
@@ -33,14 +23,10 @@
     :members: asdict, fromdict, asblack
 ```
 
-```{eval-rst}
-.. autoclass:: fwdpy11.MultivariateGSS
-    :members: asdict, fromdict, asblack
-```
 
 ```{eval-rst}
-.. autoclass:: fwdpy11.MultivariateGSSmo
-    :members: asdict, fromdict, asblack
+.. autoclass:: fwdpy11.GaussianStabilizingSelection
+    :members:
 ```
 
 

doc/short_vignettes/evolvets_vignette.md

@@ -35,7 +35,7 @@ pop = fwdpy11.DiploidPopulation(500, 1.0)
 
 rng = fwdpy11.GSLrng(54321)
 
-GSSmo = fwdpy11.GSSmo(
+GSSmo = fwdpy11.GaussianStabilizingSelection.single_trait(
     [
         fwdpy11.Optimum(when=0, optimum=0.0, VS=1.0),
         fwdpy11.Optimum(when=10 * pop.N - 200, optimum=1.0, VS=1.0),