diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 7855e7397..9a434d82e 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -73,7 +73,7 @@ jobs:
run: .github/workflows/install_deps.sh amici pysb
- name: Run tests
- timeout-minutes: 25
+ timeout-minutes: 35
run: tox -e petab
- name: Coverage
@@ -166,15 +166,15 @@ jobs:
steps:
- name: Check out repository
- uses: actions/checkout@v2
+ uses: actions/checkout@v3
- name: Prepare python ${{ matrix.python-version }}
- uses: actions/setup-python@v1
+ uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Cache
- uses: actions/cache@v1
+ uses: actions/cache@v3
with:
path: ~/.cache
key: ${{ runner.os }}-${{ matrix.python-version }}-ci-hierarchical
diff --git a/.github/workflows/install_deps.sh b/.github/workflows/install_deps.sh
index 260d48628..09957e254 100755
--- a/.github/workflows/install_deps.sh
+++ b/.github/workflows/install_deps.sh
@@ -37,7 +37,7 @@ for par in "$@"; do
pysb)
# bionetgen
wget -q -O bionetgen.tar \
- https://github.com/RuleWorld/bionetgen/releases/download/BioNetGen-2.6.0/BioNetGen-2.6.0-linux.tgz
+ https://github.com/RuleWorld/bionetgen/releases/download/BioNetGen-2.8.5/BioNetGen-2.8.5-linux.tar.gz
tar -xf bionetgen.tar
;;
diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 8724e6fc2..b51746437 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -6,6 +6,33 @@ Release notes
..........
+0.3.1 (2023-06-22)
+-------------------
+* Visualize:
+ * Parameter plot w/ hier. pars, noise estimation for splines (#1061)
+* Sampling:
+ * AdaptiveMetropolis failure fix for bounded priors (#1065)
+* Ensembles
+ * Speed up Ensemble from History (#1063)
+* PEtab support:
+ * Support for petab 0.2.x (#1073)
+ * Remove PetabImporterPysb #1082)
+* Objective
+ * AggregatedObjective: objective-specific kwargs for call_unprocessed (#1068)
+* Select
+ * Use predecessor stored in file (#1059)
+ * support petab-select version 0.1.8 (#1070)
+* Examples
+ * Synthetic data: update for libpetab-python v0.2.0 (#1060)
+ * Fix error in sampling_diagnostics which led to test failure(#1092)
+* General
+ * Test fixes (#1064)
+ * Fix numpy DeprecationWarnings (#1076)
+ * GHA: Fix deprecation warnings (#1075)
+ * Fixed bug on existing file and no overwrite (#1046)
+ * Fix error in bound checking (#1081)
+
+
0.3.0 (2023-05-02)
-------------------
diff --git a/doc/example/example_nonlinear_monotone.ipynb b/doc/example/example_nonlinear_monotone.ipynb
index 7604b9fef..9c5881d5c 100644
--- a/doc/example/example_nonlinear_monotone.ipynb
+++ b/doc/example/example_nonlinear_monotone.ipynb
@@ -46,7 +46,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
@@ -83,7 +83,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
@@ -105,7 +105,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
@@ -453,6 +453,153 @@
" display(petab_problem.measurement_df)"
]
},
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "To estimate the noise parameters of the nonlinear-monotone observables, those noise parameters in the `parameter.tsv` file have to have column entries `estimate` with value 1 and column entry `parameterType` with value `sigma`, as in case of using relative data:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " parameterId | \n",
+ " parameterName | \n",
+ " parameterScale | \n",
+ " lowerBound | \n",
+ " upperBound | \n",
+ " nominalValue | \n",
+ " estimate | \n",
+ " parameterType | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " K1 | \n",
+ " K1 | \n",
+ " lin | \n",
+ " -5.00000 | \n",
+ " 5.0 | \n",
+ " 0.04 | \n",
+ " 0 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 1 | \n",
+ " K2 | \n",
+ " K2 | \n",
+ " lin | \n",
+ " -5.00000 | \n",
+ " 5.0 | \n",
+ " 20.00 | \n",
+ " 0 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 2 | \n",
+ " K3 | \n",
+ " K3 | \n",
+ " log10 | \n",
+ " 0.10000 | \n",
+ " 100000.0 | \n",
+ " 4000.00 | \n",
+ " 1 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 3 | \n",
+ " K5 | \n",
+ " K5 | \n",
+ " log10 | \n",
+ " 0.00001 | \n",
+ " 100000.0 | \n",
+ " 0.10 | \n",
+ " 1 | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " 4 | \n",
+ " sd_Activity | \n",
+ " \\sigma_{activity} | \n",
+ " lin | \n",
+ " 0.00000 | \n",
+ " inf | \n",
+ " 1.00 | \n",
+ " 1 | \n",
+ " sigma | \n",
+ "
\n",
+ " \n",
+ " 5 | \n",
+ " sd_Ybar | \n",
+ " \\sigma_{ybar} | \n",
+ " lin | \n",
+ " 0.00000 | \n",
+ " inf | \n",
+ " 1.00 | \n",
+ " 1 | \n",
+ " sigma | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " parameterId parameterName parameterScale lowerBound upperBound \\\n",
+ "0 K1 K1 lin -5.00000 5.0 \n",
+ "1 K2 K2 lin -5.00000 5.0 \n",
+ "2 K3 K3 log10 0.10000 100000.0 \n",
+ "3 K5 K5 log10 0.00001 100000.0 \n",
+ "4 sd_Activity \\sigma_{activity} lin 0.00000 inf \n",
+ "5 sd_Ybar \\sigma_{ybar} lin 0.00000 inf \n",
+ "\n",
+ " nominalValue estimate parameterType \n",
+ "0 0.04 0 NaN \n",
+ "1 20.00 0 NaN \n",
+ "2 4000.00 1 NaN \n",
+ "3 0.10 1 NaN \n",
+ "4 1.00 1 sigma \n",
+ "5 1.00 1 sigma "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import pandas as pd\n",
+ "\n",
+ "noise_parameter_file = 'parameters_example_nonlinear_monotone_noise.tsv'\n",
+ "# load the csv file\n",
+ "noise_parameter_df = pd.read_csv(petab_folder + noise_parameter_file, sep='\\t')\n",
+ "with option_context('display.max_colwidth', 400):\n",
+ " display(noise_parameter_df)"
+ ]
+ },
{
"attachments": {},
"cell_type": "markdown",
@@ -502,7 +649,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
@@ -519,7 +666,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
@@ -551,7 +698,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
@@ -584,7 +731,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 20,
"metadata": {
"scrolled": true
},
@@ -593,7 +740,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "100%|██████████| 10/10 [00:15<00:00, 1.55s/it]\n"
+ "100%|██████████| 10/10 [00:13<00:00, 1.35s/it]\n"
]
}
],
@@ -615,12 +762,12 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
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",
+ "image/png": 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",
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