call to tests now work from every folder, updated tutorial

.github/workflows/test_publish_pypi.yml

@@ -29,12 +29,12 @@ jobs:
         pip install -e .
 
     - name: Run tests
-      run: |
-        it=100 python3 -m unittest linfa.tests.test_linfa.linfa_test_suite.trivial_example
-        it=100 python3 -m unittest linfa.tests.test_linfa.linfa_test_suite.highdim_example
-        it=100 python3 -m unittest linfa.tests.test_linfa.linfa_test_suite.rc_example
-        it=100 python3 -m unittest linfa.tests.test_linfa.linfa_test_suite.rcr_example
-        it=100 python3 -m unittest linfa.tests.test_linfa.linfa_test_suite.adaann_example
+      run: |      
+        it=100 python3 -m unittest linfa.linfa_test_suite.trivial_example
+        it=100 python3 -m unittest linfa.linfa_test_suite.highdim_example
+        it=100 python3 -m unittest linfa.linfa_test_suite.rc_example
+        it=100 python3 -m unittest linfa.linfa_test_suite.rcr_example
+        it=100 python3 -m unittest linfa.linfa_test_suite.adaann_example
 
     - name: Publish to PyPI
       # if: startsWith(github.ref, 'refs/tags')      

README.md

@@ -47,14 +47,15 @@ The implementation of the lumped parameter network models (RC and RCR models) fo
 
 To run the tests type
 ```sh
-python -m unittest linfa.tests.test_linfa.linfa_test_suite.NAME_example
+python -m unittest linfa.linfa_test_suite.NAME_example
 ```
 where `NAME` need to be replaced by
 * `trivial` for the trivial example (Ex 1).
 * `highdim` for the high-dimensional example (Ex 2).
 * `rc` for the RC model (Ex 3).
 * `rcr` for the RCR model (Ex 4).
 * `adaann` for the Friedman model example (Ex 5).
+* `rcr_nofas_adaann_example` for the RCR model, combining NoFAS with adaptive annealing (AdaAnn)
 
 At regular intervals set by the parameter `experiment.save_interval` LINFA writes a few results files. The sub-string `NAME` refers to the experiment name specified in the `experiment.name` variable, and `IT` indicates the iteration at which the file is written. The results files are
 
@@ -89,7 +90,7 @@ In addition you need to specify a list of options as discussed in the [documenta
 
 ### Tutorial
 
-A (tutorial)[] is also available which will guide you through the definition of each of the quantities and function required by LINFA. 
+A step by step [tutorial](tutorial/TutorialwithPhys.ipynb) is also available which will guide you through the an inference problem for a ballistic simulation. 
 
 ### Citation
 

linfa/__init__.py

@@ -1 +1 @@
-from tests.test_linfa import linfa_test_suite
+from linfa.tests.test_linfa import linfa_test_suite

linfa/tests/__init__.py

@@ -1 +1 @@
-from test_linfa import linfa_test_suite
+from linfa.tests.test_linfa import linfa_test_suite

linfa/tests/test_linfa.py

@@ -1,5 +1,6 @@
 import unittest
 import os
+import linfa
 from linfa.run_experiment import experiment
 from linfa.transform import Transformation
 from linfa.nofas import Surrogate
@@ -77,7 +78,8 @@ def trivial_example(self):
         exp.model = model
 
         # Get data
-        model.data = np.loadtxt('./resource/data/data_trivial.txt')
+        res_path = os.path.abspath(os.path.join(os.path.dirname(linfa.__file__), os.pardir))
+        model.data = np.loadtxt(res_path + '/resource/data/data_trivial.txt')
 
         # Define surrogate
         exp.surrogate = Surrogate(exp.name, lambda x: model.solve_t(trsf.forward(x)), 2, 2, 
@@ -196,7 +198,8 @@ def highdim_example(self):
         exp.model = model
 
         # Read data
-        model.data = np.loadtxt('./resource/data/data_highdim.txt')
+        res_path = os.path.abspath(os.path.join(os.path.dirname(linfa.__file__), os.pardir))
+        model.data = np.loadtxt(res_path + '/resource/data/data_highdim.txt')
 
         # Define the surrogate
         exp.surrogate = Surrogate(exp.name, lambda x: model.solve_t(trsf.forward(x)), model.input_num, model.output_num,
@@ -310,12 +313,13 @@ def rc_example(self):
         # Define model
         cycleTime = 1.07
         totalCycles = 10
-        forcing = np.loadtxt('./resource/data/inlet.flow')
+        res_path = os.path.abspath(os.path.join(os.path.dirname(linfa.__file__), os.pardir))
+        forcing = np.loadtxt(res_path + '/resource/data/inlet.flow')
         model = rcModel(cycleTime, totalCycles, forcing, device=exp.device)  # RCR Model Defined
         exp.model = model
 
         # Read Data
-        model.data = np.loadtxt('./resource/data/data_rc.txt')
+        model.data = np.loadtxt(res_path + '/resource/data/data_rc.txt')
 
         # Define surrogate model
         exp.surrogate = Surrogate(exp.name, lambda x: model.solve_t(trsf.forward(x)), exp.input_size, 3,
@@ -430,12 +434,13 @@ def rcr_example(self):
         # Define model
         cycleTime = 1.07
         totalCycles = 10
-        forcing = np.loadtxt('./resource/data/inlet.flow')
+        res_path = os.path.abspath(os.path.join(os.path.dirname(linfa.__file__), os.pardir))
+        forcing = np.loadtxt(res_path + '/resource/data/inlet.flow')
         model = rcrModel(cycleTime, totalCycles, forcing, device=exp.device)  # RCR Model Defined
         exp.model = model
 
         # Read data
-        model.data = np.loadtxt('./resource/data/data_rcr.txt')
+        model.data = np.loadtxt(res_path + '/resource/data/data_rcr.txt')
 
         # Define surrogate
         exp.surrogate = Surrogate(exp.name, lambda x: model.solve_t(trsf.forward(x)), exp.input_size, 3,
@@ -551,7 +556,8 @@ def adaann_example(self):
         exp.device = torch.device('cuda:0' if torch.cuda.is_available() and not exp.no_cuda else 'cpu')
 
         # Model Setting
-        data_set = np.loadtxt('./resource/data/D1000.csv',delimiter=',',skiprows=1)
+        res_path = os.path.abspath(os.path.join(os.path.dirname(linfa.__file__), os.pardir))
+        data_set = np.loadtxt(res_path + '/resource/data/D1000.csv',delimiter=',',skiprows=1)
         data = torch.tensor(data_set).to(exp.device)
 
         def log_density(params, d):
@@ -659,12 +665,13 @@ def rcr_nofas_adaann_example(run_nofas=True, run_adaann=False):
         # Define model
         cycleTime = 1.07
         totalCycles = 10
-        forcing = np.loadtxt('./resource/data/inlet.flow')
+        res_path = os.path.abspath(os.path.join(os.path.dirname(linfa.__file__), os.pardir))
+        forcing = np.loadtxt(res_path + '/resource/data/inlet.flow')
         model = rcrModel(cycleTime, totalCycles, forcing, device=exp.device)  # RCR Model Defined
         exp.model = model
 
         # Read data
-        model.data = np.loadtxt('./resource/data/data_rcr.txt')
+        model.data = np.loadtxt(res_path + '/resource/data/data_rcr.txt')
 
         # Define surrogate
         exp.surrogate = Surrogate(exp.name, lambda x: model.solve_t(trsf.forward(x)), exp.input_size, 3,

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "linfa_vi"
-version = "1.1.4"
+version = "1.1.5"
 description = "A Python library for inference with normalizing flow and annealing"
 readme = "README.md"
 authors = [{ name = "resDesLab ", email = "daniele.schiavazzi@gmail.com" }]