Merge pull request #38 from vinferrer/integration

add Integration tests to the toolbox

.circleci/config.yml

@@ -165,6 +165,27 @@ jobs:
       - codecov/upload:
           file: /tmp/src/connPFM/coverage.xml
 
+  py39_integration_and_coverage:
+    working_directory: /tmp/src/connPFM
+    docker:
+      - image: connpfm/afni_miniconda
+    steps:
+      - attach_workspace:  # get connPFM
+          at: /tmp
+      - restore_cache:  # load environment
+          key: deps1-{{ checksum "connPFM/info.py" }}-{{ checksum "setup.py" }}
+      - run:
+          name: Run tests and compile coverage
+          command:  |
+            apt-get update
+            apt-get install -yqq make
+            apt-get install -yqq curl
+            cp -r /opt/conda/envs/py39_env /opt/miniconda-latest/envs/py39_env
+            source activate py39_env
+            make integration
+      - codecov/upload:
+          file: /tmp/src/connPFM/coverage.xml
+
   build_docs:
     working_directory: /tmp/src/connPFM
     docker:
@@ -283,6 +304,9 @@ workflows:
       - py39_unittest_and_coverage:
           requires:
             - py39_env
+      - py39_integration_and_coverage:
+          requires:
+            - py39_env
       - build_slim_latest:
           requires:
            - py39_unittest_and_coverage

Makefile

@@ -12,7 +12,8 @@ lint:
 	@flake8 connPFM
 
 unittest:
-	@py.test -m "not integration" --cov-append --cov-report xml --cov-report term-missing --cov=connPFM connPFM
+	@py.test --skipintegration --cov-append --cov-report xml --cov-report term-missing --cov=connPFM connPFM
 
-performancetest:
-	@py.test -m "integration" --cov-append --cov-report xml --cov-report term-missing --cov=connPFM connPFM
+integration:
+	@pip install -e ".[test]"
+	@py.test --cov-append --cov-report xml --cov-report term-missing --cov=connPFM connPFM/tests/test_integration.py

connPFM/deconvolution/stability_lars.py

@@ -1,3 +1,5 @@
+import os
+
 import numpy as np
 from sklearn.linear_model import lars_path
 
@@ -11,6 +13,8 @@ def __init__(self, nsurrogates=100, mode=1, nTE=1, key=1, maxiterfactor=0.5):
         self.maxiterfactor = maxiterfactor
 
     def _subsampling(self):
+        if "mode" in os.environ.keys():  # only for testing
+            np.random.seed(200)
         # Subsampling for Stability Selection
         if self.mode == 1:  # different time points are selected across echoes
             subsample_idx = np.sort(

connPFM/tests/conftest.py

@@ -68,17 +68,17 @@ def bold_file(testpath):
 
 @pytest.fixture
 def AUC_file(testpath):
-    return fetch_file("h6uv3", testpath, "sub-pixar123_task-pixar_AUC_100.nii.gz")
+    return fetch_file("nh6y9", testpath, "sub-pixar123_task-pixar_AUC_100_200_seed.nii.gz")
 
 
 @pytest.fixture
 def ets_auc_original_file(testpath):
-    return fetch_file("bnp4z", testpath, "ets_AUC_original.txt")
+    return fetch_file("56apy", testpath, "ets_AUC_original_200_seed.txt")
 
 
 @pytest.fixture
 def ets_auc_denoised_file(testpath):
-    return fetch_file("jvuwn", testpath, "ets_AUC_denoised.txt")
+    return fetch_file("57fcw", testpath, "ets_AUC_denoised_200_seed.txt")
 
 
 @pytest.fixture
@@ -97,6 +97,11 @@ def atlas_file(testpath):
     )
 
 
+@pytest.fixture
+def atlas_1roi(testpath):
+    return fetch_file("ankvr", testpath, "Schaefer_1Parcel_4mm.nii.gz")
+
+
 @pytest.fixture
 def rssr_auc_file(testpath):
     return fetch_file("7pnj2", testpath, "rssr_AUC.txt")
@@ -119,16 +124,12 @@ def hrf_linear_file(testpath):
 
 @pytest.fixture
 def beta_file(testpath):
-    return fetch_file(
-        "apuv9", testpath, "sub-pixar123_task-pixar_space-MNI152-preproc_bold_beta_ETS.nii.gz"
-    )
+    return fetch_file("2pmju", testpath, "sub-pixar123_task-pixar_beta_ETS.nii.gz")
 
 
 @pytest.fixture
 def fitt_file(testpath):
-    return fetch_file(
-        "c7g69", testpath, "sub-pixar123_task-pixar_space-MNI152-preproc_bold_fitt_ETS.nii.gz"
-    )
+    return fetch_file("ud369", testpath, "sub-pixar123_task-pixar_fitt_ETS.nii.gz")
 
 
 @pytest.fixture

connPFM/tests/test_integration.py

@@ -0,0 +1,81 @@
+import subprocess
+from os.path import basename, join
+
+import numpy as np
+import pytest
+from nilearn.input_data import NiftiLabelsMasker
+
+
+def test_integration_pfm(testpath, bold_file, atlas_1roi, AUC_file, skip_integration):
+    if skip_integration:
+        pytest.skip("Skipping integration test")
+    auc_output = join(testpath, "auc_local.nii.gz")
+    subprocess.call(
+        "export mode=integration_pfm && "
+        "connPFM -i {} -a {} --AUC {} -tr 1 -u vferrer -job 0 -nsur 1 -w pfm".format(
+            bold_file, atlas_1roi, auc_output
+        ),
+        shell=True,
+    )
+    masker = NiftiLabelsMasker(
+        labels_img=atlas_1roi,
+        standardize=False,
+        strategy="mean",
+        resampling_target=None,
+    )
+    # compare the AUC values
+    auc_osf = masker.fit_transform(AUC_file)
+    auc_local = masker.fit_transform(auc_output)
+    np.allclose(auc_osf, auc_local)
+
+
+def test_integration_ev(
+    testpath, bold_file, atlas_file, AUC_file, ets_auc_denoised_file, surr_dir, skip_integration
+):
+    if skip_integration:
+        pytest.skip("Skipping integration test")
+    subprocess.call(
+        "connPFM -i {} -a {} --AUC {} -d {} -m {} -tr 1 -u vferrer -nsur 50 -w ev".format(
+            bold_file, atlas_file, AUC_file, surr_dir, join(testpath, "ets_AUC_denoised.txt")
+        ),
+        shell=True,
+    )
+    ets_auc_denoised_local = np.loadtxt(join(testpath, "ets_AUC_denoised.txt"))
+    ets_auc_osf = np.loadtxt(join(ets_auc_denoised_file))
+    np.allclose(ets_auc_denoised_local, ets_auc_osf)
+
+
+def test_integration_debias(
+    testpath,
+    bold_file,
+    atlas_file,
+    AUC_file,
+    ets_auc_denoised_file,
+    surr_dir,
+    beta_file,
+    fitt_file,
+    skip_integration,
+):
+    if skip_integration:
+        pytest.skip("Skipping integration test")
+    subprocess.call(
+        "connPFM -i {} -a {} --AUC {} -d {} -m {} -tr 1 -u vferrer -nsur 50 -w debias".format(
+            bold_file, atlas_file, AUC_file, surr_dir, ets_auc_denoised_file
+        ),
+        shell=True,
+    )
+    masker = NiftiLabelsMasker(
+        labels_img=atlas_file,
+        standardize=False,
+        strategy="mean",
+    )
+    beta_osf = masker.fit_transform(beta_file)
+    fitt_osf = masker.fit_transform(fitt_file)
+    beta_local = masker.fit_transform(
+        join(testpath, f"{basename(bold_file[:-7])}_beta_ETS.nii.gz")
+    )
+    fitt_local = masker.fit_transform(
+        join(testpath, f"{basename(bold_file[:-7])}_fitt_ETS.nii.gz")
+    )
+    np.allclose(beta_osf, beta_local)
+    np.allclose(fitt_osf, fitt_local)