tests: improve coverage (#173)

.gitignore

@@ -81,3 +81,4 @@ tests/data
 .env
 
 .pytest_cache
+htmlcov

pycorrfit/openfile.py

@@ -3,7 +3,6 @@
 This file contains definitions for opening PyCorrFit sessions and
 saving PyCorrFit correlation curves.
 """
-
 import codecs
 import csv
 import io

tests/test_session.py

@@ -0,0 +1,99 @@
+"""Session files"""
+import os
+import pathlib
+import tempfile
+import shutil
+
+import numpy as np
+import pytest
+
+import data_file_dl
+import pycorrfit as pcf
+
+NOAPITOKEN = "GITHUB_API_TOKEN" not in os.environ
+
+examplefile = "Zeiss_Confocor3_LSM780_FCCS_HeLa_2015/019_cp_KIND+BFA.fcs"
+
+
+@pytest.mark.xfail(NOAPITOKEN, reason="Restrictions to GitHub API")
+def test_basic():
+    """This is a very rudimentary test for the session handling"""
+    dfile = data_file_dl.get_data_file(examplefile)
+    data = pcf.readfiles.openAny(dfile)
+    corr = pcf.Correlation(correlation=data["Correlation"][0],
+                           traces=data["Trace"][0],
+                           corr_type=data["Type"][0],
+                           filename=os.path.basename(dfile),
+                           title="test correlation",
+                           fit_model=6035  # confocal 3D+3D)
+                           )
+    corr.fit_parameters_variable = [True, True, True, True,
+                                    False, False, False]
+    # crop triplet data
+    corr.fit_ival[0] = 8
+    pcf.Fit(corr)
+
+    tmpdir = tempfile.mkdtemp(prefix="pycorrfit_tests_")
+    path = pathlib.Path(tmpdir) / "session.pcfs"
+
+    fiterr = []
+    for ii, fitpid in enumerate(corr.fit_results["fit parameters"]):
+        fiterr.append([int(fitpid),
+                       float(corr.fit_results["fit error estimation"][ii])])
+
+    Infodict = {
+        "Correlations": {
+            1: [corr.lag_time, corr.correlation]},
+        "Parameters": {
+            1: ["#1:",
+                corr.fit_model.id,
+                corr.fit_parameters,
+                corr.fit_parameters_variable,
+                corr.fit_ival,
+                [3, 3, 5, corr.fit_algorithm],
+                [None, None],
+                True,
+                None,
+                [[0.0, np.inf],
+                 [0.0, np.inf],
+                 [0.0, np.inf],
+                 [0.0, 0.9999999999999],
+                 [-np.inf, np.inf]]
+                ]},
+        "Supplements": {
+            1: {"FitErr": fiterr,
+                "Chi sq": float(corr.fit_results["chi2"]),
+                "Global Share": [],
+            }},
+        "External Functions": {},
+        "Traces": {},
+        "Comments": {"Session": "No comment."},
+        "Backgrounds": {},
+        "External Weights": {},
+        "Preferences": {},
+        }
+
+    pcf.openfile.SaveSessionData(sessionfile=str(path),
+                                 Infodict=Infodict)
+
+    ldt = pcf.openfile.LoadSessionData(str(path))
+
+    # lag time only, shape (N,)
+    assert np.allclose(data["Correlation"][0][:,0], ldt["Correlations"][1][0])
+    # lag time and correlation, shape (N, 2)
+    assert np.allclose(corr.correlation, ldt["Correlations"][1][1])
+    # parameters
+    assert corr.fit_model.id == ldt["Parameters"][0][1]
+    assert np.allclose(corr.fit_parameters, ldt["Parameters"][0][2])
+    assert np.allclose(corr.fit_parameters_variable, ldt["Parameters"][0][3])
+    assert np.allclose(corr.git_ival, ldt["Parameters"][0][4])
+
+    shutil.rmtree(tmpdir, ignore_errors=True)
+
+
+if __name__ == "__main__":
+    # Run all tests
+    loc = locals()
+    for key in list(loc.keys()):
+        if key.startswith("test_") and hasattr(loc[key], "__call__"):
+            loc[key]()