Use new version of iterative_ensemble_smoother

Returns all correlated pairs and not just those deemed
significantly correlated.
Therefore, some tests need to be updated.

pyproject.toml

@@ -35,7 +35,7 @@ dependencies = [
     "filelock",
     "httpx",
     "humanize",
-    "iterative_ensemble_smoother<0.3.0",
+    "iterative_ensemble_smoother>=0.3.0",
     "jinja2 >= 2.10",
     "lark",
     "lxml",

tests/ert/ui_tests/cli/analysis/test_adaptive_localization.py

@@ -49,11 +49,6 @@ def test_that_adaptive_localization_with_cutoff_1_equals_ensemble_prior():
         f.writelines(lines)
     prior_ensemble, posterior_ensemble = run_cli_ES_with_case("poly_localization_1.ert")
 
-    with pytest.raises(
-        FileNotFoundError, match="No cross-correlation data available at"
-    ):
-        prior_ensemble.load_cross_correlations()
-
     prior_sample = prior_ensemble.load_parameters("COEFFS")["values"]
     posterior_sample = posterior_ensemble.load_parameters("COEFFS")["values"]
     # Check prior and posterior samples are equal
@@ -300,8 +295,8 @@ def test_that_posterior_generalized_variance_increases_in_cutoff():
     )
 
     cross_correlations = prior_ensemble_cutoff1.load_cross_correlations()
-    assert all(cross_correlations.parameter.to_numpy() == ["a", "b"])
-    assert cross_correlations["COEFFS"].values.shape == (2, 5)
+    assert all(cross_correlations.parameter.to_numpy() == ["a", "b", "c"])
+    assert cross_correlations["COEFFS"].values.shape == (3, 5)
     assert (
         (cross_correlations["COEFFS"].values >= -1)
         & (cross_correlations["COEFFS"].values <= 1)