Validate plot data

rascal2/dialogs/startup_dialog.py

@@ -173,12 +173,27 @@ def reject(self):
         if self.parent().centralWidget() is self.parent().startup_dlg:
             self.parent().startup_dlg.setVisible(True)
 
-    def project_start_success(self):
+    def project_start_success(self, warning):
         self.parent().presenter.initialise_ui()
+
         if not self.parent().toolbar.isEnabled():
             self.parent().toolbar.setEnabled(True)
         self.accept()
 
+        if warning is not None:
+            message = (
+                "The result JSON was not loaded because it is invalid. "
+                "The other project files were loaded successfully. "
+            )
+
+            message_box = QtWidgets.QMessageBox(self)
+            message_box.setStyleSheet("QMessageBox QTextEdit{color: red; font-family: monospace; font-weight:500;}")
+            message_box.setWindowTitle(self.windowTitle())
+            message_box.setIcon(QtWidgets.QMessageBox.Icon.Warning)
+            message_box.setText(message)
+            message_box.setDetailedText("\n".join(warning))
+            message_box.exec()
+
     def project_start_failed(self, exception, args):
         folder_name = args[0]
         error = str(exception).strip().replace("\n", "")

rascal2/ui/model.py

@@ -1,6 +1,7 @@
 import os
 import shutil
 import sys
+import warnings
 from json import JSONDecodeError
 from pathlib import Path
 
@@ -11,6 +12,10 @@
 from rascal2.paths import EXAMPLES_PATH, EXAMPLES_TEMP_PATH
 
 
+class InvalidResultWarning(Warning):
+    """Warning for invalid calculation results."""
+
+
 def copy_example_project(load_path):
     """Copy example project to temp directory so user does not modify original.
 
@@ -39,6 +44,106 @@ def copy_example_project(load_path):
     return str(load_path)
 
 
+def validate_plot_data(project, results):
+    """Validate plot data.
+
+    Parameters
+    ----------
+    project : ratapi.Project
+        The project
+    results : Union[ratapi.outputs.Results, ratapi.outputs.BayesResults]
+        The calculation results.
+    """
+    if results is None:
+        return
+
+    num_of_contrasts = len(project.contrasts)
+    num_of_domains = 1 if project.calculation == "normal" else 2
+
+    sub_rough_size = len(results.contrastParams.subRoughs)
+    if sub_rough_size != num_of_contrasts:
+        warnings.warn(
+            "The contrastParams.subRoughs entry in results has an incorrect size. "
+            f"The size ({sub_rough_size}) should be equal to the number of contrast ({num_of_contrasts}).",
+            InvalidResultWarning,
+            stacklevel=1,
+        )
+
+    for attr in ["reflectivity", "shiftedData", "sldProfiles", "resampledLayers"]:
+        entry = getattr(results, attr)
+        num_rows = len(entry)
+        if num_rows != num_of_contrasts:
+            warnings.warn(
+                f"The {attr} entry in results has an incorrect number of rows. "
+                f"The number of rows ({num_rows}) should be equal to the number of contrast ({num_of_contrasts}).",
+                InvalidResultWarning,
+                stacklevel=1,
+            )
+
+        for i in range(num_rows):
+            if isinstance(entry[i], list):
+                if len(entry[i]) != num_of_domains:
+                    warnings.warn(
+                        f"The {attr} entry in results has an incorrect number of columns. "
+                        f"Row {i} has {len(entry[i])} columns instead of {num_of_domains}.",
+                        InvalidResultWarning,
+                        stacklevel=1,
+                    )
+                for j in range(len(entry[i])):
+                    if len(entry[i][j].shape) != 2 or entry[i][j].shape[1] < 2:
+                        warnings.warn(
+                            f"The {attr} entry (row {i}, column {j}) in results has incorrect dimensions.",
+                            InvalidResultWarning,
+                            stacklevel=1,
+                        )
+            else:
+                if len(entry[i].shape) != 2 or entry[i].shape[1] < 2:
+                    warnings.warn(
+                        f"The {attr} entry (row {i}) in results has incorrect dimensions.",
+                        InvalidResultWarning,
+                        stacklevel=1,
+                    )
+
+    if isinstance(results, ratapi.outputs.BayesResults):
+        for attr in ["reflectivity", "sld"]:
+            entry = getattr(results.predictionIntervals, attr)
+            dim_source = results.sldProfiles if attr == "sld" else results.reflectivity
+            num_rows = len(entry)
+            if num_rows != num_of_contrasts:
+                warnings.warn(
+                    f"The predictionIntervals.{attr} entry in results has an incorrect number of rows. "
+                    f"The number of rows ({num_rows}) should match the number of contrast ({num_of_contrasts}).",
+                    InvalidResultWarning,
+                    stacklevel=1,
+                )
+
+            for i in range(num_rows):
+                if isinstance(entry[i], list):
+                    if len(entry[i]) != num_of_domains:
+                        warnings.warn(
+                            f"The predictionIntervals.{attr} entry in results has an incorrect number of columns. "
+                            f"Row {i} has {len(entry[i])} columns instead of {num_of_domains}.",
+                            InvalidResultWarning,
+                            stacklevel=1,
+                        )
+
+                    for j in range(len(entry[i])):
+                        if entry[i][j].shape != (5, dim_source[i][j].shape[0]):
+                            warnings.warn(
+                                f"The predictionIntervals.{attr} entry (row {i}, column {j}) "
+                                "in results has incorrect dimensions.",
+                                InvalidResultWarning,
+                                stacklevel=1,
+                            )
+                else:
+                    if entry[i].shape != (5, dim_source[i].shape[0]):
+                        warnings.warn(
+                            f"The predictionIntervals.{attr} entry (row {i}) in results has incorrect dimensions.",
+                            InvalidResultWarning,
+                            stacklevel=1,
+                        )
+
+
 class MainWindowModel(QtCore.QObject):
     """Manages project data and communicates to view via signals.
 

rascal2/ui/presenter.py

@@ -13,7 +13,7 @@
 from rascal2.core.writer import write_result_to_zipped_csvs
 from rascal2.settings import update_recent_projects
 
-from .model import MainWindowModel
+from .model import InvalidResultWarning, MainWindowModel, validate_plot_data
 
 
 class MainWindowPresenter:
@@ -45,19 +45,29 @@ def create_project(self, name: str, save_path: str):
         self.initialise_ui()
 
     def load_project(self, load_path: str):
-        """Load an existing RAT project then initialise UI.
+        """Load an existing RAT project.
 
         Parameters
         ----------
         load_path : str
             The path from which to load the project.
 
         """
+        warning = None
         self.model.load_project(load_path)
+        with warnings.catch_warnings(record=True) as records:
+            validate_plot_data(self.model.project, self.model.results)
+            if records:
+                self.model.results = None
+                warning = [
+                    str(record.message) for record in records if isinstance(record.message, InvalidResultWarning)
+                ]
         if self.model.results is None:
             self.model.results = self.quick_run()
         update_recent_projects(load_path)
 
+        return warning
+
     def load_r1_project(self, load_path: str):
         """Load a RAT project from a RasCAL-1 project file.
 

tests/ui/test_model.py

@@ -1,3 +1,4 @@
+import warnings
 from pathlib import Path
 from tempfile import TemporaryDirectory
 from unittest.mock import patch
@@ -8,9 +9,11 @@
 from ratapi.outputs import CalculationResults, ContrastParams
 from ratapi.utils.enums import Calculations
 
-from rascal2.ui.model import MainWindowModel
+from rascal2.ui.model import MainWindowModel, validate_plot_data
 from tests.utils import check_results_equal
 
+DATA_PATH = Path(__file__, "../../data/").resolve()
+
 
 @pytest.fixture
 def empty_results():
@@ -77,6 +80,42 @@ def test_save_project(empty_results, model):
     assert '"fitParams": []' in results
 
 
+@pytest.mark.parametrize(
+    ("result_file", "warning_count"),
+    (
+        ("results_normal_calculate.json", 5),
+        ("results_domains_dream.json", 10),
+        ("results_domains_ns.json", 10),
+    ),
+)
+def test_validate_plot_data_throws_warnings(result_file, warning_count):
+    project = Project()
+    result = Results.load(DATA_PATH / result_file)
+    with warnings.catch_warnings(record=True) as records:
+        validate_plot_data(project, result)
+        assert len(records) == warning_count
+
+
+@pytest.mark.parametrize(
+    ("result_file", "calc_type", "num_of_contrast"),
+    (
+        ("results_normal_calculate.json", Calculations.Normal, 2),
+        ("results_domains_dream.json", Calculations.Domains, 1),
+        ("results_domains_ns.json", Calculations.Domains, 1),
+    ),
+)
+def test_validate_plot_data(result_file, calc_type, num_of_contrast):
+    project = Project(calculation=calc_type)
+    for i in range(num_of_contrast):
+        project.contrasts.append(name=f"Contrast {i}")
+
+    result = Results.load(DATA_PATH / result_file)
+    with warnings.catch_warnings(record=True) as records:
+        validate_plot_data(project, result)
+        print([m.message for m in records])
+        assert len(records) == 0
+
+
 def test_save_project_as_script(model):
     model.project = Project(calculation="domains", name="test project")
     with TemporaryDirectory() as tmpdir: