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This module tests complex event interactions in the Mosaic Gradio UI, including:
- Settings state management across events
- Generator behavior and incremental updates
- Error and warning display
"""
import pytest
import pandas as pd
from unittest.mock import Mock, patch, MagicMock
from pathlib import Path
import inspect
from mosaic.ui.app import (
analyze_slides,
set_cancer_subtype_maps,
)
from mosaic.ui.utils import SETTINGS_COLUMNS, validate_settings, load_settings
class TestSettingsStateManagement:
"""Test settings state management across multiple events."""
def test_csv_upload_replaces_settings(
self, sample_csv_valid, mock_cancer_subtype_maps
):
"""Test CSV upload replaces existing settings."""
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
# Load CSV
loaded_df = load_settings(sample_csv_valid)
validated_df = validate_settings(
loaded_df, cancer_subtype_name_map, cancer_subtypes, reversed_map
)
# Verify new settings loaded
assert len(validated_df) == 3
assert validated_df.iloc[0]["Slide"] == "slide1.svs"
assert validated_df.iloc[1]["Slide"] == "slide2.svs"
class TestGeneratorBehavior:
"""Test generator behavior for incremental updates."""
@patch("mosaic.ui.app.analyze_slide")
@patch("mosaic.ui.app.create_user_directory")
def test_analyze_slides_is_generator(
self,
mock_create_dir,
mock_analyze,
sample_files_single,
mock_analyze_slide_results,
mock_cancer_subtype_maps,
temp_output_dir,
):
"""Test analyze_slides returns a generator."""
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
set_cancer_subtype_maps(cancer_subtype_name_map, reversed_map, cancer_subtypes)
mock_create_dir.return_value = temp_output_dir
mock_analyze.return_value = mock_analyze_slide_results
settings_df = pd.DataFrame(
{
"Slide": ["test_slide_1.svs"],
"Site Type": ["Primary"],
"Sex": ["Male"],
"Tissue Site": ["Unknown"],
"Cancer Subtype": ["Unknown"],
"IHC Subtype": [""],
"Segmentation Config": ["Biopsy"],
}
)
result = analyze_slides(
sample_files_single,
settings_df,
"Primary",
"Unknown",
"Unknown",
"Unknown",
"",
"Biopsy",
temp_output_dir,
)
# Verify it's a generator
assert inspect.isgenerator(result)
@patch("mosaic.ui.app.load_all_models")
@patch("mosaic.ui.app.analyze_slide")
@patch("mosaic.ui.app.create_user_directory")
def test_intermediate_yields_update_masks_only(
self,
mock_create_dir,
mock_analyze,
mock_load_models,
sample_files_multiple,
mock_analyze_slide_results,
mock_model_cache,
mock_cancer_subtype_maps,
temp_output_dir,
):
"""Test intermediate yields show only slide masks."""
from PIL import Image
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
set_cancer_subtype_maps(cancer_subtype_name_map, reversed_map, cancer_subtypes)
mock_create_dir.return_value = temp_output_dir
mock_load_models.return_value = mock_model_cache
# Return fresh DataFrames on each call
def mock_analyze_side_effect(*args, **kwargs):
mask = Image.new("RGB", (100, 100), color="red")
aeon_results = pd.DataFrame(
{"Cancer Subtype": ["LUAD"], "Confidence": [0.95]}
)
paladin_results = pd.DataFrame(
{
"Cancer Subtype": ["LUAD", "LUAD", "LUAD"],
"Biomarker": ["TP53", "KRAS", "EGFR"],
"Score": [0.85, 0.72, 0.63],
}
)
return (mask, aeon_results, paladin_results)
mock_analyze.side_effect = mock_analyze_side_effect
settings_df = pd.DataFrame(
{
"Slide": ["test_slide_1.svs", "test_slide_2.svs", "test_slide_3.svs"],
"Site Type": ["Primary", "Primary", "Primary"],
"Sex": ["Male", "Female", "Male"],
"Tissue Site": ["Unknown", "Unknown", "Unknown"],
"Cancer Subtype": ["Unknown", "Unknown", "Unknown"],
"IHC Subtype": ["", "", ""],
"Segmentation Config": ["Biopsy", "Biopsy", "Biopsy"],
}
)
gen = analyze_slides(
sample_files_multiple,
settings_df,
"Primary",
"Unknown",
"Unknown",
"Unknown",
"",
"Biopsy",
temp_output_dir,
)
# Get first intermediate yield (after first slide)
first_yield = next(gen)
# Should be tuple with 7 elements (added settings_input back)
assert len(first_yield) == 7
# First element is settings_input (visible during processing for progress)
settings = first_yield[0]
assert hasattr(settings, "visible") and settings.visible
# Second element is slide_masks (should have 1 entry)
slide_masks = first_yield[1]
assert len(slide_masks) == 1
# Third element should be AEON results DataFrame (now visible with partial results)
aeon_output = first_yield[2]
# Should have a DataFrame (not hidden anymore)
assert aeon_output is not None
# Fourth element should be AEON download button (hidden until complete)
aeon_download = first_yield[3]
# Download button should be hidden during intermediate yields
assert hasattr(aeon_download, "visible") and not aeon_download.visible
# Fifth element should be PALADIN results DataFrame (partial results)
paladin_output = first_yield[4]
# Should have data (DataFrame with partial results)
assert paladin_output is not None
# Sixth element should be PALADIN download button (hidden until complete)
paladin_download = first_yield[5]
# Download button should be hidden during intermediate yields
assert hasattr(paladin_download, "visible") and not paladin_download.visible
@patch("mosaic.ui.app.load_all_models")
@patch("mosaic.ui.app.analyze_slide")
@patch("mosaic.ui.app.create_user_directory")
def test_final_yield_has_complete_results(
self,
mock_create_dir,
mock_analyze,
mock_load_models,
sample_files_multiple,
mock_analyze_slide_results,
mock_model_cache,
mock_cancer_subtype_maps,
temp_output_dir,
):
"""Test final yield contains complete results."""
from PIL import Image
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
set_cancer_subtype_maps(cancer_subtype_name_map, reversed_map, cancer_subtypes)
mock_create_dir.return_value = temp_output_dir
mock_load_models.return_value = mock_model_cache
# Return fresh DataFrames on each call
def mock_analyze_side_effect(*args, **kwargs):
mask = Image.new("RGB", (100, 100), color="red")
aeon_results = pd.DataFrame(
{"Cancer Subtype": ["LUAD"], "Confidence": [0.95]}
)
paladin_results = pd.DataFrame(
{
"Cancer Subtype": ["LUAD", "LUAD", "LUAD"],
"Biomarker": ["TP53", "KRAS", "EGFR"],
"Score": [0.85, 0.72, 0.63],
}
)
return (mask, aeon_results, paladin_results)
mock_analyze.side_effect = mock_analyze_side_effect
settings_df = pd.DataFrame(
{
"Slide": ["test_slide_1.svs", "test_slide_2.svs", "test_slide_3.svs"],
"Site Type": ["Primary", "Primary", "Primary"],
"Sex": ["Male", "Female", "Male"],
"Tissue Site": ["Unknown", "Unknown", "Unknown"],
"Cancer Subtype": ["Unknown", "Unknown", "Unknown"],
"IHC Subtype": ["", "", ""],
"Segmentation Config": ["Biopsy", "Biopsy", "Biopsy"],
}
)
gen = analyze_slides(
sample_files_multiple,
settings_df,
"Primary",
"Unknown",
"Unknown",
"Unknown",
"",
"Biopsy",
temp_output_dir,
)
# Consume generator to get final yield
results = list(gen)
final_yield = results[-1]
# Final yield should have all results (7 elements with settings_input)
assert len(final_yield) == 7
# First element is settings_input (should be visible for 3 slides)
settings = final_yield[0]
assert hasattr(settings, "visible") and settings.visible # Visible for multiple slides
# Second element is slide_masks
slide_masks = final_yield[1]
assert len(slide_masks) == 3 # All 3 slides
# AEON download button should be visible on final yield (4th element, index 3)
aeon_download = final_yield[3]
assert hasattr(aeon_download, "visible") and aeon_download.visible
# PALADIN download button should be visible on final yield (6th element, index 5)
paladin_download = final_yield[5]
assert hasattr(paladin_download, "visible") and paladin_download.visible
class TestErrorDisplay:
"""Test error and warning display behavior."""
@patch("mosaic.ui.app.create_user_directory")
def test_no_slides_raises_gr_error(
self, mock_create_dir, mock_cancer_subtype_maps, temp_output_dir
):
"""Test that no slides raises gr.Error."""
import gradio as gr
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
set_cancer_subtype_maps(cancer_subtype_name_map, reversed_map, cancer_subtypes)
mock_create_dir.return_value = temp_output_dir
gen = analyze_slides(
None,
None,
"Primary",
"Unknown",
"Unknown",
"Unknown",
"",
"Biopsy",
temp_output_dir,
)
# Should raise gr.Error
with pytest.raises(gr.Error):
next(gen)
@patch("mosaic.ui.utils.gr.Warning")
def test_validation_warnings_shown(self, mock_warning, mock_cancer_subtype_maps):
"""Test validation warnings are displayed."""
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
# Create DataFrame with multiple invalid values
df = pd.DataFrame(
{
"Slide": ["test1.svs", "test2.svs"],
"Site Type": ["InvalidSite", "Primary"],
"Sex": ["Unknown", "InvalidSex"],
"Tissue Site": ["Unknown", "Unknown"],
"Cancer Subtype": ["InvalidSubtype", "Unknown"],
"IHC Subtype": ["", ""],
"Segmentation Config": ["Biopsy", "InvalidConfig"],
}
)
result = validate_settings(
df, cancer_subtype_name_map, cancer_subtypes, reversed_map
)
# Should have warning calls (at least 1 for the multiple invalid values)
assert mock_warning.call_count >= 1
# Verify defaults applied
assert result.iloc[0]["Site Type"] == "Primary" # Invalid → Primary
assert result.iloc[0]["Cancer Subtype"] == "Unknown" # Invalid → Unknown
assert result.iloc[1]["Sex"] == "" # Invalid → empty string
assert result.iloc[1]["Segmentation Config"] == "Biopsy" # Invalid → Biopsy
@patch("mosaic.ui.app.create_user_directory")
def test_settings_mismatch_raises_gr_error(
self,
mock_create_dir,
sample_files_multiple,
sample_settings_df,
mock_cancer_subtype_maps,
temp_output_dir,
):
"""Test settings/files count mismatch raises gr.Error."""
import gradio as gr
cancer_subtype_name_map, reversed_map, cancer_subtypes = (
mock_cancer_subtype_maps
)
set_cancer_subtype_maps(cancer_subtype_name_map, reversed_map, cancer_subtypes)
mock_create_dir.return_value = temp_output_dir
# Create mismatch: 2 files but 3 settings rows
two_files = sample_files_multiple[:2]
gen = analyze_slides(
two_files,
sample_settings_df,
"Primary",
"Unknown",
"Unknown",
"Unknown",
"",
"Biopsy",
temp_output_dir,
)
# Should raise gr.Error about mismatch
with pytest.raises(gr.Error):
next(gen)
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