From b280ec3aa56c2e05f00d1675625a1dd0b6d4e138 Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Fri, 28 Jul 2023 08:10:47 +0200
Subject: [PATCH] [tests] Make naming more explicit
---
tests/{test_in.py => test_indian.py} | 0
tests/test_mc.py | 192 -------------------------
tests/{test_ch.py => test_shenzhen.py} | 0
3 files changed, 192 deletions(-)
rename tests/{test_in.py => test_indian.py} (100%)
delete mode 100644 tests/test_mc.py
rename tests/{test_ch.py => test_shenzhen.py} (100%)
diff --git a/tests/test_in.py b/tests/test_indian.py
similarity index 100%
rename from tests/test_in.py
rename to tests/test_indian.py
diff --git a/tests/test_mc.py b/tests/test_mc.py
deleted file mode 100644
index 4d1a5a9e..00000000
--- a/tests/test_mc.py
+++ /dev/null
@@ -1,192 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-"""Tests for Montgomery dataset."""
-
-import importlib
-
-import pytest
-
-
-@pytest.mark.skip(reason="Test need to be updated")
-def test_protocol_consistency():
- # Default protocol
- datamodule = importlib.import_module(
- "ptbench.data.montgomery.datamodules.default"
- ).datamodule
-
- subset = datamodule.splits
-
- assert len(subset) == 3
-
- assert "train" in subset
- assert len(subset["train"]) == 88
- for s in subset["train"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- assert "validation" in subset
- assert len(subset["validation"]) == 22
- for s in subset["validation"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- assert "test" in subset
- assert len(subset["test"]) == 28
- for s in subset["test"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- # Check labels
- for s in subset["train"]:
- assert s[1] in [0.0, 1.0]
-
- for s in subset["validation"]:
- assert s[1] in [0.0, 1.0]
-
- for s in subset["test"]:
- assert s[1] in [0.0, 1.0]
-
- # Cross-validation fold 0-7
- for f in range(8):
- datamodule = importlib.import_module(
- f"ptbench.data.montgomery.datamodules.fold_{str(f)}"
- ).datamodule
- subset = datamodule.database_split
-
- assert len(subset) == 3
-
- assert "train" in subset
- assert len(subset["train"]) == 99
- for s in subset["train"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- assert "validation" in subset
- assert len(subset["validation"]) == 25
- for s in subset["validation"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- assert "test" in subset
- assert len(subset["test"]) == 14
- for s in subset["test"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- # Check labels
- for s in subset["train"]:
- assert s[1] in [0.0, 1.0]
-
- for s in subset["validation"]:
- assert s[1] in [0.0, 1.0]
-
- for s in subset["test"]:
- assert s[1] in [0.0, 1.0]
-
- # Cross-validation fold 8-9
- for f in range(8, 10):
- datamodule = importlib.import_module(
- f"ptbench.data.montgomery.datamodules.fold_{str(f)}"
- ).datamodule
- subset = datamodule.database_split
-
- assert len(subset) == 3
-
- assert "train" in subset
- assert len(subset["train"]) == 100
- for s in subset["train"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- assert "validation" in subset
- assert len(subset["validation"]) == 25
- for s in subset["validation"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- assert "test" in subset
- assert len(subset["test"]) == 13
- for s in subset["test"]:
- assert s[0].startswith("CXR_png/MCUCXR_0")
-
- # Check labels
- for s in subset["train"]:
- assert s[1] in [0.0, 1.0]
-
- for s in subset["validation"]:
- assert s[1] in [0.0, 1.0]
-
- for s in subset["test"]:
- assert s[1] in [0.0, 1.0]
-
-
-@pytest.mark.skip(reason="Test need to be updated")
-@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
-def test_loading():
- import torch
- import torchvision.transforms
-
- from ptbench.data.datamodule import _DelayedLoadingDataset
-
- def _check_sample(s):
- assert len(s) == 2
-
- data = s[0]
- metadata = s[1]
-
- assert isinstance(data, torch.Tensor)
-
- assert data.size(0) == 1 # check single channel
- assert data.size(1) == data.size(2) # check square image
-
- assert (
- torchvision.transforms.ToPILImage()(data).mode == "L"
- ) # Check colors
-
- assert "label" in metadata
- assert metadata["label"] in [0, 1] # Check labels
-
- limit = 30 # use this to limit testing to first images only, else None
-
- datamodule = importlib.import_module(
- "ptbench.data.montgomery.datamodules.default"
- ).datamodule
- subset = datamodule.database_split
- raw_data_loader = datamodule.raw_data_loader
-
- # Need to use private function so we can limit the number of samples to use
- dataset = _DelayedLoadingDataset(subset["train"][:limit], raw_data_loader)
-
- for s in dataset:
- _check_sample(s)
-
-
-@pytest.mark.skip(reason="Test need to be updated")
-@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
-def test_check():
- from ptbench.data.split import check_database_split_loading
-
- limit = 30 # use this to limit testing to first images only, else 0
-
- # Default protocol
- datamodule = importlib.import_module(
- "ptbench.data.montgomery.datamodules.default"
- ).datamodule
- database_split = datamodule.database_split
- raw_data_loader = datamodule.raw_data_loader
-
- assert (
- check_database_split_loading(
- database_split, raw_data_loader, limit=limit
- )
- == 0
- )
-
- # Folds
- for f in range(10):
- datamodule = importlib.import_module(
- f"ptbench.data.montgomery.datamodules.fold_{f}"
- ).datamodule
- database_split = datamodule.database_split
- raw_data_loader = datamodule.raw_data_loader
-
- assert (
- check_database_split_loading(
- database_split, raw_data_loader, limit=limit
- )
- == 0
- )
diff --git a/tests/test_ch.py b/tests/test_shenzhen.py
similarity index 100%
rename from tests/test_ch.py
rename to tests/test_shenzhen.py
--
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