Feature/na 194

python/tests/gain_test.py

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+# @license
+# Copyright 2020 Google Inc.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Tests basic screenshot functionality."""
+
+import neuroglancer
+import numpy as np
+from time import sleep
+import pytest
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.common.by import By
+from PIL import Image
+import io
+
+
+
+URL = r"zarr://s3://aind-open-data/exaSPIM_653980_2023-08-10_20-08-29_fusion_2023-08-24/fused.zarr/"
+
+def add_render_panel(side="left", row=0, col=0):
+    return neuroglancer.LayerSidePanelState(
+        side=side,
+        col=col,
+        row=row,
+        tab="rendering",
+        tabs=["rendering", "source"],
+    )
+
+
+no_gain_screenshot = None
+gain_screenshot = None
+
+@pytest.mark.timeout(600)
+def test_no_gain(webdriver):
+
+    global no_gain_avg
+    global no_gain_screenshot
+    a = np.array([[[255]]], dtype=np.uint8)
+    with webdriver.viewer.txn() as s:
+        s.dimensions = neuroglancer.CoordinateSpace(
+            names=["x", "y", "z", "t"], units=["nm", "nm", "um", "ms"], scales=[748, 748, 1, 1]
+        )
+        s.layers.append(
+            name="a",
+            layer=neuroglancer.ImageLayer(
+                source = URL,
+                panels=[add_render_panel()],
+                shader="""
+#uicontrol invlerp normalized(range=[0, 250], window=[0, 65535], clamp=true)
+void main() {
+  emitGrayscale(normalized());
+}
+""",
+                volume_rendering=True,
+                volumeRenderingDepthSamples=512,
+                 tool_bindings={
+                    "A": neuroglancer.VolumeRenderingDepthSamplesTool(),
+                    "B": neuroglancer.VolumeRenderingGainTool(),  
+                    }
+                 ),
+        )
+        s.cross_section_scale = 1e-6
+        s.show_axis_lines = False
+        s.position = [0.5, 0.5, 0.5]
+        s.layers["brain"].volumeRenderingGain = 0
+
+    WebDriverWait(webdriver.driver, 60).until(
+        EC.text_to_be_present_in_element((By.CSS_SELECTOR, '#neuroglancer-container > div > div:nth-child(2) > div.neuroglancer-side-panel-column > div.neuroglancer-side-panel > div.neuroglancer-tab-view.neuroglancer-layer-side-panel-tab-view > div.neuroglancer-stack-view > div > div:nth-child(6) > label > div.neuroglancer-render-scale-widget.neuroglancer-layer-control-control > div.neuroglancer-render-scale-widget-legend > div:nth-child(2)'), '16/16')
+    )
+    WebDriverWait(webdriver.driver, 60).until(
+        lambda driver: driver.execute_script('return document.readyState') == 'complete'
+    )
+    print("Layer loaded")
+    sleep(3)
+    screenshot = webdriver.driver.get_screenshot_as_png()
+    sleep(3)
+    print("Screenshot taken")
+     # Convert the screenshot to a NumPy array
+    image = Image.open(io.BytesIO(screenshot))
+    no_gain_screenshot = np.array(image)
+    assert no_gain_screenshot.size != 0, "Image is empty"
+    # Check if the image contains valid pixel values
+    assert np.all(no_gain_screenshot >= 0) and np.all(no_gain_screenshot <= 255), "Image contains invalid pixel values"
+    no_gain_avg = np.mean(no_gain_screenshot)
+    print('No Gain average pixel value:')
+    print(no_gain_avg)
+
+
+
+@pytest.mark.timeout(600)
+def test_gain(webdriver):
+    global gain_screenshot
+    global gain_avg
+    a = np.array([[[255]]], dtype=np.uint8)
+    with webdriver.viewer.txn() as s:
+        s.dimensions = neuroglancer.CoordinateSpace(
+            names=["x", "y", "z", "t"], units=["nm", "nm", "um", "ms"], scales=[748, 748, 1, 1]
+        )
+        s.layers.append(
+            name="a",
+            layer=neuroglancer.ImageLayer(
+                source = URL,
+                panels=[add_render_panel()],
+                shader="""
+#uicontrol invlerp normalized(range=[0, 250], window=[0, 65535], clamp=true)
+void main() {
+  emitGrayscale(normalized());
+}
+""",
+                volume_rendering=True,
+                volumeRenderingDepthSamples=512,
+                 tool_bindings={
+                    "A": neuroglancer.VolumeRenderingDepthSamplesTool(),
+                    "B": neuroglancer.VolumeRenderingGainTool(),  
+                    }
+                 ),
+        )
+        s.cross_section_scale = 1e-6
+        s.show_axis_lines = False
+        s.position = [0.5, 0.5, 0.5]
+        s.layers["brain"].volumeRenderingGain = 10
+    WebDriverWait(webdriver.driver, 60).until(
+        lambda driver: driver.execute_script('return document.readyState') == 'complete'
+    )
+    sleep(3)
+    print("Layer loaded")
+    screenshot = webdriver.driver.get_screenshot_as_png()
+    sleep(3)
+    print("Screenshot taken")
+     # Convert the screenshot to a NumPy array
+    image = Image.open(io.BytesIO(screenshot))
+    gain_screenshot = np.array(image)
+    assert gain_screenshot.size != 0, "Image is empty"
+    # Check if the image contains valid pixel values
+    assert np.all(gain_screenshot >= 0) and np.all(gain_screenshot <= 255), "Image contains invalid pixel values"
+    gain_avg = np.mean(gain_screenshot)
+    print('Gain average pixel value:')
+    print(gain_avg)
+
+
+
+def test_gain_difference():
+    sleep(2)
+    assert gain_avg > no_gain_avg, "The gain screenshot is not brighter than the no gain screenshot"