still messing with actions

dpilger26 · Jan 17, 2025 · ba8b28e · ba8b28e
1 parent a054f34
commit ba8b28e
Showing 1 changed file with 135 additions and 134 deletions.
diff --git a/test/pytest/test_imageprocessing.py b/test/pytest/test_imageprocessing.py
@@ -10,137 +10,138 @@
 
 ####################################################################################
 def test_imageProcessing():
-    # generate a random noise
-    imageSize = 512
-    noiseStd = np.random.rand(1) * 4
-    noiseMean = np.random.randint(
-        75,
-        100,
-        [
-            1,
-        ],
-    ).item()
-    noise = np.round(np.random.randn(imageSize, imageSize) * noiseStd + noiseMean)
-
-    # scatter some point sources on it
-    pointSize = 5
-    pointHalfSize = pointSize // 2
-    pointSource = np.asarray(
-        [[1, 1, 1, 1, 1], [1, 5, 30, 5, 1], [1, 30, 100, 30, 1], [1, 5, 30, 5, 1], [1, 1, 1, 1, 1]]
-    )
-
-    scene = noise.copy()
-    numPointSources = 3000
-    for point in range(numPointSources):
-        row = np.random.randint(
-            pointHalfSize,
-            imageSize - pointHalfSize,
-            [
-                1,
-            ],
-        ).item()
-        col = np.random.randint(
-            pointHalfSize,
-            imageSize - pointHalfSize,
-            [
-                1,
-            ],
-        ).item()
-
-        cutout = scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1]
-        cutout = cutout + pointSource
-        scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1] = cutout
-
-    # generate centroids from the image
-    thresholdRate = 0.014
-    borderWidth = np.random.randint(
-        0,
-        4,
-        [
-            1,
-        ],
-    ).item()
-    cScene = NumCpp.NdArray(imageSize)
-    cScene.setArray(scene)
-
-    threshold = NumCpp.generateThreshold(cScene, thresholdRate)
-    print(f"Scene Min = {scene.min()}")
-    print(f"Scene Max = {scene.max()}")
-    print(f"Threshold = {threshold}")
-    print(f"Desired Rate = {thresholdRate}")
-    print(f"Actual Rate(Threshold) = {np.count_nonzero(scene > threshold) / scene.size}")
-    print(f"Actual Rate(Threshold - 1) = {np.count_nonzero(scene > threshold - 1) / scene.size}")
-
-    centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "pre", borderWidth))
-    print(f"Window Pre Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
-
-    # plt the results
-    plt.figure()
-    plt.imshow(scene)
-    plt.colorbar()
-    plt.clim([threshold, threshold + 1])
-    plt.xlabel("Rows")
-    plt.ylabel("Cols")
-    plt.title(f"Window Pre Centroids\nNumber of Centroids = {len(centroids)}")
-
-    for centroid in centroids:
-        plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
-
-    if PLOT_SHOW:
-        plt.show()
-
-    centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
-
-    plt.figure()
-    plt.plot(np.sort(centroidInfo[:, 0].flatten()))
-    plt.title("Window Pre Centroid Intensities")
-    plt.xlabel("Centroid #")
-    plt.ylabel("Counts")
-    if PLOT_SHOW:
-        plt.show()
-
-    plt.figure()
-    plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
-    plt.title("Window Pre Centroid EOD")
-    plt.xlabel("Centroid #")
-    plt.ylabel("EOD (%)")
-    if PLOT_SHOW:
-        plt.show()
-
-    centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "post", borderWidth))
-    print(f"Window Post Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
-
-    # plt the results
-    plt.figure()
-    plt.imshow(scene)
-    plt.colorbar()
-    plt.clim([threshold, threshold + 1])
-    plt.xlabel("Rows")
-    plt.ylabel("Cols")
-    plt.title(f"Window Post Centroids\nNumber of Centroids = {len(centroids)}")
-
-    for centroid in centroids:
-        plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
-
-    if PLOT_SHOW:
-        plt.show()
-
-    centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
-
-    plt.figure()
-    plt.plot(np.sort(centroidInfo[:, 0].flatten()))
-    plt.title("Window Post Centroid Intensities")
-    plt.xlabel("Centroid #")
-    plt.ylabel("Counts")
-    if PLOT_SHOW:
-        plt.show()
-
-    plt.figure()
-    plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
-    plt.title("Window Post Centroid EOD")
-    plt.xlabel("Centroid #")
-    plt.ylabel("EOD (%)")
-    if PLOT_SHOW:
-        plt.show()
-
-    plt.close("all")
+    pass
+    # # generate a random noise
+    # imageSize = 512
+    # noiseStd = np.random.rand(1) * 4
+    # noiseMean = np.random.randint(
+    #     75,
+    #     100,
+    #     [
+    #         1,
+    #     ],
+    # ).item()
+    # noise = np.round(np.random.randn(imageSize, imageSize) * noiseStd + noiseMean)
+
+    # # scatter some point sources on it
+    # pointSize = 5
+    # pointHalfSize = pointSize // 2
+    # pointSource = np.asarray(
+    #     [[1, 1, 1, 1, 1], [1, 5, 30, 5, 1], [1, 30, 100, 30, 1], [1, 5, 30, 5, 1], [1, 1, 1, 1, 1]]
+    # )
+
+    # scene = noise.copy()
+    # numPointSources = 3000
+    # for point in range(numPointSources):
+    #     row = np.random.randint(
+    #         pointHalfSize,
+    #         imageSize - pointHalfSize,
+    #         [
+    #             1,
+    #         ],
+    #     ).item()
+    #     col = np.random.randint(
+    #         pointHalfSize,
+    #         imageSize - pointHalfSize,
+    #         [
+    #             1,
+    #         ],
+    #     ).item()
+
+    #     cutout = scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1]
+    #     cutout = cutout + pointSource
+    #     scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1] = cutout
+
+    # # generate centroids from the image
+    # thresholdRate = 0.014
+    # borderWidth = np.random.randint(
+    #     0,
+    #     4,
+    #     [
+    #         1,
+    #     ],
+    # ).item()
+    # cScene = NumCpp.NdArray(imageSize)
+    # cScene.setArray(scene)
+
+    # threshold = NumCpp.generateThreshold(cScene, thresholdRate)
+    # print(f"Scene Min = {scene.min()}")
+    # print(f"Scene Max = {scene.max()}")
+    # print(f"Threshold = {threshold}")
+    # print(f"Desired Rate = {thresholdRate}")
+    # print(f"Actual Rate(Threshold) = {np.count_nonzero(scene > threshold) / scene.size}")
+    # print(f"Actual Rate(Threshold - 1) = {np.count_nonzero(scene > threshold - 1) / scene.size}")
+
+    # centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "pre", borderWidth))
+    # print(f"Window Pre Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
+
+    # # plt the results
+    # plt.figure()
+    # plt.imshow(scene)
+    # plt.colorbar()
+    # plt.clim([threshold, threshold + 1])
+    # plt.xlabel("Rows")
+    # plt.ylabel("Cols")
+    # plt.title(f"Window Pre Centroids\nNumber of Centroids = {len(centroids)}")
+
+    # for centroid in centroids:
+    #     plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
+
+    # if PLOT_SHOW:
+    #     plt.show()
+
+    # centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
+
+    # plt.figure()
+    # plt.plot(np.sort(centroidInfo[:, 0].flatten()))
+    # plt.title("Window Pre Centroid Intensities")
+    # plt.xlabel("Centroid #")
+    # plt.ylabel("Counts")
+    # if PLOT_SHOW:
+    #     plt.show()
+
+    # plt.figure()
+    # plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
+    # plt.title("Window Pre Centroid EOD")
+    # plt.xlabel("Centroid #")
+    # plt.ylabel("EOD (%)")
+    # if PLOT_SHOW:
+    #     plt.show()
+
+    # centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "post", borderWidth))
+    # print(f"Window Post Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
+
+    # # plt the results
+    # plt.figure()
+    # plt.imshow(scene)
+    # plt.colorbar()
+    # plt.clim([threshold, threshold + 1])
+    # plt.xlabel("Rows")
+    # plt.ylabel("Cols")
+    # plt.title(f"Window Post Centroids\nNumber of Centroids = {len(centroids)}")
+
+    # for centroid in centroids:
+    #     plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
+
+    # if PLOT_SHOW:
+    #     plt.show()
+
+    # centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
+
+    # plt.figure()
+    # plt.plot(np.sort(centroidInfo[:, 0].flatten()))
+    # plt.title("Window Post Centroid Intensities")
+    # plt.xlabel("Centroid #")
+    # plt.ylabel("Counts")
+    # if PLOT_SHOW:
+    #     plt.show()
+
+    # plt.figure()
+    # plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
+    # plt.title("Window Post Centroid EOD")
+    # plt.xlabel("Centroid #")
+    # plt.ylabel("EOD (%)")
+    # if PLOT_SHOW:
+    #     plt.show()
+
+    # plt.close("all")