forked from M-Labs/artiq
remote_exec_processing: style
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@ -13,13 +13,14 @@ def compute_gaussian(r, img_w, img_h,
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gaussian_cx, gaussian_cy):
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gaussian_cx, gaussian_cy):
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for y in range(img_h):
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for y in range(img_h):
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for x in range(img_w):
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for x in range(img_w):
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ds = ((gaussian_cx-x)/gaussian_w)**2
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ds = ((gaussian_cx-x)/gaussian_w)**2
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ds += ((gaussian_cy-y)/gaussian_h)**2
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ds += ((gaussian_cy-y)/gaussian_h)**2
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r[x, y] = np.exp(-ds/2)
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r[x, y] = np.exp(-ds/2)
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def fit(data, get_dataset):
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def fit(data, get_dataset):
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img_w, img_h = data.shape
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img_w, img_h = data.shape
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def err(parameters):
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def err(parameters):
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r = np.empty((img_w, img_h))
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r = np.empty((img_w, img_h))
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compute_gaussian(r, img_w, img_h, *parameters)
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compute_gaussian(r, img_w, img_h, *parameters)
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@ -38,6 +39,7 @@ def fit(data, get_dataset):
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def get_and_fit():
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def get_and_fit():
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if "dataset_db" in globals():
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if "dataset_db" in globals():
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logger.info("using dataset DB for Gaussian fit guess")
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logger.info("using dataset DB for Gaussian fit guess")
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def get_dataset(name, default):
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def get_dataset(name, default):
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try:
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try:
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return dataset_db.get(name)
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return dataset_db.get(name)
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@ -45,7 +47,7 @@ def get_and_fit():
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return default
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return default
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else:
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else:
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logger.info("using defaults for Gaussian fit guess")
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logger.info("using defaults for Gaussian fit guess")
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def get_dataset(name, default):
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def get_dataset(name, default):
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return default
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return default
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get_dataset = lambda name, default: default
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return fit(controller_driver.get_picture(), get_dataset)
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return fit(controller_driver.get_picture(), get_dataset)
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