renamed data -> image
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@ -90,9 +90,9 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
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double_pixels = results.get("double_pixels", "mask")
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double_pixels = results.get("double_pixels", "mask")
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data = jfdata.process(raw_data, metadata, double_pixels)
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image = jfdata.process(raw_data, metadata, double_pixels)
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if not data:
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if not image:
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continue
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continue
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pixel_mask_pf = jfdata.get_pixel_mask(results, double_pixels)
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pixel_mask_pf = jfdata.get_pixel_mask(results, double_pixels)
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@ -104,9 +104,9 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
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results["saturated_pixels_y"] = saturated_pixels_y.tolist()
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results["saturated_pixels_y"] = saturated_pixels_y.tolist()
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calc_radial_integration(results, data, pixel_mask_pf)
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calc_radial_integration(results, image, pixel_mask_pf)
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pfdata = data.copy() #TODO: is this copy needed?
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pfdata = image.copy() #TODO: is this copy needed?
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calc_mask_pixels(pfdata, pixel_mask_pf) # changes pfdata in place
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calc_mask_pixels(pfdata, pixel_mask_pf) # changes pfdata in place
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calc_apply_threshold(results, pfdata) # changes pfdata in place
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calc_apply_threshold(results, pfdata) # changes pfdata in place
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@ -115,10 +115,10 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
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calc_peakfinder_analysis(results, pfdata, pixel_mask_pf)
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calc_peakfinder_analysis(results, pfdata, pixel_mask_pf)
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# ???
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# ???
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data, aggregation_is_ready = calc_apply_aggregation(results, data, pixel_mask_pf, aggregator)
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image, aggregation_is_ready = calc_apply_aggregation(results, image, pixel_mask_pf, aggregator)
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results["type"] = str(data.dtype)
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results["type"] = str(image.dtype)
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results["shape"] = data.shape
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results["shape"] = image.shape
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zmq_socks.send_accumulator(results)
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zmq_socks.send_accumulator(results)
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@ -136,11 +136,11 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
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is_no_hit_frame_and_skipped = (is_no_hit_frame and random_skip)
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is_no_hit_frame_and_skipped = (is_no_hit_frame and random_skip)
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if aggregation_is_enabled_but_not_ready or is_bad_frame or is_no_hit_frame_and_skipped:
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if aggregation_is_enabled_but_not_ready or is_bad_frame or is_no_hit_frame_and_skipped:
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data = np.empty((2, 2), dtype=np.uint16)
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image = np.empty((2, 2), dtype=np.uint16)
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results["type"] = str(data.dtype)
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results["type"] = str(image.dtype)
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results["shape"] = data.shape
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results["shape"] = image.shape
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zmq_socks.send_visualisation(results, data)
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zmq_socks.send_visualisation(results, image)
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