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renamed variable d to pfdata

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This commit is contained in:
augustin_s
2024-07-30 17:27:04 +02:00
parent 399b887516
commit a01a6e6ed5
1 changed files with 8 additions and 8 deletions
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16
dap/worker.py
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@ -180,11 +180,11 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
#copy image to work with peakfinder, just in case #copy image to work with peakfinder, just in case
d = np.copy(data) pfdata = np.copy(data)
# make all masked pixels values nans # make all masked pixels values nans
if pixel_mask_pf is not None: if pixel_mask_pf is not None:
d[pixel_mask_pf != 1] = np.nan pfdata[pixel_mask_pf != 1] = np.nan
apply_threshold = results.get("apply_threshold", False) apply_threshold = results.get("apply_threshold", False)
threshold_value_choice = results.get("threshold_value", "NaN") threshold_value_choice = results.get("threshold_value", "NaN")
@ -192,9 +192,9 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
if apply_threshold and all(k in results for k in ("threshold_min", "threshold_max")): if apply_threshold and all(k in results for k in ("threshold_min", "threshold_max")):
threshold_min = float(results["threshold_min"]) threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"]) threshold_max = float(results["threshold_max"])
d[d < threshold_min] = threshold_value pfdata[pfdata < threshold_min] = threshold_value
if threshold_max > threshold_min: if threshold_max > threshold_min:
d[d > threshold_max] = threshold_value pfdata[pfdata > threshold_max] = threshold_value
# if roi calculation request is present, make it # if roi calculation request is present, make it
roi_x1 = results.get("roi_x1", []) roi_x1 = results.get("roi_x1", [])
@ -212,7 +212,7 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
results["roi_intensities_proj_x"] = [] results["roi_intensities_proj_x"] = []
for iRoi in range(len(roi_x1)): for iRoi in range(len(roi_x1)):
data_roi = np.copy(d[roi_y1[iRoi]:roi_y2[iRoi], roi_x1[iRoi]:roi_x2[iRoi]]) data_roi = np.copy(pfdata[roi_y1[iRoi]:roi_y2[iRoi], roi_x1[iRoi]:roi_x2[iRoi]])
roi_results[iRoi] = np.nansum(data_roi) roi_results[iRoi] = np.nansum(data_roi)
if threshold_value_choice == "NaN": if threshold_value_choice == "NaN":
@ -252,7 +252,7 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
hitfinder_min_pix_count = int(results["hitfinder_min_pix_count"]) hitfinder_min_pix_count = int(results["hitfinder_min_pix_count"])
hitfinder_adc_thresh = results["hitfinder_adc_thresh"] hitfinder_adc_thresh = results["hitfinder_adc_thresh"]
asic_ny, asic_nx = d.shape asic_ny, asic_nx = pfdata.shape
nasics_y, nasics_x = 1, 1 nasics_y, nasics_x = 1, 1
hitfinder_max_pix_count = 100 hitfinder_max_pix_count = 100
max_num_peaks = 10000 max_num_peaks = 10000
@ -263,12 +263,12 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
# in case of further modification with the mask, make a new one, independent from real mask # in case of further modification with the mask, make a new one, independent from real mask
maskPr = np.copy(pixel_mask_pf) maskPr = np.copy(pixel_mask_pf)
y, x = np.indices(d.shape) y, x = np.indices(pfdata.shape)
pix_r = np.sqrt((x-x_beam)**2 + (y-y_beam)**2) pix_r = np.sqrt((x-x_beam)**2 + (y-y_beam)**2)
peak_list_x, peak_list_y, peak_list_value = peakfinder_8( peak_list_x, peak_list_y, peak_list_value = peakfinder_8(
max_num_peaks, max_num_peaks,
d.astype(np.float32), pfdata.astype(np.float32),
maskPr.astype(np.int8), maskPr.astype(np.int8),
pix_r.astype(np.float32), pix_r.astype(np.float32),
asic_nx, asic_ny, asic_nx, asic_ny,