sf-daq/dap
0
0
Fork 1
Code Issues Pull Requests 1 Actions Packages Projects Releases Wiki Activity

moved peakfinder_analysis out of work function

Browse Source
This commit is contained in:
augustin_s
2024-07-30 17:51:08 +02:00
parent a01a6e6ed5
commit 6a926bcede
3 changed files with 67 additions and 55 deletions
Download Patch File Download Diff File Expand all files Collapse all files

1
dap/algos/__init__.py
View File

@ -1,5 +1,6 @@
from .radprof import calc_radial_integration
from .addmask import calc_apply_additional_mask
from .peakfind import calc_peakfinder_analysis

63
dap/algos/peakfind.py Normal file
View File

@ -0,0 +1,63 @@
from copy import copy
import numpy as np
from peakfinder8_extension import peakfinder_8
def calc_peakfinder_analysis(results, pfdata, pixel_mask_pf):
x_beam = results["beam_center_x"] - 0.5 # to coordinates where position of first pixel/point is 0.5, 0.5
y_beam = results["beam_center_y"] - 0.5 # to coordinates where position of first pixel/point is 0.5, 0.5
hitfinder_min_snr = results["hitfinder_min_snr"]
hitfinder_min_pix_count = int(results["hitfinder_min_pix_count"])
hitfinder_adc_thresh = results["hitfinder_adc_thresh"]
asic_ny, asic_nx = pfdata.shape
nasics_y, nasics_x = 1, 1
hitfinder_max_pix_count = 100
max_num_peaks = 10000
# usually don't need to change this value, rather robust
hitfinder_local_bg_radius= 20.
# in case of further modification with the mask, make a new one, independent from real mask
maskPr = np.copy(pixel_mask_pf)
y, x = np.indices(pfdata.shape)
pix_r = np.sqrt((x-x_beam)**2 + (y-y_beam)**2)
peak_list_x, peak_list_y, peak_list_value = peakfinder_8(
max_num_peaks,
pfdata.astype(np.float32),
maskPr.astype(np.int8),
pix_r.astype(np.float32),
asic_nx, asic_ny,
nasics_x, nasics_y,
hitfinder_adc_thresh,
hitfinder_min_snr,
hitfinder_min_pix_count,
hitfinder_max_pix_count,
hitfinder_local_bg_radius
)
number_of_spots = len(peak_list_x)
results["number_of_spots"] = number_of_spots
if number_of_spots != 0:
results["spot_x"] = [-1.0] * number_of_spots
results["spot_y"] = [-1.0] * number_of_spots
results["spot_intensity"] = copy(peak_list_value)
for i in range(number_of_spots):
results["spot_x"][i] = peak_list_x[i] + 0.5
results["spot_y"][i] = peak_list_y[i] + 0.5
else:
results["spot_x"] = []
results["spot_y"] = []
results["spot_intensity"] = []
npeaks_threshold_hit = results.get("npeaks_threshold_hit", 15)
if number_of_spots >= npeaks_threshold_hit:
results["is_hit_frame"] = True

58
dap/worker.py
View File

@ -6,9 +6,8 @@ from time import sleep
import jungfrau_utils as ju
import numpy as np
from peakfinder8_extension import peakfinder_8
from algos import calc_radial_integration, calc_apply_additional_mask
from algos import calc_radial_integration, calc_apply_additional_mask, calc_peakfinder_analysis
from zmqsocks import ZMQSockets
from utils import json_load, read_bit
@ -246,60 +245,9 @@ def work(backend_address, accumulator_host, accumulator_port, visualisation_host
# in case all needed parameters are present, make peakfinding
do_peakfinder_analysis = results.get("do_peakfinder_analysis", False)
if do_peakfinder_analysis and pixel_mask_pf is not None and all(k in results for k in ("beam_center_x", "beam_center_y", "hitfinder_min_snr", "hitfinder_min_pix_count", "hitfinder_adc_thresh")):
x_beam = results["beam_center_x"] - 0.5 # to coordinates where position of first pixel/point is 0.5, 0.5
y_beam = results["beam_center_y"] - 0.5 # to coordinates where position of first pixel/point is 0.5, 0.5
hitfinder_min_snr = results["hitfinder_min_snr"]
hitfinder_min_pix_count = int(results["hitfinder_min_pix_count"])
hitfinder_adc_thresh = results["hitfinder_adc_thresh"]
asic_ny, asic_nx = pfdata.shape
nasics_y, nasics_x = 1, 1
hitfinder_max_pix_count = 100
max_num_peaks = 10000
# usually don't need to change this value, rather robust
hitfinder_local_bg_radius= 20.
# in case of further modification with the mask, make a new one, independent from real mask
maskPr = np.copy(pixel_mask_pf)
y, x = np.indices(pfdata.shape)
pix_r = np.sqrt((x-x_beam)**2 + (y-y_beam)**2)
peak_list_x, peak_list_y, peak_list_value = peakfinder_8(
max_num_peaks,
pfdata.astype(np.float32),
maskPr.astype(np.int8),
pix_r.astype(np.float32),
asic_nx, asic_ny,
nasics_x, nasics_y,
hitfinder_adc_thresh,
hitfinder_min_snr,
hitfinder_min_pix_count,
hitfinder_max_pix_count,
hitfinder_local_bg_radius
)
number_of_spots = len(peak_list_x)
results["number_of_spots"] = number_of_spots
if number_of_spots != 0:
results["spot_x"] = [-1.0] * number_of_spots
results["spot_y"] = [-1.0] * number_of_spots
results["spot_intensity"] = copy(peak_list_value)
for i in range(number_of_spots):
results["spot_x"][i] = peak_list_x[i] + 0.5
results["spot_y"][i] = peak_list_y[i] + 0.5
else:
results["spot_x"] = []
results["spot_y"] = []
results["spot_intensity"] = []
npeaks_threshold_hit = results.get("npeaks_threshold_hit", 15)
if number_of_spots >= npeaks_threshold_hit:
results["is_hit_frame"] = True
calc_peakfinder_analysis(results, pfdata, pixel_mask_pf)
# ???
forceSendVisualisation = False
if data.dtype != np.uint16:
apply_threshold = results.get("apply_threshold", False)