diff --git a/AWAControl/algorithms/curv.py b/AWAControl/algorithms/curv.py
index d0f856cb795bf149525ee08938bcd14e38e421f9..74a77bb4ac8328ac5b5a17d7487a3a763c81e594 100644
--- a/AWAControl/algorithms/curv.py
+++ b/AWAControl/algorithms/curv.py
@@ -109,4 +109,7 @@ class CurvatureGridOptimize(GridOptimize):
# ignore locations where the first derivative is less than zero
result = torch.where(first_order_diff > 0, second_order_diff, 0.0)
+ #ignore locations above 0.2 nC
+ result = torch.where(objective_values[:,1:-1] < 0.2, result, 0.0)
+
return result
diff --git a/AWAControl/configs/awa_camera_config.yml b/AWAControl/configs/awa_camera_config.yml
index e9d1f39cba4e49c6385320ebb833448a6f8bb69c..414b787a43b6ebc1e3e1fb31975460a6beb9dd4c 100644
--- a/AWAControl/configs/awa_camera_config.yml
+++ b/AWAControl/configs/awa_camera_config.yml
@@ -21,20 +21,23 @@ DYG3:
- 251.55576493685035
radius: 202.62023172988742
video_number: 3
+
DYG4:
type: frame_grabber
center:
- - 350
+ - 345
- 277
radius: 230
video_number: 4
+
DYG5:
type: frame_grabber
center:
- - 293.6070723016849
- - 248.12799438794332
- radius: 206.9578032921999
+ - 375
+ - 269
+ radius: 220
video_number: 5
+
DYG7:
type: blackfly
center:
@@ -43,6 +46,7 @@ DYG7:
radius: 350
ip_address: 192.168.2.106
gain: 1.0
+
DYG14:
type: blackfly
center:
@@ -51,6 +55,7 @@ DYG14:
radius: 350
ip_address: 192.168.2.111
gain: 1.0
+
DYG15:
type: blackfly
center:
@@ -59,13 +64,16 @@ DYG15:
radius: 350
ip_address: 192.168.2.111
gain: 1.0
+
EYG1:
- type: frame_grabber
+ type: blackfly
center:
- - 365.0686486037925
- - 231.07420853906464
- radius: 236.83693372959985
- video_number: 32
+ - 960
+ - 540
+ radius: 380.0
+ ip_address: 192.168.2.43
+ gain: 10
+
EYG2:
type: frame_grabber
center:
@@ -73,6 +81,7 @@ EYG2:
- 288.8650297445553
radius: 243.35671576658976
video_number: 22
+
YAGPerm:
type: frame_grabber
center:
@@ -80,6 +89,7 @@ YAGPerm:
- 235.78765345303117
radius: 240.27518749518512
video_number: 30
+
EYG3:
type: frame_grabber
center:
@@ -87,6 +97,7 @@ EYG3:
- 228.31807007324025
radius: 154.73401858047842
video_number: 28
+
EYG5:
type: frame_grabber
center:
@@ -94,20 +105,32 @@ EYG5:
- 224.53486976686574
radius: 194.8
video_number: 36
+
+EYG_BEFORE_TDC:
+ type: frame_grabber
+ center:
+ - 302.59830583753643
+ - 224.53486976686574
+ radius: 194.8
+ video_number: 35
+
DYG6:
type: frame_grabber
center:
- - 263.9821715894023
- - 230.3264518612156
- radius: 197.20866357719058
- video_number: 36
+ - 396.25
+ - 271.346
+ radius: 211
+ video_number: 6
+
SLIT_YAG:
- type: frame_grabber
+ type: blackfly
center:
- - 232.21534477812514
- - 229.76375219200324
- radius: 150
- video_number: 29
+ - 925
+ - 380
+ radius: 350
+ ip_address: 192.168.2.17
+ gain: 5
+
WYG8:
type: blackfly
center:
@@ -116,19 +139,71 @@ WYG8:
radius: 350
ip_address: 192.168.2.111
gain: 1.0
+
EYG7:
type: blackfly
center:
- - 1316.661483278318
- - 609.2225709973745
+ - 1040
+ - 615
radius: 650.8327079387865
- ip_address: 192.168.2.46
- gain: 10
+ ip_address: 192.168.2.42
+ gain: 25
+
EYG8:
type: blackfly
center:
- 966.7950192322188
- 574.5583167280876
radius: 564.0886521410309
- ip_address: 192.168.2.36
+ ip_address: 192.168.2.32
gain: 1
+
+DYG8:
+ type: frame_grabber
+ center:
+ - 337
+ - 216
+ radius: 220
+ video_number: 8
+
+DYG10:
+ type: frame_grabber
+ center:
+ - 337
+ - 216
+ radius: 220
+ video_number: 10
+
+DYG9:
+ type: frame_grabber
+ center:
+ - 337
+ - 216
+ radius: 220
+ video_number: 9
+
+AfterPETSDipole:
+ type: frame_grabber
+ center:
+ - 337
+ - 216
+ radius: 220
+ video_number: 23
+
+Yag12:
+ type: blackfly
+ center:
+ - 939
+ - 644
+ radius: 530
+ ip_address: 192.168.2.3
+ gain: 1.0
+
+Yag11:
+ type: blackfly
+ center:
+ - 939
+ - 644
+ radius: 530
+ ip_address: 192.168.2.138
+ gain: 1.0
\ No newline at end of file
diff --git a/AWAControl/diagnostics/screen.py b/AWAControl/diagnostics/screen.py
index 8c09c6dcc9bb025ef4b7f06dad09275eabde7e60..e21dd80f10831479a69af29a7fe344b241b7059f 100644
--- a/AWAControl/diagnostics/screen.py
+++ b/AWAControl/diagnostics/screen.py
@@ -6,7 +6,7 @@ from copy import copy
from pprint import pprint
from time import sleep
from typing import List, Optional, Union
-
+import warnings
import h5py
import numpy as np
import pandas as pd
@@ -14,6 +14,7 @@ import yaml
from epics import caget, caget_many, caput, PV
from matplotlib import patches, pyplot as plt
from pydantic import BaseModel, PositiveFloat, PositiveInt, field_validator
+from scipy.ndimage import median_filter
from .. import CAMERA_CONFIG
@@ -161,8 +162,9 @@ class AWAImageDiagnostic(BaseModel):
extra_pvs: List[str] = []
background_file: str = None
- save_image_location: Union[str, None] = None
+ save_image_location: Union[str] = "."
roi: Union[RectangularROI, CircularROI] = None
+ filter_size: Optional[int] = None
min_log_intensity: float = 4.0
bounding_box_half_width: PositiveFloat = 2.0
@@ -233,7 +235,7 @@ class AWAImageDiagnostic(BaseModel):
result = {}
results += [result | extra_data]
- images += [img]
+ images += [raw_img]
sleep(self.wait_time)
@@ -340,6 +342,14 @@ class AWAImageDiagnostic(BaseModel):
if self.roi is not None:
img = self.roi.crop_image(img.T).T
+ # filter image
+ if self.filter_size is not None:
+ img = median_filter(img, self.filter_size)
+
+ # raise a warning if more than a small percentage is saturated
+ if np.sum(img == np.max(img)) / img.size > 0.0001:
+ warnings.warn("More than 0.01% of the image pixels are the same max value, image might be oversaturated -- fit values may be incorrect")
+
return img, extra_data, raw_img
def measure_background(self, n_measurements: int = 5, file_location: str = None):
@@ -353,16 +363,25 @@ class AWAImageDiagnostic(BaseModel):
filename = os.path.join(file_location, f"{name}_background.npy")
- print("please shutter beam")
- input()
+ print(f"saving to {filename}")
+ print("shuttering beam")
+ shutter_pv = "AWA:DO0:Ch01"
+ old_state = caget(shutter_pv)
+
+ # put in shutter
+ #caput(shutter_pv,1)
+ input("please sutter beam")
+ sleep(2)
+
images = []
for i in range(n_measurements):
images += [self.get_raw_data()[0]]
sleep(self.wait_time)
- print("please un-shutter beam")
- input()
-
+ # return shutter to old state
+ #caput(shutter_pv, old_state)
+ input("please unshutter beam")
+
# return average
images = np.stack(images)
mean = images.mean(axis=0)
@@ -504,6 +523,7 @@ class AWAImageDiagnostic(BaseModel):
y_projection, visualize=self.visualize, n_restarts=self.n_fitting_restarts
)
+
return {
"centroid": np.array((para_x[1], para_y[1])),
"rms_sizes": np.array((para_x[2], para_y[2])),
@@ -637,6 +657,8 @@ class AWAFrameGrabberDiagnostic(AWAImageDiagnostic):
# TODO: add runtime error if the img array is empty ->
# means that the frame grabber is not actively taking measurements
# (EPICS PV returns all zeros)
+
img = img.reshape(480, 640)
+ img = median_filter(img, size=2)
return img, extra_data
diff --git a/AWAControl/diagnostics/utils/roi_finder.py b/AWAControl/diagnostics/utils/roi_finder.py
index d83bc3557bb74150cd327225729f69b52b31219d..15e900ca14037c3723272db0494d41ba26d4847b 100644
--- a/AWAControl/diagnostics/utils/roi_finder.py
+++ b/AWAControl/diagnostics/utils/roi_finder.py
@@ -1,5 +1,5 @@
from AWAControl.diagnostics.screen import load_screen
-image_diagnostic = load_screen("EYG8")
+image_diagnostic = load_screen("DYG5")
import matplotlib.pyplot as plt
from circle_detection import ScreenFinder
diff --git a/AWAControl/processes/schottky.py b/AWAControl/processes/schottky.py
index 0f19ee306a08c33b791a67f48b61a893b1385c49..01a9598fb2dcbd90d4b202b8eff1da642a551da3 100644
--- a/AWAControl/processes/schottky.py
+++ b/AWAControl/processes/schottky.py
@@ -1,10 +1,12 @@
import time
+import numpy as np
import torch
from xopt import VOCS, Xopt, Evaluator
from xopt.generators.bayesian.bax_generator import BaxGenerator
from AWAControl.algorithms.curv import CurvatureGridOptimize
-
+from epics import caget, caput
+from gpytorch.priors import GammaPrior
from xopt.generators.bayesian.turbo import EntropyTurboController
import matplotlib.pyplot as plt
@@ -14,6 +16,15 @@ warnings.filterwarnings("ignore")
def run_schottky_scan(
awa_env, n_steps=10
):
+ # LLRF feedback old state
+ pv = "AWALLRF:K1:EnableFC"
+ old_llrf_feedback_state = caget(pv)
+
+ # turn feedback off
+ print("turning llrf feedback off")
+ caput(pv, 0)
+
+
def evaluate(inputs: dict):
# caput values
awa_env.set_variables(inputs)
@@ -22,7 +33,7 @@ def run_schottky_scan(
time.sleep(1)
results = awa_env.get_observables(['ICT1_nC'])
-
+ print(results)
return results
vocs = VOCS(
@@ -33,17 +44,19 @@ def run_schottky_scan(
)
algorithm = CurvatureGridOptimize(
- n_mesh_points=200, minimize=False, observable_names_ordered=["ICT1_nC"]
+ n_mesh_points=200, minimize=False,
+ observable_names_ordered=["ICT1_nC"],
+ use_mean=True
)
# construct BAX generator
generator = BaxGenerator(
vocs=vocs, algorithm=algorithm,
- n_interpolate_points=3,
- turbo_controller=EntropyTurboController(vocs)
+ n_interpolate_points=5,
+ #turbo_controller=EntropyTurboController(vocs)
)
- generator.gp_constructor.use_low_noise_prior = False
- generator.turbo_controller.restrict_model_data = False
+ generator.gp_constructor.custom_noise_prior = GammaPrior(1.202, 8.744)
+ #generator.turbo_controller.restrict_model_data = False
X = Xopt(
vocs=vocs,
@@ -59,7 +72,7 @@ def run_schottky_scan(
print(e)
- X.evaluate_data({'K1SetPhase': 0})
+ X.evaluate_data({'K1SetPhase': np.linspace(-20,360,20)})
test_x = torch.linspace(*X.vocs.variables["K1SetPhase"], 200)
@@ -135,4 +148,8 @@ def run_schottky_scan(
print("Setting K1Phase to "+str(mean+50))
evaluate({'K1SetPhase': mean+50})
+
+ print("returning LLRF feedback from old state")
+ caput(pv, old_llrf_feedback_state)
+
return X