From 8c5251de0c33e9463c04cb2fe90df6aa007ae48e Mon Sep 17 00:00:00 2001
From: philippe piot <ppiot@anl.gov>
Date: Wed, 31 Jul 2024 23:33:10 -0500
Subject: [PATCH] update diagnstics for numpy 2.0
---
AWAControl/diagnostics/screen.py | 24 +++++++++----------
.../diagnostics/utils/circle_detection.py | 4 ++--
.../diagnostics/utils/fitting_methods.py | 2 +-
3 files changed, 15 insertions(+), 15 deletions(-)
diff --git a/AWAControl/diagnostics/screen.py b/AWAControl/diagnostics/screen.py
index 88e5f31..0a9e6a1 100644
--- a/AWAControl/diagnostics/screen.py
+++ b/AWAControl/diagnostics/screen.py
@@ -340,11 +340,11 @@ class AWAImageDiagnostic(BaseModel):
print(f"log10 image intensity {log10_total_intensity} below threshold")
result = {
- "Cx": np.NaN,
- "Cy": np.NaN,
- "Sx": np.NaN,
- "Sy": np.NaN,
- "bb_penalty": np.NaN,
+ "Cx": np.nan,
+ "Cy": np.nan,
+ "Sx": np.nan,
+ "Sy": np.nan,
+ "bb_penalty": np.nan,
"total_intensity": 10**log10_total_intensity,
"log10_total_intensity": log10_total_intensity,
}
@@ -416,15 +416,15 @@ class AWAImageDiagnostic(BaseModel):
# bounding box constraint is active
if bb_penalty > 0 and self.apply_bounding_box_constraint:
for name in ["Cx", "Cy", "Sx", "Sy"]:
- result[name] = np.NaN
+ result[name] = np.nan
else:
result = {
- "Cx": np.NaN,
- "Cy": np.NaN,
- "Sx": np.NaN,
- "Sy": np.NaN,
- "bb_penalty": np.NaN,
+ "Cx": np.nan,
+ "Cy": np.nan,
+ "Sx": np.nan,
+ "Sy": np.nan,
+ "bb_penalty": np.nan,
"total_intensity": fits["total_intensity"],
"log10_total_intensity": log10_total_intensity,
}
@@ -566,7 +566,7 @@ class AWAFrameGrabberDiagnostic(AWAImageDiagnostic):
}
else:
# get pvs
- results = caget_many(self.pv_names)
+ results = caget_many(self.pv_names, timeout=5.0)
e_pvs = copy(self.extra_pvs)
if self.target_charge_pv is not None:
e_pvs += [self.target_charge_pv]
diff --git a/AWAControl/diagnostics/utils/circle_detection.py b/AWAControl/diagnostics/utils/circle_detection.py
index 9bafa53..ae66754 100644
--- a/AWAControl/diagnostics/utils/circle_detection.py
+++ b/AWAControl/diagnostics/utils/circle_detection.py
@@ -30,7 +30,7 @@ class ScreenFinder:
return
self.points.append((event.xdata, event.ydata))
- self.line.set_data(*np.asfarray(self.points).T)
+ self.line.set_data(*np.array(self.points).T)
# draw a circle if the number of points is enough
if len(self.points) > 3:
@@ -74,7 +74,7 @@ class ScreenFinder:
def fit_circle(self, points):
# https://scipy-cookbook.readthedocs.io/items/Least_Squares_Circle.html
- npts = np.asfarray(points).T
+ npts = np.array(points).T
x = npts[0]
y = npts[1]
x_m = np.mean(x)
diff --git a/AWAControl/diagnostics/utils/fitting_methods.py b/AWAControl/diagnostics/utils/fitting_methods.py
index 6c62510..04f88bd 100644
--- a/AWAControl/diagnostics/utils/fitting_methods.py
+++ b/AWAControl/diagnostics/utils/fitting_methods.py
@@ -157,7 +157,7 @@ def fit_gaussian_linear_background(y, inital_guess=None, visualize=True, n_resta
fig, ax = plot_fit(x, normed_y, bad_candidate)
ax.set_title("bad fit")
- candidate = [np.NaN] * 4
+ candidate = [np.nan] * 4
return candidate
--
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