From 6125776041a27f7af818dbe57ff8935119eef762 Mon Sep 17 00:00:00 2001
From: Egor Sobolev <egor.sobolev@xfel.eu>
Date: Wed, 6 Sep 2023 13:30:49 +0200
Subject: [PATCH] Improve integrated intensity addon
---
.../correction_addons/integrated_intensity.py | 67 +++++++++++++++++--
1 file changed, 61 insertions(+), 6 deletions(-)
diff --git a/src/calng/correction_addons/integrated_intensity.py b/src/calng/correction_addons/integrated_intensity.py
index 61b1ab5b..231f0722 100644
--- a/src/calng/correction_addons/integrated_intensity.py
+++ b/src/calng/correction_addons/integrated_intensity.py
@@ -1,5 +1,5 @@
import numpy as np
-from karabo.bound import NDARRAY_ELEMENT
+from karabo.bound import DOUBLE_ELEMENT, NDARRAY_ELEMENT, NODE_ELEMENT
from .base_addon import BaseCorrectionAddon
@@ -13,18 +13,73 @@ def maybe_get(a):
class IntegratedIntensityAddon(BaseCorrectionAddon):
_node_name = "integratedIntensity"
+ def __init__(self, config):
+ global cupy
+ import cupy
+
+ self._vmin = config["valueMin"]
+ self._vmax = config["valueMax"]
+
+ def reconfigure(self, changed_config):
+ if changed_config.has("valueMin"):
+ self._vmin = changed_config["valueMin"]
+ if changed_config.has("valueMax"):
+ self._vmax = changed_config["valueMax"]
+
@staticmethod
def extend_output_schema(schema):
# note: sort of assumes XTDF hash structure
(
+ NODE_ELEMENT(schema)
+ .key("integratedIntensity")
+ .commit(),
+
+ NDARRAY_ELEMENT(schema)
+ .key("integratedIntensity.mean")
+ .dtype("DOUBLE")
+ .commit(),
+
NDARRAY_ELEMENT(schema)
- .key("image.integratedIntensity")
+ .key("integratedIntensity.variance")
.dtype("DOUBLE")
+ .commit(),
+
+ NDARRAY_ELEMENT(schema)
+ .key("integratedIntensity.count")
+ .dtype("UINT64")
.commit()
)
- def post_correction(self, processed_data, cell_table, pulse_table, output_hash):
- # Numpy should handle CuPy dispatch for us
- output_hash["image.integratedIntensity"] = maybe_get(
- np.nansum(processed_data, axis=(1, 2))
+ @staticmethod
+ def extend_device_schema(schema, prefix):
+ (
+ DOUBLE_ELEMENT(schema)
+ .key(f"{prefix}.valueMin")
+ .tags("managed")
+ .assignmentOptional()
+ .defaultValue(-10.0)
+ .reconfigurable()
+ .commit(),
+
+ DOUBLE_ELEMENT(schema)
+ .key(f"{prefix}.valueMax")
+ .tags("managed")
+ .assignmentOptional()
+ .defaultValue(20000.0)
+ .reconfigurable()
+ .commit()
)
+
+ def post_correction(self, data, cell_table, pulse_table, output_hash):
+ # Numpy should handle CuPy dispatch for us
+ mask = np.isfinite(data) & (self._vmin < data) & (data < self._vmax)
+
+ count = np.sum(mask, axis=(1, 2))
+
+ tmp = mask * data
+ mu = np.sum(tmp, axis=(1, 2)) / count
+ var = np.sum(tmp * data, axis=(1, 2)) / count - mu * mu
+
+ output_hash["integratedIntensity.mean"] = maybe_get(mu)
+ output_hash["integratedIntensity.variance"] = maybe_get(var)
+ output_hash["integratedIntensity.count"] = maybe_get(count)
--
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