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fix: gui even horiz_roi

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This commit is contained in:
appel_c
2023-08-11 09:46:57 +02:00
parent 028279795c
commit be862ef526
1 changed files with 50 additions and 35 deletions
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85
bec_plugins/data_processing/saxs_imaging_processor.py
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@@ -16,22 +16,36 @@ class SaxsImagingProcessor(StreamProcessor):
self.metadata_consumer = None
self.parameter_consumer = None
self.metadata = {}
# self._init_data_output()
# Initit
self.proj_nr = None
self.azi_angle = None
self.qranges = [20, 50]
self.contrast = 0
self.num_received_msgs = 0
self.queue = Queue()
self._init_metadata(endpoint="px_stream/proj_nr")
self.start_metadata_consumer(endpoint="px_stream/projection_*/metadata")
self._init_parameter(endpoint="px_stream/gui_event")
self.start_parameter_consumer(endpoint="px_stream/gui_event")
self._init_metadata_and_proj_nr(endpoint="px_stream/proj_nr")
self.start_metadata_consumer(endpoint="px_stream/projection_*/metadata")
def _init_parameter(self, endpoint: str) -> None:
"""Initialize the parameters azi_angle, contrast and horiz_roi.
Args:
endpoint (str): Endpoint for redis topic.
Returns:
None
"""
self.azi_angle = None
self.horiz_roi = [20, 50]
self.contrast = 0
msg = self.producer.get(topic=endpoint)
if msg is None:
return None
msg_raw = BECMessage.DeviceMessage.loads(msg)
self._parameter_msg_handler(msg_raw)
def start_parameter_consumer(self, endpoint: str) -> None:
"""Initialize the consumers for gui_event parameters.
Consumer is started with a callback function that updates
the parameters: azi_angle, contrast and qranges.
the parameters: azi_angle, contrast and horiz_roi.
Args:
endpoint (str): Endpoint for redis topic.
@@ -62,33 +76,33 @@ class SaxsImagingProcessor(StreamProcessor):
"""
msg_raw = BECMessage.DeviceMessage.loads(msg.value)
parent._parameter_msg_handler(msg_raw, msg.topic.decode())
parent._parameter_msg_handler(msg_raw)
def _parameter_msg_handler(self, msg: BECMessage, topic) -> None:
def _parameter_msg_handler(self, msg: BECMessage) -> None:
"""Handle the parameter message.
There can be updates on three different parameters:
azi_angle, contrast and qranges.
azi_angle, contrast and horiz_roi.
Args:
msg (BECMessage): Message object.
topic (str): Topic for the message.
Returns:
None
"""
if msg.content["signals"].get("qranges") is not None:
self.qranges = msg.content["signals"]["qranges"]
if msg.content["signals"].get("horiz_roi") is not None:
self.horiz_roi = msg.content["signals"]["horiz_roi"]
if msg.content["signals"].get("azi_angles") is not None:
self.azi_angle = msg.content["signals"]["azi_angle"]
if msg.content["signals"].get("contrast") is not None:
self.contrast = msg.content["signals"]["contrast"]
if len(self.metadata) > 0:
self._update_queue(self.metadata[self.proj_nr], self.proj_nr)
# self._init_parameter_updated = True
# if len(self.metadata) > 0:
# self._update_queue(self.metadata[self.proj_nr], self.proj_nr)
def _init_metadata(self, endpoint: str) -> None:
"""Initialize the metadata.
def _init_metadata_and_proj_nr(self, endpoint: str) -> None:
"""Initialize the metadata and proj_nr.
Args:
endpoint (str): Endpoint for redis topic.
@@ -100,6 +114,7 @@ class SaxsImagingProcessor(StreamProcessor):
msg = self.producer.get(topic=endpoint)
if msg is None:
self.proj_nr = None
return None
msg_raw = BECMessage.DeviceMessage.loads(msg)
self.proj_nr = msg_raw.content["signals"]["proj_nr"]
@@ -199,15 +214,13 @@ class SaxsImagingProcessor(StreamProcessor):
proj_nr, metadata = self.queue.get()
self.num_received_msgs = 0
# TODO initiate output, such that self.process only runs on new data
# self._init_data_output()
data = []
while self.queue.empty():
# TODO debug code for timing
data_msgs = self._get_data(proj_nr)
if data_msgs is None:
continue
data.extend([msg.content["signals"]["data"] for msg in data_msgs if msg is not None])
if data_msgs is not None:
data.extend(
[msg.content["signals"]["data"] for msg in data_msgs if msg is not None]
)
# print(f"Loading took {time.time() - start}")
# start = time.time()
result = self.process(data, metadata)
@@ -259,13 +272,13 @@ class SaxsImagingProcessor(StreamProcessor):
out = []
contrast = self.contrast
qranges = self.qranges
horiz_roi = self.horiz_roi
azi_angle = self.azi_angle
if azi_angle is None:
azi_angle = 0
f1amp, f2amp, f2phase = self._colorfulplot(
qranges=qranges,
horiz_roi=horiz_roi,
q=q,
norm_sum=norm_sum,
data=azint_data,
@@ -289,7 +302,7 @@ class SaxsImagingProcessor(StreamProcessor):
def _colorfulplot(
self,
qranges: list,
horiz_roi: list,
q: np.ndarray,
norm_sum: np.ndarray,
data: np.ndarray,
@@ -300,7 +313,7 @@ class SaxsImagingProcessor(StreamProcessor):
Pending: hsv_to_rgb conversion for colorful output
Args:
qranges (list): List with q edges for binning.
horiz_roi (list): List with q edges for binning.
q (np.ndarray): q values.
norm_sum (np.ndarray): Normalization sum.
data (np.ndarray): Data to be binned.
@@ -312,7 +325,9 @@ class SaxsImagingProcessor(StreamProcessor):
"""
output, output_norm = self._bin_qrange(qranges=qranges, q=q, norm_sum=norm_sum, data=data)
output, output_norm = self._bin_qrange(
horiz_roi=horiz_roi, q=q, norm_sum=norm_sum, data=data
)
output_sym = self._sym_data(data=output, norm_sum=output_norm)
output_sym = output_sym
shape = output_sym.shape[0:2]
@@ -347,12 +362,12 @@ class SaxsImagingProcessor(StreamProcessor):
return f1amp, f2amp, f2phase # , comb_all
def _bin_qrange(self, qranges, q, norm_sum, data) -> Tuple[np.ndarray, np.ndarray]:
def _bin_qrange(self, horiz_roi, q, norm_sum, data) -> Tuple[np.ndarray, np.ndarray]:
"""Reintegrate data for given q range.
Weighted sum for data using norm_sum as weights
Args:
qranges (list): List with q edges for binning.
horiz_roi (list): List with q edges for binning.
q (np.ndarray): q values.
norm_sum (np.ndarray): Normalization sum.
data (np.ndarray): Data to be binned.
@@ -362,11 +377,11 @@ class SaxsImagingProcessor(StreamProcessor):
np.ndarray: Binned normalization sum.
"""
output = np.zeros((*data.shape[:-1], len(qranges) - 1))
output_norm = np.zeros((data.shape[-2], len(qranges) - 1))
output = np.zeros((*data.shape[:-1], len(horiz_roi) - 1))
output_norm = np.zeros((data.shape[-2], len(horiz_roi) - 1))
with np.errstate(divide="ignore", invalid="ignore"):
q_mask = np.logical_and(q >= q[qranges[0]], q <= q[qranges[1]])
q_mask = np.logical_and(q >= q[horiz_roi[0]], q <= q[horiz_roi[1]])
output_norm[..., 0] = np.nansum(norm_sum[..., q_mask], axis=-1)
output[..., 0] = np.nansum(data[..., q_mask] * norm_sum[..., q_mask], axis=-1)
output[..., 0] = np.divide(