diff --git a/src/Correction/dssc_correction.py b/src/Correction/dssc_correction.py
index 27565f7e094cedcd8405ce656a9c7bdd6b84979f..df2f16ad865cd7cd0fdc4923ea97a1eed4c63081 100644
--- a/src/Correction/dssc_correction.py
+++ b/src/Correction/dssc_correction.py
@@ -64,251 +64,307 @@ class DsscCorrection(calibrationBase.CalibrationReceiverBaseDevice):
"Offset", "Dark", expected, optional=True, mandatoryForIteration=True
)
- SLOT_ELEMENT(expected).key("askConnectedReadersToSendMySources").displayedName(
- "Request sources from connected RunToPipe"
- ).description(
- "Only relevant for development environment. When running without a "
- "CAL_MANAGER, we need to tell RunToPipe instances which sources "
- "to send us."
- ).commit()
-
- BOOL_ELEMENT(expected).key("doAnything").displayedName(
- "Enable input processing"
- ).description(
- "Toggle handling of input (at all). If False, the input handler "
- "of this device will be skipped. Useful to decrease logspam if "
- "device is misconfigured."
- ).assignmentOptional().defaultValue(
- True
- ).reconfigurable().commit()
-
- BOOL_ELEMENT(expected).key("applyCorrection").displayedName(
- "Enable correction(s)"
- ).description(
- "Toggle whether or not correction(s) are applied to image data. "
- "If false, this device still reshapes data to output shape, "
- "applies the pulse filter, and casts to output dtype. Useful for "
- "inspecting the raw data in the same format as corrected data."
- ).assignmentOptional().defaultValue(
- True
- ).reconfigurable().commit()
-
- INPUT_CHANNEL(expected).key("dataInput").commit()
- # note: output schema not set, will be updated to match data later
- OUTPUT_CHANNEL(expected).key("dataOutput").commit()
-
- VECTOR_STRING_ELEMENT(expected).key("fastSources").displayedName(
- "Fast data sources"
- ).description(
- "Sources to fast data as provided in channel metadata. "
- "Provide in the form source@path.in.hash to identify both source "
- "and path in the source data hash.\n"
- "Currently ignores the path.in.hash part (for hardcoded image.data)"
- ).assignmentMandatory().commit()
-
- STRING_ELEMENT(expected).key("pulseFilter").displayedName(
- "Pulse filter"
- ).description(
- "Filter pulses: will be evaluated as array of indices to keep from data. "
- "Can be anything which can be turned into numpy uint16 array. "
- "Numpy is available as np. "
- "Take care not to include duplicates. "
- "If empty, will not filter at all."
- ).assignmentOptional().defaultValue(
- ""
- ).reconfigurable().commit()
-
- NODE_ELEMENT(expected).key("dataFormat").displayedName(
- "Data format (in/out)"
- ).commit()
- STRING_ELEMENT(expected).key("dataFormat.inputImageDtype").displayedName(
- "Input image data dtype"
- ).description("The (numpy) dtype to expect for incoming image data.").options(
- "uint16,float32"
- ).assignmentOptional().defaultValue(
- "uint16"
- ).commit()
- STRING_ELEMENT(expected).key("dataFormat.outputImageDtype").displayedName(
- "Output image data dtype"
- ).description(
- "The (numpy) dtype to use for outgoing image data. "
- "Input is cast to float32, corrections are applied, and only then "
- "will the result be cast back to outputImageDtype (all on GPU)."
- ).options(
- "float16,float32,uint16"
- ).assignmentOptional().defaultValue(
- "float32"
- ).commit()
- # important: shape of data as going into correction
- UINT32_ELEMENT(expected).key("dataFormat.pixelsX").displayedName(
- "Pixels x"
- ).description(
- "Number of pixels of image data along X axis"
- ).assignmentMandatory().commit()
- UINT32_ELEMENT(expected).key("dataFormat.pixelsY").displayedName(
- "Pixels y"
- ).description(
- "Number of pixels of image data along Y axis"
- ).assignmentMandatory().commit()
- UINT32_ELEMENT(expected).key("dataFormat.memoryCells").displayedName(
- "Memory cells"
- ).description(
- "Full number of memory cells in incoming data"
- ).assignmentMandatory().commit()
- UINT32_ELEMENT(expected).key("dataFormat.memoryCellsCorrection").displayedName(
- "(Debug) Memory cells in correction map"
- ).description(
- "Full number of memory cells in currently loaded correction map. "
- "May exceed memory cell number in input if veto is on. "
- "This value just displayed for debugging."
- ).readOnly().initialValue(
- 0
- ).commit()
- VECTOR_UINT32_ELEMENT(expected).key("dataFormat.inputDataShape").displayedName(
- "Input data shape"
- ).description(
- "Image data shape in incoming data (from reader / DAQ). "
- "Value computed from pixelsX, pixelsY, and memoryCells - "
- "this slot is just showing you what is currently expected."
- ).readOnly().initialValue(
- []
- ).commit()
- VECTOR_UINT32_ELEMENT(expected).key("dataFormat.outputDataShape").displayedName(
- "Output data shape"
- ).description(
- "Image data shape for data output from this device. "
- "Value computed from pixelsX, pixelsY, and the size of the pulse filter - "
- "this slot is just showing what is currently expected."
- ).readOnly().initialValue(
- []
- ).commit()
-
- UINT32_ELEMENT(expected).key("outputShmemBufferLength").displayedName(
- "Output buffer length"
- ).description(
- "Corrected trains are written to shared memory locations. These are "
- "pre-allocated and re-used. This parameter determines how big "
- "(number of trains) the circular buffer will be."
- ).assignmentOptional().defaultValue(
- 50
- ).commit()
-
- # preview schema (WIP)
- NODE_ELEMENT(expected).key("preview").displayedName("Preview").commit()
+ (
+ SLOT_ELEMENT(expected)
+ .key("askConnectedReadersToSendMySources")
+ .displayedName("Request sources from connected RunToPipe")
+ .description(
+ "Only relevant for development environment. When running "
+ "without a CAL_MANAGER, we need to tell RunToPipe instances "
+ "which sources to send us."
+ )
+ .commit(),
+ BOOL_ELEMENT(expected)
+ .key("doAnything")
+ .displayedName("Enable input processing")
+ .description(
+ "Toggle handling of input (at all). If False, the input "
+ "handler of this device will be skipped. Useful to decrease "
+ "logspam if device is misconfigured."
+ )
+ .assignmentOptional()
+ .defaultValue(True)
+ .reconfigurable()
+ .commit(),
+ BOOL_ELEMENT(expected)
+ .key("applyCorrection")
+ .displayedName("Enable correction(s)")
+ .description(
+ "Toggle whether or not correction(s) are applied to image data. "
+ "If false, this device still reshapes data to output shape, "
+ "applies the pulse filter, and casts to output dtype. Useful for "
+ "inspecting the raw data in the same format as corrected data."
+ )
+ .assignmentOptional()
+ .defaultValue(True)
+ .reconfigurable()
+ .commit(),
+ INPUT_CHANNEL(expected).key("dataInput").commit(),
+ # note: output schema not set, will be updated to match data later
+ OUTPUT_CHANNEL(expected).key("dataOutput").commit(),
+ VECTOR_STRING_ELEMENT(expected)
+ .key("fastSources")
+ .displayedName("Fast data sources")
+ .description(
+ "Sources to fast data as provided in channel metadata. "
+ "Provide in the form source@path.in.hash to identify both source "
+ "and path in the source data hash.\n"
+ "Currently ignores the path.in.hash part (for hardcoded image.data)"
+ )
+ .assignmentMandatory()
+ .commit(),
+ STRING_ELEMENT(expected)
+ .key("pulseFilter")
+ .displayedName("Pulse filter")
+ .description(
+ "Filter pulses: will be evaluated as array of indices to keep from data. "
+ "Can be anything which can be turned into numpy uint16 array. "
+ "Numpy is available as np. "
+ "Take care not to include duplicates. "
+ "If empty, will not filter at all."
+ )
+ .assignmentOptional()
+ .defaultValue("")
+ .reconfigurable()
+ .commit(),
+ UINT32_ELEMENT(expected)
+ .key("outputShmemBufferLength")
+ .displayedName("Output buffer length")
+ .description(
+ "Corrected trains are written to shared memory locations. "
+ "These are pre-allocated and re-used. This parameter "
+ "determines how big (number of trains) the circular buffer "
+ "will be."
+ )
+ .assignmentOptional()
+ .defaultValue(50)
+ .commit(),
+ )
+
+ (
+ NODE_ELEMENT(expected)
+ .key("dataFormat")
+ .displayedName("Data format (in/out)")
+ .commit(),
+ STRING_ELEMENT(expected)
+ .key("dataFormat.inputImageDtype")
+ .displayedName("Input image data dtype")
+ .description("The (numpy) dtype to expect for incoming image data.")
+ .options("uint16,float32")
+ .assignmentOptional()
+ .defaultValue("uint16")
+ .commit(),
+ STRING_ELEMENT(expected)
+ .key("dataFormat.outputImageDtype")
+ .displayedName("Output image data dtype")
+ .description(
+ "The (numpy) dtype to use for outgoing image data. Input is "
+ "cast to float32, corrections are applied, and only then will "
+ "the result be cast back to outputImageDtype (all on GPU)."
+ )
+ .options("float16,float32,uint16")
+ .assignmentOptional()
+ .defaultValue("float32")
+ .commit(),
+ # important: shape of data as going into correction
+ UINT32_ELEMENT(expected)
+ .key("dataFormat.pixelsX")
+ .displayedName("Pixels x")
+ .description("Number of pixels of image data along X axis")
+ .assignmentMandatory()
+ .commit(),
+ UINT32_ELEMENT(expected)
+ .key("dataFormat.pixelsY")
+ .displayedName("Pixels y")
+ .description("Number of pixels of image data along Y axis")
+ .assignmentMandatory()
+ .commit(),
+ UINT32_ELEMENT(expected)
+ .key("dataFormat.memoryCells")
+ .displayedName("Memory cells")
+ .description("Full number of memory cells in incoming data")
+ .assignmentMandatory()
+ .commit(),
+ UINT32_ELEMENT(expected)
+ .key("dataFormat.memoryCellsCorrection")
+ .displayedName("(Debug) Memory cells in correction map")
+ .description(
+ "Full number of memory cells in currently loaded correction map. "
+ "May exceed memory cell number in input if veto is on. "
+ "This value just displayed for debugging."
+ )
+ .readOnly()
+ .initialValue(0)
+ .commit(),
+ VECTOR_UINT32_ELEMENT(expected)
+ .key("dataFormat.inputDataShape")
+ .displayedName("Input data shape")
+ .description(
+ "Image data shape in incoming data (from reader / DAQ). "
+ "Value computed from pixelsX, pixelsY, and memoryCells - "
+ "this slot is just showing you what is currently expected."
+ )
+ .readOnly()
+ .initialValue([])
+ .commit(),
+ VECTOR_UINT32_ELEMENT(expected)
+ .key("dataFormat.outputDataShape")
+ .displayedName("Output data shape")
+ .description(
+ "Image data shape for data output from this device. "
+ "Value computed from pixelsX, pixelsY, and the size of the pulse filter - "
+ "this slot is just showing what is currently expected."
+ )
+ .readOnly()
+ .initialValue([])
+ .commit(),
+ )
+
preview_schema = Schema()
- NODE_ELEMENT(preview_schema).key("data").commit()
- NDARRAY_ELEMENT(preview_schema).key("data.adc").dtype("FLOAT").commit()
- OUTPUT_CHANNEL(expected).key("preview.outputRaw").dataSchema(
- preview_schema
- ).commit()
- OUTPUT_CHANNEL(expected).key("preview.outputCorrected").dataSchema(
- preview_schema
- ).commit()
- BOOL_ELEMENT(expected).key("preview.enable").displayedName(
- "Enable preview data generation"
- ).assignmentOptional().defaultValue(True).reconfigurable().commit()
- INT32_ELEMENT(expected).key("preview.pulse").displayedName(
- "Pulse (or stat) for preview"
- ).description(
- "If this value is ≥ 0, the corresponding index from data will be "
- "sliced for the preview. If this value is ≤ 0, preview will be one "
- "of the following stats:\n"
- "-1: max\n"
- "-2: mean\n"
- "-3: sum\n"
- "-4: stdev\n"
- "Max means selecting the pulse with the maximum integrated value. "
- "The others are computed across all filtered pulses in the train."
- ).assignmentOptional().defaultValue(
- 0
- ).reconfigurable().commit()
- UINT32_ELEMENT(expected).key("preview.trainIdModulo").displayedName(
- "Train modulo for throttling"
- ).description(
- "Preview will only be sent for trains whose ID modulo this number "
- "is zero. Higher values means fewer preview updates. Should be "
- "adjusted based on input rate. Keep in mind that the GUI has "
- "limited refresh rate anyway and that network is precious."
- ).assignmentOptional().defaultValue(
- 6
- ).reconfigurable().commit()
-
- # timer-related settings
- NODE_ELEMENT(expected).key("performance").displayedName(
- "Performance measures"
- ).commit()
- FLOAT_ELEMENT(expected).key("performance.rateUpdateInterval").displayedName(
- "Rate update interval"
- ).description(
- "Maximum interval (seconds) between updates of the rate. "
- "Mostly relevant if not rateUpdateOnEachInput or if input is slow."
- ).assignmentOptional().defaultValue(
- 1
- ).reconfigurable().commit()
- FLOAT_ELEMENT(expected).key("performance.rateBufferSpan").displayedName(
- "Rate measurement buffer span"
- ).description(
- "Event buffer timespan (in seconds) for measuring rate"
- ).assignmentOptional().defaultValue(
- 20
- ).reconfigurable().commit()
- BOOL_ELEMENT(expected).key("performance.rateUpdateOnEachInput").displayedName(
- "Update rate on each input"
- ).description(
- "Whether or not to update the device rate for each input "
- "(otherwise only based on rateUpdateInterval). "
- "Note that processed trains are always registered - this just "
- "impacts when the rate is computed based on this."
- ).assignmentOptional().defaultValue(
- False
- ).reconfigurable().commit()
-
- FLOAT_ELEMENT(expected).key("processingStateTimeout").description(
- "Timeout after which the device goes from PROCESSING back to ACTIVE "
- "if no new input is processed"
- ).assignmentOptional().defaultValue(10).reconfigurable().commit()
-
- # just measurements and counters to display
- UINT64_ELEMENT(expected).key("trainId").displayedName("Train ID").description(
- "ID of latest train processed by this device."
- ).readOnly().initialValue(0).commit()
- FLOAT_ELEMENT(expected).key("performance.lastProcessingDuration").displayedName(
- "Processing time"
- ).description(
- "Amount of time spent in processing latest train. "
- "Time includes generating preview and sending data."
- ).unit(
- Unit.SECOND
- ).metricPrefix(
- MetricPrefix.MILLI
- ).readOnly().initialValue(
- 0
- ).commit()
- FLOAT_ELEMENT(expected).key("performance.rate").displayedName(
- "Rate"
- ).description(
- "Actual rate with which this device gets / processes / sends trains"
- ).unit(
- Unit.HERTZ
- ).readOnly().initialValue(
- 0
- ).commit()
- FLOAT_ELEMENT(expected).key("performance.theoreticalRate").displayedName(
- "Processing rate (hypothetical)"
- ).description(
- "Rate with which this device could hypothetically process trains. "
- "Based on lastProcessingDuration."
- ).unit(
- Unit.HERTZ
- ).readOnly().initialValue(
- float("NaN")
- ).warnLow(
- 10
- ).info(
- "Processing not fast enough for full speed"
- ).needsAcknowledging(
- False
- ).commit()
+ (
+ NODE_ELEMENT(expected).key("preview").displayedName("Preview").commit(),
+ NODE_ELEMENT(preview_schema).key("data").commit(),
+ NDARRAY_ELEMENT(preview_schema).key("data.adc").dtype("FLOAT").commit(),
+ OUTPUT_CHANNEL(expected)
+ .key("preview.outputRaw")
+ .dataSchema(preview_schema)
+ .commit(),
+ OUTPUT_CHANNEL(expected)
+ .key("preview.outputCorrected")
+ .dataSchema(preview_schema)
+ .commit(),
+ BOOL_ELEMENT(expected)
+ .key("preview.enable")
+ .displayedName("Enable preview data generation")
+ .assignmentOptional()
+ .defaultValue(True)
+ .reconfigurable()
+ .commit(),
+ INT32_ELEMENT(expected)
+ .key("preview.pulse")
+ .displayedName("Pulse (or stat) for preview")
+ .description(
+ "If this value is ≥ 0, the corresponding index from data will be "
+ "sliced for the preview. If this value is ≤ 0, preview will be one "
+ "of the following stats:\n"
+ "-1: max\n"
+ "-2: mean\n"
+ "-3: sum\n"
+ "-4: stdev\n"
+ "Max means selecting the pulse with the maximum integrated value. "
+ "The others are computed across all filtered pulses in the train."
+ )
+ .assignmentOptional()
+ .defaultValue(0)
+ .reconfigurable()
+ .commit(),
+ UINT32_ELEMENT(expected)
+ .key("preview.trainIdModulo")
+ .displayedName("Train modulo for throttling")
+ .description(
+ "Preview will only be sent for trains whose ID modulo this number "
+ "is zero. Higher values means fewer preview updates. Should be "
+ "adjusted based on input rate. Keep in mind that the GUI has "
+ "limited refresh rate anyway and that network is precious."
+ )
+ .assignmentOptional()
+ .defaultValue(6)
+ .reconfigurable()
+ .commit(),
+ )
+
+ (
+ NODE_ELEMENT(expected)
+ .key("performance")
+ .displayedName("Performance measures")
+ .commit(),
+ FLOAT_ELEMENT(expected)
+ .key("performance.rateUpdateInterval")
+ .displayedName("Rate update interval")
+ .description(
+ "Maximum interval (seconds) between updates of the rate. "
+ "Mostly relevant if not rateUpdateOnEachInput or if input is slow."
+ )
+ .assignmentOptional()
+ .defaultValue(1)
+ .reconfigurable()
+ .commit(),
+ FLOAT_ELEMENT(expected)
+ .key("performance.rateBufferSpan")
+ .displayedName("Rate measurement buffer span")
+ .description("Event buffer timespan (in seconds) for measuring rate")
+ .assignmentOptional()
+ .defaultValue(20)
+ .reconfigurable()
+ .commit(),
+ BOOL_ELEMENT(expected)
+ .key("performance.rateUpdateOnEachInput")
+ .displayedName("Update rate on each input")
+ .description(
+ "Whether or not to update the device rate for each input "
+ "(otherwise only based on rateUpdateInterval). "
+ "Note that processed trains are always registered - this just "
+ "impacts when the rate is computed based on this."
+ )
+ .assignmentOptional()
+ .defaultValue(False)
+ .reconfigurable()
+ .commit(),
+ FLOAT_ELEMENT(expected)
+ .key("processingStateTimeout")
+ .description(
+ "Timeout after which the device goes from PROCESSING back to ACTIVE "
+ "if no new input is processed"
+ )
+ .assignmentOptional()
+ .defaultValue(10)
+ .reconfigurable()
+ .commit(),
+ # just measurements and counters to display
+ UINT64_ELEMENT(expected)
+ .key("trainId")
+ .displayedName("Train ID")
+ .description("ID of latest train processed by this device.")
+ .readOnly()
+ .initialValue(0)
+ .commit(),
+ FLOAT_ELEMENT(expected)
+ .key("performance.lastProcessingDuration")
+ .displayedName("Processing time")
+ .description(
+ "Amount of time spent in processing latest train. "
+ "Time includes generating preview and sending data."
+ )
+ .unit(Unit.SECOND)
+ .metricPrefix(MetricPrefix.MILLI)
+ .readOnly()
+ .initialValue(0)
+ .commit(),
+ FLOAT_ELEMENT(expected)
+ .key("performance.rate")
+ .displayedName("Rate")
+ .description(
+ "Actual rate with which this device gets / processes / sends trains"
+ )
+ .unit(Unit.HERTZ)
+ .readOnly()
+ .initialValue(0)
+ .commit(),
+ FLOAT_ELEMENT(expected)
+ .key("performance.theoreticalRate")
+ .displayedName("Processing rate (hypothetical)")
+ .description(
+ "Rate with which this device could hypothetically process trains. "
+ "Based on lastProcessingDuration."
+ )
+ .unit(Unit.HERTZ)
+ .readOnly()
+ .initialValue(float("NaN"))
+ .warnLow(10)
+ .info("Processing not fast enough for full speed")
+ .needsAcknowledging(False)
+ .commit(),
+ )
# stuff from typical calPy that we don't use right now
# Included to avoid errors due to unexpected configuration from init device