MeasurementStatistics¶
Properties¶
Name | Type | Description | Notes |
|---|---|---|---|
file_prefix | str | [optional] | |
run_number | int | Number of data collection run. This can be either automatically incremented or provided externally for each data collection. | [optional] |
experiment_group | str | Name of group owning the data (e.g. p-group or proposal number). | [optional] |
images_expected | int | [optional] | |
images_collected | int | Images collected by the receiver. This number will be lower than images expected if there were issues with data collection performance. | [optional] |
images_sent | int | Images sent to the writer. The value does not include images discarded by lossy compression filter and images not forwarded due to full ZeroMQ queue. | [optional] |
images_written | int | Images successfully written to disk. The value is live updated for TCP/IP socket and direct HDF5 writer, while for ZeroMQ it is only updated at the end of experiment. | [optional] |
images_discarded_lossy_compression | int | Images discarded by the lossy compression filter | [optional] |
max_image_number_sent | int | [optional] | |
collection_efficiency | float | [optional] | |
compression_ratio | float | [optional] | |
cancelled | bool | [optional] | |
max_receiver_delay | int | [optional] | |
indexing_rate | float | [optional] | |
detector_width | int | [optional] | |
detector_height | int | [optional] | |
detector_pixel_depth | int | [optional] | |
bkg_estimate | float | [optional] | |
unit_cell | str | [optional] | |
error_pixels | float | Moving average of 1000 images counting number of error pixels on the detector | [optional] |
saturated_pixels | float | Moving average of 1000 images counting number of saturated pixels on the detector | [optional] |
roi_beam_pixels | float | If there is an ROI defined with name "beam", this number will hold moving average of 1000 images for number of valid pixels within this ROI | [optional] |
roi_beam_sum | float | If there is an ROI defined with name "beam", this number will hold moving average of 1000 images for sum of valid pixels within this ROI | [optional] |
Example¶
from jfjoch_client.models.measurement_statistics import MeasurementStatistics
# TODO update the JSON string below
json = "{}"
# create an instance of MeasurementStatistics from a JSON string
measurement_statistics_instance = MeasurementStatistics.from_json(json)
# print the JSON string representation of the object
print(MeasurementStatistics.to_json())
# convert the object into a dict
measurement_statistics_dict = measurement_statistics_instance.to_dict()
# create an instance of MeasurementStatistics from a dict
measurement_statistics_from_dict = MeasurementStatistics.from_dict(measurement_statistics_dict)