parameters

class Hdf5Compression(*values)

gzip = 'gzip'

bitshuffle_with_zstd = 'bitshuffle_with_zstd'

none = None

class CustomBaseModel

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class OmParameters(*, parallelization_layer, data_retrieval_layer, processing_layer, source='', configuration_file=PosixPath('.'))

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• parallelization_layer (str)

• data_retrieval_layer (str)

• processing_layer (str)

• source (str)

• configuration_file (Path)

parallelization_layer: str

data_retrieval_layer: str

processing_layer: str

source: str

configuration_file: Path

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class DataSourceParameters(*, type, **extra_data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• type (str)

• extra_data (Any)

type: str

model_config: ClassVar[ConfigDict] = {'extra': 'allow'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class DataRetrievalLayerParameters(*, asapo_url=None, asapo_path=None, asapo_data_source=None, asapo_has_filesystem=None, asapo_token=None, asapo_group_id='default_om_group', buffer_size=None, psana_calibration_directory=None, data_sources, node_pool_size=0)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• asapo_url (str | None)

• asapo_path (str | None)

• asapo_data_source (str | None)

• asapo_has_filesystem (bool | None)

• asapo_token (str | None)

• asapo_group_id (str)

• buffer_size (int | None)

• psana_calibration_directory (str | None)

• data_sources (dict[str, DataSourceParameters])

• node_pool_size (int)

asapo_url: str | None

asapo_path: str | None

asapo_data_source: str | None

asapo_has_filesystem: bool | None

asapo_token: str | None

asapo_group_id: str

buffer_size: int | None

psana_calibration_directory: str | None

data_sources: dict[str, DataSourceParameters]

node_pool_size: int

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class Peakfinder8PeakDetectionParameters(*, max_num_peaks, adc_threshold, minimum_snr, min_pixel_count, max_pixel_count, local_bg_radius, min_res, max_res, fast_mode=False, num_pixel_per_bin_in_radial_statistics=100, bad_pixel_map_filename=None, bad_pixel_map_hdf5_path=None)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• max_num_peaks (int)

• adc_threshold (float)

• minimum_snr (float)

• min_pixel_count (int)

• max_pixel_count (int)

• local_bg_radius (int)

• min_res (int)

• max_res (int)

• fast_mode (bool)

• num_pixel_per_bin_in_radial_statistics (int)

• bad_pixel_map_filename (Path | None)

• bad_pixel_map_hdf5_path (str | None)

max_num_peaks: int

adc_threshold: float

minimum_snr: float

min_pixel_count: int

max_pixel_count: int

local_bg_radius: int

min_res: int

max_res: int

fast_mode: bool

num_pixel_per_bin_in_radial_statistics: int

bad_pixel_map_filename: Path | None

bad_pixel_map_hdf5_path: str | None

check_hd5_path()

Return type:

Self

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class BinningParameters(*, bin_size, min_good_pix_count=None, bad_pixel_value=None, bad_pixel_map_filename=None, bad_pixel_map_hdf5_path=None)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• bin_size (int)

• min_good_pix_count (int | None)

• bad_pixel_value (int | float | None)

• bad_pixel_map_filename (str | None)

• bad_pixel_map_hdf5_path (str | None)

bin_size: int

min_good_pix_count: int | None

bad_pixel_value: int | float | None

bad_pixel_map_filename: str | None

bad_pixel_map_hdf5_path: str | None

check_hd5_path()

Return type:

Self

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class XesParameters(*, intensity_threshold=None, rotation_in_degrees, geometry_file, data_broadcast_url=None, data_broadcast_interval, time_resolved=False, min_row_in_pix_for_integration, max_row_in_pix_for_integration, running_average_window_size, speed_report_interval, hit_frame_sending_interval=None, non_hit_frame_sending_interval=None)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• intensity_threshold (float | None)

• rotation_in_degrees (float)

• geometry_file (str)

• data_broadcast_url (str | None)

• data_broadcast_interval (int)

• time_resolved (bool)

• min_row_in_pix_for_integration (int)

• max_row_in_pix_for_integration (int)

• running_average_window_size (int)

• speed_report_interval (int)

• hit_frame_sending_interval (int | None)

• non_hit_frame_sending_interval (int | None)

intensity_threshold: float | None

rotation_in_degrees: float

geometry_file: str

data_broadcast_url: str | None

data_broadcast_interval: int

time_resolved: bool

min_row_in_pix_for_integration: int

max_row_in_pix_for_integration: int

running_average_window_size: int

speed_report_interval: int

hit_frame_sending_interval: int | None

non_hit_frame_sending_interval: int | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class RadialProfileParameters(*, speed_report_interval, data_broadcast_interval, hit_frame_sending_interval, non_hit_frame_sending_interval, data_broadcast_url=None, radius_bin_size, geometry_file, post_processing_binning=False, bad_pixel_map_filename=None, bad_pixel_map_hdf5_path=None, running_average_window_size, num_radials_to_send, num_hits_in_cum_radial_avg, total_intensity_jet_threshold=-1.0, background_subtraction=False, background_profile_filename='', background_profile_hdf5_path='', background_subtraction_min_fit_bin=-1, background_subtraction_max_fit_bin=-1, sample_detection=True, minimum_roi1_to_roi2_intensity_ratio_for_sample=-1.0, maximum_roi1_to_roi2_intensity_ratio_for_sample=-1.0, estimate_particle_size=False, size_estimation_method='guinier', roi1_qmin=-1.0, roi1_qmax=-1.0, roi2_qmin=-1.0, roi2_qmax=-1.0, guinier_qmin=-1.0, guinier_qmax=-1.0)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• speed_report_interval (int)

• data_broadcast_interval (int)

• hit_frame_sending_interval (int)

• non_hit_frame_sending_interval (int)

• data_broadcast_url (str | None)

• radius_bin_size (int)

• geometry_file (str)

• post_processing_binning (bool)

• bad_pixel_map_filename (str | None)

• bad_pixel_map_hdf5_path (str | None)

• running_average_window_size (int)

• num_radials_to_send (int)

• num_hits_in_cum_radial_avg (int)

• total_intensity_jet_threshold (float)

• background_subtraction (bool)

• background_profile_filename (str)

• background_profile_hdf5_path (str)

• background_subtraction_min_fit_bin (int)

• background_subtraction_max_fit_bin (int)

• sample_detection (bool)

• minimum_roi1_to_roi2_intensity_ratio_for_sample (float)

• maximum_roi1_to_roi2_intensity_ratio_for_sample (float)

• estimate_particle_size (bool)

• size_estimation_method (Literal['guinier', 'sphere', 'peak'])

• roi1_qmin (float)

• roi1_qmax (float)

• roi2_qmin (float)

• roi2_qmax (float)

• guinier_qmin (float)

• guinier_qmax (float)

speed_report_interval: int

data_broadcast_interval: int

hit_frame_sending_interval: int

non_hit_frame_sending_interval: int

data_broadcast_url: str | None

radius_bin_size: int

geometry_file: str

post_processing_binning: bool

bad_pixel_map_filename: str | None

bad_pixel_map_hdf5_path: str | None

running_average_window_size: int

num_radials_to_send: int

num_hits_in_cum_radial_avg: int

total_intensity_jet_threshold: float

background_subtraction: bool

background_profile_filename: str

background_profile_hdf5_path: str

background_subtraction_min_fit_bin: int

background_subtraction_max_fit_bin: int

sample_detection: bool

minimum_roi1_to_roi2_intensity_ratio_for_sample: float

maximum_roi1_to_roi2_intensity_ratio_for_sample: float

estimate_particle_size: bool

size_estimation_method: Literal['guinier', 'sphere', 'peak']

roi1_qmin: float

roi1_qmax: float

roi2_qmin: float

roi2_qmax: float

guinier_qmin: float

guinier_qmax: float

check_hd5_path()

Return type:

Self

check_background_subtraction()

Return type:

Self

check_sample_detection()

Return type:

Self

check_particle_size_estimation()

Return type:

Self

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class CheetahParameters(*, processed_directory, processed_filename_prefix='processed', processed_filename_extension='h5', hdf5_fields, hdf5_file_data_type=None, hdf5_file_compression=Hdf5Compression.none, hdf5_file_gzip_compression_level=4, hdf5_file_zstd_compression_level=3, hdf5_file_compression_shuffle=False, hdf5_file_max_num_peaks=1024, write_class_sums, class_sums_sending_interval=-1, class_sums_update_interval, class_sums_filename_prefix='sums', status_file_update_interval, responding_url=None, external_data_request_list_size=20)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• processed_directory (str)

• processed_filename_prefix (str)

• processed_filename_extension (str)

• hdf5_fields (dict[str, str])

• hdf5_file_data_type (str | None)

• hdf5_file_compression (Hdf5Compression)

• hdf5_file_gzip_compression_level (int)

• hdf5_file_zstd_compression_level (int)

• hdf5_file_compression_shuffle (bool)

• hdf5_file_max_num_peaks (int)

• write_class_sums (bool)

• class_sums_sending_interval (int)

• class_sums_update_interval (int)

• class_sums_filename_prefix (str)

• status_file_update_interval (int)

• responding_url (str | None)

• external_data_request_list_size (int)

processed_directory: str

processed_filename_prefix: str

processed_filename_extension: str

hdf5_fields: dict[str, str]

hdf5_file_data_type: str | None

hdf5_file_compression: Hdf5Compression

hdf5_file_gzip_compression_level: int

hdf5_file_zstd_compression_level: int

hdf5_file_compression_shuffle: bool

hdf5_file_max_num_peaks: int

write_class_sums: bool

class_sums_sending_interval: int

class_sums_update_interval: int

class_sums_filename_prefix: str

status_file_update_interval: int

responding_url: str | None

external_data_request_list_size: int

check_sums_update_interval()

Return type:

Self

classmethod check_status_file_update_interval(v)

Parameters:

v (int)

Return type:

int

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class CrystallographyParameters(*, peakfinding_algorithm='peakfinder8', min_num_peaks_for_hit, max_num_peaks_for_hit, peakogram_intensity_bin_size=100.0, peakogram_radius_bin_size=5.0, running_average_window_size, post_processing_binning=False, pump_probe_experiment=False, geometry_file, geometry_is_optimized=False, speed_report_interval, data_broadcast_url=None, responding_url=None, external_data_request_list_size=20, data_broadcast_interval, hit_frame_sending_interval=0, non_hit_frame_sending_interval=0)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• peakfinding_algorithm (str)

• min_num_peaks_for_hit (int)

• max_num_peaks_for_hit (int)

• peakogram_intensity_bin_size (float)

• peakogram_radius_bin_size (float)

• running_average_window_size (int)

• post_processing_binning (bool)

• pump_probe_experiment (bool)

• geometry_file (str)

• geometry_is_optimized (bool)

• speed_report_interval (int)

• data_broadcast_url (str | None)

• responding_url (str | None)

• external_data_request_list_size (int)

• data_broadcast_interval (int)

• hit_frame_sending_interval (int)

• non_hit_frame_sending_interval (int)

peakfinding_algorithm: str

min_num_peaks_for_hit: int

max_num_peaks_for_hit: int

peakogram_intensity_bin_size: float

peakogram_radius_bin_size: float

running_average_window_size: int

post_processing_binning: bool

pump_probe_experiment: bool

geometry_file: str

geometry_is_optimized: bool

speed_report_interval: int

data_broadcast_url: str | None

responding_url: str | None

external_data_request_list_size: int

data_broadcast_interval: int

hit_frame_sending_interval: int

non_hit_frame_sending_interval: int

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class MonitorParameters(*, om, data_retrieval_layer, peakfinder8_peak_detection=None, radial_profile=None, binning=None, crystallography=None, xes=None, cheetah=None)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• om (OmParameters)

• data_retrieval_layer (DataRetrievalLayerParameters)

• peakfinder8_peak_detection (Peakfinder8PeakDetectionParameters | None)

• radial_profile (RadialProfileParameters | None)

• binning (BinningParameters | None)

• crystallography (CrystallographyParameters | None)

• xes (XesParameters | None)

• cheetah (CheetahParameters | None)

om: OmParameters

data_retrieval_layer: DataRetrievalLayerParameters

peakfinder8_peak_detection: Peakfinder8PeakDetectionParameters | None

radial_profile: RadialProfileParameters | None

binning: BinningParameters | None

crystallography: CrystallographyParameters | None

xes: XesParameters | None

cheetah: CheetahParameters | None

check_peakfinder8_peak_detection_parameters()

Return type:

Self

check_binning_parameters()

Return type:

Self

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].