Model Predictions#
Commands to compute prior and posterior state distributions from model samples.
This can in turn speed up the computation of risks and prevalences.
- pydantic settings lyscripts.compute.ComputeCLI[source]#
Compute priors, posteriors, risks, prevalences and model evidence from model samples.
Show JSON schema
{ "title": "ComputeCLI", "description": "Compute priors, posteriors, risks, prevalences and model evidence from model samples.", "type": "object", "properties": { "priors": { "anyOf": [ { "$ref": "#/$defs/PriorsCLI" }, { "type": "null" } ] }, "posteriors": { "anyOf": [ { "$ref": "#/$defs/PosteriorsCLI" }, { "type": "null" } ] }, "risks": { "anyOf": [ { "$ref": "#/$defs/RisksCLI" }, { "type": "null" } ] }, "prevalences": { "anyOf": [ { "$ref": "#/$defs/PrevalencesCLI" }, { "type": "null" } ] }, "evidence": { "anyOf": [ { "$ref": "#/$defs/EvidenceCLI" }, { "type": "null" } ] } }, "$defs": { "DataConfig": { "description": "Where to load lymphatic progression data from and how to feed it into a model.", "properties": { "source": { "anyOf": [ { "format": "file-path", "type": "string" }, { "$ref": "#/$defs/LyDataset" } ], "description": "Either a path to a CSV file or a config that specifies how and where to fetch the data from.", "title": "Source" }, "side": { "anyOf": [ { "enum": [ "ipsi", "contra" ], "type": "string" }, { "type": "null" } ], "default": null, "description": "Side of the neck to load data for. Only for Unilateral models.", "title": "Side" }, "mapping": { "additionalProperties": { "anyOf": [ { "type": "integer" }, { "type": "string" } ] }, "description": "Optional mapping of numeric T-stages to model T-stages.", "title": "Mapping", "type": "object" } }, "required": [ "source" ], "title": "DataConfig", "type": "object" }, "DiagnosisConfig": { "description": "Defines an ipsi- and contralateral diagnosis pattern.", "properties": { "ipsi": { "additionalProperties": { "additionalProperties": { "anyOf": [ { "enum": [ false, 0, "healthy", true, 1, "involved", "micro", "macro", "notmacro" ] }, { "type": "null" } ] }, "type": "object" }, "default": {}, "description": "Observed diagnoses by different modalities on the ipsi neck.", "examples": [ { "CT": { "II": true, "III": false } } ], "title": "Ipsi", "type": "object" }, "contra": { "additionalProperties": { "additionalProperties": { "anyOf": [ { "enum": [ false, 0, "healthy", true, 1, "involved", "micro", "macro", "notmacro" ] }, { "type": "null" } ] }, "type": "object" }, "default": {}, "description": "Observed diagnoses by different modalities on the contra neck.", "title": "Contra", "type": "object" } }, "title": "DiagnosisConfig", "type": "object" }, "DistributionConfig": { "description": "Configuration defining a distribution over diagnose times.", "properties": { "kind": { "default": "frozen", "description": "Parametric distributions may be updated.", "enum": [ "frozen", "parametric" ], "title": "Kind", "type": "string" }, "func": { "const": "binomial", "default": "binomial", "description": "Name of predefined function to use as distribution.", "title": "Func", "type": "string" }, "params": { "additionalProperties": { "anyOf": [ { "type": "integer" }, { "type": "number" } ] }, "default": {}, "description": "Parameters to pass to the predefined function.", "title": "Params", "type": "object" } }, "title": "DistributionConfig", "type": "object" }, "EvidenceCLI": { "description": "Compute model evidence from thermodynamic integration samples.", "properties": { "configs": { "default": [ "config.yaml" ], "description": "Path to the YAML file(s) that contain the configuration(s). Configs from YAML files may be overwritten by command line arguments. When multiple files are specified, the configs are merged in the order they are given. Note that every config file must have a `version: 1` key in it.", "items": { "format": "path", "type": "string" }, "title": "Configs", "type": "array" }, "data": { "$ref": "#/$defs/DataConfig" }, "sampling": { "$ref": "#/$defs/SamplingConfig" }, "schedule": { "$ref": "#/$defs/ScheduleConfig", "description": "Configuration for generating inverse temperature schedule." }, "plots": { "default": "./plots", "description": "Directory for storing plots.", "format": "path", "title": "Plots", "type": "string" }, "metrics": { "default": "./metrics.json", "description": "Path to metrics file.", "format": "path", "title": "Metrics", "type": "string" } }, "required": [ "data", "sampling", "schedule" ], "title": "EvidenceCLI", "type": "object" }, "GraphConfig": { "description": "Specifies how the tumor(s) and LNLs are connected in a DAG.", "properties": { "tumor": { "additionalProperties": { "items": { "type": "string" }, "type": "array" }, "description": "Define the name of the tumor(s) and which LNLs it/they drain to.", "title": "Tumor", "type": "object" }, "lnl": { "additionalProperties": { "items": { "type": "string" }, "type": "array" }, "description": "Define the name of the LNL(s) and which LNLs it/they drain to.", "title": "Lnl", "type": "object" } }, "required": [ "tumor", "lnl" ], "title": "GraphConfig", "type": "object" }, "HDF5FileStorage": { "description": "HDF5 file storage for in- and outputs of computations.", "properties": { "file": { "description": "Path to the HDF5 file. Parent directories are created if needed.", "format": "path", "title": "File", "type": "string" }, "dataset": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name of the dataset in the HDF5 file. Save/load methods can override this.", "title": "Dataset" } }, "required": [ "file" ], "title": "HDF5FileStorage", "type": "object" }, "InvolvementConfig": { "description": "Config that defines an ipsi- and contralateral involvement pattern.", "properties": { "ipsi": { "additionalProperties": { "anyOf": [ { "enum": [ false, 0, "healthy", true, 1, "involved", "micro", "macro", "notmacro" ] }, { "type": "null" } ] }, "default": {}, "description": "Involvement pattern for the ipsilateral side of the neck.", "examples": [ { "II": true, "III": false } ], "title": "Ipsi", "type": "object" }, "contra": { "additionalProperties": { "anyOf": [ { "enum": [ false, 0, "healthy", true, 1, "involved", "micro", "macro", "notmacro" ] }, { "type": "null" } ] }, "default": {}, "description": "Involvement pattern for the contralateral side of the neck.", "title": "Contra", "type": "object" } }, "title": "InvolvementConfig", "type": "object" }, "LyDataset": { "description": "Specification of a dataset.", "properties": { "year": { "description": "Release year of dataset.", "exclusiveMinimum": 0, "maximum": 2026, "title": "Year", "type": "integer" }, "institution": { "description": "Institution's short code. E.g., University Hospital Zurich: `usz`.", "minLength": 1, "title": "Institution", "type": "string" }, "subsite": { "description": "Tumor subsite(s) patients in this dataset were diagnosed with.", "minLength": 1, "title": "Subsite", "type": "string" }, "repo_name": { "anyOf": [ { "minLength": 1, "type": "string" }, { "type": "null" } ], "default": "lycosystem/lydata", "description": "GitHub `repository/owner`.", "title": "Repo Name" }, "ref": { "anyOf": [ { "minLength": 1, "type": "string" }, { "type": "null" } ], "default": "main", "description": "Branch/tag/commit of the repo.", "title": "Ref" }, "local_dataset_dir": { "anyOf": [ { "format": "directory-path", "type": "string" }, { "type": "null" } ], "default": null, "description": "Path to directory containing all the dataset subdirectories. So, e.g. if `path_on_disk` is `~/datasets` and the dataset is `2023-clb-multisite`, then the CSV file is expected to be at `~/datasets/2023-clb-multisite/data.csv`.", "title": "Local Dataset Dir" } }, "required": [ "year", "institution", "subsite" ], "title": "LyDataset", "type": "object" }, "ModalityConfig": { "description": "Define a diagnostic or pathological modality.", "properties": { "spec": { "description": "Specificity of the modality.", "maximum": 1.0, "minimum": 0.5, "title": "Spec", "type": "number" }, "sens": { "description": "Sensitivity of the modality.", "maximum": 1.0, "minimum": 0.5, "title": "Sens", "type": "number" }, "kind": { "default": "clinical", "description": "Clinical modalities cannot detect microscopic disease.", "enum": [ "clinical", "pathological" ], "title": "Kind", "type": "string" } }, "required": [ "spec", "sens" ], "title": "ModalityConfig", "type": "object" }, "ModelConfig": { "description": "Define which of the ``lymph`` models to use and how to set them up.", "properties": { "external_file": { "anyOf": [ { "format": "file-path", "type": "string" }, { "type": "null" } ], "default": null, "description": "Path to a Python file that defines a model.", "title": "External File" }, "class_name": { "default": "Unilateral", "description": "Name of the model class to use.", "enum": [ "Unilateral", "Bilateral", "Midline" ], "title": "Class Name", "type": "string" }, "constructor": { "default": "binary", "description": "Trinary models differentiate btw. micro- and macroscopic disease.", "enum": [ "binary", "trinary" ], "title": "Constructor", "type": "string" }, "max_time": { "default": 10, "description": "Max. number of time-steps to evolve the model over.", "title": "Max Time", "type": "integer" }, "named_params": { "default": null, "description": "Subset of valid model parameters a sampler may provide in the form of a dictionary to the model instead of as an array. Or, after sampling, with this list, one may safely recover which parameter corresponds to which index in the sample.", "items": { "type": "string" }, "title": "Named Params", "type": "array" }, "kwargs": { "additionalProperties": true, "default": {}, "description": "Additional keyword arguments to pass to the model constructor.", "title": "Kwargs", "type": "object" } }, "title": "ModelConfig", "type": "object" }, "PosteriorsCLI": { "description": "Compute posterior state distributions for different diagnosis scenarios.", "properties": { "configs": { "default": [ "config.yaml" ], "description": "Path to the YAML file(s) that contain the configuration(s). Configs from YAML files may be overwritten by command line arguments. When multiple files are specified, the configs are merged in the order they are given. Note that every config file must have a `version: 1` key in it.", "items": { "format": "path", "type": "string" }, "title": "Configs", "type": "array" }, "graph": { "$ref": "#/$defs/GraphConfig" }, "model": { "$ref": "#/$defs/ModelConfig", "default": { "external_file": null, "class_name": "Unilateral", "constructor": "binary", "max_time": 10, "named_params": null, "kwargs": {} } }, "distributions": { "additionalProperties": { "$ref": "#/$defs/DistributionConfig" }, "default": {}, "description": "Mapping of model T-categories to predefined distributions over diagnose times.", "title": "Distributions", "type": "object" }, "cache_dir": { "default": "/home/docs/checkouts/readthedocs.org/user_builds/lyscripts/checkouts/latest/docs/source/.cache", "description": "Cache directory for storing function calls.", "format": "path", "title": "Cache Dir", "type": "string" }, "scenarios": { "default": [], "description": "List of scenarios to compute risks for.", "items": { "$ref": "#/$defs/ScenarioConfig" }, "title": "Scenarios", "type": "array" }, "sampling": { "$ref": "#/$defs/SamplingConfig" }, "modalities": { "additionalProperties": { "$ref": "#/$defs/ModalityConfig" }, "default": {}, "description": "Maps names of diagnostic modalities to their specificity/sensitivity.", "title": "Modalities", "type": "object" }, "posteriors": { "$ref": "#/$defs/HDF5FileStorage", "description": "Storage for the computed posteriors." } }, "required": [ "graph", "sampling", "posteriors" ], "title": "PosteriorsCLI", "type": "object" }, "PrevalencesCLI": { "description": "Predict the prevalence of an involvement pattern from model samples.", "properties": { "configs": { "default": [ "config.yaml" ], "description": "Path to the YAML file(s) that contain the configuration(s). Configs from YAML files may be overwritten by command line arguments. When multiple files are specified, the configs are merged in the order they are given. Note that every config file must have a `version: 1` key in it.", "items": { "format": "path", "type": "string" }, "title": "Configs", "type": "array" }, "graph": { "$ref": "#/$defs/GraphConfig" }, "model": { "$ref": "#/$defs/ModelConfig", "default": { "external_file": null, "class_name": "Unilateral", "constructor": "binary", "max_time": 10, "named_params": null, "kwargs": {} } }, "distributions": { "additionalProperties": { "$ref": "#/$defs/DistributionConfig" }, "default": {}, "description": "Mapping of model T-categories to predefined distributions over diagnose times.", "title": "Distributions", "type": "object" }, "cache_dir": { "default": "/home/docs/checkouts/readthedocs.org/user_builds/lyscripts/checkouts/latest/docs/source/.cache", "description": "Cache directory for storing function calls.", "format": "path", "title": "Cache Dir", "type": "string" }, "scenarios": { "default": [], "description": "List of scenarios to compute risks for.", "items": { "$ref": "#/$defs/ScenarioConfig" }, "title": "Scenarios", "type": "array" }, "sampling": { "$ref": "#/$defs/SamplingConfig" }, "modalities": { "additionalProperties": { "$ref": "#/$defs/ModalityConfig" }, "default": {}, "description": "Maps names of diagnostic modalities to their specificity/sensitivity.", "title": "Modalities", "type": "object" }, "prevalences": { "$ref": "#/$defs/HDF5FileStorage", "description": "Storage for the computed prevalences." }, "data": { "$ref": "#/$defs/DataConfig" } }, "required": [ "graph", "sampling", "prevalences", "data" ], "title": "PrevalencesCLI", "type": "object" }, "PriorsCLI": { "description": "Compute the prior state distributions from MCMC samples.", "properties": { "configs": { "default": [ "config.yaml" ], "description": "Path to the YAML file(s) that contain the configuration(s). Configs from YAML files may be overwritten by command line arguments. When multiple files are specified, the configs are merged in the order they are given. Note that every config file must have a `version: 1` key in it.", "items": { "format": "path", "type": "string" }, "title": "Configs", "type": "array" }, "graph": { "$ref": "#/$defs/GraphConfig" }, "model": { "$ref": "#/$defs/ModelConfig", "default": { "external_file": null, "class_name": "Unilateral", "constructor": "binary", "max_time": 10, "named_params": null, "kwargs": {} } }, "distributions": { "additionalProperties": { "$ref": "#/$defs/DistributionConfig" }, "default": {}, "description": "Mapping of model T-categories to predefined distributions over diagnose times.", "title": "Distributions", "type": "object" }, "cache_dir": { "default": "/home/docs/checkouts/readthedocs.org/user_builds/lyscripts/checkouts/latest/docs/source/.cache", "description": "Cache directory for storing function calls.", "format": "path", "title": "Cache Dir", "type": "string" }, "scenarios": { "default": [], "description": "List of scenarios to compute risks for.", "items": { "$ref": "#/$defs/ScenarioConfig" }, "title": "Scenarios", "type": "array" }, "sampling": { "$ref": "#/$defs/SamplingConfig" }, "priors": { "$ref": "#/$defs/HDF5FileStorage", "description": "Storage for the computed priors." } }, "required": [ "graph", "sampling", "priors" ], "title": "PriorsCLI", "type": "object" }, "RisksCLI": { "description": "Predict the risk of involvement scenarios from model samples given diagnoses.", "properties": { "configs": { "default": [ "config.yaml" ], "description": "Path to the YAML file(s) that contain the configuration(s). Configs from YAML files may be overwritten by command line arguments. When multiple files are specified, the configs are merged in the order they are given. Note that every config file must have a `version: 1` key in it.", "items": { "format": "path", "type": "string" }, "title": "Configs", "type": "array" }, "graph": { "$ref": "#/$defs/GraphConfig" }, "model": { "$ref": "#/$defs/ModelConfig", "default": { "external_file": null, "class_name": "Unilateral", "constructor": "binary", "max_time": 10, "named_params": null, "kwargs": {} } }, "distributions": { "additionalProperties": { "$ref": "#/$defs/DistributionConfig" }, "default": {}, "description": "Mapping of model T-categories to predefined distributions over diagnose times.", "title": "Distributions", "type": "object" }, "cache_dir": { "default": "/home/docs/checkouts/readthedocs.org/user_builds/lyscripts/checkouts/latest/docs/source/.cache", "description": "Cache directory for storing function calls.", "format": "path", "title": "Cache Dir", "type": "string" }, "scenarios": { "default": [], "description": "List of scenarios to compute risks for.", "items": { "$ref": "#/$defs/ScenarioConfig" }, "title": "Scenarios", "type": "array" }, "sampling": { "$ref": "#/$defs/SamplingConfig" }, "modalities": { "additionalProperties": { "$ref": "#/$defs/ModalityConfig" }, "default": {}, "description": "Maps names of diagnostic modalities to their specificity/sensitivity.", "title": "Modalities", "type": "object" }, "risks": { "$ref": "#/$defs/HDF5FileStorage", "description": "Storage for the computed risks." } }, "required": [ "graph", "sampling", "risks" ], "title": "RisksCLI", "type": "object" }, "SamplingConfig": { "description": "Settings to configure the MCMC sampling.", "properties": { "storage_file": { "description": "Path to HDF5 file store results or load last state.", "format": "path", "title": "Storage File", "type": "string" }, "history_file": { "anyOf": [ { "format": "path", "type": "string" }, { "type": "null" } ], "default": null, "description": "Path to store the burn-in metrics (as CSV file).", "title": "History File" }, "dataset": { "default": "mcmc", "description": "Name of the dataset in the HDF5 file.", "title": "Dataset", "type": "string" }, "cores": { "anyOf": [ { "exclusiveMinimum": 0, "type": "integer" }, { "type": "null" } ], "default": 2, "description": "Number of cores to use for parallel sampling. If `None`, no parallel processing is used.", "title": "Cores" }, "seed": { "default": 42, "description": "Seed for the random number generator.", "title": "Seed", "type": "integer" }, "walkers_per_dim": { "default": 20, "description": "Number of walkers per parameter space dimension.", "title": "Walkers Per Dim", "type": "integer" }, "check_interval": { "default": 50, "description": "Check for convergence each time after this many steps.", "title": "Check Interval", "type": "integer" }, "trust_factor": { "default": 50.0, "description": "Trust the autocorrelation time only when it's smaller than this factor times the length of the chain.", "title": "Trust Factor", "type": "number" }, "relative_thresh": { "default": 0.05, "description": "Relative threshold for convergence.", "title": "Relative Thresh", "type": "number" }, "burnin_steps": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": null, "description": "Number of burn-in steps to take. If None, burn-in runs until convergence.", "title": "Burnin Steps" }, "num_steps": { "anyOf": [ { "type": "integer" }, { "type": "null" } ], "default": 100, "description": "Number of steps to take in the MCMC sampling.", "title": "Num Steps" }, "thin_by": { "default": 10, "description": "How many samples to draw before for saving one.", "title": "Thin By", "type": "integer" }, "inverse_temp": { "default": 1.0, "description": "Inverse temperature for thermodynamic integration. Note that this is not yet fully implemented.", "title": "Inverse Temp", "type": "number" } }, "required": [ "storage_file" ], "title": "SamplingConfig", "type": "object" }, "ScenarioConfig": { "description": "Define a scenario for which e.g. prevalences and risks may be computed.", "properties": { "t_stages": { "description": "List of T-stages to marginalize over in the scenario.", "examples": [ [ "early" ], [ 3, 4 ] ], "items": { "anyOf": [ { "type": "integer" }, { "type": "string" } ] }, "title": "T Stages", "type": "array" }, "t_stages_dist": { "default": [ 1.0 ], "description": "Distribution over T-stages to use for marginalization.", "examples": [ [ 1.0 ], [ 0.6, 0.4 ] ], "items": { "type": "number" }, "title": "T Stages Dist", "type": "array" }, "midext": { "anyOf": [ { "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Whether the patient's tumor extends over the midline.", "title": "Midext" }, "mode": { "default": "HMM", "description": "Which underlying model architecture to use.", "enum": [ "HMM", "BN" ], "title": "Mode", "type": "string" }, "involvement": { "$ref": "#/$defs/InvolvementConfig", "default": { "ipsi": {}, "contra": {} } }, "diagnosis": { "$ref": "#/$defs/DiagnosisConfig", "default": { "ipsi": {}, "contra": {} } } }, "required": [ "t_stages" ], "title": "ScenarioConfig", "type": "object" }, "ScheduleConfig": { "description": "Configuration for generating a schedule of inverse temperatures.", "properties": { "method": { "default": "power", "description": "Method to generate the inverse temperature schedule.", "enum": [ "geometric", "linear", "power" ], "title": "Method", "type": "string" }, "num": { "default": 32, "description": "Number of inverse temperatures in the schedule.", "title": "Num", "type": "integer" }, "power": { "default": 4.0, "description": "If a power schedule is chosen, use this as power.", "title": "Power", "type": "number" }, "values": { "anyOf": [ { "items": { "type": "number" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "List of inverse temperatures to use instead of generating a schedule. If a list is provided, the other parameters are ignored.", "title": "Values" } }, "title": "ScheduleConfig", "type": "object" } }, "additionalProperties": false, "required": [ "priors", "posteriors", "risks", "prevalences", "evidence" ] }
- field posteriors: Annotated[PosteriorsCLI | None, _CliSubCommand] [Required]#
- field prevalences: Annotated[PrevalencesCLI | None, _CliSubCommand] [Required]#
Command Help#
Usage: lyscripts compute [-h]
{priors,posteriors,risks,prevalences,evidence} ...
Compute priors, posteriors, risks, prevalences and model evidence from model
samples.
Options:
-h, --help show this help message and exit
Subcommands:
{priors,posteriors,risks,prevalences,evidence}
priors Compute the prior state distributions from MCMC
samples.
posteriors Compute posterior state distributions for different
diagnosis scenarios.
risks Predict the risk of involvement scenarios from model
samples given diagnoses.
prevalences Predict the prevalence of an involvement pattern from
model samples.
evidence Compute model evidence from thermodynamic integration
samples.