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EXtra-proposal¤

These are the development docs for extra-proposal. You probably want to check out the official documentation in the EXtra docs instead.

extra_proposal.Proposal ¤

Proposal(proposal: int | str, user_id: Optional[str] = None, user_secret: Optional[str] = None, user_email: Optional[str] = None, timeout=10)

Proposal object. It can be instantiated as Proposal(2112) or Proposal("p002112")

Parameters:

Name Type Description Default
proposal int | str

Proposal number.

 required
user_id Optional[str]

UID (can be generated at https://in.xfel.eu/metadata/oauth/applications). Defaults to None.

 None
user_secret Optional[str]

Secret (can be generated at https://in.xfel.eu/metadata/oauth/applications). Defaults to None.

 None
user_email Optional[str]

User's email. Defaults to None.

 None

Raises:

Type Description
ProposalNotFoundError

The proposal does not exist.

instrument property ¤

instrument: str

The instrument this proposal belongs to (e.g. "SPB", "MID").

damnit ¤

damnit()

Access DAMNIT results from this proposal.

Returns:

Type Description
Damnit

A Damnit object for this proposal.

Raises:

Type Description
FileNotFoundError

If no DAMNIT database exists for this proposal.

title ¤

title() -> str

Get the proposal title from myMdC

runs ¤

runs() -> list[int]

Get the sorted list of runs available in RAW.

run_techniques ¤

run_techniques(run: int) -> list[dict]

Get the techniques associated with a run from myMdC.

Parameters:

Name Type Description Default
run int

The run number.

 required

Returns:

Type Description
list[dict]

A list of technique dictionaries with 'identifier' and 'name' keys.

run_sample_name ¤

run_sample_name(run: int) -> str

Get the sample name for a run from myMdC.

Parameters:

Name Type Description Default
run int

The run number.

 required

Returns:

Type Description
str

The sample name.

run_type ¤

run_type(run: int) -> str

Get the run type for a run from myMdC.

Parameters:

Name Type Description Default
run int

The run number.

 required

Returns:

Type Description
str

The run type (e.g. "Sample", "Dark", "Calibration").

samples_table ¤

samples_table()

Get a table of samples and their associated runs from myMdC.

Returns:

Type Description
DataFrame

A DataFrame with columns 'name', 'id', 'url', 'description', and 'runs'.

info ¤

info()

Print summary information about this proposal.

search_source ¤

search_source(pattern: str, run: int | list[int] | None = None) -> dict[int, list[str]]

Search for data sources and aliases matching a glob pattern.

Performs a case-insensitive search across all data sources and aliases in the specified run(s).

Parameters:

Name Type Description Default
pattern str

A glob-style pattern (e.g. *xgm* or *agipd*).

 required
run int | list[int] | None

A run number, list of run numbers, or None to search all runs.

 None

Returns:

Type Description
dict[int, list[str]]

A dictionary mapping run numbers to lists of matching source names and aliases.

Raises:

Type Description
TypeError

If run is not an int, list of ints, or None.

Example: 

proposal = Proposal(1234)
proposal.search_source("*xgm*", run=[43, 44, 45, 46])

extra_proposal.proposal.RunReference ¤

RunReference(proposal: Proposal, run_num: int)

A reference to a specific run within a proposal.

Provides access to run data, metadata, and DAMNIT results. Typically obtained by indexing a Proposal object.

Example: 

prop = Proposal(1234)
run = prop[42]  # Returns a RunReference
data = run.data()  # Open DAQ data with extra_data

data ¤

data(**kwargs)

Open the data of this run with extra_data.

Parameters:

Name Type Description Default
**kwargs

Additional arguments passed to open_run().

 {}

Returns:

Type Description
DataCollection

A DataCollection for this run.

damnit ¤

damnit()

Access DAMNIT results from this run.

Returns:

Type Description
RunVariables

A RunVariables object for this run.

sample_name ¤

sample_name() -> str

Get the sample name from myMdC for this run.

Returns:

Type Description
str

The sample name.

run_type ¤

run_type() -> str

Get the run type from myMdC for this run.

Returns:

Type Description
str

The run type (e.g. "Sample", "Dark", "Calibration").

techniques ¤

techniques() -> list[dict]

Get the run techniques from myMdC for this run.

Returns:

Type Description
list[dict]

A list of technique dictionaries with 'identifier' and 'name' keys.

plot_timeline ¤

plot_timeline()

Plot a timeline of when this run was taken, migrated, and calibrated.

Returns:

Type Description
Axes

A matplotlib.axes.Axes object.