CLI

The cli module implements a command line interface that allows to interact with Curveball through a command line or terminal, without any knowledge in Python programming.

The Tutorial includes a complete walkthrough on using the CLI to analyse growth cruves data.

Fit-and-compete

Use curveball fit_compete to estimate competition coefficients from mixed-culture data (requires a plate template that includes a total strain):

>>> curveball fit_compete mixed.xlsx --analyse_file=summary.csv --ref_strain=G --total=RG

This command reads the per-strain fits generated by curveball analyse but does not rerun individual competitions; instead it combines the reference and competitor parameter estimates, fits the predicted mixed OD curve to the observed total trace, and adjusts the competition coefficients to minimize the mean squared error.

The output CSV contains:

• a1, a2: competition coefficients from curveball.competitions.fit_and_compete()

• MSE: mean squared error of the mixed-culture fit

Because fit_compete never reconstructs the separate time series for the assay and reference strains, it cannot derive the LTEE-style relative fitness (w). That value is only available through curveball analyse, which fits each strain individually, runs curveball.competitions.compete(), and evaluates fitness_LTEE on the resulting time course.

Analyse output columns

The curveball analyse command outputs a CSV table with one row per strain. Key columns include:

• folder, filename: input file location and base name.

• strain: strain label from the plate template.

• model: best-fit model name.

• RSS, RMSD, NRMSD, CV(RMSD): fit error metrics.

• bic, aic, weighted_bic, weighted_aic: model selection scores.

• y0, K, r, nu, q0, v: fitted growth parameters.

• has_lag, has_nu: model selection flags.

• max_growth_rate, min_doubling_time, lag: derived metrics.

• w: relative fitness vs. reference strain.

If --ci is used, additional *_low/*_high columns are included for confidence intervals (e.g., lag_low, lag_high, K_low, K_high).

Members

curveball.scripts.cli.find_plate_file(plate_folder, plate_file)

Finds a plate file, either in the current working dir or in the package data resources.

Parameters

plate_filestr

the filename of the plate file, may include absolute or relative path

Returns

str

the full path of the plate file.

curveball.scripts.cli.get_filename(filepath)

Get a file name out of a file path.

Parameters

filepath : str

Returns

str

filename

curveball.scripts.cli.load_plate(plate_path)

Loads a plate template from a CSV file.

Parameters

plate_pathstr

full or relative path to the plate template file.

Returns

pandas.DataFrame

the plate template in tidy data format (see ioutils).

See also

find_plate_file

curveball.scripts.cli.where(ctx, param, value)

Prints the path where Curveball is installed and exits.

Parameters are generally ignored; if value or ctx.resilient_parsing are not empty/False/None, the function returns without doing anything.