ConvergenceLogger

class esis.optics.ConvergenceLogger(directory, offset_energy=1000.0)

Bases: Printable

A callback which logs the convergence of an optimization to disk.

Intended for scipy.optimize.differential_evolution(). On every iteration, the best objective value and the standard deviation of the population energies are appended to a CSV file, the best parameter vector is appended to a text log, and a convergence plot is saved, so that long-running fits can be monitored and post-mortemed.

Attributes

offset_energy	An offset added to the objective values before plotting on a logarithmic scale, chosen to keep the (typically negative) correlation objective of DistortionObjective positive.
path_data	The path of the CSV file containing the convergence history.
path_log	The path of the text file mirroring the console output.
path_plot	The path of the convergence plot.
directory	The directory where the log files are saved.

Methods

__init__(directory[, offset_energy])
log(message)	Print a message to the console and append it to path_log.
save_plot()	Save a plot of the convergence history to path_plot.
to_string([prefix])	Public-facing version of the __repr__ method that allows for defining a prefix string, which can be used to calculate how much whitespace to add to the beginning of each line of the result.

Inheritance Diagram

Parameters:

• directory (Path)

• offset_energy (float)

log(message)

Print a message to the console and append it to path_log.

Parameters:

message (str) – The message to log.

Return type:

None

save_plot()

Save a plot of the convergence history to path_plot.

Return type:

None

to_string(prefix=None)

Public-facing version of the __repr__ method that allows for defining a prefix string, which can be used to calculate how much whitespace to add to the beginning of each line of the result.

Parameters:

prefix (None | str) – an optional string, the length of which is used to calculate how much whitespace to add to the result.

Return type:

str

directory: Path

The directory where the log files are saved.

offset_energy: float = 1000.0

An offset added to the objective values before plotting on a logarithmic scale, chosen to keep the (typically negative) correlation objective of DistortionObjective positive.

property path_data: Path

The path of the CSV file containing the convergence history.

property path_log: Path

The path of the text file mirroring the console output.

property path_plot: Path

The path of the convergence plot.