Reference

YAML configuration parsing

A plotIt YAML configuration file should have the following structure:

configuration:
  # Configuration block
files:
  file_name:
    # File block
  ...
groups: # optional
  group_name:
    # Group block
  ...
plots:
  plot_name:
    # Plot block
  ...
systematics: # optional
  # just name (for shape) or name with systematic block
  ...
legend: # optional
  # legend block

Such YAML files can be parsed with the loadFromYAML() method. It will return instances of the classes defined in the plotit.config module, whose attribute listings below serve as a reference of the allowed attributes in each block, and their types.

plotit.loadFromYAML(histodir=None, eras=None)

Parse a plotIt YAML file. The returned objects are stateless, except for the list of samples, which consists of stateful Group or ungrouped File instances that carry a TFile pointer.

Parameters:

yamlFileName (str) – config file path
histodir (str | None) – base path for finding histograms (to be combined with 'root' in configuration and the sample file names; yamlFileName directory by default)
eras (None | str | List[str]) – selected era, or list of selected eras (default: all that are present)

Return type:

Tuple[Configuration, List[File | Group], List[Plot], List[SystVar], Legend]

The plotit.config module contains classes that represent parts of the YAML configuration file, and helper methods for parsing the different blocks. Configuration, File, Group, Configuration, Label, Legend, Plot, Point, and Position are the “stateless” classes mentioned here.

class plotit.config.Configuration(width=800, height=800, margin_left=0.17, margin_right=0.03, margin_top=0.05, margin_bottom=0.13, eras=<factory>, luminosity=<factory>, scale=1.0, no_lumi_rescaling=False, luminosity_error=0.0, y_axis_format='%1% / %2$.2f', ratio_y_axis_title='Data / MC', ratio_style='P0', error_fill_color=42, error_fill_style=3154, fit_n_points=1000, fit_line_color=46, fit_line_width=1, fit_line_style=1, fit_error_fill_color=42, fit_error_fill_style=1001, ratio_fit_n_points=1000, ratio_fit_line_color=46, ratio_fit_line_width=1, ratio_fit_line_style=1, ratio_fit_error_fill_color=42, ratio_fit_error_fill_style=1001, experiment='CMS', extra_label='', luminosity_label='', root='.', transparent_background=False, show_overflow=False, errors_type='Poisson', x_axis_label_size=18, y_axis_label_size=18, x_axis_top_ticks=True, y_axis_right_ticks=True, blinded_range_fill_color=42, blinded_range_fill_style=1001, yields_table_stretch=1.15, yields_table_align='h', yields_table_text_align='c', yields_table_numerical_precision_yields=1, yields_table_numerical_precision_ratio=2)

blinded_range_fill_color: int = 42

blinded_range_fill_style: int = 1001

eras: List[str]

error_fill_color: int = 42

error_fill_style: int = 3154

errors_type: str = 'Poisson'

experiment: str = 'CMS'

extra_label: str = ''

fit_error_fill_color: int = 42

fit_error_fill_style: int = 1001

fit_line_color: int = 46

fit_line_style: int = 1

fit_line_width: int = 1

fit_n_points: int = 1000

getLumi(eras=None)

Return type:: float

height: int = 800

luminosity: Dict[str, float]

luminosity_error: float = 0.0

luminosity_label: str = ''

margin_bottom: float = 0.13

margin_left: float = 0.17

margin_right: float = 0.03

margin_top: float = 0.05

no_lumi_rescaling: bool = False

ratio_fit_error_fill_color: int = 42

ratio_fit_error_fill_style: int = 1001

ratio_fit_line_color: int = 46

ratio_fit_line_style: int = 1

ratio_fit_line_width: int = 1

ratio_fit_n_points: int = 1000

ratio_style: str = 'P0'

ratio_y_axis_title: str = 'Data / MC'

root: str = '.'

scale: float = 1.0

show_overflow: bool = False

transparent_background: bool = False

width: int = 800

x_axis_label_size: int = 18

x_axis_top_ticks: bool = True

y_axis_format: str = '%1% / %2$.2f'

y_axis_label_size: int = 18

y_axis_right_ticks: bool = True

yields_table_align: str = 'h'

yields_table_numerical_precision_ratio: int = 2

yields_table_numerical_precision_yields: int = 1

yields_table_stretch: float = 1.15

yields_table_text_align: str = 'c'

class plotit.config.File(type, name, order=None, legend='', legend_style=None, legend_order=0, drawing_options='', marker_size=None, marker_color=None, marker_type=None, fill_color=None, fill_type=None, line_width=None, line_color=None, line_type=None, era=None, group=None, cross_section=1.0, branching_ratio=1.0, generated_events=1.0, scale=1.0, pretty_name=None, yields_title=None, yields_group=None, legend_group=None)

Configuration for a single sample

branching_ratio: float = 1.0

cross_section: float = 1.0

era: str | None = None

generated_events: float = 1.0

group: str | None = None

legend_group: str | None = None

pretty_name: str | None = None

scale: float = 1.0

yields_group: str | None = None

yields_title: str | None = None

class plotit.config.Group(type, name, order=None, legend='', legend_style=None, legend_order=0, drawing_options='', marker_size=None, marker_color=None, marker_type=None, fill_color=None, fill_type=None, line_width=None, line_color=None, line_type=None, files=<factory>)

files: List[File]

class plotit.config.Label(text, position, size=18)

position: Point

size: int = 18

text: str

class plotit.config.Legend(position=<factory>, columns=1, entries=<factory>)

class Entry(label, type='MC', order=0)

label: str

order: int = 0

type: str = 'MC'

columns: int = 1

entries: List[Entry]

position: Position

class plotit.config.Plot(name, x_axis='', x_axis_format='', y_axis='', y_axis_format=None, normalized=False, no_data=False, override=False, log_y=False, log_x=False, save_extensions=<factory>, book_keeping_folder='', show_ratio=False, fit=False, fit_ratio=False, fit_function='', fit_legend='', fit_legend_position=None, fit_range=None, ratio_fit_function='', ratio_fit_legend='', ratio_fit_legend_position=None, ratio_fit_range=None, show_errors=True, x_axis_range=None, y_axis_range=None, log_y_axis_range=None, ratio_y_axis_range=None, blinded_range=None, y_axis_show_zero=False, inherits_from=None, rebin=1, labels=<factory>, extra_label=None, legend_position=None, legend_columns=1, show_overflow=False, errors_type='Poisson', binning_x=None, binning_y=None, draw_string=None, selection_string=None, for_yields=True, yields_title=True, yields_table_order=True, sort_by_yields=False, vertical_lines=<factory>, horizontal_lines=<factory>, lines=<factory>)

binning_x: str | None = None

binning_y: str | None = None

blinded_range: List[float] | None = None

book_keeping_folder: str = ''

draw_string: str | None = None

errors_type: str = 'Poisson'

exclude = ''

extra_label: str | None = None

fit: bool = False

fit_function: str = ''

fit_legend: str = ''

fit_legend_position: Position | None = None

fit_range: List[float] | None = None

fit_ratio: bool = False

for_yields: bool = True

horizontal_lines: List[float]

inherits_from: str | None = None

labels: List[Label]

legend_columns: int = 1

legend_position: Position | None = None

lines: List[str]

log_x: bool = False

log_y: bool = False

log_y_axis_range: List[float] | None = None

name: str

no_data: bool = False

normalized: bool = False

override: bool = False

ratio_fit_function: str = ''

ratio_fit_legend: str = ''

ratio_fit_legend_position: Position | None = None

ratio_fit_range: List[float] | None = None

ratio_y_axis_range: List[float] | None = None

rebin: int = 1

save_extensions: List[str]

selection_string: str | None = None

show_errors: bool = True

show_overflow: bool = False

show_ratio: bool = False

sort_by_yields: bool = False

vertical_lines: List[float]

x_axis: str = ''

x_axis_format: str = ''

x_axis_range: List[float] | None = None

y_axis: str = ''

y_axis_format: str | None = None

y_axis_range: List[float] | None = None

y_axis_show_zero: bool = False

yields_table_order: bool = True

yields_title: bool = True

class plotit.config.Point(x, y)

x: float

y: float

class plotit.config.Position(x1, y1, x2, y2)

x1: float

x2: float

y1: float

y2: float

plotit.config.loadConfiguration(confConfig=None)

Load a Configuration from a dict

Return type:: Configuration

plotit.config.loadFiles(fileConfigs=None)

Load a list of File instances from a dictionary with settings

Return type:: List[File]

plotit.config.loadGroups(groupConfigs=None, files=None, includeEmpty=False)

Load a list of Group instances from a dictionary with settings

Return type:: List[Group]

plotit.config.loadLegend(legendConfig=None)

Load a Legend instance from a dictionary with settings

Return type:: Legend

plotit.config.loadPlots(plotsConfig, defaultStyle=None)

Load a list of Plot instances from a config dictionary

Return type:: List[Plot]

plotit.config.loadSystematics(systConfigs, configuration)

Load a list of SystVar instances from config entries

Return type:: List[Any]

plotit.config.parseWithIncludes(yamlPath)

Parse a YAML file, with ‘includes’ relative to its path

Return type:: Any