elphick.geomet.sample.Sample

class elphick.geomet.sample.Sample(data=None, name=None, moisture_in_scope=True, mass_wet_var=None, mass_dry_var=None, moisture_var=None, component_vars=None, composition_units='%', components_as_symbols=True, ranges=None, config_file=None)

__init__(data=None, name=None, moisture_in_scope=True, mass_wet_var=None, mass_dry_var=None, moisture_var=None, component_vars=None, composition_units='%', components_as_symbols=True, ranges=None, config_file=None)

Parameters:

• data (Optional[DataFrame]) – The input data

• name (Optional[str]) – The name of the sample

• moisture_in_scope (bool) – Whether the moisture is in scope. If False, only dry mass is processed.

• mass_wet_var (Optional[str]) – The name of the wet mass column

• mass_dry_var (Optional[str]) – The name of the dry mass column

• moisture_var (Optional[str]) – The name of the moisture column

• component_vars (Optional[list[str]]) – The names of the chemical columns

• components_as_symbols (bool) – If True, convert the composition variables to symbols, e.g. Fe

• ranges (Optional[dict[str, list]]) – The range of valid data for each column in the data

• config_file (Optional[Path]) – The configuration file

Methods

__init__([data, name, moisture_in_scope, ...])
add(other[, name, include_supplementary_data])	Add two objects together
balance_composition([epsilon])	Balance the composition data
clip_composition([ranges, epsilon])	Clip the components
clip_recovery(other[, recovery_bounds, ...])	Clip the recovery to the specified bounds and recalculate the estimate.
compare(other[, comparisons, explicit_names])
create_congruent_object(name[, ...])	Create an object with the same attributes
div(other[, name, include_supplementary_data])	Divide two objects
filter_by_index(index)	Update the data by index
from_mass_dataframe(mass_df[, mass_wet, ...])	Class method to create a MassComposition object from a mass dataframe.
get_mass_data([include_moisture])	Get the mass data
plot_comparison(other[, color, ...])	Create an interactive parallel plot
plot_parallel([color, vars_include, ...])	Create an interactive parallel plot
plot_ternary(variables[, color, title])	Plot a ternary diagram
query(expr[, name])	Reduce the data by a query expression
reset_index(index_name)
set_moisture(moisture[, mass_to_adjust])	Set the moisture to the specified value
split(fraction[, name_1, name_2, ...])	Split the object by mass
sub(other[, name, include_supplementary_data])	Subtract other from self
to_stream()
update_mass_data(value)
weight_average([group_by])

Attributes

aggregate
composition_columns
data
data_columns
mass_columns
mass_data
moisture_column
supplementary_columns
variable_map	A map from lower case standard names to the actual column names