illumina::interop::logic::plot Namespace Reference

Classes
class	by_cycle_average_plot
class	by_cycle_candle_stick_plot
class	by_lane_candle_stick_plot
class	flowcell_plot
class	plot_metric_proxy

Functions
void	filter_by_cycle_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_accumulated=false)
void	filter_by_lane_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_pf=false)
template<typename Point >
void	auto_scale (model::plot::plot_data< Point > &data, const bool zero_min=true, const float scale_y_max=1.1f)
template<typename Point >
void	auto_scale_x (model::plot::plot_data< Point > &data, const bool zero_min=true)
template<typename Point >
void	auto_scale_y (model::plot::plot_data< Point > &data, const bool zero_min=true, const float scale_y_max=1.1f)
std::string	color_name_for_index (const size_t index)
void	list_flowcell_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_accumulated=false)
void	filter_flowcell_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_accumulated=false)
size_t	calculate_flowcell_buffer_size (const model::metrics::run_metrics &metrics, const model::plot::filter_options &options)
void	list_plot_metrics (std::vector< logic::utils::metric_type_description_t > &types)
void	list_available_plot_metrics (const model::metrics::run_metrics &metrics, std::vector< logic::utils::metric_type_description_t > &types)
template<typename I >
void	plot_candle_stick (model::plot::candle_stick_point &point, I beg, I end, const float x, std::vector< float > &outliers)
size_t	count_columns_for_heatmap (const model::metrics::run_metrics &metrics)
template<class Point >
void	setup_series_by_channel (const std::vector< std::string > &channels, model::plot::plot_data< Point > &data)
template<class Point >
void	setup_series_by_base (model::plot::plot_data< Point > &data)
template<class Point >
void	plot_by_cycle_t (model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::plot_data< Point > &data, const bool skip_empty)
template<class Point >
void	plot_by_cycle_t (model::metrics::run_metrics &metrics, const std::string &metric_name, const model::plot::filter_options &options, model::plot::plot_data< Point > &data, const bool skip_empty)
void	plot_by_cycle (model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty) INTEROP_THROW_SPEC((model
void	plot_by_cycle (model::metrics::run_metrics &metrics, const std::string &metric_name, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty) INTEROP_THROW_SPEC((model
void	list_by_cycle_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_accumulated)
template<class Point >
void	plot_by_lane_t (const model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::plot_data< Point > &data, const bool skip_empty) INTEROP_THROW_SPEC((model
void	plot_by_lane (const model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty) INTEROP_THROW_SPEC((model
void	plot_by_lane (const model::metrics::run_metrics &metrics, const std::string &metric_name, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty) INTEROP_THROW_SPEC((model
void	list_by_lane_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_pf)
void	plot_flowcell_map (model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::flowcell_data &data, float *buffer,::uint32_t *tile_buffer, const bool skip_empty) INTEROP_THROW_SPEC((model
void	plot_flowcell_map (model::metrics::run_metrics &metrics, const std::string &metric_name, const model::plot::filter_options &options, model::plot::flowcell_data &data, float *buffer,::uint32_t *tile_buffer, const bool skip_empty) INTEROP_THROW_SPEC((model
template<typename I , typename B >
void	populate_heatmap_from_compressed (I beg, I end, const std::vector< B > &bins, const model::plot::filter_options &options, model::plot::heatmap_data &data)
template<typename I >
void	populate_heatmap_from_uncompressed (I beg, I end, const model::plot::filter_options &options, model::plot::heatmap_data &data)
void	normalize_heatmap (model::plot::heatmap_data &data)
template<typename I >
void	remap_to_bins (I beg, I end, const size_t max_cycle, model::plot::heatmap_data &data)
template<class Metric >
void	populate_heatmap (const model::metric_base::metric_set< Metric > &metric_set, const model::plot::filter_options &options, model::plot::heatmap_data &data, float *buffer)
void	plot_qscore_heatmap (model::metrics::run_metrics &metrics, const model::plot::filter_options &options, model::plot::heatmap_data &data, float *buffer, const size_t) INTEROP_THROW_SPEC((model
size_t	count_rows_for_heatmap (const model::metrics::run_metrics &metrics)
template<typename I >
void	populate_distribution (I beg, I end, const model::plot::filter_options &options, const size_t first_cycle, const size_t last_cycle, std::vector< float > &histogram)
std::string	scale_histogram (std::vector< float > &histogram)
size_t	get_last_filtered_cycle (const model::run::info &run_info, const model::plot::filter_options &options, const size_t max_cycle) INTEROP_THROW_SPEC((model
template<typename Point >
float	plot_unbinned_histogram (const std::vector< float > &histogram, model::plot::data_point_collection< Point > &points)
template<typename I , typename Point >
float	plot_binned_histogram (I beg, I end, const std::vector< float > &histogram, model::plot::data_point_collection< Point > &points)
void	plot_qscore_histogram (model::metrics::run_metrics &metrics, const model::plot::filter_options &options, model::plot::plot_data< model::plot::bar_point > &data, const size_t boundary) INTEROP_THROW_SPEC((model
template<typename Point >
float	populate_reads_identified (model::metric_base::metric_set< model::metrics::index_metric > &index_metrics, const model::metric_base::metric_set< model::metrics::tile_metric > &tile_metrics, const size_t lane, model::plot::data_point_collection< Point > &points)
void	plot_sample_qc (model::metrics::run_metrics &metrics, const size_t lane, model::plot::plot_data< model::plot::bar_point > &data)

Variables
void plot_by_cycle(model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty=true) INTEROP_THROW_SPEC((model void plot_by_cycle(model::metrics::run_metrics &metrics, const std::string &metric_name, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty=true) INTEROP_THROW_SPEC((model void	list_by_cycle_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_accumulated=false)
void plot_by_lane(const model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty=true) INTEROP_THROW_SPEC((model void plot_by_lane(const model::metrics::run_metrics &metrics, const std::string &metric_name, const model::plot::filter_options &options, model::plot::plot_data< model::plot::candle_stick_point > &data, const bool skip_empty=true) INTEROP_THROW_SPEC((model void	list_by_lane_metrics (std::vector< logic::utils::metric_type_description_t > &types, const bool ignore_pf=false)
void plot_flowcell_map(model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::flowcell_data &data, float *buffer=0,::uint32_t *tile_buffer=0, const bool skip_empty=true) INTEROP_THROW_SPEC((model voi	plot_flowcell_map2 )(model::metrics::run_metrics &metrics, const constants::metric_type type, const model::plot::filter_options &options, model::plot::flowcell_data &data, float *buffer, const size_t buffer_size,::uint32_t *id_buffer, const size_t id_buffer_size, const bool skip_empty=true) INTEROP_THROW_SPEC((model
void plot_qscore_heatmap(model::metrics::run_metrics &metrics, const model::plot::filter_options &options, model::plot::heatmap_data &data, float *buffer=0, const size_t buffer_size=0) INTEROP_THROW_SPEC((model size_	count_rows_for_heatmap )(const model::metrics::run_metrics &metrics)

Function Documentation

void illumina::interop::logic::plot::auto_scale	(	model::plot::plot_data< Point > &	data,
		const bool	zero_min = true,
		const float	scale_y_max = 1.1f
	)

Logic for auto scaling both axes of plot data

Parameters

data	model for plot data
zero_min	if true, set minimum to 0
scale_y_max	factor to scale maximum Y value

void illumina::interop::logic::plot::auto_scale_x	(	model::plot::plot_data< Point > &	data,
		const bool	zero_min = true
	)

Logic for auto scaling the x-axis of plot data

Parameters

data	model for plot data
zero_min	if true, set minimum to 0

void illumina::interop::logic::plot::auto_scale_y	(	model::plot::plot_data< Point > &	data,
		const bool	zero_min = true,
		const float	scale_y_max = 1.1f
	)

Logic for auto scaling the y-axis of plot data

Parameters

data	model for plot data
zero_min	if true, set minimum to 0
scale_y_max	factor to scale maximum Y value

size_t calculate_flowcell_buffer_size	(	const model::metrics::run_metrics &	metrics,
		const model::plot::filter_options &	options
	)

Calculate the required buffer size

Parameters

metrics	run metrics
options	options to filter the data

std::string illumina::interop::logic::plot::color_name_for_index ( const size_t  index )

inline

Get the color for a specific line index

Note

From: http://stackoverflow.com/questions/1168260/algorithm-for-generating-unique-colors

Parameters

index

line index

Returns

color name

size_t count_columns_for_heatmap

(

const model::metrics::run_metrics &

metrics

)

Count number of columns for the heat map

Parameters

metrics

run metrics

Returns

number of columns

size_t illumina::interop::logic::plot::count_rows_for_heatmap

(

const model::metrics::run_metrics &

metrics

)

Count number of rows for the heat map

Parameters

metrics

run metrics

Returns

number of rows

void filter_by_cycle_metrics	(	std::vector< logic::utils::metric_type_description_t > &	types,
		const bool	ignore_accumulated = false
	)

Filter metric types available for by cycle plots

Parameters

types	destination vector to fill with metric types
ignore_accumulated	if true, ignore accumulated Q20 and Q30

void filter_by_lane_metrics	(	std::vector< logic::utils::metric_type_description_t > &	types,
		const bool	ignore_pf = false
	)

Filter metric types available for by lane plots

Parameters

types	destination vector to fill with metric types
ignore_pf	if true, ignore density PF and cluster PF

void filter_flowcell_metrics	(	std::vector< logic::utils::metric_type_description_t > &	types,
		const bool	ignore_accumulated = false
	)

Filter metric type names available for flowcell

Parameters

types	destination vector to fill with metric type names
ignore_accumulated	exclude accumulated q-metrics

size_t illumina::interop::logic::plot::get_last_filtered_cycle ( const model::run::info &  run_info, const model::plot::filter_options &  options, const size_t  max_cycle  )

inline

Get the last cycle based on the filter options

Parameters

run_info	run info with reads information
options	options to filter the data
max_cycle	maximum cycle for q_metrics

Returns

last cycle based on run info and filter options

void list_available_plot_metrics	(	const model::metrics::run_metrics &	metrics,
		std::vector< logic::utils::metric_type_description_t > &	types
	)

List all available metric types for all plots

That is, the metric must be populated

Parameters

metrics	run metrics object
types	destination vector to fill with metric types

List all available metric types for all plots

That is, the metric must be populated

Parameters

types

destination vector to fill with metric types

void illumina::interop::logic::plot::list_by_cycle_metrics	(	std::vector< logic::utils::metric_type_description_t > &	types,
		const bool	ignore_accumulated
	)

List metric types available for by cycle plots

Parameters

types	destination vector to fill with metric types
ignore_accumulated	if true, ignore accumulated Q20 and Q30

void illumina::interop::logic::plot::list_by_lane_metrics	(	std::vector< logic::utils::metric_type_description_t > &	types,
		const bool	ignore_pf
	)

List metric types available for by lane plots

Parameters

types	destination vector to fill with metric types
ignore_pf	if true, ignore density PF and cluster PF

void list_flowcell_metrics	(	std::vector< logic::utils::metric_type_description_t > &	types,
		const bool	ignore_accumulated = false
	)

List metric type names available for flowcell

Parameters

types	destination vector to fill with metric type names
ignore_accumulated	exclude accumulated q-metrics

void list_plot_metrics

(

std::vector< logic::utils::metric_type_description_t > &

types

)

List metric types available for all plots

Parameters

types

destination vector to fill with metric types

void illumina::interop::logic::plot::normalize_heatmap

(

model::plot::heatmap_data &

data

)

Normalize the heat map to a percent

Parameters

data	output heat map data

float illumina::interop::logic::plot::plot_binned_histogram	(	I	beg,
		I	end,
		const std::vector< float > &	histogram,
		model::plot::data_point_collection< Point > &	points
	)

Plot a binned histogram

Parameters

beg	iterator to start of the histogram bins
end	iterator to end of the histogram bins
histogram	q-score histogram
points	collection of points where x is lane number and y is the candle stick metric values

Returns

max x-value

void illumina::interop::logic::plot::plot_candle_stick	(	model::plot::candle_stick_point &	point,
		I	beg,
		I	end,
		const float	x,
		std::vector< float > &	outliers
	)

Logic for creating a candle stick point

Parameters

point	candle stick point
beg	iterator to start of collection of values
end	iterator to end of collection of values
x	x-coordinate
outliers	reusable memory for collecting outliers

float illumina::interop::logic::plot::plot_unbinned_histogram	(	const std::vector< float > &	histogram,
		model::plot::data_point_collection< Point > &	points
	)

Plot an unbinned histogram

Parameters

histogram	q-score histogram
points	collection of points where x is lane number and y is the candle stick metric values

Returns

max x-value

void illumina::interop::logic::plot::populate_distribution	(	I	beg,
		I	end,
		const model::plot::filter_options &	options,
		const size_t	first_cycle,
		const size_t	last_cycle,
		std::vector< float > &	histogram
	)

Populate the q-score histogram based on the filter options

Parameters

beg	iterator to start of q-metric collection
end	iterator to end of q-metric collection
options	filter for metric records
first_cycle	first cycle to keep
last_cycle	last cycle to keep
histogram	q-score histogram

void illumina::interop::logic::plot::populate_heatmap	(	const model::metric_base::metric_set< Metric > &	metric_set,
		const model::plot::filter_options &	options,
		model::plot::heatmap_data &	data,
		float *	buffer
	)

Plot a heat map of q-scores

Parameters

metric_set	q-metrics (full or by lane)
options	options to filter the data
data	output heat map data
buffer	preallocated memory

void illumina::interop::logic::plot::populate_heatmap_from_compressed	(	I	beg,
		I	end,
		const std::vector< B > &	bins,
		const model::plot::filter_options &	options,
		model::plot::heatmap_data &	data
	)

Populate the q-score heat map based on the filter options

Parameters

beg	iterator to start of q-metric collection
end	iterator to end of q-metric collection
bins	q-score bins
options	filter for metric records
data	q-score heatmap

void illumina::interop::logic::plot::populate_heatmap_from_uncompressed	(	I	beg,
		I	end,
		const model::plot::filter_options &	options,
		model::plot::heatmap_data &	data
	)

Populate the q-score heatmap based on the filter options

Parameters

beg	iterator to start of q-metric collection
end	iterator to end of q-metric collection
options	filter for metric records
data	q-score heatmap

float illumina::interop::logic::plot::populate_reads_identified	(	model::metric_base::metric_set< model::metrics::index_metric > &	index_metrics,
		const model::metric_base::metric_set< model::metrics::tile_metric > &	tile_metrics,
		const size_t	lane,
		model::plot::data_point_collection< Point > &	points
	)

Populate reads identified versus the index

Parameters

index_metrics	set of metric records
tile_metrics	source collection of tile metrics
lane	lane index
points	collection of points where x is lane number and y is the candle stick metric values

void illumina::interop::logic::plot::remap_to_bins	(	I	beg,
		I	end,
		const size_t	max_cycle,
		model::plot::heatmap_data &	data
	)

Spread the bins out

Parameters

beg	iterator to start of bins
end	iterator to end of bins
max_cycle	maximum cycle number
data	output heat map data

std::string illumina::interop::logic::plot::scale_histogram ( std::vector< float > &  histogram )

inline

Scale the histogram if necessary and provide the scale label

Parameters

histogram

q-score histogram

Returns

label of the scale

void illumina::interop::logic::plot::setup_series_by_base

(

model::plot::plot_data< Point > &

data

)

Generate meta data for multiple plot series that compare data by base

Parameters

data	plot data that holds a collection of plot series

void illumina::interop::logic::plot::setup_series_by_channel	(	const std::vector< std::string > &	channels,
		model::plot::plot_data< Point > &	data
	)

Generate meta data for multiple plot series that compare data by channel

Parameters

channels	collection of channel names
data	plot data that holds a collection of plot series