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# datacolumn.rb: a class holding a 'column' of data
# copyright (c) 2009-2011 by Vincent Fourmond
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details (in the COPYING file).
require 'Dobjects/Dvector'
require 'ctioga2/utils'
# This module contains all the classes used by ctioga
module CTioga2
Version::register_svn_info('$Revision: 229 $', '$Date: 2011-01-17 17:34:57 +0100 (Mon, 17 Jan 2011) $')
module Data
# This class holds one column, possibly with error bars.
#
# \todo a way to concatenate two DataColumns
#
# \todo a way to easily access the by "lines"
class DataColumn
# A Dvector holding ``real'' values
attr_accessor :values
# A Dvector holding minimal values
attr_accessor :min_values
# A Dvector holding maximal values
attr_accessor :max_values
# \todo a method that resembles the code in the old text backend
# to set errors according to a speficication (relative,
# absolute, already max/min)
# \todo a dup !
def initialize(values, min = nil, max = nil)
@values = values
@min_values = min
@max_values = max
end
# Creates a DataColumn object
def self.create(number, with_errors = false)
a = Dobjects::Dvector.new(number, NaN::NaN)
if with_errors
b = Dobjects::Dvector.new(number, NaN::NaN)
c = Dobjects::Dvector.new(number, NaN::NaN)
else
b = nil
c = nil
end
return self.new(a, b, c)
end
# Yields all the vectors in turn to apply a given
# transformation.
def apply
for v in all_vectors
yield v if v
end
end
# Sorts the values according to the index vector given.
def reindex(idx_vector)
for v in all_vectors
# This is slow !
# Code should be written in C on the dvector side.
#
# Or we could use Function.sort, though this is not very
# elegant nor efficient. (but it would be memory-efficient,
# though).
next unless v
w = Dobjects::Dvector.new(idx_vector.size) do |i|
v[idx_vector[i]]
end
v.replace(w)
end
end
# Whether there are error bars.
def has_errors?
return (@min_values && @max_values)
end
# Column names. _base_ is used as a base for the names. If
# _expand_ is on, always return all the names.
def column_names(base, expand = false)
if expand || has_errors?
return [base, "#{base}min", "#{base}max"]
else
return [base]
end
end
# Values at the given index.
#
# If _with_errors_ is false, only [value] is returned.
#
# If _with_errors_ is true, then, non-existent values are
# expanded to _nil_ if _expand_nil_ is true or to value if not.
def values_at(i, with_errors = false, expand_nil = true)
if ! with_errors
return [@values[i]]
end
if has_errors?
return [@values[i], @min_values[i], @max_values[i]]
else
if expand_nil
return [@values[i], nil, nil]
else
return [@values[i], @values[i], @values[i]]
end
end
end
# Vectors: all values if there are error bars, or only the
# #value one if there isn't.
def vectors
if has_errors?
return [@values, @min_values, @max_values]
else
return [@values]
end
end
# Returns the number of elements.
def size
return @values.size
end
# Sets the values at the given index
def set_values_at(i, value, min = nil, max = nil)
@values[i] = value
if min && max
ensure_has_errors
@min_values[i] = min
@max_vaklues[i] = max
end
end
# Appends the given values at the end of the DataColumn
#
# @todo This isn't very efficient. Does it really matter ?
def push_values(value, min=nil, max=nil)
set_values_at(@values.size, value, min, max)
end
# Creates dummy errors (ie, min_values = max_values = values) if
# the datacolumn does not currently have one.
def ensure_has_errors
if ! has_errors?
@min_values = @values.dup
@max_values = @values.dup
end
end
# Concatenates with another DataColumn, making sure the errors
# and such are not lost.
def <<(column)
# If there are error bars, wew make sure we concatenate all of them
if has_errors? || column.has_errors?
self.ensure_has_errors
column.ensure_has_errors
@min_values.concat(column.min_values)
@max_values.concat(column.max_values)
end
@values.concat(column.values)
end
# Only keeps every _n_ points in the DataColumn
def trim!(nb)
nb = nb.to_i
if nb < 2
return
end
new_vects = []
for v in all_vectors
if v
new_values = Dobjects::Dvector.new
i = 0
for val in v
if (i % nb) == 0
new_values << val
end
i+=1
end
new_vects << new_values
else
new_vects << nil
end
end
set_vectors(new_vects)
end
ColumnSpecsRE = /|min|max|err/i
# This function sets the value of the DataColumn object
# according to a hash: _spec_ => _vector_. _spec_ can be any of:
# * 'value', 'values' or '' : the #values
# * 'min' : #min
# * 'max' : #max
# * 'err' : absolute error: min is value - error, max is value +
# error
def from_hash(spec)
s = spec.dup
@values = spec['value'] || spec['values'] ||
spec['']
if ! @values
raise "Need a 'value' specification"
end
for k in ['value', 'values', '']
s.delete(k)
end
for key in s.keys
case key
when /^min$/i
@min_values = s[key]
when /^max$/i
@max_values = s[key]
when /^err$/i
@min_values = @values - s[key]
@max_values = @values + s[key]
else
raise "Unkown key: #{key}"
end
end
end
# Creates and returns a DataColumn object according to the
# _spec_. See #from_hash for more information.
def self.from_hash(spec)
a = DataColumn.new(nil)
a.from_hash(spec)
return a
end
# Returns the minimum value of all vectors held in this column
def min
m = @values.min
for v in [@min_values, @max_values]
if v
m1 = v.min
if m1 < m # This also works if m1 is NaN
m = m1
end
end
end
return m
end
# Returns the maximum value of all vectors held in this column
def max
m = @values.max
for v in [@min_values, @max_values]
if v
m1 = v.max
if m1 > m # This also works if m1 is NaN
m = m1
end
end
end
return m
end
def convolve!(kernel, middle = nil)
middle ||= kernel.size/2
# We smooth everything, stupidly?
for v in all_vectors
v.replace(v.convolve(kernel,middle)) if v
end
end
protected
# All the vectors held by the DataColumn
def all_vectors
return [@values, @min_values, @max_values]
end
# Sets the vectors to the given list, as might have been
# returned by #all_vectors
def set_vectors(vectors)
@values, @min_values, @max_values = *vectors
end
end
end
end
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