Class: LaunchDarklyApi::TreatmentResultRep

Inherits:
Object
  • Object
show all
Defined in:
lib/launchdarkly_api/models/treatment_result_rep.rb

Defined Under Namespace

Classes: EnumAttributeValidator

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(attributes = {}) ⇒ TreatmentResultRep

Initializes the object

Parameters:

  • attributes (Hash) (defaults to: {}) —

    Model attributes in the form of hash



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 156

def initialize(attributes = {})
  if (!attributes.is_a?(Hash))
    fail ArgumentError, "The input argument (attributes) must be a hash in `LaunchDarklyApi::TreatmentResultRep` initialize method"
  end

  # check to see if the attribute exists and convert string to symbol for hash key
  attributes = attributes.each_with_object({}) { |(k, v), h|
    if (!self.class.attribute_map.key?(k.to_sym))
      fail ArgumentError, "`#{k}` is not a valid attribute in `LaunchDarklyApi::TreatmentResultRep`. Please check the name to make sure it's valid. List of attributes: " + self.class.attribute_map.keys.inspect
    end
    h[k.to_sym] = v
  }

  if attributes.key?(:'treatment_id')
    self.treatment_id = attributes[:'treatment_id']
  end

  if attributes.key?(:'treatment_name')
    self.treatment_name = attributes[:'treatment_name']
  end

  if attributes.key?(:'mean')
    self.mean = attributes[:'mean']
  end

  if attributes.key?(:'data_mean')
    self.data_mean = attributes[:'data_mean']
  end

  if attributes.key?(:'data_std_dev')
    self.data_std_dev = attributes[:'data_std_dev']
  end

  if attributes.key?(:'credible_interval')
    self.credible_interval = attributes[:'credible_interval']
  end

  if attributes.key?(:'p_best')
    self.p_best = attributes[:'p_best']
  end

  if attributes.key?(:'relative_differences')
    if (value = attributes[:'relative_differences']).is_a?(Array)
      self.relative_differences = value
    end
  end

  if attributes.key?(:'units')
    self.units = attributes[:'units']
  end

  if attributes.key?(:'traffic')
    self.traffic = attributes[:'traffic']
  end

  if attributes.key?(:'event_values_sum')
    self.event_values_sum = attributes[:'event_values_sum']
  end

  if attributes.key?(:'distribution')
    self.distribution = attributes[:'distribution']
  end

  if attributes.key?(:'correlation')
    self.correlation = attributes[:'correlation']
  end

  if attributes.key?(:'standard_deviation_ratio')
    self.standard_deviation_ratio = attributes[:'standard_deviation_ratio']
  end

  if attributes.key?(:'covariate_imbalance')
    self.covariate_imbalance = attributes[:'covariate_imbalance']
  end

  if attributes.key?(:'variance_reduction')
    self.variance_reduction = attributes[:'variance_reduction']
  end

  if attributes.key?(:'model')
    self.model = attributes[:'model']
  end

  if attributes.key?(:'bayesian_normal')
    self.bayesian_normal = attributes[:'bayesian_normal']
  end

  if attributes.key?(:'bayesian_beta')
    self.bayesian_beta = attributes[:'bayesian_beta']
  end
end

Instance Attribute Details

#bayesian_beta ⇒ Object

Returns the value of attribute bayesian_beta.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 69

def bayesian_beta
  @bayesian_beta
end

#bayesian_normal ⇒ Object

Returns the value of attribute bayesian_normal.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 67

def bayesian_normal
  @bayesian_normal
end

#correlation ⇒ Object

The outcome-covariate correlation



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 53

def correlation
  @correlation
end

#covariate_imbalance ⇒ Object

The imbalance between the covariate mean for the arm and the covariate mean for the experiment



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 59

def covariate_imbalance
  @covariate_imbalance
end

#credible_interval ⇒ Object

Returns the value of attribute credible_interval.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 33

def credible_interval
  @credible_interval
end

#data_mean ⇒ Object

The mean of the data, with no priors effecting the result.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 28

def data_mean
  @data_mean
end

#data_std_dev ⇒ Object

The standard deviation of the data, with no priors effecting the result.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 31

def data_std_dev
  @data_std_dev
end

#distribution ⇒ Object

Returns the value of attribute distribution.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 50

def distribution
  @distribution
end

#event_values_sum ⇒ Object

The sum of the event values for the units exposed to this treatment.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 48

def event_values_sum
  @event_values_sum
end

#mean ⇒ Object

The average value of the variation in this sample. It doesn’t capture the uncertainty in the measurement, so it should not be the only measurement you use to make decisions.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 25

def mean
  @mean
end

#model ⇒ Object

The model used to calculate the results. Parameters specific to this model will be defined under the field under the same name



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 65

def model
  @model
end

#p_best ⇒ Object

The likelihood that this variation has the biggest effect on the primary metric. The variation with the highest probability is likely the best of the variations you’re testing



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 36

def p_best
  @p_best
end

#relative_differences ⇒ Object

Estimates of the relative difference between this treatment’s mean and the mean of each other treatment



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 39

def relative_differences
  @relative_differences
end

#standard_deviation_ratio ⇒ Object

The ratio of the outcome SD to covariate SD



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 56

def standard_deviation_ratio
  @standard_deviation_ratio
end

#traffic ⇒ Object

The number of units exposed to this treatment.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 45

def traffic
  @traffic
end

#treatment_id ⇒ Object

The ID of the treatment



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 19

def treatment_id
  @treatment_id
end

#treatment_name ⇒ Object

The name of the treatment



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 22

def treatment_name
  @treatment_name
end

#units ⇒ Object

The number of units exposed to this treatment that have event values, including those that are configured to default to 0



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 42

def units
  @units
end

#variance_reduction ⇒ Object

The reduction in variance resulting from CUPED



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 62

def variance_reduction
  @variance_reduction
end

Class Method Details

.acceptable_attributes ⇒ Object

Returns all the JSON keys this model knows about



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 119

def self.acceptable_attributes
  attribute_map.values
end

.attribute_map ⇒ Object

Attribute mapping from ruby-style variable name to JSON key.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 94

def self.attribute_map
  {
    :'treatment_id' => :'treatmentId',
    :'treatment_name' => :'treatmentName',
    :'mean' => :'mean',
    :'data_mean' => :'dataMean',
    :'data_std_dev' => :'dataStdDev',
    :'credible_interval' => :'credibleInterval',
    :'p_best' => :'pBest',
    :'relative_differences' => :'relativeDifferences',
    :'units' => :'units',
    :'traffic' => :'traffic',
    :'event_values_sum' => :'eventValuesSum',
    :'distribution' => :'distribution',
    :'correlation' => :'correlation',
    :'standard_deviation_ratio' => :'standardDeviationRatio',
    :'covariate_imbalance' => :'covariateImbalance',
    :'variance_reduction' => :'varianceReduction',
    :'model' => :'model',
    :'bayesian_normal' => :'bayesianNormal',
    :'bayesian_beta' => :'bayesianBeta'
  }
end

.build_from_hash(attributes) ⇒ Object

Builds the object from hash

Parameters:

  • attributes (Hash) —

    Model attributes in the form of hash

Returns:

  • (Object) —

    Returns the model itself



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 314

def self.build_from_hash(attributes)
  new.build_from_hash(attributes)
end

.openapi_nullable ⇒ Object

List of attributes with nullable: true



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 149

def self.openapi_nullable
  Set.new([
  ])
end

.openapi_types ⇒ Object

Attribute type mapping.



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 124

def self.openapi_types
  {
    :'treatment_id' => :'String',
    :'treatment_name' => :'String',
    :'mean' => :'Float',
    :'data_mean' => :'Float',
    :'data_std_dev' => :'Float',
    :'credible_interval' => :'CredibleIntervalRep',
    :'p_best' => :'Float',
    :'relative_differences' => :'Array<RelativeDifferenceRep>',
    :'units' => :'Integer',
    :'traffic' => :'Integer',
    :'event_values_sum' => :'Float',
    :'distribution' => :'Distribution',
    :'correlation' => :'Float',
    :'standard_deviation_ratio' => :'Float',
    :'covariate_imbalance' => :'Float',
    :'variance_reduction' => :'Float',
    :'model' => :'String',
    :'bayesian_normal' => :'BayesianNormalStatsRep',
    :'bayesian_beta' => :'BayesianBetaBinomialStatsRep'
  }
end

Instance Method Details

#==(o) ⇒ Object

Checks equality by comparing each attribute.

Parameters:

  • Object (Object) —

    to be compared



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 275

def ==(o)
  return true if self.equal?(o)
  self.class == o.class &&
      treatment_id == o.treatment_id &&
      treatment_name == o.treatment_name &&
      mean == o.mean &&
      data_mean == o.data_mean &&
      data_std_dev == o.data_std_dev &&
      credible_interval == o.credible_interval &&
      p_best == o.p_best &&
      relative_differences == o.relative_differences &&
      units == o.units &&
      traffic == o.traffic &&
      event_values_sum == o.event_values_sum &&
      distribution == o.distribution &&
      correlation == o.correlation &&
      standard_deviation_ratio == o.standard_deviation_ratio &&
      covariate_imbalance == o.covariate_imbalance &&
      variance_reduction == o.variance_reduction &&
      model == o.model &&
      bayesian_normal == o.bayesian_normal &&
      bayesian_beta == o.bayesian_beta
end

#_deserialize(type, value) ⇒ Object

Deserializes the data based on type

Parameters:

  • string —

    type Data type

  • string —

    value Value to be deserialized

Returns:

  • (Object) —

    Deserialized data



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 345

def _deserialize(type, value)
  case type.to_sym
  when :Time
    Time.parse(value)
  when :Date
    Date.parse(value)
  when :String
    value.to_s
  when :Integer
    value.to_i
  when :Float
    value.to_f
  when :Boolean
    if value.to_s =~ /\A(true|t|yes|y|1)\z/i
      true
    else
      false
    end
  when :Object
    # generic object (usually a Hash), return directly
    value
  when /\AArray<(?<inner_type>.+)>\z/
    inner_type = Regexp.last_match[:inner_type]
    value.map { |v| _deserialize(inner_type, v) }
  when /\AHash<(?<k_type>.+?), (?<v_type>.+)>\z/
    k_type = Regexp.last_match[:k_type]
    v_type = Regexp.last_match[:v_type]
    {}.tap do |hash|
      value.each do |k, v|
        hash[_deserialize(k_type, k)] = _deserialize(v_type, v)
      end
    end
  else # model
    # models (e.g. Pet) or oneOf
    klass = LaunchDarklyApi.const_get(type)
    klass.respond_to?(:openapi_one_of) ? klass.build(value) : klass.build_from_hash(value)
  end
end

#_to_hash(value) ⇒ Hash

Outputs non-array value in the form of hash For object, use to_hash. Otherwise, just return the value

Parameters:

  • value (Object) —

    Any valid value

Returns:

  • (Hash) —

    Returns the value in the form of hash



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 416

def _to_hash(value)
  if value.is_a?(Array)
    value.compact.map { |v| _to_hash(v) }
  elsif value.is_a?(Hash)
    {}.tap do |hash|
      value.each { |k, v| hash[k] = _to_hash(v) }
    end
  elsif value.respond_to? :to_hash
    value.to_hash
  else
    value
  end
end

#build_from_hash(attributes) ⇒ Object

Builds the object from hash

Parameters:

  • attributes (Hash) —

    Model attributes in the form of hash

Returns:

  • (Object) —

    Returns the model itself



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 321

def build_from_hash(attributes)
  return nil unless attributes.is_a?(Hash)
  attributes = attributes.transform_keys(&:to_sym)
  self.class.openapi_types.each_pair do |key, type|
    if attributes[self.class.attribute_map[key]].nil? && self.class.openapi_nullable.include?(key)
      self.send("#{key}=", nil)
    elsif type =~ /\AArray<(.*)>/i
      # check to ensure the input is an array given that the attribute
      # is documented as an array but the input is not
      if attributes[self.class.attribute_map[key]].is_a?(Array)
        self.send("#{key}=", attributes[self.class.attribute_map[key]].map { |v| _deserialize($1, v) })
      end
    elsif !attributes[self.class.attribute_map[key]].nil?
      self.send("#{key}=", _deserialize(type, attributes[self.class.attribute_map[key]]))
    end
  end

  self
end

#eql?(o) ⇒ Boolean

Parameters:

  • Object (Object) —

    to be compared

Returns:

  • (Boolean)

See Also:

  • `==` method


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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 301

def eql?(o)
  self == o
end

#hash ⇒ Integer

Calculates hash code according to all attributes.

Returns:

  • (Integer) —

    Hash code



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 307

def hash
  [treatment_id, treatment_name, mean, data_mean, data_std_dev, credible_interval, p_best, relative_differences, units, traffic, event_values_sum, distribution, correlation, standard_deviation_ratio, covariate_imbalance, variance_reduction, model, bayesian_normal, bayesian_beta].hash
end

#list_invalid_properties ⇒ Object

Show invalid properties with the reasons. Usually used together with valid?

Returns:

  • Array for valid properties with the reasons



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 250

def list_invalid_properties
  invalid_properties = Array.new
  invalid_properties
end

#to_body ⇒ Hash

to_body is an alias to to_hash (backward compatibility)

Returns:

  • (Hash) —

    Returns the object in the form of hash



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 392

def to_body
  to_hash
end

#to_hash ⇒ Hash

Returns the object in the form of hash

Returns:

  • (Hash) —

    Returns the object in the form of hash



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 398

def to_hash
  hash = {}
  self.class.attribute_map.each_pair do |attr, param|
    value = self.send(attr)
    if value.nil?
      is_nullable = self.class.openapi_nullable.include?(attr)
      next if !is_nullable || (is_nullable && !instance_variable_defined?(:"@#{attr}"))
    end

    hash[param] = _to_hash(value)
  end
  hash
end

#to_s ⇒ String

Returns the string representation of the object

Returns:

  • (String) —

    String presentation of the object



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 386

def to_s
  to_hash.to_s
end

#valid? ⇒ Boolean

Check to see if the all the properties in the model are valid

Returns:

  • (Boolean) —

    true if the model is valid



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# File 'lib/launchdarkly_api/models/treatment_result_rep.rb', line 257

def valid?
  model_validator = EnumAttributeValidator.new('String', ["bayesianNormal", "bayesianBeta"])
  return false unless model_validator.valid?(@model)
  true
end