Class: LaunchDarklyApi::AiConfigsMetricDenominatorRep

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

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Methods inherited from ApiModelBase

_deserialize, #_to_hash, #to_body, #to_s

Constructor Details

#initialize(attributes = {}) ⇒ AiConfigsMetricDenominatorRep

Initializes the object

Parameters:

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

    Model attributes in the form of hash



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 106

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Instance Attribute Details

#data_source ⇒ Object

Returns the value of attribute data_source.



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 30

def data_source
  @data_source
end

#event_name ⇒ Object

The warehouse event column for the denominator



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

def event_name
  @event_name
end

#filters ⇒ Object

Returns the value of attribute filters.



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 32

def filters
  @filters
end

#is_numeric ⇒ Object

Whether the denominator aggregates a numeric value



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

def is_numeric
  @is_numeric
end

#unit_aggregation_field ⇒ Object

The column to count distinct values of; required when unitAggregationType is count_distinct



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

def unit_aggregation_field
  @unit_aggregation_field
end

#unit_aggregation_type ⇒ Object

How individual unit values are aggregated for the denominator



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

def unit_aggregation_type
  @unit_aggregation_type
end

#window_end_offset ⇒ Object

End of the measurement window in milliseconds



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 38

def window_end_offset
  @window_end_offset
end

#window_start_offset ⇒ Object

Start of the measurement window in milliseconds



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 35

def window_start_offset
  @window_start_offset
end

#winsor_exclude_imputed ⇒ Object

Deprecated and ignored. Use winsorIncludeImputed instead.



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 47

def winsor_exclude_imputed
  @winsor_exclude_imputed
end

#winsor_include_imputed ⇒ Object

When true, the percentile bound calculation includes imputed zeros



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

def winsor_include_imputed
  @winsor_include_imputed
end

#winsor_lower_percentile ⇒ Object

Lower winsorization percentile in the open interval (0, 100)



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 41

def winsor_lower_percentile
  @winsor_lower_percentile
end

#winsor_upper_percentile ⇒ Object

Upper winsorization percentile in the open interval (0, 100)



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 44

def winsor_upper_percentile
  @winsor_upper_percentile
end

Class Method Details

.acceptable_attribute_map ⇒ Object

Returns attribute mapping this model knows about



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 71

def self.acceptable_attribute_map
  attribute_map
end

.acceptable_attributes ⇒ Object

Returns all the JSON keys this model knows about



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 76

def self.acceptable_attributes
  acceptable_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/ai_configs_metric_denominator_rep.rb', line 53

def self.attribute_map
  {
    :'event_name' => :'eventName',
    :'is_numeric' => :'isNumeric',
    :'unit_aggregation_type' => :'unitAggregationType',
    :'unit_aggregation_field' => :'unitAggregationField',
    :'data_source' => :'dataSource',
    :'filters' => :'filters',
    :'window_start_offset' => :'windowStartOffset',
    :'window_end_offset' => :'windowEndOffset',
    :'winsor_lower_percentile' => :'winsorLowerPercentile',
    :'winsor_upper_percentile' => :'winsorUpperPercentile',
    :'winsor_exclude_imputed' => :'winsorExcludeImputed',
    :'winsor_include_imputed' => :'winsorIncludeImputed'
  }
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/ai_configs_metric_denominator_rep.rb', line 218

def self.build_from_hash(attributes)
  return nil unless attributes.is_a?(Hash)
  attributes = attributes.transform_keys(&:to_sym)
  transformed_hash = {}
  openapi_types.each_pair do |key, type|
    if attributes.key?(attribute_map[key]) && attributes[attribute_map[key]].nil?
      transformed_hash["#{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[attribute_map[key]].is_a?(Array)
        transformed_hash["#{key}"] = attributes[attribute_map[key]].map { |v| _deserialize($1, v) }
      end
    elsif !attributes[attribute_map[key]].nil?
      transformed_hash["#{key}"] = _deserialize(type, attributes[attribute_map[key]])
    end
  end
  new(transformed_hash)
end

.openapi_nullable ⇒ Object

List of attributes with nullable: true



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 99

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

.openapi_types ⇒ Object

Attribute type mapping.



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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 81

def self.openapi_types
  {
    :'event_name' => :'String',
    :'is_numeric' => :'Boolean',
    :'unit_aggregation_type' => :'String',
    :'unit_aggregation_field' => :'String',
    :'data_source' => :'AiConfigsMetricDataSourceRefRep',
    :'filters' => :'AiConfigsFilter',
    :'window_start_offset' => :'Integer',
    :'window_end_offset' => :'Integer',
    :'winsor_lower_percentile' => :'Float',
    :'winsor_upper_percentile' => :'Float',
    :'winsor_exclude_imputed' => :'Boolean',
    :'winsor_include_imputed' => :'Boolean'
  }
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/ai_configs_metric_denominator_rep.rb', line 186

def ==(o)
  return true if self.equal?(o)
  self.class == o.class &&
      event_name == o.event_name &&
      is_numeric == o.is_numeric &&
      unit_aggregation_type == o.unit_aggregation_type &&
      unit_aggregation_field == o.unit_aggregation_field &&
      data_source == o.data_source &&
      filters == o.filters &&
      window_start_offset == o.window_start_offset &&
      window_end_offset == o.window_end_offset &&
      winsor_lower_percentile == o.winsor_lower_percentile &&
      winsor_upper_percentile == o.winsor_upper_percentile &&
      winsor_exclude_imputed == o.winsor_exclude_imputed &&
      winsor_include_imputed == o.winsor_include_imputed
end

#eql?(o) ⇒ Boolean

Parameters:

  • Object (Object) —

    to be compared

Returns:

  • (Boolean)

See Also:

  • `==` method


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# File 'lib/launchdarkly_api/models/ai_configs_metric_denominator_rep.rb', line 205

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/ai_configs_metric_denominator_rep.rb', line 211

def hash
  [event_name, is_numeric, unit_aggregation_type, unit_aggregation_field, data_source, filters, window_start_offset, window_end_offset, winsor_lower_percentile, winsor_upper_percentile, winsor_exclude_imputed, winsor_include_imputed].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/ai_configs_metric_denominator_rep.rb', line 171

def list_invalid_properties
  warn '[DEPRECATED] the `list_invalid_properties` method is obsolete'
  invalid_properties = Array.new
  invalid_properties
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/ai_configs_metric_denominator_rep.rb', line 240

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

#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/ai_configs_metric_denominator_rep.rb', line 179

def valid?
  warn '[DEPRECATED] the `valid?` method is obsolete'
  true
end