Module: Enumerable

Defined in:
(unknown)

Instance Method Summary collapse

Instance Method Details

#mean ⇒ Number

Calculate a mean of the values in enum. This method utilizes Kahan summation algorithm to compensate the result precision when the enum includes Float values.

Returns:

  • (Number) —

    A mean value



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1327

static VALUE
enum_mean(VALUE obj)
{
  VALUE mean;
  enum_mean_variance(obj, &mean, NULL, 1);
  return mean;
}

#mean_stdev(population: false) ⇒ mean, stdev

Calculate a mean and a standard deviation of the values in enum. The first element of the result array is the mean, and the second is the standard deviation.

This method is equivalent to:

def mean_stdev(population: false)
  m, v = mean_variance(population: population)
  [m, Math.sqrt(v)]
end

Returns:



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1392

static VALUE
enum_mean_stdev(int argc, VALUE* argv, VALUE obj)
{
  VALUE opts, mean, variance;
  size_t ddof = 1;

  rb_scan_args(argc, argv, "0:", &opts);
  if (opt_population_p(opts))
    ddof = 0;

  enum_mean_variance(obj, &mean, &variance, ddof);
  VALUE stdev = sqrt_value(variance);
  return rb_assoc_new(mean, stdev);
}

#mean_variance(population: false) ⇒ mean, variance

Calculate a mean and a variance of the values in enum. The first element of the result array is the mean, and the second is the variance.

When the population: keyword parameter is true, the variance is calculated as a population variance (divided by $n$). The default population: keyword parameter is false; this means the variance is a sample variance (divided by $n-1$).

This method scan values in enum only once, and does not cache the values on memory.

Returns:

  • (mean, variance) —

    Two element array consists of mean and variance values



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1303

static VALUE
enum_mean_variance_m(int argc, VALUE* argv, VALUE obj)
{
  VALUE opts, mean, variance;
  size_t ddof = 1;

  rb_scan_args(argc, argv, "0:", &opts);
  if (opt_population_p(opts))
    ddof = 0;

  enum_mean_variance(obj, &mean, &variance, ddof);
  return rb_assoc_new(mean, variance);
}

#stdev(population: false) ⇒ Number

Calculate a standard deviation of the values in enum.

This method is equivalent to:

Math.sqrt(enum.variance(population: population))

Returns:

  • (Number) —

    A standard deviation value



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1420

static VALUE
enum_stdev(int argc, VALUE* argv, VALUE obj)
{
  VALUE variance = enum_variance(argc, argv, obj);
  VALUE stdev = sqrt_value(variance);
  return stdev;
}

#sum ⇒ Number

Calculate the sum of the values in enum. This method utilizes Kahan summation algorithm to compensate the result precision when the enum includes Float values.

Note that This library does not redefine sum method introduced in Ruby 2.4.

Returns:

  • (Number) —

    A summation value



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1154

static VALUE
enum_sum(int argc, VALUE* argv, VALUE obj)
{
  VALUE sum, init;

  if (rb_scan_args(argc, argv, "01", &init) == 0)
    init = LONG2FIX(0);

  enum_sum_count(obj, init, &sum, NULL);

  return sum;
}

#value_counts(*args) ⇒ Object 



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1964

static VALUE
enum_value_counts(int argc, VALUE* argv, VALUE obj)
{
  return any_value_counts(argc, argv, obj, enum_value_counts_without_sort);
}

#variance(population: false) ⇒ Number

Calculate a variance of the values in enum. This method scan values in enum only once, and does not cache the values on memory.

When the population: keyword parameter is true, the variance is calculated as a population variance (divided by $n$). The default population: keyword parameter is false; this means the variance is a sample variance (divided by $n-1$).

Returns:

  • (Number) —

    A variance value



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# File 'ext/enumerable/statistics/extension/statistics.c', line 1349

static VALUE
enum_variance(int argc, VALUE* argv, VALUE obj)
{
  VALUE opts, variance;
  size_t ddof = 1;

  rb_scan_args(argc, argv, "0:", &opts);
  if (opt_population_p(opts))
    ddof = 0;

  enum_mean_variance(obj, NULL, &variance, ddof);
  return variance;
}