Increment given array (starting at offset index) with contents of this DoubleSeq, multiplied by factor f.
Increment given array (starting at offset index) with contents of this DoubleSeq, multiplied by factor f.
Return the values as an Array[Double].
Return the values as an Array[Double]. Guaranteed to be a copy, not just a pointer to an internal array that would change with changes to the DoubleSeq
Increment by the element-wise product of ds and factor.
Increment by the element-wise product of ds and factor.
Append a string representation of this DoubleSeq to the StringBuilder.
Append a string representation of this DoubleSeq to the StringBuilder.
Return the values as an Array[Double].
Return the values as an Array[Double]. Not guaranteed to be a copy; in fact if it is possible to return a pointer to an internal array, it will simply return this.
With uncopied contents
With uncopied contents
The default value at indices not covered by activeDomain.
The default value at indices not covered by activeDomain. Subclasses may override this
Assumes that the values are already normalized to sum to 1.
Assumes that the values are already normalized to sum to 1.
Exponential the elements of the array such that they are normalized to sum to one, but do so efficiently by providing logZ.
Exponential the elements of the array such that they are normalized to sum to one, but do so efficiently by providing logZ. Note that to maximize efficiency, this method does not verify that the logZ value was the correct one to cause proper normalization.
Exponentiate the elements of the array, and then normalize them to sum to one.
Exponentiate the elements of the array, and then normalize them to sum to one.
Assumes that the values are already normalized to sum to 1.
Assumes that the values are already normalized to sum to 1.
Assumes that the values in both DoubleSeq are already normalized to sum to 1.
Assumes that the values in both DoubleSeq are already normalized to sum to 1.
expNormalize, then put back into log-space.
expNormalize, then put back into log-space.
Get a normalized entry in this Masses, which can be interpreted as a probability.
Get a normalized entry in this Masses, which can be interpreted as a probability.
Careful, for many subclasses this is inefficient because it calls the method "sum" to get the normalizer.
With copied contents
With copied contents
Return records for the n elements with the largest values.
Return records for the n elements with the largest values.
A Tensor containing non-negative numbers summing to 1.0. It is the parameter of a Discrete or Multinomial distribution. Proportions contain Masses, which may not sum to 1.0; some Proportions subclasses can have their value changed by incrementing these inner masses. All Proportions also inherit directly from Masses, but, naturally, these Masses always sum to 1.0, and generally are not directly mutable.