DictWrapper

DictWrapper(values, name)

An base class for generation an object contains a dictionary.

@Params:

param	type	description
values	string	array
name	string	sequence of values

@Methods:

.initSequence(values)

Initializes with a sequence of equally-likely values.

@Params:

param	type	description
values	array	sequence of values

.initMapping(values)

Initializes with a map from value to probability.

@Params:

param	type	description
values	map	map from value to probability

.initPmf(values)

Initializes with a Pmf.

@Params:

param	type	description
values	pmf	Pmf object

.initFailure(values)

Throw an error.

.values()

Gets an unsorted sequence of values.

Note: One source of confusion is that the keys of this

dictionary are the values of the Hist/Pmf, and the

values of the dictionary are frequencies/probabilities.

.items()

Gets an unsorted sequence of (value, freq/prob) pairs.

.set(value, prob)

Sets the freq/prob associated with the value x.

@Params:

param	type	description
value	any	number value or case name
prob	number	number freq or prob

.incr(x, term = 1)

Increments the freq/prob associated with the value x.

@Params:

param	type	description
x	any	number value or case name
term	number	how much to increment by

.mult(x, factor = 1)

Scales the freq/prob associated with the value x.

@Params:

param	type	description
x	any	number value or case name
factor	number	how much to multiply by

.remove(value)

Removes a value.

Throws an exception if the value is not there.

@Params:

param	type	description
value	any	value to remove

.total()

Returns the total of the frequencies/probabilities in the map.

.maxLike()

Returns the largest frequency/probability in the map.

.copy(name)

Returns a copy.

Make a shallow copy of d. If you want a deep copy of d,

use one method to deep clone the whole object.

@Params:

param	type	description
name	string	string name for the new Hist

@Returns: new object

.scale(factor)

Multiplies the values by a factor.

@Params:

param	type	description
factor	number	what to multiply by

@Returns: new object

.log(m)

Log transforms the probabilities.

Removes values with probability 0.

Normalizes so that the largest logprob is 0.

@Params:

param	type	description
m	number	how much to shift the ps before exponentiating

.exp(m)

Exponentiates the probabilities.

If m is un-exist, normalizes so that the largest prob is 1.

@Params:

param	type	description
m	number	how much to shift the ps before exponentiating

.getDict()

Gets the dictionary.

.setDict(d)

Sets the dictionary.

@Params:

param	type	description
d	map	object

.render()

Generates a sequence of points suitable for plotting.

@Returns: array of [sorted value sequence, freq/prob sequence]

.print()

Prints the values and freqs/probs in ascending order.

@Params:

param	type	description
indent