Once a `DPF` generated, the *eval_* * functions are used to evaluate differents inputs.
The appropriate function depends on your specific needs. If you only need the DPF's output
for a single input value, use `eval_point`. For evaluating a continuous range of inputs,
`eval_interval` is suitable. To analyze the DPF's behavior across its entire domain, use `eval_full`.
The code likely offers different implementations of memoization and output buffers, allowing you to
optimize for memory usage or execution speed depending on your needs.\n
Using a PRG while making a `DPF` allows the user to check how much it cost to manipulate the `DPF`s.
# Memoizers
The `memoizers` remembers the most used path while the DPF is being created. These are usefull functions
to improve the speed and the cost of execution.
**Code samples**\n
For instance, in the code below the utilization of `dpf::make_basic_path_memoizer` reduced by 10 the time of execution
compare to the code that is commented that doesn't use the `memoizers`.
- memoizers.cpp \include{cpp} evaluation/memoizers.cpp
# dpf::eval_point
This function evaluate a single input of a DPF. The XOR result of the `eval_point` for both shares will only be equal to 1 if it represents the correct input in both evaluations. As input arguments it uses the `share` and the input to evaluate (note: it can't be a wildcard, otherwise it will throw an error).\n
**See also**\n
PIR
**Pro tip**\n
Use the `dpf::pathmemoizer` for a faster execution.\n
**Code samples**\n
- eval_point.cpp \include{cpp} evaluation/eval_point.cpp
# dpf::eval_interval
This function evaluates a contiguous range of inputs. As input arguments it uses the `share` generated by `make_dpf`,
`from` and `to` for the range of inputs to evaluate.\n
**See also**\n
PIR
**Code samples**\n
- eval_interval.cpp \include{cpp} evaluation/eval_interval.cpp
# dpf::eval_full
This function evaluate all the passible inputs it only uses as argument the `share` of the `DPF` to evaluate.
**Code samples**\n
- eval_full.cpp \include{cpp} evaluation/eval_full.cpp
# dpf::eval_sequence
This function evaluate a subset of inputs that is not contiguous (useful for a `DPF` made with `keyword`),
it uses as arguments the `share` generated by `make_dpf`, `from` and `to` for the subset of inputs to evaluate.\n
For a better utilization, you can use the `make_sequence_recipe` it takes as input a sorted list and returns a `recipe`.
The cost of creating is a little bit worse than just calling `eval_sequence`, however once the `recipe` created
`eval_sequence` is faster and has a better cost.
**Code samples**\n
- eval_sequence.cpp \include{cpp} evaluation/eval_sequence.cpp
# Output buffers