Implementation of ReadVar and ResetVar IO process and bugfixes for LIF, Dense and Conv processes

[bamsumit]

Issue Number: 155

Objective of pull request:

• Implementation of ReadVar and ResetVar IO process
• bugfixes for LIF, Dense and Conv processes

Pull request checklist

Your PR fulfills the following requirements:

• Issue created that explains the change and why it's needed
• Tests are part of the PR (for bug fixes / features)
• Docs reviewed and added / updated if needed (for bug fixes / features)
• PR conforms to Coding Conventions
• PR applys BSD 3-clause or LGPL2.1+ Licenses to all code files
• Lint (pyb) passes locally
• Build tests (pyb -E unit) or (python -m unittest) passes locally

Pull request type

Please check your PR type:

• Bugfix
• Feature
• Code style update (formatting, renaming)
• Refactoring (no functional changes, no api changes)
• Build related changes
• Documentation changes
• Other (please describe):

What is the current behavior?

• The feature does not exist.

What is the new behavior?

# Reset Var
ResetVar(existing_proc.var, reset_value, interval, offset)
# Read Var
read_proc = ReadVar(existing_proc.var, interval, offset)
... run network
data = read_proc.data.get()

Does this introduce a breaking change?

• Yes
• No

Supplemental information

[PhilippPlank]

Some minor things to change. Please also resolve the conflict in lif/models.py

[drager-intel]

Still in favor of using the same (int) data type and connection process logic for binary vs graded spikes. Maybe I will run some quick tests to see if summing the binary vectors is substantially more performative than np.dot