Interest rate modeling

[peer2f00l]

Introduces InterestRateStrategy which provides a few different strategies:

• Linear takes two parameters: the minimum interest rate (at 0% usage) and the maximum interest rate (at 100% usage) and linearly interpolates between them.

$$ r(u) = (t - b)u + b $$

• Piecewise takes four parameters: the base rate, the optimal usage ratio, and two slopes: one for 0%<->optimal%, and the other for optimal%<->100%.

$$ r(u) = \begin{cases} r_{1} u + b & \text{if } u < o \\ r_{2} u + o ( r_{1} - r_{2} ) + b \\ \end{cases} $$

• Exponential2 takes three parameters, and implements this function:

$$ r(u) = (t - b) \frac{2^{ku} - 1}{2^{k} - 1} + b $$

Additionally:

• Renames logs -> snapshots.
• Improved snapshot processing: simpler, linear algorithm.
• Contract self-reports interest and yield rates with two new functions: get_last_interest_rate and get_last_yield_rate.

[github-actions]

Staging contract is deployed to gh-34.templar-in-training.testnet account

[github-actions]

Staging contract is deployed to gh-34.templar-in-training.testnet account

[github-actions]

Staging contract is deployed to gh-34.templar-in-training.testnet account

[github-actions]

Staging contract is deployed to gh-34.templar-in-training.testnet account

[github-actions]

Staging contract is deployed to gh-34.templar-in-training.testnet account

[github-actions]

Staging contract is deployed to gh-34.templar-in-training.testnet account