Post History

## MoshiBot

```python
from numpy.polynomial import Polynomial
def MoshiBot(data, history):
	if len(history) < 10:
		return [180, 180, 0]

	lastmin = min(history[-1])
	lastmid = sorted(history[-1])[1]
	projectedmin = lastmin
	projectedmid = lastmid

	if len(history) >= 10:
		cutoff = len(history) - 10
		snapshot = history[cutoff:]
		minvalues = list(map(min, snapshot))
		midvalues = list(map(lambda vals: sorted(vals)[1], snapshot))
		
		xpoints = range(cutoff, cutoff + len(snapshot))
		minprojection = Polynomial.fit(xpoints, minvalues, deg=2)
		midprojection = Polynomial.fit(xpoints, midvalues, deg=2)

		projectedmin = minprojection(len(history))
		projectedmid = midprojection(len(history))

	safemin = max(0, min(360, math.ceil(projectedmin + 1)))

	if safemin >= 180:
		# The model broke down
		return [180, 180, 0]
	
	mid = math.floor(180 - safemin / 2)
	
	if mid > projectedmid:
		return [safemin, mid, 360 - safemin - mid]
	else:
		mid = max(safemin, min(360 - safemin, math.ceil(projectedmid + 1)))
		return [safemin, mid, 360 - safemin - mid]
```

Attempts to predict the opponents next move using a regressive model.