Fixed residual handling bug in Arrhenius.fitToData
Fixed residual handling bug in Arrhenius.fitToData

Numpy's linalg.lstsq(A,b) will return a blank residual array if
A does not contain at least as many rows as it does columns.

Now that the database entries contain valid temperature ranges,
the website's get_rate_coefficients rendering filter was
generating tiny arrays for narrow temperature ranges, leading
to an IndexError when trying to work with the blank residual
array.

Thus, fitToData will now attempt to assign uncertainties only
if a valid residual array has been generated.

The website filter will also be updated to generate a standard
number of points for each data set regardless of temperature
range.

faribas/RMG-Py,nickvandewiele/RMG-Py,nyee/RMG-Py,KEHANG/RMG-Py,comocheng/RMG-Py,nickvandewiele/RMG-Py,pierrelb/RMG-Py,faribas/RMG-Py,KEHANG/RMG-Py,comocheng/RMG-Py,chatelak/RMG-Py,enochd/RMG-Py,chatelak/RMG-Py,enochd/RMG-Py,nyee/RMG-Py,pierrelb/RMG-Py