GitLab

Further improvements to multi-GPU performance

Improvements to multi-GPU performance

testInstallation.py gives more information about errors

Fix compatibility with `unit.Quantity` and numpy arrays by having array methods accept and pass through relevant arguments.

range check getPlatform()

Add a test for the various numpy attributes (and the arguments they take) for
the unit module.

Traceback (most recent call last):
  File ".../python/tests/TestNumpyCompatibility.py", line 87, in testNumpyAttributes
    d = self.data.reshape((100, 3))
  File ".../simtk/unit/quantity.py", line 575, in reshape
    return Quantity(self._value.reshape(shape, order=order))
  File ".../simtk/unit/quantity.py", line 142, in __init__
    if value == first_item:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Also add a test for new unit numpy capabilities.

Updated broken links in travis badge in README

If CUDA or OpenCL is not being built, default to not building the corresponding plugins

underlying numpy array. This function would be used in instances where, for
instance, a certain API would send a flattened array of coordinates or
velocities with units attached, and you wanted to reshape the array into
(natom, 3) to be consistent with OpenMM's Context object.

arguments and pass them to the numpy function if applicable. That way, users get
the full flexibility of the numpy API on those particular methods AND get the
added benefit that the result has the correct units (and it all runs fast).

Minor updates to manual for 6.2.

Checked in install.sh script

Updated version number to 6.2

Reduced share memory for CustomGBForce

Added manifests to use for creating source and binary distributions

Added 64 bit version of Windows pthreads library

Mac builds are 64 bit only by default

Handle hex values for atom and residue numbers

Minor optimization to discrete tabulated functions

Optimizations to the custom GB models

Optimizations to multi-GPU calculations