This PR does two things:

1. I moved `package.json` into the root directory. Why? We are using `npx` from the `Makefile` which is executing usually under the root directory. If we install `node_modules` in `src/js` then these invocations don't see `node_modules` and install an extra copy of the packages. So we want `node_modules` in the root directory. node wants to put `node_modules` in the same directory as `package.json` hence I moved `package.json`. I also updated the build rules so that any recipe that uses `npx` has a dependency on `node_modules/.installed`.
2. We invoke `file_packager.py` from both the Makefile (in two places) and from `build_pkg`. There has been some drift in which options are applied in the two places. I extracted the common options and the task of locating the `file_packager.py` script into `tools/file_packager.sh`. I also shortened the make rules for `distutils.data` and `test.data` and made some minor updates to the dev docs about `file_packager.py`.
MAINT Improvements to node and file_packager invocations. This PR does two things:

1. I moved `package.json` into the root directory. Why? We are using `npx` from the `Makefile` which is executing usually under the root directory. If we install `node_modules` in `src/js` then these invocations don't see `node_modules` and install an extra copy of the packages. So we want `node_modules` in the root directory. node wants to put `node_modules` in the same directory as `package.json` hence I moved `package.json`. I also updated the build rules so that any recipe that uses `npx` has a dependency on `node_modules/.installed`.
2. We invoke `file_packager.py` from both the Makefile (in two places) and from `build_pkg`. There has been some drift in which options are applied in the two places. I extracted the common options and the task of locating the `file_packager.py` script into `tools/file_packager.sh`. I also shortened the make rules for `distutils.data` and `test.data` and made some minor updates to the dev docs about `file_packager.py`.
# from: http://stackoverflow.com/questions/17112550/python-and-numba-for-vectorized-functions # noqa
# setup: import numpy as np ; N = 100000 ; a, b, c = np.random.rand(N), np.random.rand(N), np.random.rand(N)  # noqa
# run: vibr_energy(a, b, c)

# pythran export vibr_energy(float64[], float64[], float64[])
import numpy


def vibr_energy(harmonic, anharmonic, i):
    return numpy.exp(-harmonic * i - anharmonic * (i ** 2))

# from: http://stackoverflow.com/questions/17112550/python-and-numba-for-vectorized-functions # noqa
# setup: import numpy as np ; N = 100000 ; a, b, c = np.random.rand(N), np.random.rand(N), np.random.rand(N)  # noqa
# run: vibr_energy(a, b, c)

# pythran export vibr_energy(float64[], float64[], float64[])
import numpy


def vibr_energy(harmonic, anharmonic, i):
    return numpy.exp(-harmonic * i - anharmonic * (i ** 2))
