Switch build system to use CMake completely. (#200)

* switch to CMake completely

...

* cleanup

* Run C tests, update installation instructions.

python/ray/experimental/array/remote/core.py

@@ -0,0 +1,86 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+import ray
+
+__all__ = ["zeros", "zeros_like", "ones", "eye", "dot", "vstack", "hstack", "subarray", "copy", "tril", "triu", "diag", "transpose", "add", "subtract", "sum", "shape", "sum_list"]
+
+@ray.remote
+def zeros(shape, dtype_name="float", order="C"):
+  return np.zeros(shape, dtype=np.dtype(dtype_name), order=order)
+
+@ray.remote
+def zeros_like(a, dtype_name="None", order="K", subok=True):
+  dtype_val = None if dtype_name == "None" else np.dtype(dtype_name)
+  return np.zeros_like(a, dtype=dtype_val, order=order, subok=subok)
+
+@ray.remote
+def ones(shape, dtype_name="float", order="C"):
+  return np.ones(shape, dtype=np.dtype(dtype_name), order=order)
+
+@ray.remote
+def eye(N, M=-1, k=0, dtype_name="float"):
+  M = N if M == -1 else M
+  return np.eye(N, M=M, k=k, dtype=np.dtype(dtype_name))
+
+@ray.remote
+def dot(a, b):
+  return np.dot(a, b)
+
+@ray.remote
+def vstack(*xs):
+  return np.vstack(xs)
+
+@ray.remote
+def hstack(*xs):
+  return np.hstack(xs)
+
+# TODO(rkn): instead of this, consider implementing slicing
+@ray.remote
+def subarray(a, lower_indices, upper_indices): # TODO(rkn): be consistent about using "index" versus "indices"
+  return a[[slice(l, u) for (l, u) in zip(lower_indices, upper_indices)]]
+
+@ray.remote
+def copy(a, order="K"):
+  return np.copy(a, order=order)
+
+@ray.remote
+def tril(m, k=0):
+  return np.tril(m, k=k)
+
+@ray.remote
+def triu(m, k=0):
+  return np.triu(m, k=k)
+
+@ray.remote
+def diag(v, k=0):
+  return np.diag(v, k=k)
+
+@ray.remote
+def transpose(a, axes=[]):
+  axes = None if axes == [] else axes
+  return np.transpose(a, axes=axes)
+
+@ray.remote
+def add(x1, x2):
+  return np.add(x1, x2)
+
+@ray.remote
+def subtract(x1, x2):
+  return np.subtract(x1, x2)
+
+@ray.remote
+def sum(x, axis=-1):
+  return np.sum(x, axis=axis if axis != -1 else None)
+
+@ray.remote
+def shape(a):
+  return np.shape(a)
+
+# We use Any to allow different numerical types as well as numpy arrays.
+# TODO(rkn):this isn't in the numpy API, so be careful about exposing this.
+@ray.remote
+def sum_list(*xs):
+  return np.sum(xs, axis=0)