from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import numpy as np
from numpy.testing import assert_equal, assert_almost_equal
import pytest
import sys

import ray
import ray.experimental.array.remote as ra
import ray.experimental.array.distributed as da

if sys.version_info >= (3, 0):
    from importlib import reload


@pytest.fixture
def ray_start_regular():
    for module in [
            ra.core, ra.random, ra.linalg, da.core, da.random, da.linalg
    ]:
        reload(module)
    # Start the Ray processes.
    ray.init(num_cpus=2)
    yield None
    # The code after the yield will run as teardown code.
    ray.shutdown()


def test_remote_array_methods(ray_start_regular):
    # test eye
    object_id = ra.eye.remote(3)
    val = ray.get(object_id)
    assert_almost_equal(val, np.eye(3))

    # test zeros
    object_id = ra.zeros.remote([3, 4, 5])
    val = ray.get(object_id)
    assert_equal(val, np.zeros([3, 4, 5]))

    # test qr - pass by value
    a_val = np.random.normal(size=[10, 11])
    q_id, r_id = ra.linalg.qr.remote(a_val)
    q_val = ray.get(q_id)
    r_val = ray.get(r_id)
    assert_almost_equal(np.dot(q_val, r_val), a_val)

    # test qr - pass by objectid
    a = ra.random.normal.remote([10, 13])
    q_id, r_id = ra.linalg.qr.remote(a)
    a_val = ray.get(a)
    q_val = ray.get(q_id)
    r_val = ray.get(r_id)
    assert_almost_equal(np.dot(q_val, r_val), a_val)


def test_distributed_array_assemble(ray_start_regular):
    a = ra.ones.remote([da.BLOCK_SIZE, da.BLOCK_SIZE])
    b = ra.zeros.remote([da.BLOCK_SIZE, da.BLOCK_SIZE])
    x = da.DistArray([2 * da.BLOCK_SIZE, da.BLOCK_SIZE], np.array([[a], [b]]))
    assert_equal(
        x.assemble(),
        np.vstack([
            np.ones([da.BLOCK_SIZE, da.BLOCK_SIZE]),
            np.zeros([da.BLOCK_SIZE, da.BLOCK_SIZE])
        ]))


@pytest.fixture
def ray_start_two_nodes():
    for module in [
            ra.core, ra.random, ra.linalg, da.core, da.random, da.linalg
    ]:
        reload(module)
    # Start the Ray processes.
    ray.worker._init(
        start_ray_local=True, num_local_schedulers=2, num_cpus=[10, 10])
    yield None
    # The code after the yield will run as teardown code.
    ray.shutdown()


def test_distributed_array_methods(ray_start_two_nodes):
    x = da.zeros.remote([9, 25, 51], "float")
    assert_equal(ray.get(da.assemble.remote(x)), np.zeros([9, 25, 51]))

    x = da.ones.remote([11, 25, 49], dtype_name="float")
    assert_equal(ray.get(da.assemble.remote(x)), np.ones([11, 25, 49]))

    x = da.random.normal.remote([11, 25, 49])
    y = da.copy.remote(x)
    assert_equal(
        ray.get(da.assemble.remote(x)), ray.get(da.assemble.remote(y)))

    x = da.eye.remote(25, dtype_name="float")
    assert_equal(ray.get(da.assemble.remote(x)), np.eye(25))

    x = da.random.normal.remote([25, 49])
    y = da.triu.remote(x)
    assert_equal(
        ray.get(da.assemble.remote(y)), np.triu(
            ray.get(da.assemble.remote(x))))

    x = da.random.normal.remote([25, 49])
    y = da.tril.remote(x)
    assert_equal(
        ray.get(da.assemble.remote(y)), np.tril(
            ray.get(da.assemble.remote(x))))

    x = da.random.normal.remote([25, 49])
    y = da.random.normal.remote([49, 18])
    z = da.dot.remote(x, y)
    w = da.assemble.remote(z)
    u = da.assemble.remote(x)
    v = da.assemble.remote(y)
    assert_almost_equal(ray.get(w), np.dot(ray.get(u), ray.get(v)))
    assert_almost_equal(ray.get(w), np.dot(ray.get(u), ray.get(v)))

    # test add
    x = da.random.normal.remote([23, 42])
    y = da.random.normal.remote([23, 42])
    z = da.add.remote(x, y)
    assert_almost_equal(
        ray.get(da.assemble.remote(z)),
        ray.get(da.assemble.remote(x)) + ray.get(da.assemble.remote(y)))

    # test subtract
    x = da.random.normal.remote([33, 40])
    y = da.random.normal.remote([33, 40])
    z = da.subtract.remote(x, y)
    assert_almost_equal(
        ray.get(da.assemble.remote(z)),
        ray.get(da.assemble.remote(x)) - ray.get(da.assemble.remote(y)))

    # test transpose
    x = da.random.normal.remote([234, 432])
    y = da.transpose.remote(x)
    assert_equal(
        ray.get(da.assemble.remote(x)).T, ray.get(da.assemble.remote(y)))

    # test numpy_to_dist
    x = da.random.normal.remote([23, 45])
    y = da.assemble.remote(x)
    z = da.numpy_to_dist.remote(y)
    w = da.assemble.remote(z)
    assert_equal(
        ray.get(da.assemble.remote(x)), ray.get(da.assemble.remote(z)))
    assert_equal(ray.get(y), ray.get(w))

    # test da.tsqr
    for shape in [[123, da.BLOCK_SIZE], [7, da.BLOCK_SIZE],
                  [da.BLOCK_SIZE, da.BLOCK_SIZE], [da.BLOCK_SIZE, 7],
                  [10 * da.BLOCK_SIZE, da.BLOCK_SIZE]]:
        x = da.random.normal.remote(shape)
        K = min(shape)
        q, r = da.linalg.tsqr.remote(x)
        x_val = ray.get(da.assemble.remote(x))
        q_val = ray.get(da.assemble.remote(q))
        r_val = ray.get(r)
        assert r_val.shape == (K, shape[1])
        assert_equal(r_val, np.triu(r_val))
        assert_almost_equal(x_val, np.dot(q_val, r_val))
        assert_almost_equal(np.dot(q_val.T, q_val), np.eye(K))

    # test da.linalg.modified_lu
    def test_modified_lu(d1, d2):
        print("testing dist_modified_lu with d1 = " + str(d1) + ", d2 = " +
              str(d2))
        assert d1 >= d2
        m = ra.random.normal.remote([d1, d2])
        q, r = ra.linalg.qr.remote(m)
        l, u, s = da.linalg.modified_lu.remote(da.numpy_to_dist.remote(q))
        q_val = ray.get(q)
        ray.get(r)
        l_val = ray.get(da.assemble.remote(l))
        u_val = ray.get(u)
        s_val = ray.get(s)
        s_mat = np.zeros((d1, d2))
        for i in range(len(s_val)):
            s_mat[i, i] = s_val[i]
        # Check that q - s = l * u.
        assert_almost_equal(q_val - s_mat, np.dot(l_val, u_val))
        # Check that u is upper triangular.
        assert_equal(np.triu(u_val), u_val)
        # Check that l is lower triangular.
        assert_equal(np.tril(l_val), l_val)

    for d1, d2 in [(100, 100), (99, 98), (7, 5), (7, 7), (20, 7), (20, 10)]:
        test_modified_lu(d1, d2)

    # test dist_tsqr_hr
    def test_dist_tsqr_hr(d1, d2):
        print("testing dist_tsqr_hr with d1 = " + str(d1) + ", d2 = " +
              str(d2))
        a = da.random.normal.remote([d1, d2])
        y, t, y_top, r = da.linalg.tsqr_hr.remote(a)
        a_val = ray.get(da.assemble.remote(a))
        y_val = ray.get(da.assemble.remote(y))
        t_val = ray.get(t)
        y_top_val = ray.get(y_top)
        r_val = ray.get(r)
        tall_eye = np.zeros((d1, min(d1, d2)))
        np.fill_diagonal(tall_eye, 1)
        q = tall_eye - np.dot(y_val, np.dot(t_val, y_top_val.T))
        # Check that q.T * q = I.
        assert_almost_equal(np.dot(q.T, q), np.eye(min(d1, d2)))
        # Check that a = (I - y * t * y_top.T) * r.
        assert_almost_equal(np.dot(q, r_val), a_val)

    for d1, d2 in [(123, da.BLOCK_SIZE), (7, da.BLOCK_SIZE), (da.BLOCK_SIZE,
                                                              da.BLOCK_SIZE),
                   (da.BLOCK_SIZE, 7), (10 * da.BLOCK_SIZE, da.BLOCK_SIZE)]:
        test_dist_tsqr_hr(d1, d2)

    def test_dist_qr(d1, d2):
        print("testing qr with d1 = {}, and d2 = {}.".format(d1, d2))
        a = da.random.normal.remote([d1, d2])
        K = min(d1, d2)
        q, r = da.linalg.qr.remote(a)
        a_val = ray.get(da.assemble.remote(a))
        q_val = ray.get(da.assemble.remote(q))
        r_val = ray.get(da.assemble.remote(r))
        assert q_val.shape == (d1, K)
        assert r_val.shape == (K, d2)
        assert_almost_equal(np.dot(q_val.T, q_val), np.eye(K))
        assert_equal(r_val, np.triu(r_val))
        assert_almost_equal(a_val, np.dot(q_val, r_val))

    for d1, d2 in [(123, da.BLOCK_SIZE), (7, da.BLOCK_SIZE), (da.BLOCK_SIZE,
                                                              da.BLOCK_SIZE),
                   (da.BLOCK_SIZE, 7), (13, 21), (34, 35), (8, 7)]:
        test_dist_qr(d1, d2)
        test_dist_qr(d2, d1)
    for _ in range(20):
        d1 = np.random.randint(1, 35)
        d2 = np.random.randint(1, 35)
        test_dist_qr(d1, d2)
