import pytest
from numpy.testing import assert_array_equal, assert_equal

from brian2 import *
from brian2.core.network import schedule_propagation_offset
from brian2.devices.device import reinit_and_delete
from brian2.tests.utils import assert_allclose
from brian2.units.fundamentalunits import DIMENSIONLESS
from brian2.utils.logger import catch_logs


@pytest.mark.codegen_independent
def test_str_repr():
    """
    Test the string representation of a subgroup.
    """
    G = NeuronGroup(10, "v:1")
    SG = G[5:8]
    # very basic test, only make sure no error is raised
    assert len(str(SG))
    assert len(repr(SG))


def test_state_variables():
    """
    Test the setting and accessing of state variables in subgroups.
    """
    G = NeuronGroup(10, "v : volt")
    SG = G[4:9]
    with pytest.raises(DimensionMismatchError):
        SG.__setattr__("v", -70)
    SG.v_ = float(-80 * mV)
    assert_allclose(G.v, np.array([0, 0, 0, 0, -80, -80, -80, -80, -80, 0]) * mV)
    assert_allclose(SG.v, np.array([-80, -80, -80, -80, -80]) * mV)
    assert_allclose(
        G.v_, np.array([0, 0, 0, 0, -80, -80, -80, -80, -80, 0]) * float(mV)
    )
    assert_allclose(SG.v_, np.array([-80, -80, -80, -80, -80]) * float(mV))
    # You should also be able to set variables with a string
    SG.v = "v + i*mV"
    assert_allclose(SG.v[0], -80 * mV)
    assert_allclose(SG.v[4], -76 * mV)
    assert_allclose(G.v[4:9], -80 * mV + np.arange(5) * mV)

    # Calculating with state variables should work too
    assert all(G.v[4:9] - SG.v == 0)

    # And in-place modification should work as well
    SG.v += 10 * mV
    assert_allclose(G.v[4:9], -70 * mV + np.arange(5) * mV)
    SG.v *= 2
    assert_allclose(G.v[4:9], 2 * (-70 * mV + np.arange(5) * mV))
    # with unit checking
    with pytest.raises(DimensionMismatchError):
        SG.v.__iadd__(3 * second)
    with pytest.raises(DimensionMismatchError):
        SG.v.__iadd__(3)
    with pytest.raises(DimensionMismatchError):
        SG.v.__imul__(3 * second)

    # Indexing with subgroups
    assert_equal(G.v[SG], SG.v[:])


@pytest.mark.standalone_compatible
def test_state_variables_simple():
    G = NeuronGroup(
        10,
        """
        a : 1
        b : 1
        c : 1
        d : 1
        """,
    )
    SG = G[3:7]
    SG.a = 1
    SG.a["i == 0"] = 2
    SG.b = "i"
    SG.b["i == 3"] = "i * 2"
    SG.c = np.arange(3, 7)
    SG.d[1:2] = 4
    SG.d[2:4] = [1, 2]
    run(0 * ms)
    assert_equal(G.a[:], [0, 0, 0, 2, 1, 1, 1, 0, 0, 0])
    assert_equal(G.b[:], [0, 0, 0, 0, 1, 2, 6, 0, 0, 0])
    assert_equal(G.c[:], [0, 0, 0, 3, 4, 5, 6, 0, 0, 0])
    assert_equal(G.d[:], [0, 0, 0, 0, 4, 1, 2, 0, 0, 0])


def test_state_variables_string_indices():
    """
    Test accessing subgroups with string indices.
    """
    G = NeuronGroup(10, "v : volt")
    SG = G[4:9]
    assert len(SG.v["i>3"]) == 1

    G.v = np.arange(10) * mV
    assert len(SG.v["v>7.5*mV"]) == 1

    # Combined string indexing and assignment
    SG.v["i > 3"] = "i*10*mV"

    assert_allclose(G.v[:], [0, 1, 2, 3, 4, 5, 6, 7, 40, 9] * mV)


@pytest.mark.codegen_independent
def test_state_variables_group_as_index():
    G = NeuronGroup(10, "v : 1")
    SG = G[4:9]
    G.v[SG] = 1
    assert_equal(G.v[:], np.array([0, 0, 0, 0, 1, 1, 1, 1, 1, 0]))
    G.v = 1
    G.v[SG] = "2*v"
    assert_equal(G.v[:], np.array([1, 1, 1, 1, 2, 2, 2, 2, 2, 1]))


@pytest.mark.codegen_independent
def test_state_variables_group_as_index_problematic():
    G = NeuronGroup(10, "v : 1")
    SG = G[4:9]
    G.v = 1
    tests = [("i", 1), ("N", 1), ("N + i", 2), ("v", 0)]
    for value, n_warnings in tests:
        with catch_logs() as l:
            G.v.__setitem__(SG, value)
            assert (
                len(l) == n_warnings
            ), f"expected {int(n_warnings)}, got {len(l)} warnings"
            assert all(
                [entry[1].endswith("ambiguous_string_expression") for entry in l]
            )


@pytest.mark.standalone_compatible
def test_variableview_calculations():
    # Check that you can directly calculate with "variable views"
    G = NeuronGroup(
        10,
        """
        x : 1
        y : volt
        idx : integer
        """,
    )
    G.x = np.arange(10)
    G.y = np.arange(10)[::-1] * mV
    G.idx = np.arange(10, dtype=int)
    SG = G[3:8]

    assert_allclose(SG.x * SG.y, np.arange(3, 8) * np.arange(6, 1, -1) * mV)
    assert_allclose(-SG.x, -np.arange(3, 8))
    assert_allclose(-SG.y, -np.arange(6, 1, -1) * mV)

    assert_allclose(3 * SG.x, 3 * np.arange(3, 8))
    assert_allclose(3 * SG.y, 3 * np.arange(6, 1, -1) * mV)
    assert_allclose(SG.x * 3, 3 * np.arange(3, 8))
    assert_allclose(SG.y * 3, 3 * np.arange(6, 1, -1) * mV)
    assert_allclose(SG.x / 2.0, np.arange(3, 8) / 2.0)
    assert_allclose(SG.y / 2, np.arange(6, 1, -1) * mV / 2)
    assert_equal(SG.idx % 2, np.arange(3, 8, dtype=int) % 2)
    assert_allclose(SG.x + 2, 2 + np.arange(3, 8))
    assert_allclose(SG.y + 2 * mV, 2 * mV + np.arange(6, 1, -1) * mV)
    assert_allclose(2 + SG.x, 2 + np.arange(3, 8))
    assert_allclose(2 * mV + SG.y, 2 * mV + np.arange(6, 1, -1) * mV)
    assert_allclose(SG.x - 2, np.arange(3, 8) - 2)
    assert_allclose(SG.y - 2 * mV, np.arange(6, 1, -1) * mV - 2 * mV)
    assert_allclose(2 - SG.x, 2 - np.arange(3, 8))
    assert_allclose(2 * mV - SG.y, 2 * mV - np.arange(6, 1, -1) * mV)
    assert_allclose(SG.x**2, np.arange(3, 8) ** 2)
    assert_allclose(SG.y**2, (np.arange(6, 1, -1) * mV) ** 2)
    assert_allclose(2**SG.x, 2 ** np.arange(3, 8))

    # incorrect units
    with pytest.raises(DimensionMismatchError):
        SG.x + SG.y
    with pytest.raises(DimensionMismatchError):
        SG.x[:] + SG.y
    with pytest.raises(DimensionMismatchError):
        SG.x + SG.y[:]
    with pytest.raises(DimensionMismatchError):
        SG.x + 3 * mV
    with pytest.raises(DimensionMismatchError):
        3 * mV + SG.x
    with pytest.raises(DimensionMismatchError):
        SG.y + 3
    with pytest.raises(DimensionMismatchError):
        3 + SG.y
    with pytest.raises(TypeError):
        2**SG.y  # raising to a power with units


@pytest.mark.standalone_compatible
def test_variableview_properties():
    G = NeuronGroup(
        10,
        """
    x : 1
    y : volt
    idx : integer
    """,
    )
    # The below properties should not require access to the values
    G.x = "rand()"
    G.y = "rand()*mV"
    G.idx = "int(rand()*10)"
    SG = G[3:8]

    assert have_same_dimensions(SG.x.unit, DIMENSIONLESS)
    assert have_same_dimensions(SG.y.unit, volt)
    assert have_same_dimensions(SG.idx.unit, DIMENSIONLESS)
    # See github issue #1555
    assert SG.x.shape == SG.y.shape == SG.idx.shape == (5,)
    assert SG.x.ndim == SG.y.ndim == SG.idx.ndim == 1
    assert SG.x.dtype == SG.y.dtype == prefs.core.default_float_dtype
    assert SG.idx.dtype == np.int32


@pytest.mark.standalone_compatible
def test_state_monitor():
    G = NeuronGroup(10, "v : volt")
    G.v = np.arange(10) * volt
    SG = G[5:]
    mon_all = StateMonitor(SG, "v", record=True)
    mon_0 = StateMonitor(SG, "v", record=0)
    run(defaultclock.dt)

    assert_allclose(mon_0[0].v, mon_all[0].v)
    assert_allclose(mon_0[0].v, np.array([5]) * volt)
    assert_allclose(mon_all.v.flatten(), np.arange(5, 10) * volt)

    with pytest.raises(IndexError):
        mon_all[5]


def test_shared_variable():
    """Make sure that shared variables work with subgroups"""
    G = NeuronGroup(10, "v : volt (shared)")
    G.v = 1 * volt
    SG = G[5:]
    assert SG.v == 1 * volt


@pytest.mark.standalone_compatible
def test_synapse_creation():
    G1 = NeuronGroup(10, "")
    G2 = NeuronGroup(20, "")
    SG1 = G1[:5]
    SG2 = G2[10:]
    S = Synapses(SG1, SG2)
    S.connect(i=2, j=2)  # Should correspond to (2, 12)
    S.connect("i==2 and j==5")  # Should correspond to (2, 15)

    run(0 * ms)  # for standalone

    # Internally, the "real" neuron indices should be used
    assert_equal(S._synaptic_pre[:], np.array([2, 2]))
    assert_equal(S._synaptic_post[:], np.array([12, 15]))
    # For the user, the subgroup-relative indices should be presented
    assert_equal(S.i[:], np.array([2, 2]))
    assert_equal(S.j[:], np.array([2, 5]))
    # N_incoming and N_outgoing should also be correct
    assert all(S.N_outgoing[2, :] == 2)
    assert all(S.N_incoming[:, 2] == 1)
    assert all(S.N_incoming[:, 5] == 1)


@pytest.mark.standalone_compatible
def test_synapse_creation_state_vars():
    G1 = NeuronGroup(10, "v : 1")
    G2 = NeuronGroup(20, "v : 1")
    G1.v = "i"
    G2.v = "10 + i"
    SG1 = G1[:5]
    SG2 = G2[10:]

    # connect based on pre-/postsynaptic state variables
    S2 = Synapses(SG1, SG2, "w:1")
    S2.connect("v_pre > 2")

    S3 = Synapses(SG1, SG2, "w:1")
    S3.connect("v_post < 25")

    S4 = Synapses(SG2, SG1, "w:1")
    S4.connect("v_post > 2")

    S5 = Synapses(SG2, SG1, "w:1")
    S5.connect("v_pre < 25")

    run(0 * ms)  # for standalone

    assert len(S2) == 2 * len(SG2), str(len(S2))
    assert all(S2.v_pre[:] > 2)
    assert len(S3) == 5 * len(SG1), f"{len(S3)} != {5 * len(SG1)} "
    assert all(S3.v_post[:] < 25)

    assert len(S4) == 2 * len(SG2), str(len(S4))
    assert all(S4.v_post[:] > 2)
    assert len(S5) == 5 * len(SG1), f"{len(53)} != {5 * len(SG1)} "
    assert all(S5.v_pre[:] < 25)


@pytest.mark.standalone_compatible
def test_synapse_creation_generator():
    G1 = NeuronGroup(10, "v:1")
    G2 = NeuronGroup(20, "v:1")
    G1.v = "i"
    G2.v = "10 + i"
    SG1 = G1[:5]
    SG2 = G2[10:]
    S = Synapses(SG1, SG2, "w:1")
    S.connect(j="i*2 + k for k in range(2)")  # diverging connections

    # connect based on pre-/postsynaptic state variables
    S2 = Synapses(SG1, SG2, "w:1")
    S2.connect(j="k for k in range(N_post) if v_pre > 2")

    S3 = Synapses(SG1, SG2, "w:1")
    S3.connect(j="k for k in range(N_post) if v_post < 25")

    S4 = Synapses(SG2, SG1, "w:1")
    S4.connect(j="k for k in range(N_post) if v_post > 2")

    S5 = Synapses(SG2, SG1, "w:1")
    S5.connect(j="k for k in range(N_post) if v_pre < 25")

    run(0 * ms)  # for standalone

    # Internally, the "real" neuron indices should be used
    assert_equal(S._synaptic_pre[:], np.arange(5).repeat(2))
    assert_equal(S._synaptic_post[:], np.arange(10) + 10)
    # For the user, the subgroup-relative indices should be presented
    assert_equal(S.i[:], np.arange(5).repeat(2))
    assert_equal(S.j[:], np.arange(10))

    # N_incoming and N_outgoing should also be correct
    assert all(S.N_outgoing[:] == 2)
    assert all(S.N_incoming[:] == 1)

    assert len(S2) == 2 * len(SG2), str(len(S2))
    assert all(S2.v_pre[:] > 2)
    assert len(S3) == 5 * len(SG1), f"{len(S3)} != {5 * len(SG1)} "
    assert all(S3.v_post[:] < 25)

    assert len(S4) == 2 * len(SG2), str(len(S4))
    assert all(S4.v_post[:] > 2)
    assert len(S5) == 5 * len(SG1), f"{len(S5)} != {5 * len(SG1)} "
    assert all(S5.v_pre[:] < 25)


@pytest.mark.standalone_compatible
def test_synapse_creation_generator_multiple_synapses():
    G1 = NeuronGroup(10, "v:1")
    G2 = NeuronGroup(20, "v:1")
    G1.v = "i"
    G2.v = "10 + i"
    SG1 = G1[:5]
    SG2 = G2[10:]
    S1 = Synapses(SG1, SG2)
    S1.connect(j="k for k in range(N_post)", n="i")

    S2 = Synapses(SG1, SG2)
    S2.connect(j="k for k in range(N_post)", n="j")

    S3 = Synapses(SG2, SG1)
    S3.connect(j="k for k in range(N_post)", n="i")

    S4 = Synapses(SG2, SG1)
    S4.connect(j="k for k in range(N_post)", n="j")

    S5 = Synapses(SG1, SG2)
    S5.connect(j="k for k in range(N_post)", n="i+j")

    S6 = Synapses(SG2, SG1)
    S6.connect(j="k for k in range(N_post)", n="i+j")

    S7 = Synapses(SG1, SG2)
    S7.connect(j="k for k in range(N_post)", n="int(v_pre>2)*2")

    S8 = Synapses(SG2, SG1)
    S8.connect(j="k for k in range(N_post)", n="int(v_post>2)*2")

    S9 = Synapses(SG1, SG2)
    S9.connect(j="k for k in range(N_post)", n="int(v_post>22)*2")

    S10 = Synapses(SG2, SG1)
    S10.connect(j="k for k in range(N_post)", n="int(v_pre>22)*2")

    run(0 * ms)  # for standalone

    # straightforward loop instead of doing something clever...
    for source in range(len(SG1)):
        assert_equal(S1.j[source, :], np.arange(len(SG2)).repeat(source))
        assert_equal(S2.j[source, :], np.arange(len(SG2)).repeat(np.arange(len(SG2))))
        assert_equal(S3.i[:, source], np.arange(len(SG2)).repeat(np.arange(len(SG2))))
        assert_equal(S4.i[:, source], np.arange(len(SG2)).repeat(source))
        assert_equal(
            S5.j[source, :], np.arange(len(SG2)).repeat(np.arange(len(SG2)) + source)
        )
        assert_equal(
            S6.i[:, source], np.arange(len(SG2)).repeat(np.arange(len(SG2)) + source)
        )
        if source > 2:
            assert_equal(S7.j[source, :], np.arange(len(SG2)).repeat(2))
            assert_equal(S8.i[:, source], np.arange(len(SG2)).repeat(2))
        else:
            assert len(S7.j[source, :]) == 0
            assert len(S8.i[:, source]) == 0
        assert_equal(S9.j[source, :], np.arange(3, len(SG2)).repeat(2))
        assert_equal(S10.i[:, source], np.arange(3, len(SG2)).repeat(2))


@pytest.mark.standalone_compatible
def test_synapse_creation_generator_complex_ranges():
    G1 = NeuronGroup(10, "v:1")
    G2 = NeuronGroup(20, "v:1")
    G1.v = "i"
    G2.v = "10 + i"
    SG1 = G1[:5]
    SG2 = G2[10:]
    S = Synapses(SG1, SG2)
    S.connect(j="i+k for k in range(N_post-i)")  # Connect to all j>i

    # connect based on pre-/postsynaptic state variables
    S2 = Synapses(SG1, SG2)
    S2.connect(j="k for k in range(N_post * int(v_pre > 2))")

    # connect based on pre-/postsynaptic state variables
    S3 = Synapses(SG2, SG1)
    S3.connect(j="k for k in range(N_post * int(v_pre > 22))")

    run(0 * ms)  # for standalone

    for syn_source in range(5):
        # Internally, the "real" neuron indices should be used
        assert_equal(
            S._synaptic_post[syn_source, :],
            10 + syn_source + np.arange(10 - syn_source),
        )
        # For the user, the subgroup-relative indices should be presented
        assert_equal(S.j[syn_source, :], syn_source + np.arange(10 - syn_source))

    assert len(S2) == 2 * len(SG2), str(len(S2))
    assert all(S2.v_pre[:] > 2)
    assert len(S3) == 7 * len(SG1), str(len(S3))
    assert all(S3.v_pre[:] > 22)


@pytest.mark.standalone_compatible
def test_synapse_creation_generator_random():
    G1 = NeuronGroup(10, "v:1")
    G2 = NeuronGroup(20, "v:1")
    G1.v = "i"
    G2.v = "10 + i"
    SG1 = G1[:5]
    SG2 = G2[10:]

    # connect based on pre-/postsynaptic state variables
    S2 = Synapses(SG1, SG2)
    S2.connect(j="k for k in sample(N_post, p=1.0*int(v_pre > 2))")

    S3 = Synapses(SG2, SG1)
    S3.connect(j="k for k in sample(N_post, p=1.0*int(v_pre > 22))")

    run(0 * ms)  # for standalone

    assert len(S2) == 2 * len(SG2), str(len(S2))
    assert all(S2.v_pre[:] > 2)
    assert len(S3) == 7 * len(SG1), str(len(S3))
    assert all(S3.v_pre[:] > 22)


def test_synapse_access():
    G1 = NeuronGroup(10, "v:1")
    G1.v = "i"
    G2 = NeuronGroup(20, "v:1")
    G2.v = "i"
    SG1 = G1[:5]
    SG2 = G2[10:]
    S = Synapses(SG1, SG2, "w:1")
    S.connect(True)
    S.w["j == 0"] = 5
    assert all(S.w["j==0"] == 5)
    S.w[2, 2] = 7
    assert all(S.w["i==2 and j==2"] == 7)
    S.w = "2*j"
    assert all(S.w[:, 1] == 2)

    assert len(S.w[:, 10]) == 0
    assert len(S.w["j==10"]) == 0

    # Test referencing pre- and postsynaptic variables
    assert_equal(S.w[2:, :], S.w["v_pre >= 2"])
    assert_equal(S.w[:, :5], S.w["v_post < 15"])
    S.w = "v_post"
    assert_equal(S.w[:], S.j[:] + 10)
    S.w = "v_post + v_pre"
    assert_equal(S.w[:], S.j[:] + 10 + S.i[:])

    # Test using subgroups as indices
    assert len(S) == len(S.w[SG1, SG2])
    assert_equal(S.w[SG1, 1], S.w[:, 1])
    assert_equal(S.w[1, SG2], S.w[1, :])
    assert len(S.w[SG1, 10]) == 0


def test_synapses_access_subgroups():
    G1 = NeuronGroup(5, "x:1")
    G2 = NeuronGroup(10, "y:1")
    SG1 = G1[2:5]
    SG2 = G2[4:9]
    S = Synapses(G1, G2, "w:1")
    S.connect()
    S.w[SG1, SG2] = 1
    assert_equal(S.w["(i>=2 and i<5) and (j>=4 and j<9)"], 1)
    assert_equal(S.w["not ((i>=2 and i<5) and (j>=4 and j<9))"], 0)
    S.w = 0
    S.w[SG1, :] = 1
    assert_equal(S.w["i>=2 and i<5"], 1)
    assert_equal(S.w["not (i>=2 and i<5)"], 0)
    S.w = 0
    S.w[:, SG2] = 1
    assert_equal(S.w["j>=4 and j<9"], 1)
    assert_equal(S.w["not (j>=4 and j<9)"], 0)


@pytest.mark.codegen_independent
def test_synapses_access_subgroups_problematic():
    G1 = NeuronGroup(5, "x:1")
    G2 = NeuronGroup(10, "y:1")
    SG1 = G1[2:5]
    SG2 = G2[4:9]
    S = Synapses(G1, G2, "w:1")
    S.connect()

    # Note that "j" is not ambiguous, because the equivalent in the target group
    # is called "i" (this previously raised a warning)
    tests = [
        ((SG1, slice(None)), "i", 1),
        ((SG1, slice(None)), "i + N_pre", 2),
        ((SG1, slice(None)), "N_pre", 1),
        ((slice(None), SG2), "j", 0),
        ((slice(None), SG2), "N_post", 1),
        ((slice(None), SG2), "N", 1),
        ((SG1, SG2), "i", 1),
        ((SG1, SG2), "i + j", 1),
        ((SG1, SG2), "N_pre", 1),
        ((SG1, SG2), "j", 0),
        ((SG1, SG2), "N_post", 1),
        ((SG1, SG2), "N", 1),
        # These should not raise a warning
        ((SG1, SG2), "w", 0),
        ((SG1, SG2), "x_pre", 0),
        ((SG1, SG2), "y_post", 0),
        ((SG1, SG2), "y", 0),
    ]
    for item, value, n_warnings in tests:
        with catch_logs() as l:
            S.w.__setitem__(item, value)
            assert (
                len(l) == n_warnings
            ), f"expected {int(n_warnings)}, got {len(l)} warnings"
            assert all(
                [entry[1].endswith("ambiguous_string_expression") for entry in l]
            )


@pytest.mark.standalone_compatible
def test_subgroup_summed_variable():
    # Check in particular that only neurons targeted are reset to 0 (see github issue #925)
    source = NeuronGroup(1, "")
    target = NeuronGroup(5, "Iin : 1")
    target.Iin = 10
    target1 = target[1:2]
    target2 = target[3:]

    syn1 = Synapses(source, target1, "Iin_post = 5 : 1  (summed)")
    syn1.connect(True)
    syn2 = Synapses(source, target2, "Iin_post = 1 : 1  (summed)")
    syn2.connect(True)

    run(2 * defaultclock.dt)

    assert_array_equal(target.Iin, [10, 5, 10, 1, 1])


def test_subexpression_references():
    """
    Assure that subexpressions in targeted groups are handled correctly.
    """
    G = NeuronGroup(
        10,
        """
        v : 1
        v2 = 2*v : 1
        """,
    )
    G.v = np.arange(10)
    SG1 = G[:5]
    SG2 = G[5:]

    S1 = Synapses(
        SG1,
        SG2,
        """
        w : 1
        u = v2_post + 1 : 1
        x = v2_pre + 1 : 1
        """,
    )
    S1.connect("i==(5-1-j)")
    assert_equal(S1.i[:], np.arange(5))
    assert_equal(S1.j[:], np.arange(5)[::-1])
    assert_equal(S1.u[:], np.arange(10)[:-6:-1] * 2 + 1)
    assert_equal(S1.x[:], np.arange(5) * 2 + 1)

    S2 = Synapses(
        G,
        SG2,
        """
        w : 1
        u = v2_post + 1 : 1
        x = v2_pre + 1 : 1
        """,
    )
    S2.connect("i==(5-1-j)")
    assert_equal(S2.i[:], np.arange(5))
    assert_equal(S2.j[:], np.arange(5)[::-1])
    assert_equal(S2.u[:], np.arange(10)[:-6:-1] * 2 + 1)
    assert_equal(S2.x[:], np.arange(5) * 2 + 1)

    S3 = Synapses(
        SG1,
        G,
        """
        w : 1
        u = v2_post + 1 : 1
        x = v2_pre + 1 : 1
        """,
    )
    S3.connect("i==(10-1-j)")
    assert_equal(S3.i[:], np.arange(5))
    assert_equal(S3.j[:], np.arange(10)[:-6:-1])
    assert_equal(S3.u[:], np.arange(10)[:-6:-1] * 2 + 1)
    assert_equal(S3.x[:], np.arange(5) * 2 + 1)


def test_subexpression_no_references():
    """
    Assure that subexpressions  are handled correctly, even
    when the subgroups are created on-the-fly.
    """
    G = NeuronGroup(
        10,
        """
        v : 1
        v2 = 2*v : 1
        """,
    )
    G.v = np.arange(10)

    assert_equal(G[5:].v2, np.arange(5, 10) * 2)

    S1 = Synapses(
        G[:5],
        G[5:],
        """
        w : 1
        u = v2_post + 1 : 1
        x = v2_pre + 1 : 1
        """,
    )
    S1.connect("i==(5-1-j)")
    assert_equal(S1.i[:], np.arange(5))
    assert_equal(S1.j[:], np.arange(5)[::-1])
    assert_equal(S1.u[:], np.arange(10)[:-6:-1] * 2 + 1)
    assert_equal(S1.x[:], np.arange(5) * 2 + 1)

    S2 = Synapses(
        G,
        G[5:],
        """
        w : 1
        u = v2_post + 1 : 1
        x = v2_pre + 1 : 1
        """,
    )
    S2.connect("i==(5-1-j)")
    assert_equal(S2.i[:], np.arange(5))
    assert_equal(S2.j[:], np.arange(5)[::-1])
    assert_equal(S2.u[:], np.arange(10)[:-6:-1] * 2 + 1)
    assert_equal(S2.x[:], np.arange(5) * 2 + 1)

    S3 = Synapses(
        G[:5],
        G,
        """
        w : 1
        u = v2_post + 1 : 1
        x = v2_pre + 1 : 1
        """,
    )
    S3.connect("i==(10-1-j)")
    assert_equal(S3.i[:], np.arange(5))
    assert_equal(S3.j[:], np.arange(10)[:-6:-1])
    assert_equal(S3.u[:], np.arange(10)[:-6:-1] * 2 + 1)
    assert_equal(S3.x[:], np.arange(5) * 2 + 1)


@pytest.mark.standalone_compatible
def test_synaptic_propagation():
    G1 = NeuronGroup(10, "v:1", threshold="v>1", reset="v=0")
    G1.v["i%2==1"] = 1.1  # odd numbers should spike
    G2 = NeuronGroup(20, "v:1")
    SG1 = G1[1:6]
    SG2 = G2[10:]
    S = Synapses(SG1, SG2, on_pre="v+=1")
    S.connect("i==j")
    run(defaultclock.dt + schedule_propagation_offset())
    expected = np.zeros(len(G2))
    # Neurons 1, 3, 5 spiked and are connected to 10, 12, 14
    expected[[10, 12, 14]] = 1
    assert_equal(np.asarray(G2.v).flatten(), expected)


@pytest.mark.standalone_compatible
def test_synaptic_propagation_2():
    # This tests for the bug in github issue #461
    source = NeuronGroup(100, "", threshold="True")
    sub_source = source[99:]
    target = NeuronGroup(1, "v:1")
    syn = Synapses(sub_source, target, on_pre="v+=1")
    syn.connect()
    run(defaultclock.dt + schedule_propagation_offset())
    assert target.v[0] == 1.0


@pytest.mark.standalone_compatible
def test_run_regularly():
    # See github issue #922

    group = NeuronGroup(10, "v: integer")
    # Full group
    group.run_regularly("v += 16")
    # Subgroup with explicit reference
    subgroup = group[:2]
    subgroup.run_regularly("v += 8")
    # Subgroup with explicit reference and reference for run_regularly operation
    subgroup2 = group[2:4]
    updater = subgroup2.run_regularly("v += 4")
    # Subgroup without reference
    group[4:6].run_regularly("v += 2")
    # Subgroup without reference, with reference for run_regularly operation
    updater2 = group[6:8].run_regularly("v += 1")

    run(defaultclock.dt)
    assert_array_equal(group.v, [24, 24, 20, 20, 18, 18, 17, 17, 16, 16])


@pytest.mark.standalone_compatible
def test_spike_monitor():
    G = NeuronGroup(10, "v:1", threshold="v>1", reset="v=0")
    G.v[0] = 1.1
    G.v[2] = 1.1
    G.v[5] = 1.1
    SG = G[3:]
    SG2 = G[:3]
    s_mon = SpikeMonitor(G)
    sub_s_mon = SpikeMonitor(SG)
    sub_s_mon2 = SpikeMonitor(SG2)
    run(defaultclock.dt)
    assert_equal(s_mon.i, np.array([0, 2, 5]))
    assert_equal(s_mon.t_, np.zeros(3))
    assert_equal(sub_s_mon.i, np.array([2]))
    assert_equal(sub_s_mon.t_, np.zeros(1))
    assert_equal(sub_s_mon2.i, np.array([0, 2]))
    assert_equal(sub_s_mon2.t_, np.zeros(2))
    expected = np.zeros(10, dtype=int)
    expected[[0, 2, 5]] = 1
    assert_equal(s_mon.count, expected)
    expected = np.zeros(7, dtype=int)
    expected[[2]] = 1
    assert_equal(sub_s_mon.count, expected)
    assert_equal(sub_s_mon2.count, np.array([1, 0, 1]))


@pytest.mark.codegen_independent
def test_wrong_indexing():
    G = NeuronGroup(10, "v:1")
    with pytest.raises(TypeError):
        G["string"]

    with pytest.raises(IndexError):
        G[10]
    with pytest.raises(IndexError):
        G[10:]
    with pytest.raises(IndexError):
        G[::2]
    with pytest.raises(IndexError):
        G[3:2]
    with pytest.raises(IndexError):
        G[[5, 4, 3]]
    with pytest.raises(IndexError):
        G[[2, 4, 6]]
    with pytest.raises(IndexError):
        G[[-1, 0, 1]]
    with pytest.raises(IndexError):
        G[[9, 10, 11]]
    with pytest.raises(IndexError):
        G[[9, 10]]
    with pytest.raises(IndexError):
        G[[10, 11]]
    with pytest.raises(TypeError):
        G[[2.5, 3.5, 4.5]]


@pytest.mark.codegen_independent
def test_alternative_indexing():
    G = NeuronGroup(10, "v : integer")
    G.v = "i"
    assert_equal(G[-3:].v, np.array([7, 8, 9]))
    assert_equal(G[3].v, np.array([3]))
    assert_equal(G[[3, 4, 5]].v, np.array([3, 4, 5]))


def test_no_reference_1():
    """
    Using subgroups without keeping an explicit reference. Basic access.
    """
    G = NeuronGroup(10, "v:1")
    G.v = np.arange(10)
    assert_equal(G[:5].v[:], G.v[:5])


@pytest.mark.standalone_compatible
def test_no_reference_2():
    """
    Using subgroups without keeping an explicit reference. Monitors
    """
    G = NeuronGroup(2, "v:1", threshold="v>1", reset="v=0")
    G.v = [0, 1.1]
    state_mon = StateMonitor(G[:1], "v", record=True)
    spike_mon = SpikeMonitor(G[1:])
    rate_mon = PopulationRateMonitor(G[:2])
    run(2 * defaultclock.dt)
    assert_equal(state_mon[0].v[:], np.zeros(2))
    assert_equal(spike_mon.i[:], np.array([0]))
    assert_equal(spike_mon.t[:], np.array([0]) * second)
    assert_equal(rate_mon.rate[:], np.array([0.5, 0]) / defaultclock.dt)


@pytest.mark.standalone_compatible
def test_no_reference_3():
    """
    Using subgroups without keeping an explicit reference. Monitors
    """
    G = NeuronGroup(2, "v:1", threshold="v>1", reset="v=0")
    G.v = [1.1, 0]
    S = Synapses(G[:1], G[1:], on_pre="v+=1")
    S.connect()
    run(defaultclock.dt + schedule_propagation_offset())
    assert_equal(G.v[:], np.array([0, 1]))


@pytest.mark.standalone_compatible
def test_no_reference_4():
    """
    Using subgroups without keeping an explicit reference. Synapses
    """
    G1 = NeuronGroup(10, "v:1", threshold="v>1", reset="v=0")
    G1.v["i%2==1"] = 1.1  # odd numbers should spike
    G2 = NeuronGroup(20, "v:1")
    S = Synapses(G1[1:6], G2[10:], on_pre="v+=1")
    S.connect("i==j")
    run(defaultclock.dt + schedule_propagation_offset())
    expected = np.zeros(len(G2))
    # Neurons 1, 3, 5 spiked and are connected to 10, 12, 14
    expected[[10, 12, 14]] = 1
    assert_equal(np.asarray(G2.v).flatten(), expected)


def test_recursive_subgroup():
    """
    Create a subgroup of a subgroup
    """
    G = NeuronGroup(10, "v : 1")
    G.v = "i"
    SG = G[3:8]
    SG2 = SG[2:4]
    assert_equal(SG2.v[:], np.array([5, 6]))
    assert_equal(SG2.v[:], SG.v[2:4])
    assert SG2.source.name == G.name


if __name__ == "__main__":
    test_str_repr()
    test_state_variables()
    test_state_variables_simple()
    test_state_variables_string_indices()
    test_state_variables_group_as_index()
    test_state_variables_group_as_index_problematic()
    test_state_monitor()
    test_shared_variable()
    test_synapse_creation()
    test_synapse_creation_state_vars()
    test_synapse_creation_generator()
    test_synapse_creation_generator_complex_ranges()
    test_synapse_creation_generator_random()
    test_synapse_creation_generator_multiple_synapses()
    test_synapse_access()
    test_synapses_access_subgroups()
    test_synapses_access_subgroups_problematic()
    test_subgroup_summed_variable()
    test_subexpression_references()
    test_subexpression_no_references()
    test_synaptic_propagation()
    test_synaptic_propagation_2()
    test_run_regularly()
    test_spike_monitor()
    test_wrong_indexing()
    test_no_reference_1()
    test_no_reference_2()
    test_no_reference_3()
    test_no_reference_4()
    test_recursive_subgroup()