import numpy as np from kyupy.wave_sim import WaveSim, WaveSimCuda, wave_eval, TMIN, TMAX from kyupy.logic_sim import LogicSim from kyupy import verilog, sdf, logic from kyupy.saed import pin_index from kyupy.logic import MVArray, BPArray def test_wave_eval(): # SDF specifies IOPATH delays with respect to output polarity # SDF pulse rejection value is determined by IOPATH causing last transition and polarity of last transition line_times = np.zeros((3, 2, 2)) line_times[0, 0, 0] = 0.1 # A -> Z rise delay line_times[0, 0, 1] = 0.2 # A -> Z fall delay line_times[0, 1, 0] = 0.1 # A -> Z negative pulse limit (terminate in rising Z) line_times[0, 1, 1] = 0.2 # A -> Z positive pulse limit line_times[1, 0, 0] = 0.3 # as above for B -> Z line_times[1, 0, 1] = 0.4 line_times[1, 1, 0] = 0.3 line_times[1, 1, 1] = 0.4 state = np.zeros((3*16, 1)) + TMAX # 3 waveforms of capacity 16 state[::16, 0] = 16 # first entry is capacity a = state[0:16, 0] b = state[16:32, 0] z = state[32:, 0] sat = np.zeros((3, 3), dtype='int') sat[0] = 0, 16, 0 sat[1] = 16, 16, 0 sat[2] = 32, 16, 0 wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMIN == z[0] a[0] = TMIN wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMIN == z[0] b[0] = TMIN wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMAX == z[0] a[0] = 1 # A _/^^^ b[0] = 2 # B __/^^ wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMIN == z[0] # ^^^\___ B -> Z fall delay assert 2.4 == z[1] assert TMAX == z[2] a[0] = TMIN # A ^^^^^^ b[0] = TMIN # B ^^^\__ b[1] = 2 wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert 2.3 == z[0] # ___/^^^ B -> Z rise delay assert TMAX == z[1] # pos pulse of 0.35 at B -> 0.45 after delays a[0] = TMIN # A ^^^^^^^^ b[0] = TMIN b[1] = 2 # B ^^\__/^^ b[2] = 2.35 wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert 2.3 == z[0] # __/^^\__ assert 2.75 == z[1] assert TMAX == z[2] # neg pulse of 0.45 at B -> 0.35 after delays a[0] = TMIN # A ^^^^^^^^ b[0] = 2 # B __/^^\__ b[1] = 2.45 b[2] = TMAX wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMIN == z[0] # ^^\__/^^ assert 2.4 == z[1] assert 2.75 == z[2] assert TMAX == z[3] # neg pulse of 0.35 at B -> 0.25 after delays (filtered) a[0] = TMIN # A ^^^^^^^^ b[0] = 2 # B __/^^\__ b[1] = 2.35 b[2] = TMAX wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMIN == z[0] # ^^^^^^ assert TMAX == z[1] # pos pulse of 0.25 at B -> 0.35 after delays (filtered) a[0] = TMIN # A ^^^^^^^^ b[0] = TMIN b[1] = 2 # B ^^\__/^^ b[2] = 2.25 wave_eval((0b0111, 2, 0, 1), state, sat, 0, line_times) assert TMAX == z[0] # ______ def compare_to_logic_sim(wsim): tests = MVArray((len(wsim.interface), wsim.sims)) choices = np.asarray([logic.ZERO, logic.ONE, logic.RISE, logic.FALL], dtype=np.uint8) rng = np.random.default_rng(10) tests.data[...] = rng.choice(choices, tests.data.shape) tests_bp = BPArray(tests) wsim.assign(tests_bp) wsim.propagate() cdata = wsim.capture() resp = MVArray(tests) for iidx, inode in enumerate(wsim.interface): if len(inode.ins) > 0: for vidx in range(wsim.sims): resp.data[iidx, vidx] = logic.ZERO if cdata[iidx, vidx, 0] < 0.5 else logic.ONE # resp.set_value(vidx, iidx, 0 if cdata[iidx, vidx, 0] < 0.5 else 1) lsim = LogicSim(wsim.circuit, len(tests_bp)) lsim.assign(tests_bp) lsim.propagate() exp_bp = BPArray(tests_bp) lsim.capture(exp_bp) exp = MVArray(exp_bp) for i in range(8): exp_str = exp[i].replace('R', '1').replace('F', '0').replace('P', '0').replace('N', '1') res_str = resp[i].replace('R', '1').replace('F', '0').replace('P', '0').replace('N', '1') assert res_str == exp_str def test_b14(mydir): c = verilog.load(mydir / 'b14.v.gz', branchforks=True) df = sdf.load(mydir / 'b14.sdf.gz') lt = df.annotation(c, pin_index) wsim = WaveSim(c, lt, 8) compare_to_logic_sim(wsim) def test_b14_strip_forks(mydir): c = verilog.load(mydir / 'b14.v.gz', branchforks=True) df = sdf.load(mydir / 'b14.sdf.gz') lt = df.annotation(c, pin_index) wsim = WaveSim(c, lt, 8, strip_forks=True) compare_to_logic_sim(wsim) def test_b14_cuda(mydir): c = verilog.load(mydir / 'b14.v.gz', branchforks=True) df = sdf.load(mydir / 'b14.sdf.gz') lt = df.annotation(c, pin_index) wsim = WaveSimCuda(c, lt, 8) compare_to_logic_sim(wsim)