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