def test_final_variance_runs(self):
exp = VarianceExperiment()
printer_final = Print(name="Final")
avgr = Averager('repeats', name="TestAverager")
var_buff = DataBuffer(name='Variance Buffer')
mean_buff = DataBuffer(name='Mean Buffer')
edges = [(exp.chan1, avgr.sink),
(avgr.final_variance, printer_final.sink),
(avgr.final_variance, var_buff.sink),
(avgr.source, mean_buff.sink)]
exp.set_graph(edges)
exp.run_sweeps()
# var_data = var_buff.get_data()['Variance'].reshape(var_buff.descriptor.data_dims())
# mean_data = mean_buff.get_data()['chan1'].reshape(mean_buff.descriptor.data_dims())
var_data = var_buff.output_data.reshape(
var_buff.descriptor.data_dims())
mean_data = mean_buff.output_data.reshape(
mean_buff.descriptor.data_dims())
orig_data = exp.vals.reshape(exp.chan1.descriptor.data_dims())
self.assertTrue(
np.abs(np.sum(mean_data - np.mean(orig_data, axis=0))) <= 1e-3)
self.assertTrue(
np.abs(np.sum(var_data -
np.var(orig_data, axis=0, ddof=1))) <= 1e-3)
def test_final_average_runs(self):
exp = TestExperiment()
printer_final = Print(name="Final")
avgr = Averager('trials', name="TestAverager")
edges = [(exp.chan1, avgr.sink), (avgr.source, printer_final.sink)]
exp.set_graph(edges)
exp.run_sweeps()
def test_sameness(self):
exp = TestExperiment()
printer_partial = Print(name="Partial")
printer_final = Print(name="Final")
avgr = Averager(name="TestAverager", axis='freq_1')
edges = [(exp.chan1, avgr.sink),
(avgr.partial_average, printer_partial.sink),
(avgr.source, printer_final.sink)]
exp.set_graph(edges)
exp.add_sweep(exp.freq_1, np.linspace(0, 9, 10))
exp.run_sweeps()
exp.polarity = 1 # 1: AP to P; -1: P to AP
exp.measure_current = 3e-6
exp.reset_amplitude = 0.78
exp.reset_duration = 5.0e-9
exp.settle_delay = 200e-6
exp.pspl_atten = 3
max_points = 100
sample_name = "CSHE-Die7-C6R7"
date = datetime.datetime.today().strftime('%Y-%m-%d')
pol = "APtoP" if exp.polarity < 0 else "PtoAP"
file_path = "data\CSHE-Switching\{samp:}\{samp:}-PulseSwitching-{pol:}_{date:}.h5".format(
pol=pol, samp=sample_name, date=date)
wr = WriteToHDF5(file_path)
avg = Averager('sample')
edges = [(exp.voltage, avg.sink), (avg.final_average, wr.sink)]
exp.set_graph(edges)
# Construct the coarse grid
coarse_ts = np.linspace(0.1, 10.0, 7) * 1e-9
coarse_vs = np.linspace(0.40, 0.90, 7)
points = [coarse_ts, coarse_vs]
points = list(itertools.product(*points))
# Add an extra plotter
fig1 = MeshPlotter(name="Switching Phase Diagram")
def refine_func(sweep_axis):
points, mean = sw.load_switching_data(wr.filename)
return "<SweptTestExperiment>"
def run(self):
for _ in range(500):
time.sleep(0.01)
data = np.zeros((100, 100))
data[25:75, 25:75] = 1.0
data = data + 25 * np.random.random((100, 100))
self.voltage.push(data.flatten())
if __name__ == '__main__':
exp = TestExperiment()
avg = Averager("repeats", name="Averager")
pl1 = Plotter(name="Partial",
plot_dims=2,
plot_mode="real",
palette="Spectral11")
pl2 = Plotter(name="Final",
plot_dims=2,
plot_mode="real",
palette="Spectral11")
edges = [(exp.voltage, avg.sink), (avg.partial_average, pl1.sink),
(avg.source, pl2.sink)]
avg.update_interval = 0.2
pl1.update_interval = 0.2
pl2.update_interval = 0.2
if __name__ == '__main__':
exp = TestExperiment()
channelizer = Channelizer(frequency=10e6,
bandwidth=5e6,
decimation_factor=8,
name="Demod")
ki = KernelIntegrator(kernel="",
bias=0,
simple_kernel=True,
box_car_start=0,
box_car_stop=64e-9,
frequency=0,
name="KI")
avg1 = Averager("round_robins", name="Average channelizer RRs")
avg2 = Averager("round_robins", name="Average KI RRs")
pl1 = Plotter(name="2D Scope", plot_dims=2, palette="Spectral11")
pl2 = Plotter(name="Demod",
plot_dims=2,
plot_mode="quad",
palette="Spectral11")
pl3 = Plotter(name="KI", plot_dims=1, plot_mode='real')
# pl4 = Plotter(name="KI", plot_dims=2, palette="Spectral11")
edges = [(exp.voltage, channelizer.sink), (channelizer.source, avg1.sink),
(channelizer.source, ki.sink), (ki.source, avg2.sink),
(avg1.final_average, pl2.sink), (avg2.final_average, pl3.sink)]
exp.set_graph(edges)