forked from M-Labs/artiq
examples/flopping_f_simulation: demonstrate previous functionality
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@ -31,14 +31,18 @@ class FloppingF(EnvExperiment):
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default=LinearScan(1000, 2000, 100)))
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self.attr_argument("F0", NumberValue(1500, min=1000, max=2000))
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self.attr_argument("noise_amplitude", NumberValue(0.1, min=0, max=100))
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self.frequency = self.set_result("flopping_f_frequency", [], True)
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self.brightness = self.set_result("flopping_f_brightness", [], True)
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self.attr_argument("noise_amplitude", NumberValue(0.1, min=0, max=100,
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step=0.01))
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self.attr_device("scheduler")
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def run(self):
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self.frequency = self.set_result("flopping_f_frequency", [],
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realtime=True, store=False)
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self.brightness = self.set_result("flopping_f_brightness", [],
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realtime=True)
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self.set_result("flopping_f_fit", [], realtime=True, store=False)
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for frequency in self.frequency_scan:
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brightness = model(frequency, self.F0) + self.noise_amplitude*random.random()
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self.frequency.append(frequency)
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@ -48,9 +52,16 @@ class FloppingF(EnvExperiment):
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self.scheduler.priority, time.time() + 20, False)
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def analyze(self):
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# Use get_result so that analyze can be run stand-alone.
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frequency = self.get_result("flopping_f_frequency")
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brightness = self.get_result("flopping_f_brightness")
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popt, pcov = curve_fit(model_numpy,
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self.frequency.read, self.brightness.read,
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frequency, brightness,
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p0=[self.get_parameter("flopping_freq")])
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perr = np.sqrt(np.diag(pcov))
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if perr < 0.1:
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self.set_parameter("flopping_freq", float(popt))
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F0 = float(popt)
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self.set_parameter("flopping_freq", F0)
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self.set_result("flopping_f_fit",
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[model(x, F0) for x in frequency],
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realtime=True, store=False)
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