replace old example and update performance docs
This commit is contained in:
parent
547a02e6d3
commit
6f475e5c20
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@ -29,12 +29,7 @@ nix develop
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- RAM usage and execution time estimate for simulation **ONLY**
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- RAM usage and execution time estimate for simulation **ONLY**
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1. 100,000,000 time steps: 6GiB RAM and 12 seconds
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- 500,000,000 time steps: 8GiB RAM and 55 seconds
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2. 200,000,000 time steps: 11GiB RAM and 20 seconds
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3. 300,000,000 time steps: 16GiB RAM and 35 seconds
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<br>
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<br>
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<details><summary><b>WRPLL formulas</b></summary>
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<details><summary><b>WRPLL formulas</b></summary>
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@ -0,0 +1,68 @@
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# %%
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from plotly_resampler import FigureWidgetResampler
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from plotly.subplots import make_subplots
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import plotly.graph_objects as go
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import numpy as np
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from wrpll_simulation.config import Timesim_Config, PI_Config
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from wrpll_simulation.timesim import WRPLL_Timesim
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# %%
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KP, KI = 6, 2
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sim_config = Timesim_Config(
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timestep_size=1e-11,
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sim_length=500_000_000,
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helper_PI=PI_Config(KP=KP, KI=KI),
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main_PI=PI_Config(KP=KP, KI=KI),
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has_jitter=False,
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step_input_time=10e-6,
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step_frequency=6.25,
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step_phase=0,
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)
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sim = WRPLL_Timesim(sim_config, np.random.default_rng(1))
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fig = FigureWidgetResampler(make_subplots(rows=2))
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# ROW 1
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fig.add_trace(
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go.Scattergl(name="main - gtx freq diff"),
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hf_x=sim.time,
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hf_y=sim.freq_diff,
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row=1,
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col=1,
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)
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# ROW 2
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fig.add_trace(
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go.Scattergl(name="main - gtx phase diff"),
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hf_x=sim.time,
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hf_y=sim.phase_diff,
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row=2,
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col=1,
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)
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title = (
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f'step freq = {sim_config.step_frequency}Hz, '
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f'step phase = {sim_config.step_phase}° | '
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f'KP = {KP}, KI = {KI}'
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)
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fig.update_layout(
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xaxis2=dict(title="Time (sec)", exponentformat="SI"),
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yaxis1=dict(title="Frequency (Hz)"),
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yaxis2=dict(title="Phase (degree)"),
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height=950,
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showlegend=True,
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title_text=title,
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legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1,
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),
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)
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fig
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# %%
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@ -1,136 +0,0 @@
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# %% [markdown]
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# ## Both PLL mode example
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#
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# Time domain simulation with helper and main PLL mode.
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#
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# - Period error (**Helper PLL**)
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# - $\Delta{period} = N - (tag_{gtx}[n] - tag_{gtx}[n-1]) $
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# - where ideally $f_{helper} = \dfrac{f_{in} * (N-1)}{N}$
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#
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# - Phase error (**Main PLL**)
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# - $\text{Let } \Delta tag[n] = tag_{main}[n] - tag_{gtx}[n] \text{ mod N}$
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#
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# - $\Delta\phi[n] = \begin{cases}
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# \Delta tag[n] - N, & \text{if } \Delta tag > N/2 \\
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# \Delta tag[n], & otherwise
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# \end{cases} \quad$
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#
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#
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# - ADPLL PID (common for main and helper PLL)
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# - $P[n] = err[n] * K_P$
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# - $I[n] = I[n-1] + err[n] * K_I$
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# - $D[n] = (err[n] - err[n-1]) * K_D$
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# - $adpll[n] = \text{base adpll} + P[i] + I[n] + D[n] $
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# - where $\text{base adpll}$ is constant and obtain from frequency counter in HW
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# %%
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from plotly_resampler import FigureResampler, FigureWidgetResampler
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from plotly.subplots import make_subplots
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import plotly.graph_objects as go
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import numpy as np
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from wrpll_simulation.wrpll import WRPLL_simulator
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# %%
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# settings
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timestep = 1e-10
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total_steps = 200_000_000
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sim_mode = "both"
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adpll_period = 200e-6 # in seconds, the period that pll will trigger, (minimum > total DCXO frequency change delay)
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start_up_delay = 100e-6 # in seconds, the frequency adjustment is DISABLE until time > start_up_delay
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gtx_freq = 125_001_519
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helper_filter = {
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"KP": 2,
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"KI": 0.5,
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"KD": 0,
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}
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main_filter = {
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"KP": 12,
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"KI": 0,
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"KD": 0,
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}
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# simulation have RNG for
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# - gtx, main and helper jitter
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# - starting phase for main and helper
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# - base_adpll error
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wrpll_sim = WRPLL_simulator(
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timestep=timestep,
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total_steps=total_steps,
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sim_mode=sim_mode,
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helper_filter=helper_filter,
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main_filter=main_filter,
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gtx_freq=gtx_freq,
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adpll_write_period=adpll_period,
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start_up_delay=start_up_delay,
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)
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wrpll_sim.run()
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# %%
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# faster than pyplot with resampling feature
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# see https://github.com/predict-idlab/plotly-resampler
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fig = FigureWidgetResampler(make_subplots(rows=4, shared_xaxes=True))
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fig.add_trace(
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go.Scattergl(name="phase error"),
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hf_x=wrpll_sim.time,
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hf_y=wrpll_sim.phase_err,
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row=1,
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col=1,
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)
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fig.add_trace(
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go.Scattergl(name="freq error (ppm)"),
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hf_x=wrpll_sim.time,
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hf_y=(wrpll_sim.mainfreq - gtx_freq) * (1e6 / gtx_freq),
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row=2,
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col=1,
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)
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fig.add_trace(
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go.Scattergl(name="period error"),
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hf_x=wrpll_sim.time,
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hf_y=wrpll_sim.period_err,
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row=3,
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col=1,
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)
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fig.add_trace(
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go.Scattergl(name="gtx"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.gtx + 1, row=4, col=1
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)
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fig.add_trace(
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go.Scattergl(name="main"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.main, row=4, col=1
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)
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fig.add_trace(
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go.Scattergl(name="helper"),
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hf_x=wrpll_sim.time,
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hf_y=wrpll_sim.helper - 1,
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row=4,
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col=1,
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)
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fig.update_layout(
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xaxis4=dict(title="time (sec)"),
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yaxis1=dict(title="phase error"),
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yaxis2=dict(title="freq error (ppm)"),
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yaxis3=dict(title="beating period error"),
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yaxis4=dict(title="Signal"),
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height=1000,
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showlegend=True,
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title_text="PLL example",
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legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1,
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),
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)
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fig
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@ -1,116 +0,0 @@
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# %% [markdown]
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# ## Helper PLL mode example
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#
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# Time domain simulation with helper PLL mode
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#
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# - Period error (**Helper PLL**)
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# - $\Delta{period} = N - (tag_{gtx}[n] - tag_{gtx}[n-1]) $
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# - where ideally $f_{helper} = \dfrac{f_{in} * (N-1)}{N}$
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#
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# - Phase error (**Main PLL**)
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# - $\text{Let } \Delta tag[n] = tag_{main}[n] - tag_{gtx}[n] \text{ mod N}$
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#
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# - $\Delta\phi[n] = \begin{cases}
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# \Delta tag[n] - N, & \text{if } \Delta tag > N/2 \\
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# \Delta tag[n], & otherwise
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# \end{cases} \quad$
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#
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#
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# - ADPLL PID (common for main and helper PLL)
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# - $P[n] = err[n] * K_P$
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# - $I[n] = I[n-1] + err[n] * K_I$
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# - $D[n] = (err[n] - err[n-1]) * K_D$
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# - $adpll[n] = \text{base adpll} + P[i] + I[n] + D[n] $
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# - where $\text{base adpll}$ is constant and obtain from frequency counter in HW
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# %%
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from plotly_resampler import FigureResampler, FigureWidgetResampler
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from plotly.subplots import make_subplots
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import plotly.graph_objects as go
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import numpy as np
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from wrpll_simulation.wrpll import WRPLL_simulator
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# %%
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# settings
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timestep = 1e-10
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total_steps = 100_000_000
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sim_mode = "helper_pll"
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adpll_period = 200e-6 # in seconds, the period that pll will trigger, (minimum > total DCXO frequency change delay)
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start_up_delay = 100e-6 # in seconds, the frequency adjustment is DISABLE until time > start_up_delay
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gtx_freq = 125_001_519
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helper_filter = {
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"KP": 2,
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"KI": 0.5,
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"KD": 0,
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}
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main_filter = { # unused
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"KP": 12,
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"KI": 0,
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"KD": 0,
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}
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# simulation have RNG for
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# - gtx, main and helper jitter
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# - starting phase for main and helper
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# - base_adpll error
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wrpll_sim = WRPLL_simulator(
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timestep=timestep,
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total_steps=total_steps,
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sim_mode=sim_mode,
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helper_filter=helper_filter,
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main_filter=main_filter,
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gtx_freq=gtx_freq,
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adpll_write_period=adpll_period,
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start_up_delay=start_up_delay,
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)
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wrpll_sim.run()
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# %%
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# faster than pyplot with resampling feature
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# see https://github.com/predict-idlab/plotly-resampler
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fig = FigureWidgetResampler(make_subplots(rows=2, shared_xaxes=True))
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fig.add_trace(
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go.Scattergl(name="period error"),
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hf_x=wrpll_sim.time,
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hf_y=wrpll_sim.period_err,
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row=1,
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col=1,
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)
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fig.add_trace(
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go.Scattergl(name="gtx"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.gtx + 1, row=2, col=1
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)
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fig.add_trace(
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go.Scattergl(name="main"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.main, row=2, col=1
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)
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fig.add_trace(
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go.Scattergl(name="helper"),
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hf_x=wrpll_sim.time,
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hf_y=wrpll_sim.helper - 1,
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row=2,
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col=1,
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)
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fig.update_layout(
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xaxis2=dict(title="time (sec)"),
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yaxis1=dict(title="beating period error"),
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yaxis2=dict(title="Signal"),
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height=1000,
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showlegend=True,
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title_text="PLL example",
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legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1,
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),
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)
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fig
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@ -1,142 +0,0 @@
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# %% [markdown]
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# ## Main PLL mode example
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#
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# Time domain simulation with main PLL mode, and helper PLL is assumed to be locked
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#
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# (`helper_init_freq` variable need to be set)
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#
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#
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# - Period error (**Helper PLL**)
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# - $\Delta{period} = N - (tag_{gtx}[n] - tag_{gtx}[n-1]) $
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# - where ideally $f_{helper} = \dfrac{f_{in} * (N-1)}{N}$
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#
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# - Phase error (**Main PLL**)
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# - $\text{Let } \Delta tag[n] = tag_{main}[n] - tag_{gtx}[n] \text{ mod N}$
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#
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# - $\Delta\phi[n] = \begin{cases}
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# \Delta tag[n] - N, & \text{if } \Delta tag > N/2 \\
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# \Delta tag[n], & otherwise
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# \end{cases} \quad$
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#
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#
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# - ADPLL PID (common for main and helper PLL)
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# - $P[n] = err[n] * K_P$
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# - $I[n] = I[n-1] + err[n] * K_I$
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# - $D[n] = (err[n] - err[n-1]) * K_D$
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# - $adpll[n] = \text{base adpll} + P[i] + I[n] + D[n] $
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# - where $\text{base adpll}$ is constant and obtain from frequency counter in HW
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# %%
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from plotly_resampler import FigureResampler, FigureWidgetResampler
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from plotly.subplots import make_subplots
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import plotly.graph_objects as go
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import numpy as np
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from wrpll_simulation.wrpll import WRPLL_simulator
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# %%
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# settings
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timestep = 1e-10
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total_steps = 100_000_000
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sim_mode = "main_pll"
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adpll_period = 200e-6 # in seconds, the period that pll will trigger, (minimum > total DCXO frequency change delay)
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start_up_delay = 100e-6 # in seconds, the frequency adjustment is DISABLE until time > start_up_delay
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gtx_freq = 125_001_519
|
|
||||||
|
|
||||||
helper_init_freq = gtx_freq * (4096 - 1) / 4096
|
|
||||||
|
|
||||||
helper_filter = { # unused
|
|
||||||
"KP": 2,
|
|
||||||
"KI": 0.5,
|
|
||||||
"KD": 0,
|
|
||||||
}
|
|
||||||
|
|
||||||
main_filter = {
|
|
||||||
"KP": 12,
|
|
||||||
"KI": 0,
|
|
||||||
"KD": 0,
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
# simulation have RNG for
|
|
||||||
# - gtx, main and helper jitter
|
|
||||||
# - starting phase for main and helper
|
|
||||||
# - base_adpll error
|
|
||||||
|
|
||||||
|
|
||||||
wrpll_sim = WRPLL_simulator(
|
|
||||||
timestep=timestep,
|
|
||||||
total_steps=total_steps,
|
|
||||||
sim_mode=sim_mode,
|
|
||||||
helper_filter=helper_filter,
|
|
||||||
main_filter=main_filter,
|
|
||||||
gtx_freq=gtx_freq,
|
|
||||||
adpll_write_period=adpll_period,
|
|
||||||
start_up_delay=start_up_delay,
|
|
||||||
helper_init_freq=helper_init_freq,
|
|
||||||
)
|
|
||||||
wrpll_sim.run()
|
|
||||||
|
|
||||||
# %%
|
|
||||||
# faster than pyplot with resampling feature
|
|
||||||
# see https://github.com/predict-idlab/plotly-resampler
|
|
||||||
|
|
||||||
fig = FigureWidgetResampler(make_subplots(rows=4, shared_xaxes=True))
|
|
||||||
fig.add_trace(
|
|
||||||
go.Scattergl(name="phase error"),
|
|
||||||
hf_x=wrpll_sim.time,
|
|
||||||
hf_y=wrpll_sim.phase_err,
|
|
||||||
row=1,
|
|
||||||
col=1,
|
|
||||||
)
|
|
||||||
|
|
||||||
fig.add_trace(
|
|
||||||
go.Scattergl(name="freq error (ppm)"),
|
|
||||||
hf_x=wrpll_sim.time,
|
|
||||||
hf_y=(wrpll_sim.mainfreq - gtx_freq) * (1e6 / gtx_freq),
|
|
||||||
row=2,
|
|
||||||
col=1,
|
|
||||||
)
|
|
||||||
|
|
||||||
fig.add_trace(
|
|
||||||
go.Scattergl(name="period error"),
|
|
||||||
hf_x=wrpll_sim.time,
|
|
||||||
hf_y=wrpll_sim.period_err,
|
|
||||||
row=3,
|
|
||||||
col=1,
|
|
||||||
)
|
|
||||||
|
|
||||||
fig.add_trace(
|
|
||||||
go.Scattergl(name="gtx"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.gtx + 1, row=4, col=1
|
|
||||||
)
|
|
||||||
fig.add_trace(
|
|
||||||
go.Scattergl(name="main"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.main, row=4, col=1
|
|
||||||
)
|
|
||||||
fig.add_trace(
|
|
||||||
go.Scattergl(name="helper"),
|
|
||||||
hf_x=wrpll_sim.time,
|
|
||||||
hf_y=wrpll_sim.helper - 1,
|
|
||||||
row=4,
|
|
||||||
col=1,
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
fig.update_layout(
|
|
||||||
xaxis4=dict(title="time (sec)"),
|
|
||||||
yaxis1=dict(title="phase error"),
|
|
||||||
yaxis2=dict(title="freq error (ppm)"),
|
|
||||||
yaxis3=dict(title="beating period error"),
|
|
||||||
yaxis4=dict(title="Signal"),
|
|
||||||
height=1000,
|
|
||||||
showlegend=True,
|
|
||||||
title_text="PLL example",
|
|
||||||
legend=dict(
|
|
||||||
orientation="h",
|
|
||||||
yanchor="bottom",
|
|
||||||
y=1.02,
|
|
||||||
xanchor="right",
|
|
||||||
x=1,
|
|
||||||
),
|
|
||||||
)
|
|
||||||
|
|
||||||
fig
|
|
||||||
Loading…
Reference in New Issue