replace old example and update performance docs

This commit is contained in:
morgan 2024-01-26 16:55:38 +08:00
parent 547a02e6d3
commit 6f475e5c20
5 changed files with 69 additions and 400 deletions

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@ -29,12 +29,7 @@ nix develop
- RAM usage and execution time estimate for simulation **ONLY**
1. 100,000,000 time steps: 6GiB RAM and 12 seconds
2. 200,000,000 time steps: 11GiB RAM and 20 seconds
3. 300,000,000 time steps: 16GiB RAM and 35 seconds
- 500,000,000 time steps: 8GiB RAM and 55 seconds
<br>
<details><summary><b>WRPLL formulas</b></summary>

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@ -0,0 +1,68 @@
# %%
from plotly_resampler import FigureWidgetResampler
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import numpy as np
from wrpll_simulation.config import Timesim_Config, PI_Config
from wrpll_simulation.timesim import WRPLL_Timesim
# %%
KP, KI = 6, 2
sim_config = Timesim_Config(
timestep_size=1e-11,
sim_length=500_000_000,
helper_PI=PI_Config(KP=KP, KI=KI),
main_PI=PI_Config(KP=KP, KI=KI),
has_jitter=False,
step_input_time=10e-6,
step_frequency=6.25,
step_phase=0,
)
sim = WRPLL_Timesim(sim_config, np.random.default_rng(1))
fig = FigureWidgetResampler(make_subplots(rows=2))
# ROW 1
fig.add_trace(
go.Scattergl(name="main - gtx freq diff"),
hf_x=sim.time,
hf_y=sim.freq_diff,
row=1,
col=1,
)
# ROW 2
fig.add_trace(
go.Scattergl(name="main - gtx phase diff"),
hf_x=sim.time,
hf_y=sim.phase_diff,
row=2,
col=1,
)
title = (
f'step freq = {sim_config.step_frequency}Hz, '
f'step phase = {sim_config.step_phase}° | '
f'KP = {KP}, KI = {KI}'
)
fig.update_layout(
xaxis2=dict(title="Time (sec)", exponentformat="SI"),
yaxis1=dict(title="Frequency (Hz)"),
yaxis2=dict(title="Phase (degree)"),
height=950,
showlegend=True,
title_text=title,
legend=dict(
orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1,
),
)
fig
# %%

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@ -1,136 +0,0 @@
# %% [markdown]
# ## Both PLL mode example
#
# Time domain simulation with helper and main PLL mode.
#
# - Period error (**Helper PLL**)
# - $\Delta{period} = N - (tag_{gtx}[n] - tag_{gtx}[n-1]) $
# - where ideally $f_{helper} = \dfrac{f_{in} * (N-1)}{N}$
#
# - Phase error (**Main PLL**)
# - $\text{Let } \Delta tag[n] = tag_{main}[n] - tag_{gtx}[n] \text{ mod N}$
#
# - $\Delta\phi[n] = \begin{cases}
# \Delta tag[n] - N, & \text{if } \Delta tag > N/2 \\
# \Delta tag[n], & otherwise
# \end{cases} \quad$
#
#
# - ADPLL PID (common for main and helper PLL)
# - $P[n] = err[n] * K_P$
# - $I[n] = I[n-1] + err[n] * K_I$
# - $D[n] = (err[n] - err[n-1]) * K_D$
# - $adpll[n] = \text{base adpll} + P[i] + I[n] + D[n] $
# - where $\text{base adpll}$ is constant and obtain from frequency counter in HW
# %%
from plotly_resampler import FigureResampler, FigureWidgetResampler
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import numpy as np
from wrpll_simulation.wrpll import WRPLL_simulator
# %%
# settings
timestep = 1e-10
total_steps = 200_000_000
sim_mode = "both"
adpll_period = 200e-6 # in seconds, the period that pll will trigger, (minimum > total DCXO frequency change delay)
start_up_delay = 100e-6 # in seconds, the frequency adjustment is DISABLE until time > start_up_delay
gtx_freq = 125_001_519
helper_filter = {
"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,
)
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

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@ -1,116 +0,0 @@
# %% [markdown]
# ## Helper PLL mode example
#
# Time domain simulation with helper PLL mode
#
# - Period error (**Helper PLL**)
# - $\Delta{period} = N - (tag_{gtx}[n] - tag_{gtx}[n-1]) $
# - where ideally $f_{helper} = \dfrac{f_{in} * (N-1)}{N}$
#
# - Phase error (**Main PLL**)
# - $\text{Let } \Delta tag[n] = tag_{main}[n] - tag_{gtx}[n] \text{ mod N}$
#
# - $\Delta\phi[n] = \begin{cases}
# \Delta tag[n] - N, & \text{if } \Delta tag > N/2 \\
# \Delta tag[n], & otherwise
# \end{cases} \quad$
#
#
# - ADPLL PID (common for main and helper PLL)
# - $P[n] = err[n] * K_P$
# - $I[n] = I[n-1] + err[n] * K_I$
# - $D[n] = (err[n] - err[n-1]) * K_D$
# - $adpll[n] = \text{base adpll} + P[i] + I[n] + D[n] $
# - where $\text{base adpll}$ is constant and obtain from frequency counter in HW
# %%
from plotly_resampler import FigureResampler, FigureWidgetResampler
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import numpy as np
from wrpll_simulation.wrpll import WRPLL_simulator
# %%
# settings
timestep = 1e-10
total_steps = 100_000_000
sim_mode = "helper_pll"
adpll_period = 200e-6 # in seconds, the period that pll will trigger, (minimum > total DCXO frequency change delay)
start_up_delay = 100e-6 # in seconds, the frequency adjustment is DISABLE until time > start_up_delay
gtx_freq = 125_001_519
helper_filter = {
"KP": 2,
"KI": 0.5,
"KD": 0,
}
main_filter = { # unused
"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,
)
wrpll_sim.run()
# %%
# faster than pyplot with resampling feature
# see https://github.com/predict-idlab/plotly-resampler
fig = FigureWidgetResampler(make_subplots(rows=2, shared_xaxes=True))
fig.add_trace(
go.Scattergl(name="period error"),
hf_x=wrpll_sim.time,
hf_y=wrpll_sim.period_err,
row=1,
col=1,
)
fig.add_trace(
go.Scattergl(name="gtx"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.gtx + 1, row=2, col=1
)
fig.add_trace(
go.Scattergl(name="main"), hf_x=wrpll_sim.time, hf_y=wrpll_sim.main, row=2, col=1
)
fig.add_trace(
go.Scattergl(name="helper"),
hf_x=wrpll_sim.time,
hf_y=wrpll_sim.helper - 1,
row=2,
col=1,
)
fig.update_layout(
xaxis2=dict(title="time (sec)"),
yaxis1=dict(title="beating period error"),
yaxis2=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

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@ -1,142 +0,0 @@
# %% [markdown]
# ## Main PLL mode example
#
# Time domain simulation with main PLL mode, and helper PLL is assumed to be locked
#
# (`helper_init_freq` variable need to be set)
#
#
# - Period error (**Helper PLL**)
# - $\Delta{period} = N - (tag_{gtx}[n] - tag_{gtx}[n-1]) $
# - where ideally $f_{helper} = \dfrac{f_{in} * (N-1)}{N}$
#
# - Phase error (**Main PLL**)
# - $\text{Let } \Delta tag[n] = tag_{main}[n] - tag_{gtx}[n] \text{ mod N}$
#
# - $\Delta\phi[n] = \begin{cases}
# \Delta tag[n] - N, & \text{if } \Delta tag > N/2 \\
# \Delta tag[n], & otherwise
# \end{cases} \quad$
#
#
# - ADPLL PID (common for main and helper PLL)
# - $P[n] = err[n] * K_P$
# - $I[n] = I[n-1] + err[n] * K_I$
# - $D[n] = (err[n] - err[n-1]) * K_D$
# - $adpll[n] = \text{base adpll} + P[i] + I[n] + D[n] $
# - where $\text{base adpll}$ is constant and obtain from frequency counter in HW
# %%
from plotly_resampler import FigureResampler, FigureWidgetResampler
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import numpy as np
from wrpll_simulation.wrpll import WRPLL_simulator
# %%
# settings
timestep = 1e-10
total_steps = 100_000_000
sim_mode = "main_pll"
adpll_period = 200e-6 # in seconds, the period that pll will trigger, (minimum > total DCXO frequency change delay)
start_up_delay = 100e-6 # in seconds, the frequency adjustment is DISABLE until time > start_up_delay
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