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Merge pull request #81 from LemurPwned/streamlit/ui
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Streamlit/UI
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@LemurPwned
LemurPwned authored Sep 15, 2024
2 parents 7801e06 + a3b0324 commit 58f58a2
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11 changes: 9 additions & 2 deletions README.md
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Expand Up @@ -6,7 +6,7 @@
[![pages-build-deployment](https://github.com/LemurPwned/cmtj/actions/workflows/pages/pages-build-deployment/badge.svg?branch=gh-pages)](https://github.com/LemurPwned/cmtj/actions/workflows/pages/pages-build-deployment)
[![Version](https://img.shields.io/pypi/v/cmtj)](https://pypi.org/project/cmtj/)
[![License](https://img.shields.io/pypi/l/cmtj.svg)](https://github.com/LemurPwned/cmtj/blob/master/LICENSE)
[![Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](http://cmtj-simulations.streamlit.app/)
[![Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://cmtj-app.streamlit.app/spectrum)
![Downloads](https://img.shields.io/pypi/dm/cmtj.svg)

## Table of contents
Expand Down Expand Up @@ -36,7 +36,14 @@ It is also possible to connect devices in parallel or in series to have electric

## Web GUI

Check out the [streamlit hosted demo here](http://cmtj-simulations.streamlit.app/). You can simulate PIMM spectra and Spin-Diode spectra there. Let us know if you have any issues with the demo.
Check out the [streamlit hosted demo here](https://cmtj-app.streamlit.app/spectrum).
You can simulate:

* PIMM spectra and Spin-Diode spectra
* Try some optimization fitting
* Fit multi-domain or multi-level M(H) or R(H) loops in [Domain mode](https://cmtj-app.streamlit.app)

Let us know if you have any issues with the demo.

## Quickstart

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182 changes: 135 additions & 47 deletions view/domain.py
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Expand Up @@ -5,22 +5,33 @@
import streamlit as st
from helpers import read_mh_data
from simulation_fns import create_single_domain, get_axis_angles
from utils import GENERIC_BOUNDS, GENERIC_UNITS
from utils import GENERIC_BOUNDS, GENERIC_UNITS, get_init_kval

from cmtj import AxialDriver, Junction
from cmtj.utils import FieldScan

_lock = RLock()


with st.container():
st.write("# Domain fitting")

st.write(
"Fit M(H) to multidomain model. "
"Upload your file with experimental data: with columns H, mx, my, mz.\n"
"First column is always H in A/m, the rest are the components of the magnetisation in range (-1, 1)."
"If you upload just two columns, the script will assume that the data is in the form H, mx."
)
with st.expander("Explanation"):
st.write(
"#### Fit M(H) to multidomain model. \n"
"##### Experimental data\n"
"Upload your file with experimental data: with columns H, mx, my, mz.\n"
"First column is always H in A/m, the rest are the components of the magnetisation in range (-1, 1)."
"If you upload just two columns, the script will assume that the data is in the form H, mx.\n"
"##### Simulation\n"
"Add new domains in the sidebar panel. Area of each domain is a weight. The resulting $m_\mathrm{mixed}(h)$ plot is produces with\n\n"
r"$m_\mathrm{mixed} = (1/{\sum_i a_i})\sum_i a_i m_i$"
"\n\n where $a_i$ is the area of $i$th domain and $m_i$ is $m(h)$ for that domain.\n"
"##### Coordinate system\n"
r"$\theta$ is the polar angle and $\phi$ is the azimuthal angle."
r" $\theta=90^\circ$ denotes fully in-plane magnetisation, "
r"$\theta=0^\circ$ denotes out-of-plane magnetisation (positive z-direction)"
r"$\phi=0^\circ$ denotes magnetisation pointing in the positive x direction."
)

progress_bar = st.progress(0)

Expand All @@ -46,7 +57,8 @@ def simulate_domains():
weights = [st.session_state[f"area{i}"] * 1e-18 for i in range(st.session_state.N)]
wsum = sum(weights)
weights = [w / wsum for w in weights]
Mmixed = np.zeros((len(Hscan), 3))
Mmixed = np.zeros((len(Hscan), 3), dtype=np.float16)
Mdomains = np.zeros((st.session_state.N, len(Hscan), 3), np.float16)
for i, H in enumerate(Hvecs):
j.clearLog()
j.setLayerExternalFieldDriver("all", AxialDriver(*H))
Expand All @@ -60,11 +72,13 @@ def simulate_domains():
mx = np.mean(log[f"domain_{l}_mx"][-st.session_state.last_N :])
my = np.mean(log[f"domain_{l}_my"][-st.session_state.last_N :])
mz = np.mean(log[f"domain_{l}_mz"][-st.session_state.last_N :])
Mmixed[i] += np.array([mx, my, mz]) * weights[l]
Mdomains[l, i] = np.array([mx, my, mz])
Mmixed[i] += Mdomains[l, i] * weights[l]
# for each layer take last N values
progress_bar.progress(int((i / maxlen) * 100))
st.session_state["Mmixed"] = Mmixed
st.session_state["Hscan"] = Hscan
st.session_state["Mdomains"] = Mdomains


with st.sidebar:
Expand All @@ -77,6 +91,52 @@ def simulate_domains():
accept_multiple_files=False,
key="upload",
)
st.checkbox("Show domains in polar angles", key="domain_use_angle", value=False)
domain_params = st.expander("Domain parameters", expanded=True)
with domain_params:
N = st.number_input(
"Number of domains", min_value=1, max_value=10, value=1, key="N"
)
for i in range(N):
st.markdown(f"#### Domain {i+1}")
unit_k = GENERIC_UNITS["K"]
st.number_input(
f"K ({i+1}) " r" ($\mathrm{" f"{unit_k}" "}$)",
min_value=GENERIC_BOUNDS["K"][0],
max_value=GENERIC_BOUNDS["K"][1],
value=1.2e3,
step=10.0,
key=f"K{i}",
help="Uniaxial anisotropy constant of the domain. Does not include shape anisotropy.",
)

st.number_input(
f"area ({i+1}) " r"($\mathrm{nm^2}$)",
min_value=1.0,
max_value=500.0,
value=10.0,
key=f"area{i}",
help="Area of the domain. In fact, this is a weight of the domain.",
)

st.number_input(
r"$\theta_\mathrm{K}$ (deg.)",
min_value=0.0,
max_value=180.0,
value=get_init_kval(i),
key=f"theta_K{i}",
help="Polar angle of the anisotropy axis",
)
st.number_input(
r"$\phi_\mathrm{K}$ (deg.)",
min_value=0.0,
max_value=180.0,
value=get_init_kval(i),
key=f"phi_K{i}",
help="Azimuthal angle of the anisotropy axis",
)
st.markdown("-----\n")

with st.expander("Simulation parameters", expanded=True):
st.selectbox(
"H axis", options=["x", "y", "z", "xy", "xz", "yz"], key="H_axis", index=0
Expand Down Expand Up @@ -125,6 +185,7 @@ def simulate_domains():
value=1.8,
step=0.01,
key="Ms_shared",
help="Saturation magnetisation of the system. Affects the shape anisotropy",
)
st.number_input(
"thickness (nm)",
Expand All @@ -141,40 +202,9 @@ def simulate_domains():
key="alpha_shared",
format="%.3f",
)
domain_params = st.expander("Domain parameters", expanded=True)
with domain_params:
N = st.number_input(
"Number of domains", min_value=1, max_value=10, value=1, key="N"
)
for i in range(N):
st.markdown(f"#### Domain {i+1}")
unit_k = GENERIC_UNITS["K"]
st.number_input(
f"K ({i+1}) " r" ($\mathrm{" f"{unit_k}" "}$)",
min_value=GENERIC_BOUNDS["K"][0],
max_value=GENERIC_BOUNDS["K"][1],
value=1.2e3,
step=10.0,
key=f"K{i}",
)

st.number_input(
f"area ({i+1}) " r"($\mathrm{nm^2}$)",
min_value=1.0,
max_value=500.0,
value=10.0,
key=f"area{i}",
)
st.radio(
f"anisotropy axis ({i+1})",
options=["x", "y", "z"],
key=f"anisotropy_axis{i}",
index=2,
)
st.markdown("-----\n")


def render(Hscan, Mmixed):
def render(Hscan, Mmixed, Mdomains=None):
if len(Hscan) <= 0 or len(Mmixed) <= 0:
return
with _lock:
Expand All @@ -187,21 +217,35 @@ def render(Hscan, Mmixed):
fields, mh = read_mh_data()
render_from_exp(ax, fields=fields, mh=mh)
render_from_sim(ax, Hscan, Mmixed)

fig.suptitle("Mixed Domain model")
st.pyplot(fig)
n = 3
if st.session_state["domain_use_angle"]:
n = 2
w, h = plt.figaspect(st.session_state.N / n)
fig, ax = plt.subplots(
st.session_state.N, n, dpi=400, figsize=(w, h), sharex=True, sharey=True
)
if st.session_state.N <= 1:
ax = np.array([ax])
try:
render_individual_domains(fig, ax, Hscan, Mdomains)
except IndexError:
pass
st.pyplot(fig)


def render_from_exp(ax, fields, mh):
if len(fields) <= 0 or len(mh) <= 0:
st.toast("No data to render")

fields = np.asarray(fields)
m = np.asarray(mh)
for i, l in zip(range(m.shape[1]), "xyz"):
ax[i].plot(
fields,
fields / 1e3, # A/m --> kA/m
m[:, i],
label=f"$m_{l}$",
color="black",
color="yellow",
marker="x",
alpha=0.5,
linestyle="--",
Expand All @@ -221,11 +265,55 @@ def render_from_sim(ax, Hscan, Mmixed):
ax[2].set_xlabel("H (kA/m)")


def render_individual_domains(fig, ax, Hscan, M: list[list[float]]):
n = 3
if st.session_state["domain_use_angle"]:
n = 2
ax[0, 0].set_title(r"$\theta$")
ax[0, 1].set_title(r"$\phi$")
for i, domain_m in enumerate(M):
# convert to polar
theta_m, phi_m, _ = FieldScan.vector2angle(
domain_m[:, 0], domain_m[:, 1], domain_m[:, 2]
)
ax[i, 0].plot(
Hscan / 1e3, theta_m, label=rf"$\theta_{i+1}$", color="crimson"
)
ax[i, 1].plot(
Hscan / 1e3, phi_m, label=rf"$\phi_{i+1}$", color="forestgreen"
)
ax[i, 0].set_ylabel(rf"$\theta_{i+1}$ (deg.)")
ax[i, 1].set_ylabel(rf"$\phi_{i+1}$ (deg.)")
else:
n = 3
ax[0, 0].set_title(r"$m_\mathrm{x}$")
ax[0, 1].set_title(r"$m_\mathrm{y}$")
ax[0, 2].set_title(r"$m_\mathrm{z}$")
for i, domain_m in enumerate(M):
ax[i, 0].plot(
Hscan / 1e3, domain_m[:, 0], label=rf"$m_{i+1}$", color="crimson"
)
ax[i, 1].plot(
Hscan / 1e3, domain_m[:, 1], label=rf"$m_{i+1}$", color="forestgreen"
)
ax[i, 2].plot(
Hscan / 1e3, domain_m[:, 2], label=rf"$m_{i+1}$", color="royalblue"
)
ax[i, 0].set_ylabel(rf"$m_{i+1}$")
for j in range(n):
ax[-1, j].set_xlabel("H (kA/m)")
fig.suptitle("Individual Domains") # fig.legend()


simulate_btn = st.button(
"Simulate",
key="simulate",
on_click=simulate_domains,
type="primary",
)

render(st.session_state.get("Hscan", []), st.session_state.get("Mmixed", []))
render(
st.session_state.get("Hscan", []),
st.session_state.get("Mmixed", []),
Mdomains=st.session_state.get("Mdomains", []),
)
17 changes: 11 additions & 6 deletions view/simulation_fns.py
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Expand Up @@ -14,11 +14,14 @@

def create_single_domain(id_: str) -> Layer:
demag = [CVector(0, 0, 0), CVector(0, 0, 0), CVector(0, 0, 1)]
Kdir1 = get_axis_cvector(st.session_state[f"anisotropy_axis{id_}"])
# Kdir1 = get_axis_cvector(st.session_state[f"anisotropy_axis{id_}"])
Kdir = FieldScan.angle2vector(
theta=st.session_state[f"theta_K{id_}"], phi=st.session_state[f"phi_K{id_}"]
)
layer = Layer(
id=f"domain_{id_}",
mag=Kdir1,
anis=Kdir1,
mag=Kdir,
anis=Kdir,
Ms=st.session_state["Ms_shared"],
thickness=st.session_state["thickness_shared"] * 1e-9,
cellSurface=1e-16,
Expand All @@ -34,11 +37,13 @@ def create_single_domain(id_: str) -> Layer:
def create_single_layer(id_: str) -> tuple:
"""Do not forget to rescale the units!"""
demag = [CVector(0, 0, 0), CVector(0, 0, 0), CVector(0, 0, 1)]
Kdir1 = get_axis_cvector(st.session_state[f"anisotropy_axis{id_}"])
Kdir = FieldScan.angle2vector(
theta=st.session_state[f"theta_K{id_}"], phi=st.session_state[f"phi_K{id_}"]
)
layer = Layer(
id=f"layer_{id_}",
mag=Kdir1,
anis=Kdir1,
mag=Kdir,
anis=Kdir,
Ms=st.session_state[f"Ms{id_}"],
thickness=st.session_state[f"thickness{id_}"] * 1e-9,
cellSurface=1e-16,
Expand Down
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