|
importScripts("https://cdn.jsdelivr.net/pyodide/v0.24.1/full/pyodide.js"); |
|
|
|
function sendPatch(patch, buffers, msg_id) { |
|
self.postMessage({ |
|
type: 'patch', |
|
patch: patch, |
|
buffers: buffers |
|
}) |
|
} |
|
|
|
async function startApplication() { |
|
console.log("Loading pyodide!"); |
|
self.postMessage({type: 'status', msg: 'Loading pyodide'}) |
|
self.pyodide = await loadPyodide(); |
|
self.pyodide.globals.set("sendPatch", sendPatch); |
|
console.log("Loaded!"); |
|
await self.pyodide.loadPackage("micropip"); |
|
const env_spec = ['https://cdn.holoviz.org/panel/wheels/bokeh-3.3.2-py3-none-any.whl', 'https://cdn.holoviz.org/panel/1.3.6/dist/wheels/panel-1.3.6-py3-none-any.whl', 'pyodide-http==0.2.1', 'pandas'] |
|
for (const pkg of env_spec) { |
|
let pkg_name; |
|
if (pkg.endsWith('.whl')) { |
|
pkg_name = pkg.split('/').slice(-1)[0].split('-')[0] |
|
} else { |
|
pkg_name = pkg |
|
} |
|
self.postMessage({type: 'status', msg: `Installing ${pkg_name}`}) |
|
try { |
|
await self.pyodide.runPythonAsync(` |
|
import micropip |
|
await micropip.install('${pkg}'); |
|
`); |
|
} catch(e) { |
|
console.log(e) |
|
self.postMessage({ |
|
type: 'status', |
|
msg: `Error while installing ${pkg_name}` |
|
}); |
|
} |
|
} |
|
console.log("Packages loaded!"); |
|
self.postMessage({type: 'status', msg: 'Executing code'}) |
|
const code = ` |
|
|
|
import asyncio |
|
|
|
from panel.io.pyodide import init_doc, write_doc |
|
|
|
init_doc() |
|
|
|
|
|
|
|
import panel as pn |
|
import pandas as pd |
|
|
|
from bokeh.plotting import figure |
|
from bokeh.layouts import layout |
|
from bokeh.models import ( |
|
ColumnDataSource, |
|
Range1d, |
|
Slider, |
|
Button, |
|
TextInput, |
|
LabelSet, |
|
Circle, |
|
Div, |
|
) |
|
|
|
class StumpyBokehDashboard: |
|
def __init__(self): |
|
self.sizing_mode = "stretch_both" |
|
self.window = 0 |
|
self.m = None |
|
|
|
self.df = None |
|
self.ts_cds = None |
|
self.quad_cds = None |
|
self.pattern_match_cds = None |
|
self.dist_cds = None |
|
self.circle_cds = None |
|
|
|
self.ts_plot = None |
|
self.mp_plot = None |
|
self.pm_plot = None |
|
self.logo_div = None |
|
self.heroku_div = None |
|
|
|
self.slider = None |
|
self.play_btn = None |
|
self.txt_inp = None |
|
self.pattern_btn = None |
|
self.match_btn = None |
|
self.reset_btn = None |
|
self.idx = None |
|
self.min_distance_idx = None |
|
|
|
self.animation = pn.state.add_periodic_callback( |
|
self.update_animate, 50, start=False |
|
) |
|
|
|
def get_df_from_file(self): |
|
raw_df = pd.read_csv( |
|
"https://raw.githubusercontent.com/seanlaw/stumpy-live-demo/master/raw.csv" |
|
) |
|
|
|
mp_df = pd.read_csv( |
|
"https://raw.githubusercontent.com/seanlaw/stumpy-live-demo/master/matrix_profile.csv" |
|
) |
|
|
|
self.window = raw_df.shape[0] - mp_df.shape[0] + 1 |
|
self.m = raw_df.shape[0] - mp_df.shape[0] + 1 |
|
self.min_distance_idx = mp_df["distance"].argmin() |
|
|
|
df = pd.merge(raw_df, mp_df, left_index=True, how="left", right_index=True) |
|
|
|
return df.reset_index() |
|
|
|
def get_ts_dict(self, df): |
|
return self.df.to_dict(orient="list") |
|
|
|
def get_circle_dict(self, df): |
|
return self.df[["index", "y"]].to_dict(orient="list") |
|
|
|
def get_quad_dict(self, df, pattern_idx=0, match_idx=None): |
|
if match_idx is None: |
|
match_idx = df.loc[pattern_idx, "idx"].astype(int) |
|
quad_dict = dict( |
|
pattern_left=[pattern_idx], |
|
pattern_right=[pattern_idx + self.window - 1], |
|
pattern_top=[max(df["y"])], |
|
pattern_bottom=[0], |
|
match_left=[match_idx], |
|
match_right=[match_idx + self.window - 1], |
|
match_top=[max(df["y"])], |
|
match_bottom=[0], |
|
vert_line_left=[pattern_idx - 5], |
|
vert_line_right=[pattern_idx + 5], |
|
vert_line_top=[max(df["distance"])], |
|
vert_line_bottom=[0], |
|
hori_line_left=[0], |
|
hori_line_right=[max(df["index"])], |
|
hori_line_top=[df.loc[pattern_idx, "distance"] - 0.01], |
|
hori_line_bottom=[df.loc[pattern_idx, "distance"] + 0.01], |
|
) |
|
return quad_dict |
|
|
|
def get_custom_quad_dict(self, df, pattern_idx=0, match_idx=None): |
|
if match_idx is None: |
|
match_idx = df.loc[pattern_idx, "idx"].astype(int) |
|
quad_dict = dict( |
|
pattern_left=[pattern_idx], |
|
pattern_right=[pattern_idx + self.window - 1], |
|
pattern_top=[max(df["y"])], |
|
pattern_bottom=[0], |
|
match_left=[match_idx], |
|
match_right=[match_idx + self.window - 1], |
|
match_top=[max(df["y"])], |
|
match_bottom=[0], |
|
vert_line_left=[match_idx - 5], |
|
vert_line_right=[match_idx + 5], |
|
vert_line_top=[max(df["distance"])], |
|
vert_line_bottom=[0], |
|
hori_line_left=[0], |
|
hori_line_right=[max(df["index"])], |
|
hori_line_top=[df.loc[match_idx, "distance"] - 0.01], |
|
hori_line_bottom=[df.loc[match_idx, "distance"] + 0.01], |
|
) |
|
return quad_dict |
|
|
|
def get_pattern_match_dict(self, df, pattern_idx=0, match_idx=None): |
|
if match_idx is None: |
|
match_idx = df["idx"].loc[pattern_idx].astype(int) |
|
pattern_match_dict = dict( |
|
index=list(range(self.window)), |
|
pattern=df["y"].loc[pattern_idx : pattern_idx + self.window - 1], |
|
match=df["y"].loc[match_idx : match_idx + self.window - 1], |
|
) |
|
|
|
return pattern_match_dict |
|
|
|
def get_ts_plot(self, color="black"): |
|
""" |
|
Time Series Plot |
|
""" |
|
ts_plot = figure( |
|
toolbar_location="above", |
|
sizing_mode=self.sizing_mode, |
|
title="Raw Time Series or Sequence", |
|
tools=["reset"], |
|
) |
|
q = ts_plot.quad( |
|
"pattern_left", |
|
"pattern_right", |
|
"pattern_top", |
|
"pattern_bottom", |
|
source=self.quad_cds, |
|
name="pattern_quad", |
|
color="#54b847", |
|
) |
|
q.visible = False |
|
q = ts_plot.quad( |
|
"match_left", |
|
"match_right", |
|
"match_top", |
|
"match_bottom", |
|
source=self.quad_cds, |
|
name="match_quad", |
|
color="#696969", |
|
alpha=0.5, |
|
) |
|
q.visible = False |
|
l = ts_plot.line(x="index", y="y", source=self.ts_cds, color=color) |
|
ts_plot.x_range = Range1d( |
|
0, max(self.df["index"]), bounds=(0, max(self.df["x"])) |
|
) |
|
ts_plot.y_range = Range1d(0, max(self.df["y"]), bounds=(0, max(self.df["y"]))) |
|
|
|
c = ts_plot.circle( |
|
x="index", y="y", source=self.circle_cds, size=0, line_color="white" |
|
) |
|
c.selection_glyph = Circle(line_color="white") |
|
c.nonselection_glyph = Circle(line_color="white") |
|
|
|
return ts_plot |
|
|
|
def get_dist_dict(self, df, pattern_idx=0): |
|
dist = df["distance"] |
|
max_dist = dist.max() |
|
min_dist = dist.min() |
|
x_offset = self.df.shape[0] - self.window / 2 |
|
y_offset = max_dist / 2 |
|
distance = dist.loc[pattern_idx] |
|
text = distance.round(1).astype(str) |
|
gauge_dict = dict(x=[0 + x_offset], y=[0 + y_offset], text=[text]) |
|
|
|
return gauge_dict |
|
|
|
def get_mp_plot(self): |
|
""" |
|
Matrix Profile Plot |
|
""" |
|
mp_plot = figure( |
|
x_range=self.ts_plot.x_range, |
|
toolbar_location=None, |
|
sizing_mode=self.sizing_mode, |
|
title="Matrix Profile (All Minimum Distances)", |
|
) |
|
q = mp_plot.quad( |
|
"vert_line_left", |
|
"vert_line_right", |
|
"vert_line_top", |
|
"vert_line_bottom", |
|
source=self.quad_cds, |
|
name="pattern_start", |
|
color="#54b847", |
|
) |
|
q.visible = False |
|
q = mp_plot.quad( |
|
"hori_line_left", |
|
"hori_line_right", |
|
"hori_line_top", |
|
"hori_line_bottom", |
|
source=self.quad_cds, |
|
name="match_dist", |
|
color="#696969", |
|
alpha=0.5, |
|
) |
|
q.visible = False |
|
mp_plot.line(x="index", y="distance", source=self.ts_cds, color="black") |
|
|
|
mp_plot.x_range = Range1d( |
|
0, self.df.shape[0] + 1, bounds=(0, self.df.shape[0] + 1) |
|
) |
|
mp_plot.y_range = Range1d( |
|
0, max(self.df["distance"]), bounds=(0, max(self.df["distance"])) |
|
) |
|
|
|
label = LabelSet( |
|
x="x", |
|
y="y", |
|
text="text", |
|
source=self.dist_cds, |
|
text_align="center", |
|
name="gauge_label", |
|
text_color="black", |
|
text_font_size="30pt", |
|
) |
|
mp_plot.add_layout(label) |
|
|
|
return mp_plot |
|
|
|
def get_pm_plot(self): |
|
""" |
|
Pattern-Match Plot |
|
""" |
|
pm_plot = figure( |
|
toolbar_location=None, |
|
sizing_mode=self.sizing_mode, |
|
title="Pattern Match Overlay", |
|
) |
|
l = pm_plot.line( |
|
"index", |
|
"pattern", |
|
source=self.pattern_match_cds, |
|
name="pattern_line", |
|
color="#54b847", |
|
line_width=2, |
|
) |
|
l.visible = False |
|
l = pm_plot.line( |
|
"index", |
|
"match", |
|
source=self.pattern_match_cds, |
|
name="match_line", |
|
color="#696969", |
|
alpha=0.5, |
|
line_width=2, |
|
) |
|
l.visible = False |
|
|
|
return pm_plot |
|
|
|
def get_logo_div(self): |
|
""" |
|
STUMPY logo |
|
""" |
|
|
|
logo_div = Div( |
|
text="<a href='https://stumpy.readthedocs.io/en/latest/'><img src='https://raw.githubusercontent.com/TDAmeritrade/stumpy/main/docs/images/stumpy_logo_small.png' style='width:100%'></a>", sizing_mode="stretch_width" |
|
) |
|
|
|
return logo_div |
|
|
|
def get_heroku_div(self): |
|
""" |
|
STUMPY Heroku App Link |
|
""" |
|
|
|
heroku_div = Div(text="http://tiny.cc/stumpy-demo") |
|
|
|
return heroku_div |
|
|
|
def get_slider(self, value=0): |
|
slider = Slider( |
|
start=0.0, |
|
end=max(self.df["index"]) - self.window, |
|
value=value, |
|
step=1, |
|
title="Subsequence", |
|
sizing_mode=self.sizing_mode, |
|
) |
|
return slider |
|
|
|
def get_play_button(self): |
|
play_btn = Button(label="► Play") |
|
play_btn.on_click(self.animate) |
|
return play_btn |
|
|
|
def get_text_input(self): |
|
txt_inp = TextInput(sizing_mode=self.sizing_mode) |
|
return txt_inp |
|
|
|
def get_buttons(self): |
|
pattern_btn = Button(label="Show Motif", sizing_mode=self.sizing_mode) |
|
match_btn = Button(label="Show Nearest Neighbor", sizing_mode=self.sizing_mode) |
|
reset_btn = Button(label="Reset", sizing_mode=self.sizing_mode, button_type="primary") |
|
return pattern_btn, match_btn, reset_btn |
|
|
|
def update_plots(self, attr, new, old): |
|
self.quad_cds.data = self.get_quad_dict(self.df, self.slider.value) |
|
self.pattern_match_cds.data = self.get_pattern_match_dict( |
|
self.df, self.slider.value |
|
) |
|
self.dist_cds.data = self.get_dist_dict(self.df, self.slider.value) |
|
|
|
def custom_update_plots(self, attr, new, old): |
|
self.quad_cds.data = self.get_custom_quad_dict( |
|
self.df, self.pattern_idx, self.slider.value |
|
) |
|
self.pattern_match_cds.data = self.get_pattern_match_dict( |
|
self.df, self.pattern_idx, self.slider.value |
|
) |
|
self.dist_cds.data = self.get_dist_dict(self.df, self.slider.value) |
|
dist = self.df["distance"].loc[self.slider.value] |
|
|
|
def show_hide_pattern(self): |
|
pattern_quad = self.ts_plot.select(name="pattern_quad")[0] |
|
pattern_start = self.mp_plot.select(name="pattern_start")[0] |
|
pattern_line = self.pm_plot.select(name="pattern_line")[0] |
|
if pattern_quad.visible: |
|
pattern_start.visible = False |
|
pattern_line.visible = False |
|
pattern_quad.visible = False |
|
self.pattern_btn.label = "Show Motif" |
|
else: |
|
pattern_start.visible = True |
|
pattern_line.visible = True |
|
pattern_quad.visible = True |
|
self.pattern_btn.label = "Hide Motif" |
|
|
|
def show_hide_match(self): |
|
match_quad = self.ts_plot.select(name="match_quad")[0] |
|
match_dist = self.mp_plot.select(name="match_dist")[0] |
|
match_line = self.pm_plot.select(name="match_line")[0] |
|
if match_quad.visible: |
|
match_dist.visible = False |
|
match_line.visible = False |
|
match_quad.visible = False |
|
self.match_btn.label = "Show Nearest Neighbor" |
|
else: |
|
match_dist.visible = True |
|
match_line.visible = True |
|
match_quad.visible = True |
|
self.match_btn.label = "Hide Nearest Neighbor" |
|
|
|
def update_slider(self, attr, old, new): |
|
self.slider.value = int(self.txt_inp.value) |
|
|
|
def animate(self): |
|
if self.play_btn.label == "► Play": |
|
self.play_btn.label = "❚❚ Pause" |
|
self.animation.start() |
|
else: |
|
self.play_btn.label = "► Play" |
|
self.animation.stop() |
|
|
|
def update_animate(self, shift=50): |
|
if self.window < self.m: |
|
start = self.slider.value |
|
end = start + shift |
|
if self.df.loc[start:end, "distance"].min() <= 15: |
|
self.slider.value = self.df.loc[start:end, "distance"].idxmin() |
|
self.animate() |
|
elif self.slider.value + shift <= self.slider.end: |
|
self.slider.value = self.slider.value + shift |
|
else: |
|
self.slider.value = 0 |
|
elif self.slider.value + shift <= self.slider.end: |
|
self.slider.value = self.slider.value + shift |
|
else: |
|
self.slider.value = 0 |
|
|
|
def reset(self): |
|
self.sizing_mode = "stretch_both" |
|
self.window = self.m |
|
|
|
self.default_idx = self.min_distance_idx |
|
self.df = self.get_df_from_file() |
|
self.ts_cds.data = self.get_ts_dict(self.df) |
|
self.mp_plot.y_range.end = max(self.df["distance"]) |
|
self.mp_plot.title.text = "Matrix Profile (All Minimum Distances)" |
|
self.mp_plot.y_range.bounds = (0, max(self.df["distance"])) |
|
self.quad_cds.data = self.get_quad_dict(self.df, pattern_idx=self.default_idx) |
|
self.pattern_match_cds.data = self.get_pattern_match_dict( |
|
self.df, pattern_idx=self.default_idx |
|
) |
|
self.dist_cds.data = self.get_dist_dict(self.df, pattern_idx=self.default_idx) |
|
self.circle_cds.data = self.get_circle_dict(self.df) |
|
|
|
if self.custom_update_plots in self.slider._callbacks["value"]: |
|
self.slider.remove_on_change("value", self.custom_update_plots) |
|
self.slider.on_change("value", self.update_plots) |
|
self.slider.end = self.df.shape[0] - self.window |
|
self.slider.value = self.default_idx |
|
|
|
def get_data(self): |
|
self.df = self.get_df_from_file() |
|
self.default_idx = self.min_distance_idx |
|
self.ts_cds = ColumnDataSource(self.get_ts_dict(self.df)) |
|
self.quad_cds = ColumnDataSource( |
|
self.get_quad_dict(self.df, pattern_idx=self.default_idx) |
|
) |
|
self.pattern_match_cds = ColumnDataSource( |
|
self.get_pattern_match_dict(self.df, pattern_idx=self.default_idx) |
|
) |
|
self.dist_cds = ColumnDataSource( |
|
self.get_dist_dict(self.df, pattern_idx=self.default_idx) |
|
) |
|
self.circle_cds = ColumnDataSource(self.get_circle_dict(self.df)) |
|
|
|
def get_plots(self, ts_plot_color="black"): |
|
self.ts_plot = self.get_ts_plot(color=ts_plot_color) |
|
self.mp_plot = self.get_mp_plot() |
|
self.pm_plot = self.get_pm_plot() |
|
|
|
def get_widgets(self): |
|
self.slider = self.get_slider(value=self.default_idx) |
|
self.play_btn = self.get_play_button() |
|
self.txt_inp = self.get_text_input() |
|
self.pattern_btn, self.match_btn, self.reset_btn = self.get_buttons() |
|
self.logo_div = self.get_logo_div() |
|
self.heroku_div = self.get_heroku_div() |
|
|
|
def set_callbacks(self): |
|
self.slider.on_change("value", self.update_plots) |
|
self.pattern_btn.on_click(self.show_hide_pattern) |
|
self.show_hide_pattern() |
|
self.match_btn.on_click(self.show_hide_match) |
|
self.show_hide_match() |
|
self.reset_btn.on_click(self.reset) |
|
self.txt_inp.on_change("value", self.update_slider) |
|
|
|
def get_layout(self): |
|
self.get_data() |
|
self.get_plots() |
|
self.get_widgets() |
|
self.set_callbacks() |
|
|
|
l = layout( |
|
[ |
|
[self.ts_plot], |
|
[self.mp_plot], |
|
[self.pm_plot], |
|
[self.slider], |
|
[self.pattern_btn, self.match_btn, self.play_btn, self.logo_div], |
|
], |
|
sizing_mode=self.sizing_mode, |
|
) |
|
|
|
return l |
|
|
|
def get_raw_layout(self): |
|
self.get_data() |
|
self.get_plots(ts_plot_color="#54b847") |
|
|
|
l = layout([[self.ts_plot], [self.mp_plot]], sizing_mode=self.sizing_mode) |
|
|
|
return l |
|
|
|
|
|
dashboard = StumpyBokehDashboard() |
|
|
|
def get_components(dashboard: StumpyBokehDashboard=dashboard): |
|
dashboard.get_data() |
|
dashboard.get_plots() |
|
dashboard.get_widgets() |
|
dashboard.set_callbacks() |
|
|
|
logo = dashboard.logo_div |
|
settings = layout( |
|
dashboard.pattern_btn, |
|
dashboard.match_btn, |
|
dashboard.play_btn, |
|
dashboard.slider, |
|
height=150, |
|
sizing_mode="stretch_width", |
|
) |
|
main = layout( |
|
[ |
|
[dashboard.ts_plot], |
|
[dashboard.mp_plot], |
|
[dashboard.pm_plot], |
|
], |
|
sizing_mode=dashboard.sizing_mode, |
|
) |
|
return logo, settings, main |
|
|
|
pn.extension(template="fast") |
|
pn.state.template.param.update( |
|
site_url="https://awesome-panel.org", |
|
site="Awesome Panel", |
|
title="Stumpy Timeseries Analysis", |
|
favicon="https://raw.githubusercontent.com/MarcSkovMadsen/awesome-panel-assets/320297ccb92773da099f6b97d267cc0433b67c23/favicon/ap-1f77b4.ico", |
|
header_background="#459db9", |
|
theme_toggle=False, |
|
) |
|
|
|
logo, settings, main = get_components() |
|
|
|
pn.Column( |
|
logo, |
|
settings, sizing_mode="stretch_width", |
|
).servable(target="sidebar") |
|
pn.panel(main, sizing_mode="stretch_both", max_height=800).servable(target="main") |
|
|
|
|
|
await write_doc() |
|
` |
|
|
|
try { |
|
const [docs_json, render_items, root_ids] = await self.pyodide.runPythonAsync(code) |
|
self.postMessage({ |
|
type: 'render', |
|
docs_json: docs_json, |
|
render_items: render_items, |
|
root_ids: root_ids |
|
}) |
|
} catch(e) { |
|
const traceback = `${e}` |
|
const tblines = traceback.split('\n') |
|
self.postMessage({ |
|
type: 'status', |
|
msg: tblines[tblines.length-2] |
|
}); |
|
throw e |
|
} |
|
} |
|
|
|
self.onmessage = async (event) => { |
|
const msg = event.data |
|
if (msg.type === 'rendered') { |
|
self.pyodide.runPythonAsync(` |
|
from panel.io.state import state |
|
from panel.io.pyodide import _link_docs_worker |
|
|
|
_link_docs_worker(state.curdoc, sendPatch, setter='js') |
|
`) |
|
} else if (msg.type === 'patch') { |
|
self.pyodide.globals.set('patch', msg.patch) |
|
self.pyodide.runPythonAsync(` |
|
state.curdoc.apply_json_patch(patch.to_py(), setter='js') |
|
`) |
|
self.postMessage({type: 'idle'}) |
|
} else if (msg.type === 'location') { |
|
self.pyodide.globals.set('location', msg.location) |
|
self.pyodide.runPythonAsync(` |
|
import json |
|
from panel.io.state import state |
|
from panel.util import edit_readonly |
|
if state.location: |
|
loc_data = json.loads(location) |
|
with edit_readonly(state.location): |
|
state.location.param.update({ |
|
k: v for k, v in loc_data.items() if k in state.location.param |
|
}) |
|
`) |
|
} |
|
} |
|
|
|
startApplication() |