def bokeh_spacetimepop(
frm,
geometry,
title = '',
preamble = '',
varNames = None,
varNotes = dict(),
pw = 700,
ph = 700,
xZones = dict(),
):
import numpy as np
import pandas as pd
df = pd.DataFrame
idx = pd.IndexSlice
import geopandas as gpd
gdf = gpd.GeoDataFrame
from bokeh.models import ColumnDataSource, HoverTool, Legend, LegendItem, CDSView, IndexFilter
from bokeh.plotting import figure, show
from bokeh.io import output_notebook
# frm = frm.reset_index().pivot(index = frm.index.names[0], columns = frm.index.names[1])
frm = frm.copy()
frm = frm.sort_index()
# geometry = geometry.copy()
from bokeh.models import Div
title = f'<h1>{title}</h1>'
title = Div(
text = title,
width = pw,
)
preamble = Div(
text = preamble,
width = pw,
)
if varNames is None:
varNames = frm.columns.sort_values()
varMetaName = varNames.name
else:
varMetaName = 'variable'
varNames = list(varNames)
seriesNames = frm.index.levels[1].sort_values()
seriesMetaName = seriesNames.name
seriesNames = list(seriesNames)
dates = [str(int(round(i.to_numpy().astype(int) / 1e6))) for i in frm.index.levels[0]]
frm.index = frm.index.set_levels(dates, level = 0)
defaultVar = varNames[0]
defaultDate = dates[-1]
pivotFrm = frm.reset_index() \
.pivot(index = frm.index.names[0], columns = frm.index.names[1]) \
.sort_index()
defaultVar = varNames[0]
defaultDate = dates[-1]
for key in varNames:
if not key in varNotes:
varNotes[key] = ''
else:
varNotes[key] = f'<i>{varNotes[key]}</i>'
varNote = Div(
text = varNotes[defaultVar],
width = pw - 120,
)
lineSources = {
key: ColumnDataSource(pivotFrm[key])
for key in pivotFrm.columns.levels[0]
}
lineSource = ColumnDataSource(pivotFrm[defaultVar])
lineSource.name = defaultVar
barSources = dict()
for varName in varNames:
for index, date in zip(sorted(pivotFrm.index), dates):
series = pivotFrm.loc[index, varName]
subFrm = df(dict(
name = series.index,
value = series.values,
height = abs(series.values),
offset = series.values / 2.
))
barSources[varName + '_' + date] = ColumnDataSource(subFrm)
barSource = ColumnDataSource(barSources[defaultVar + '_' + defaultDate].data)
barSource.name = ', '.join([str(defaultVar), str(defaultDate)])
bounds = geometry.bounds
minx = np.min(bounds['minx'])
maxx = np.max(bounds['maxx'])
miny = np.min(bounds['miny'])
maxy = np.max(bounds['maxy'])
aspect = (maxx - minx) / (maxy - miny)
from shapely.geometry import Polygon
import itertools
corners = list(itertools.product(geometry.total_bounds[::2], geometry.total_bounds[1::2]))
allPoly = Polygon([corners[0], corners[1], corners[3], corners[2]])
allPoly = allPoly.centroid.buffer(np.sqrt(allPoly.area) / 1e6)
for name in frm.index.levels[1]:
if not name in geometry.index:
geometry[name] = allPoly
geometry = geometry.simplify(np.sqrt(geometry.area).min() * 10. ** 3.5)
geoFrm = frm.reset_index().pivot(index = frm.index.names[1], columns = frm.index.names[0])
geoFrm.columns = geoFrm.columns.map('_'.join).str.strip('_')
geoFrm['geometry'] = geometry
geoFrm = gdf(geoFrm)
from bokeh.models import GeoJSONDataSource
geoJSON = geoFrm.reset_index().to_json()
geoSource = GeoJSONDataSource(geojson = geoJSON)
mins = {n: frm[n].min() for n in varNames}
maxs = {n: frm[n].max() for n in varNames}
xName = frm.index.names[0]
lineFig = figure(
x_axis_type = 'datetime',
y_range = (mins[defaultVar], maxs[defaultVar]),
plot_height = int((ph - 100) * 1. / 3.),
plot_width = pw,
toolbar_location = 'left',
tools = 'save, xpan, box_zoom, reset, xwheel_zoom',
active_scroll = 'auto',
# title = title,
)
barFig = figure(
x_range = seriesNames,
plot_height = int((ph - 100) * 1. / 2.),
plot_width = pw,
# title = "Scores on my birthday",
toolbar_location = None,
tools = ""
)
barFig.xgrid.grid_line_color = None
barFig.xaxis.major_label_orientation = 'vertical'
mapFig = figure(
plot_width = pw - 20,
plot_height = int(round((pw - 20) / aspect)),
toolbar_location = 'right',
tools = 'pan, wheel_zoom, reset',
background_fill_color = "lightgrey"
)
mapFig.xgrid.grid_line_color = None
mapFig.ygrid.grid_line_color = None
from matplotlib.pyplot import get_cmap
from matplotlib.colors import rgb2hex
cmap = get_cmap('nipy_spectral')
cs = [rgb2hex(cmap(i / len(seriesNames), alpha = 0.5)) for i in range(len(seriesNames))]
lines = []
for seriesName, colour in zip(seriesNames, cs):
line = lineFig.line(
xName,
seriesName,
source = lineSource,
color = colour,
alpha = 0.8,
muted_color = 'gray',
muted_alpha = 0.3,
muted = True,
line_width = 2,
# legend_label = seriesName,
)
from bokeh.models import HoverTool
lineFig.add_tools(HoverTool(
renderers = [
line,
],
tooltips = [
(seriesMetaName.capitalize(), seriesName),
(xName.capitalize(), f'@{xName}' + '{%Y-%m-%d}'),
('Value', f'@{{{seriesName}}}'),
],
formatters = {
f'@{xName}': 'datetime',
seriesName: 'numeral',
},
toggleable = False
))
lines.append(line)
bars = []
for i, (seriesName, colour) in enumerate(zip(seriesNames, cs)):
view = CDSView(source = barSource, filters = [IndexFilter([i,]),])
bar = barFig.rect(
source = barSource,
view = view,
x = 'name',
y = 'offset',
height = 'height',
width = 0.9,
color = colour,
muted_color = 'gray',
muted_alpha = 0.3,
muted = True,
)
bars.append(bar)
from bokeh.palettes import Viridis256
from bokeh.models import LinearColorMapper, ColorBar
palette = Viridis256
mapColourMapper = LinearColorMapper(
palette = palette,
low = frm.loc[idx[defaultDate, :], defaultVar].min(),
high = frm.loc[idx[defaultDate, :], defaultVar].max(),
)
mapColourBar = ColorBar(
color_mapper = mapColourMapper,
label_standoff = 8,
width = 30,
height = int(round(mapFig.plot_height * 0.9)),
border_line_color = None,
location = (0, 0),
orientation = 'vertical',
)
mapFig.add_layout(mapColourBar, 'left')
patches = []
for i, seriesName in enumerate(seriesNames):
view = CDSView(source = geoSource, filters = [IndexFilter([i,]),])
patch = mapFig.patches(
'xs',
'ys',
source = geoSource,
view = view,
fill_color = dict(
field = '_'.join([defaultVar, defaultDate]),
transform = mapColourMapper,
),
line_color = 'grey',
line_width = 0.25,
fill_alpha = 0.,
name = '_'.join([defaultVar, defaultDate])
)
patches.append(patch)
from bokeh.models import HoverTool
mapHover = HoverTool(
renderers = patches,
tooltips = [
(seriesMetaName.capitalize(), f'@{seriesMetaName}'),
('Value', '@$name'),
]
)
mapFig.add_tools(mapHover)
from bokeh.models import BoxAnnotation
from bokeh.models import Label
for name, zone in xZones.items():
convD = lambda x: int(round(pd.Timestamp(x).to_numpy().astype(int) / 1e6))
left, right = [None if val is None else convD(val) for val in zone]
zone = BoxAnnotation(
left = left,
right = right,
fill_alpha = 0.1,
fill_color = 'gray',
)
zoneLabel = Label(
text = name + ' (end)' if left is None else name,
text_font_size = '8pt',
x = right if left is None else left,
y = 10,
x_units = 'data',
y_units = 'screen',
angle = -90 if left is None else 90,
angle_units = 'deg',
x_offset = -10 if left is None else 10,
y_offset = 5 * (len(name) + 6) if left is None else 0
)
lineFig.add_layout(zone)
lineFig.add_layout(zoneLabel)
from bokeh.models import Span
span = Span(
location = int(defaultDate),
dimension = 'height',
line_color = 'red',
# line_dash = 'dashed',
line_width = 1
)
lineFig.add_layout(span)
from bokeh.models.widgets import DateSlider
slider = DateSlider(
title = 'Date',
start = int(dates[0]),
end = int(dates[-1]),
step = int(8.64 * 1e7), # days
value = int(defaultDate),
width = pw - 60,
align = 'end'
)
from bokeh.models.widgets import Select
select = Select(
title = "Choose data:",
options = varNames,
value = defaultVar,
width = 100,
)
from bokeh.models import CheckboxGroup
checkboxes = CheckboxGroup(
labels = seriesNames,
active = [],
)
checkboxAll = CheckboxGroup(
labels = ['All',],
active = [],
)
from bokeh.models import CustomJS
callback = CustomJS(
args = dict(
y_range = lineFig.y_range,
lineSources = lineSources,
lineSource = lineSource,
barSources = barSources,
barSource = barSource,
bars = bars,
lines = lines,
patches = patches,
select = select,
slider = slider,
span = span,
checkboxes = checkboxes,
varNote = varNote,
varNotes = varNotes,
geoSource = geoSource,
mapColourMapper = mapColourMapper,
mins = mins,
maxs = maxs,
),
code = """
lineSource.data = lineSources[select.value].data
lineSource.name = select.value
lineSource.change.emit()
span.location = slider.value
span.change.emit()
y_range.setv({'start': mins[select.value], 'end': maxs[select.value]})
varNote.text = varNotes[select.value]
varNote.change.emit()
const barChoice = select.value + '_' + slider.value
barSource.data = barSources[barChoice].data
barSource.name = select.value.toString() + ', ' + slider.value.toString()
barSource.change.emit()
for (let i = 0; i < lines.length; i++){
let checked = checkboxes.active.includes(i)
lines[i].muted = !(checked)
bars[i].muted = !(checked)
var alpha = checked ? 1 : 0;
patches[i].glyph.fill_alpha = alpha
}
const newCol = select.value + '_' + slider.value
for (let i = 0; i < lines.length; i++){
patches[i].glyph.fill_color['field'] = newCol
patches[i].name = newCol
}
mapColourMapper.low = mins[select.value]
mapColourMapper.high = maxs[select.value]
geoSource.change.emit()
""",
)
allCheckCallback = CustomJS(
args = dict(
lines = lines,
checkboxes = checkboxes,
checkboxAll = checkboxAll,
callback = callback
),
code = """
checkboxes.active.length = 0
if (checkboxAll.active.length > 0) {
let arr = []
for (let i = 0; i < lines.length; i++){
arr.push(i)
}
checkboxes.active.push(...arr)
}
checkboxes.change.emit()
callback.execute()
"""
)
slider.js_on_change('value', callback)
select.js_on_change('value', callback)
checkboxes.js_on_change('active', callback)
checkboxAll.js_on_change('active', allCheckCallback)
from bokeh.layouts import column, row
layout = column(
title,
preamble,
row(select, varNote),
row(column(lineFig, slider, barFig), column(checkboxes, checkboxAll)),
mapFig
)
return layout
plots[0].x_range.end=len;
plots[0].y_range.end=closest;
plots[0].y_range.start=0;
plots[1].x_range.end=len;
plots[1].y_range.end=closest;
plots[1].y_range.start=1;
''')
#changes x range to be (0,slider_value)
#changes y range to be (0 or 1, the closest stastics value to slider)
slider = DateSlider(start=min(dates),
end=max(dates),
value=max(dates),
step=1,
title='Time')
slider.js_on_change('value', callback)
loopchange = CustomJS(args=dict(slider=slider,
endlen=max(dates),
minlen=min(dates)),
code='''
function sleep(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
async function run() {
var len = slider.value;
var loopcount=0;
while (cb_obj.active){
if (len>=endlen){
loopcount++;
if(loopcount==2){
def make_dateMap(frm, name, title, size = 600, nonVisKeys = {}):
minx = np.min(frm.bounds['minx'])
maxx = np.max(frm.bounds['maxx'])
miny = np.min(frm.bounds['miny'])
maxy = np.max(frm.bounds['maxy'])
aspect = (maxx - minx) / (maxy - miny)
ts = sorted(set([n.split('_')[-1] for n in frm.columns]))
ts = [n for n in ts if n.isnumeric()]
assert len(ts)
ns = sorted(set([n.split('_')[0] for n in frm.columns]))
ns = [n for n in ns if not n in [*nonVisKeys, 'geometry']]
assert len(ns)
defaultCol = '_'.join([ns[0], ts[-1]])
indexName = frm.index.name
mins = {n: frm[['_'.join([n, t]) for t in ts]].min().min() for n in ns}
maxs = {n: frm[['_'.join([n, t]) for t in ts]].max().max() for n in ns}
from bokeh.models import GeoJSONDataSource
geoJSON = frm.reset_index().to_json()
source = GeoJSONDataSource(geojson = geoJSON)
from bokeh.io import output_file
outFilename = name + '.html'
outPath = os.path.join(dataDir, outFilename)
if os.path.isfile(outPath):
os.remove(outPath)
output_file(outPath)
from bokeh.plotting import figure
fig = figure(
title = title,
plot_height = size,
plot_width = int(round(size * aspect)) + 50,
toolbar_location = 'right',
tools = 'pan, zoom_in, zoom_out, wheel_zoom, reset',
background_fill_color = "lightgrey"
)
fig.xgrid.grid_line_color = None
fig.ygrid.grid_line_color = None
from bokeh.palettes import Viridis256
from bokeh.models import LinearColorMapper, ColorBar
palette = Viridis256
colourMapper = LinearColorMapper(
palette = palette,
low = mins[ns[0]],
high = maxs[ns[0]],
)
colourBar = ColorBar(
color_mapper = colourMapper,
label_standoff = 8,
width = 30,
height = int(round(fig.plot_height * 0.9)),
border_line_color = None,
location = (0, 0),
orientation = 'vertical',
)
fig.add_layout(colourBar, 'left')
patches = fig.patches(
'xs',
'ys',
source = source,
fill_color = dict(
field = defaultCol,
transform = colourMapper,
),
line_color = 'grey',
line_width = 0.25,
fill_alpha = 1,
name = defaultCol
)
from bokeh.models.widgets import DateSlider as Slider
slider = Slider(
title = 'Date',
start = int(ts[0]),
end = int(ts[-1]),
step = int(8.64 * 1e7), # days
value = int(ts[-1]),
width = fig.plot_width - 70
)
from bokeh.models.widgets import Select
select = Select(
title = "Dataset",
options = ns,
value = defaultCol.split('_')[0],
width = 60
)
from bokeh.models import CustomJS
callback = CustomJS(
args = dict(
patches = patches,
source = source,
slider = slider,
# key = 'stay', # <--- TESTING
select = select,
colourMapper = colourMapper,
mins = mins,
maxs = maxs,
),
code = """
const newCol = select.value + '_' + slider.value
patches.glyph.fill_color['field'] = newCol
patches.name = newCol
colourMapper.low = mins[select.value]
colourMapper.high = maxs[select.value]
source.change.emit()
""",
)
from bokeh.models import HoverTool
tooltips = [
('Index', '@' + indexName),
('Value', '@$name')
]
tooltips.extend([(k.capitalize(), '@' + k) for k in nonVisKeys])
hover = HoverTool(
renderers = [patches],
tooltips = tooltips
)
fig.add_tools(hover)
slider.js_on_change('value', callback)
select.js_on_change('value', callback)
from bokeh.layouts import column, row
layout = column(fig, row(select, slider))
from bokeh.io import show
show(layout)