def generateSliders(file_name):
from bokeh.models.widgets import Slider
sliders = []
dataarray = data[file_name]
for dim in dataarray.dims:
slider = Slider(start=0, end=dataarray.sizes[dim], step=1)
#def change_value(attr, old, new):
# data
#slider.on_change("value", change_value)
slider.title = dim
sliders.append(slider)
return sliders
def plotspectra(spectra,
zcatalog=None,
model=None,
notebook=False,
title=None):
'''
TODO: document
'''
if notebook:
bk.output_notebook()
#- If inputs are frames, convert to a spectra object
if isinstance(spectra, list) and isinstance(spectra[0],
desispec.frame.Frame):
spectra = frames2spectra(spectra)
frame_input = True
else:
frame_input = False
if frame_input and title is None:
meta = spectra.meta
title = 'Night {} ExpID {} Spectrograph {}'.format(
meta['NIGHT'],
meta['EXPID'],
meta['CAMERA'][1],
)
#- Gather spectra into ColumnDataSource objects for Bokeh
nspec = spectra.num_spectra()
cds_spectra = list()
for band in spectra.bands:
#- Set masked bins to NaN so that Bokeh won't plot them
bad = (spectra.ivar[band] == 0.0) | (spectra.mask[band] != 0)
spectra.flux[band][bad] = np.nan
cdsdata = dict(
origwave=spectra.wave[band].copy(),
plotwave=spectra.wave[band].copy(),
)
for i in range(nspec):
key = 'origflux' + str(i)
cdsdata[key] = spectra.flux[band][i]
cdsdata['plotflux'] = cdsdata['origflux0']
cds_spectra.append(bk.ColumnDataSource(cdsdata, name=band))
#- Reorder zcatalog to match input targets
#- TODO: allow more than one zcatalog entry with different ZNUM per targetid
targetids = spectra.target_ids()
if zcatalog is not None:
ii = np.argsort(np.argsort(targetids))
jj = np.argsort(zcatalog['TARGETID'])
kk = jj[ii]
zcatalog = zcatalog[kk]
#- That sequence of argsorts may feel like magic,
#- so make sure we got it right
assert np.all(zcatalog['TARGETID'] == targetids)
assert np.all(zcatalog['TARGETID'] == spectra.fibermap['TARGETID'])
#- Also need to re-order input model fluxes
if model is not None:
mwave, mflux = model
model = mwave, mflux[kk]
#- Gather models into ColumnDataSource objects, row matched to spectra
if model is not None:
mwave, mflux = model
model_obswave = mwave.copy()
model_restwave = mwave.copy()
cds_model_data = dict(
origwave=mwave.copy(),
plotwave=mwave.copy(),
plotflux=np.zeros(len(mwave)),
)
for i in range(nspec):
key = 'origflux' + str(i)
cds_model_data[key] = mflux[i]
cds_model_data['plotflux'] = cds_model_data['origflux0']
cds_model = bk.ColumnDataSource(cds_model_data)
else:
cds_model = None
#- Subset of zcatalog and fibermap columns into ColumnDataSource
target_info = list()
for i, row in enumerate(spectra.fibermap):
target_bit_names = ' '.join(desi_mask.names(row['DESI_TARGET']))
txt = 'Target {}: {}'.format(row['TARGETID'], target_bit_names)
if zcatalog is not None:
txt += '<BR/>{} z={:.4f} ± {:.4f} ZWARN={}'.format(
zcatalog['SPECTYPE'][i],
zcatalog['Z'][i],
zcatalog['ZERR'][i],
zcatalog['ZWARN'][i],
)
target_info.append(txt)
cds_targetinfo = bk.ColumnDataSource(dict(target_info=target_info),
name='targetinfo')
if zcatalog is not None:
cds_targetinfo.add(zcatalog['Z'], name='z')
plot_width = 800
plot_height = 400
# tools = 'pan,box_zoom,wheel_zoom,undo,redo,reset,save'
tools = 'pan,box_zoom,wheel_zoom,reset,save'
fig = bk.figure(height=plot_height,
width=plot_width,
title=title,
tools=tools,
toolbar_location='above',
y_range=(-10, 20))
fig.toolbar.active_drag = fig.tools[1] #- box zoom
fig.toolbar.active_scroll = fig.tools[2] #- wheel zoom
fig.xaxis.axis_label = 'Wavelength [Å]'
fig.yaxis.axis_label = 'Flux'
fig.xaxis.axis_label_text_font_style = 'normal'
fig.yaxis.axis_label_text_font_style = 'normal'
colors = dict(b='#1f77b4', r='#d62728', z='maroon')
data_lines = list()
for spec in cds_spectra:
lx = fig.line('plotwave',
'plotflux',
source=spec,
line_color=colors[spec.name])
data_lines.append(lx)
if cds_model is not None:
model_lines = list()
lx = fig.line('plotwave',
'plotflux',
source=cds_model,
line_color='black')
model_lines.append(lx)
legend = Legend(items=[
("data",
data_lines[-1::-1]), #- reversed to get blue as lengend entry
("model", model_lines),
])
else:
legend = Legend(items=[
("data",
data_lines[-1::-1]), #- reversed to get blue as lengend entry
])
fig.add_layout(legend, 'center')
fig.legend.click_policy = 'hide' #- or 'mute'
#- Zoom figure around mouse hover of main plot
zoomfig = bk.figure(
height=plot_height // 2,
width=plot_height // 2,
y_range=fig.y_range,
x_range=(5000, 5100),
# output_backend="webgl",
toolbar_location=None,
tools=[])
for spec in cds_spectra:
zoomfig.line('plotwave',
'plotflux',
source=spec,
line_color=colors[spec.name],
line_width=1,
line_alpha=1.0)
if cds_model is not None:
zoomfig.line('plotwave',
'plotflux',
source=cds_model,
line_color='black')
#- Callback to update zoom window x-range
zoom_callback = CustomJS(args=dict(zoomfig=zoomfig),
code="""
zoomfig.x_range.start = cb_obj.x - 100;
zoomfig.x_range.end = cb_obj.x + 100;
""")
fig.js_on_event(bokeh.events.MouseMove, zoom_callback)
#-----
#- Emission and absorption lines
z = zcatalog['Z'][0] if (zcatalog is not None) else 0.0
line_data, lines, line_labels = add_lines(fig, z=z)
#-----
#- Add widgets for controling plots
z1 = np.floor(z * 100) / 100
dz = z - z1
zslider = Slider(start=0.0, end=4.0, value=z1, step=0.01, title='Redshift')
dzslider = Slider(start=0.0,
end=0.01,
value=dz,
step=0.0001,
title='+ Delta redshift')
dzslider.format = "0[.]0000"
#- Observer vs. Rest frame wavelengths
waveframe_buttons = RadioButtonGroup(labels=["Obs", "Rest"], active=0)
ifiberslider = Slider(start=0, end=nspec - 1, value=0, step=1)
if frame_input:
ifiberslider.title = 'Fiber'
else:
ifiberslider.title = 'Target'
zslider_callback = CustomJS(
args=dict(
spectra=cds_spectra,
model=cds_model,
targetinfo=cds_targetinfo,
ifiberslider=ifiberslider,
zslider=zslider,
dzslider=dzslider,
waveframe_buttons=waveframe_buttons,
line_data=line_data,
lines=lines,
line_labels=line_labels,
fig=fig,
),
#- TODO: reorder to reduce duplicated code
code="""
var z = zslider.value + dzslider.value
var line_restwave = line_data.data['restwave']
var ifiber = ifiberslider.value
var zfit = 0.0
if(targetinfo.data['z'] != undefined) {
zfit = targetinfo.data['z'][ifiber]
}
// Observer Frame
if(waveframe_buttons.active == 0) {
var x = 0.0
for(var i=0; i<line_restwave.length; i++) {
x = line_restwave[i] * (1+z)
lines[i].location = x
line_labels[i].x = x
}
for(var i=0; i<spectra.length; i++) {
var data = spectra[i].data
var origwave = data['origwave']
var plotwave = data['plotwave']
for (var j=0; j<plotwave.length; j++) {
plotwave[j] = origwave[j]
}
spectra[i].change.emit()
}
// Update model wavelength array
if(model) {
var origwave = model.data['origwave']
var plotwave = model.data['plotwave']
for(var i=0; i<plotwave.length; i++) {
plotwave[i] = origwave[i] * (1+z) / (1+zfit)
}
model.change.emit()
}
// Rest Frame
} else {
for(i=0; i<line_restwave.length; i++) {
lines[i].location = line_restwave[i]
line_labels[i].x = line_restwave[i]
}
for (var i=0; i<spectra.length; i++) {
var data = spectra[i].data
var origwave = data['origwave']
var plotwave = data['plotwave']
for (var j=0; j<plotwave.length; j++) {
plotwave[j] = origwave[j] / (1+z)
}
spectra[i].change.emit()
}
// Update model wavelength array
if(model) {
var origwave = model.data['origwave']
var plotwave = model.data['plotwave']
for(var i=0; i<plotwave.length; i++) {
plotwave[i] = origwave[i] / (1+zfit)
}
model.change.emit()
}
}
""")
zslider.js_on_change('value', zslider_callback)
dzslider.js_on_change('value', zslider_callback)
waveframe_buttons.js_on_click(zslider_callback)
plotrange_callback = CustomJS(args=dict(
zslider=zslider,
dzslider=dzslider,
waveframe_buttons=waveframe_buttons,
fig=fig,
),
code="""
var z = zslider.value + dzslider.value
// Observer Frame
if(waveframe_buttons.active == 0) {
fig.x_range.start = fig.x_range.start * (1+z)
fig.x_range.end = fig.x_range.end * (1+z)
} else {
fig.x_range.start = fig.x_range.start / (1+z)
fig.x_range.end = fig.x_range.end / (1+z)
}
""")
waveframe_buttons.js_on_click(plotrange_callback)
smootherslider = Slider(start=0,
end=31,
value=0,
step=1.0,
title='Gaussian Sigma Smooth')
target_info_div = Div(text=target_info[0])
#-----
#- Toggle lines
lines_button_group = CheckboxButtonGroup(labels=["Emission", "Absorption"],
active=[])
lines_callback = CustomJS(args=dict(line_data=line_data,
lines=lines,
line_labels=line_labels),
code="""
var show_emission = false
var show_absorption = false
if (cb_obj.active.indexOf(0) >= 0) { // index 0=Emission in active list
show_emission = true
}
if (cb_obj.active.indexOf(1) >= 0) { // index 1=Absorption in active list
show_absorption = true
}
for(var i=0; i<lines.length; i++) {
if(line_data.data['emission'][i]) {
lines[i].visible = show_emission
line_labels[i].visible = show_emission
} else {
lines[i].visible = show_absorption
line_labels[i].visible = show_absorption
}
}
""")
lines_button_group.js_on_click(lines_callback)
# lines_button_group.js_on_change('value', lines_callback)
#-----
update_plot = CustomJS(args=dict(
spectra=cds_spectra,
model=cds_model,
targetinfo=cds_targetinfo,
target_info_div=target_info_div,
ifiberslider=ifiberslider,
smootherslider=smootherslider,
zslider=zslider,
dzslider=dzslider,
lines_button_group=lines_button_group,
fig=fig,
),
code="""
var ifiber = ifiberslider.value
var nsmooth = smootherslider.value
target_info_div.text = targetinfo.data['target_info'][ifiber]
if(targetinfo.data['z'] != undefined) {
var z = targetinfo.data['z'][ifiber]
var z1 = Math.floor(z*100) / 100
zslider.value = z1
dzslider.value = (z - z1)
}
function get_y_minmax(pmin, pmax, data) {
// copy before sorting to not impact original, and filter out NaN
var dx = data.slice().filter(Boolean)
dx.sort()
var imin = Math.floor(pmin * dx.length)
var imax = Math.floor(pmax * dx.length)
return [dx[imin], dx[imax]]
}
// Smoothing kernel
var kernel = [];
for(var i=-2*nsmooth; i<=2*nsmooth; i++) {
kernel.push(Math.exp(-(i**2)/(2*nsmooth)))
}
var kernel_offset = Math.floor(kernel.length/2)
// Smooth plot and recalculate ymin/ymax
// TODO: add smoother function to reduce duplicated code
var ymin = 0.0
var ymax = 0.0
for (var i=0; i<spectra.length; i++) {
var data = spectra[i].data
var plotflux = data['plotflux']
var origflux = data['origflux'+ifiber]
for (var j=0; j<plotflux.length; j++) {
if(nsmooth == 0) {
plotflux[j] = origflux[j]
} else {
plotflux[j] = 0.0
var weight = 0.0
// TODO: speed could be improved by moving `if` out of loop
for (var k=0; k<kernel.length; k++) {
var m = j+k-kernel_offset
if((m >= 0) && (m < plotflux.length)) {
var fx = origflux[m]
if(fx == fx) {
plotflux[j] = plotflux[j] + fx * kernel[k]
weight += kernel[k]
}
}
}
plotflux[j] = plotflux[j] / weight
}
}
spectra[i].change.emit()
tmp = get_y_minmax(0.01, 0.99, plotflux)
ymin = Math.min(ymin, tmp[0])
ymax = Math.max(ymax, tmp[1])
}
// update model
if(model) {
var plotflux = model.data['plotflux']
var origflux = model.data['origflux'+ifiber]
for (var j=0; j<plotflux.length; j++) {
if(nsmooth == 0) {
plotflux[j] = origflux[j]
} else {
plotflux[j] = 0.0
var weight = 0.0
// TODO: speed could be improved by moving `if` out of loop
for (var k=0; k<kernel.length; k++) {
var m = j+k-kernel_offset
if((m >= 0) && (m < plotflux.length)) {
var fx = origflux[m]
if(fx == fx) {
plotflux[j] = plotflux[j] + fx * kernel[k]
weight += kernel[k]
}
}
}
plotflux[j] = plotflux[j] / weight
}
}
model.change.emit()
}
// update y_range
if(ymin<0) {
fig.y_range.start = ymin * 1.4
} else {
fig.y_range.start = ymin * 0.6
}
fig.y_range.end = ymax * 1.4
""")
smootherslider.js_on_change('value', update_plot)
ifiberslider.js_on_change('value', update_plot)
#-----
#- Add navigation buttons
navigation_button_width = 30
prev_button = Button(label="<", width=navigation_button_width)
next_button = Button(label=">", width=navigation_button_width)
prev_callback = CustomJS(args=dict(ifiberslider=ifiberslider),
code="""
if(ifiberslider.value>0) {
ifiberslider.value--
}
""")
next_callback = CustomJS(args=dict(ifiberslider=ifiberslider, nspec=nspec),
code="""
if(ifiberslider.value<nspec+1) {
ifiberslider.value++
}
""")
prev_button.js_on_event('button_click', prev_callback)
next_button.js_on_event('button_click', next_callback)
#-----
slider_width = plot_width - 2 * navigation_button_width
navigator = bk.Row(
widgetbox(prev_button, width=navigation_button_width),
widgetbox(next_button, width=navigation_button_width + 20),
widgetbox(ifiberslider, width=slider_width - 20))
bk.show(
bk.Column(
bk.Row(fig, zoomfig),
widgetbox(target_info_div, width=plot_width),
navigator,
widgetbox(smootherslider, width=plot_width // 2),
bk.Row(
widgetbox(waveframe_buttons, width=120),
widgetbox(zslider, width=plot_width // 2 - 60),
widgetbox(dzslider, width=plot_width // 2 - 60),
),
widgetbox(lines_button_group),
))
