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), ))