def load_nb(cls, inline=True):
"""
Loads the bokeh notebook resources.
"""
from bokeh.io.notebook import curstate
load_notebook(hide_banner=True, resources=INLINE if inline else CDN)
curstate().output_notebook()
def load_nb(cls, inline=True):
"""
Loads the bokeh notebook resources.
"""
kwargs = {'notebook_type': 'jupyter'} if '0.12.9' >= bokeh_version > '0.12.5' else {}
load_notebook(hide_banner=True, resources=INLINE if inline else CDN, **kwargs)
if bokeh_version <= '0.12.9':
from bokeh.io import _state
_state.output_notebook()
else:
from bokeh.io.notebook import curstate
curstate().output_notebook()
def show_app(app, state, notebook_url, port=0, **kw):
"""Show Bokeh applications
:param app: A Bokeh Application to embed in PyWebIO.
:param state: ** Unused **
:param notebook_url: ** Unused **
:param port: Bokeh Server 端口
:param kw: 传给 Bokeh Server 的额外参数
"""
from bokeh.server.server import Server
from bokeh.io.notebook import _origin_url, uuid4, curstate, _server_url
from pywebio.platform.tornado import ioloop
loop = ioloop()
loop.make_current()
asyncio.set_event_loop(loop.asyncio_loop)
# loop = IOLoop.current()
info = get_info()
allow_websocket_origin = [info.server_host]
if info.origin:
allow_websocket_origin.append(_origin_url(info.origin))
server = Server({"/": app},
io_loop=loop,
port=port,
allow_websocket_origin=allow_websocket_origin,
**kw)
server_id = uuid4().hex
curstate().uuid_to_server[server_id] = server
server.start()
url = _server_url(info.server_host, server.port)
from bokeh.embed import server_document
script = server_document(url, resources=None)
script = re.sub(
r'<script(.*?)>([\s\S]*?)</script>', r"""
<script \g<1>>
requirejs(['bokeh', 'bokeh-widgets', 'bokeh-tables', 'bokeh-gl'], function(Bokeh) {
\g<2>
});
</script>
""", script)
put_html(script, sanitize=False)
def gpt_plot_gui(gpt_data_input,
primary_notebook_port=8888,
secondary_gui_port=8889):
notebook_address = f"http://localhost:{primary_notebook_port}"
gpt_data = convert_gpt_data(gpt_data_input)
screen_z_list = gpt_data.stat('mean_z', 'screen').tolist()
screen_z_str_list = [f'{z:.3f}' for z in screen_z_list]
label_width = 150
widget_width = 150
plot_area_width = 500
text_input_params = {}
def main_gui_fnc(doc):
# Make widgets
plottype_list = ['Trends', '1D Distribution', '2D Distribution']
plottype_dropdown = Select(title='Plot Type',
value=plottype_list[0],
options=plottype_list)
trend_x_list = ['z', 't']
trend_y_list = [
'Beam Size', 'Bunch Length', 'Emittance (x,y)', 'Emittance (4D)',
'Slice emit. (x,y)', 'Slice emit. (4D)', 'Charge', 'Energy',
'Trajectory'
]
trend_x_dropdown = Select(title='X axis',
options=trend_x_list,
value=trend_x_list[0])
trend_y_dropdown = Select(title='Y axis',
options=trend_y_list,
value=trend_y_list[0])
dist_list = ['t', 'x', 'y', 'px', 'py', 'pz']
trend_slice_var_dropdown = Select(title='Slice variable',
options=dist_list,
value=dist_list[0])
trend_slice_nslices_text = make_text_input(text_input_params,
'Number of slices',
min=5,
max=500,
value=50,
step=1)
screen_z_dropdown = Select(title='Screen z (m)',
options=screen_z_str_list,
value=screen_z_str_list[0])
dist_x_1d_dropdown = Select(title='X axis',
options=dist_list,
value=dist_list[0])
dist_type_1d_list = [
'Charge Density', 'Emittance X', 'Emittance Y', 'Emittance 4D',
'Sigma X', 'Sigma Y'
]
dist_type_1d_dropdown = Select(title='Y axis',
options=dist_type_1d_list,
value=dist_type_1d_list[0])
nbin_1d_text = make_text_input(text_input_params,
'Histogram bins',
min=5,
max=500,
value=50,
step=1)
screen_z_dropdown_copy = Select(title='Screen z (m)',
options=screen_z_str_list,
value=screen_z_str_list[0])
screen_z_dropdown_copy.js_link('value', screen_z_dropdown, 'value')
screen_z_dropdown.js_link('value', screen_z_dropdown_copy, 'value')
dist_x_dropdown = Select(title='X axis',
options=dist_list,
value=dist_list[1])
dist_y_dropdown = Select(title='Y axis',
options=dist_list,
value=dist_list[2])
dist_2d_type_list = ['Scatter', 'Histogram']
dist2d_type_dropdown = Select(title='Plot method',
options=dist_2d_type_list,
value=dist_2d_type_list[1])
scatter_color_list = [
'density', 't', 'x', 'y', 'r', 'px', 'py', 'pz', 'pr'
]
scatter_color_dropdown = Select(title='Scatter color variable',
options=scatter_color_list,
value=scatter_color_list[0])
axis_equal_checkbox = CheckboxGroup(labels=['Enabled'], active=[])
nbin_x_text = make_text_input(text_input_params,
'Histogram bins, X',
min=5,
max=500,
value=50,
step=1)
nbin_y_text = make_text_input(text_input_params,
'Histogram bins, Y',
min=5,
max=500,
value=50,
step=1)
cyl_copies_checkbox = CheckboxGroup(labels=['Enabled'], active=[])
cyl_copies_text = make_text_input(text_input_params,
'Number of copies',
min=5,
max=500,
value=50,
step=1)
remove_correlation_checkbox = CheckboxGroup(labels=['Enabled'],
active=[])
remove_correlation_n_text = make_text_input(text_input_params,
'Max polynomial power',
min=0,
max=10,
value=1,
step=1)
remove_correlation_var1_dropdown = Select(title='Independent var (x)',
options=dist_list,
value=dist_list[1])
remove_correlation_var2_dropdown = Select(title='Dependent var (y)',
options=dist_list,
value=dist_list[3])
take_slice_checkbox = CheckboxGroup(labels=['Enabled'], active=[])
take_slice_var_dropdown = Select(title='Slice variable',
options=dist_list,
value=dist_list[0])
take_slice_nslices_text = make_text_input(text_input_params,
'Number of slices',
min=5,
max=500,
value=50,
step=1)
take_slice_index_text = make_text_input(
text_input_params,
'Slice index',
min=0,
max=int(take_slice_nslices_text.value) - 1,
value=0,
step=1)
trends_tab = column(add_label(trend_x_dropdown, widget_width),
add_label(trend_y_dropdown, widget_width),
add_label(trend_slice_var_dropdown, widget_width),
add_label(trend_slice_nslices_text, widget_width))
dist_1d_tab = column(add_label(screen_z_dropdown, widget_width),
add_label(dist_x_1d_dropdown, widget_width),
add_label(dist_type_1d_dropdown, widget_width),
add_label(nbin_1d_text, widget_width))
dist_2d_tab = column(
add_label(screen_z_dropdown_copy, widget_width),
add_label(dist2d_type_dropdown, widget_width),
add_label(scatter_color_dropdown, widget_width),
add_label(dist_x_dropdown, widget_width),
add_label(dist_y_dropdown, widget_width),
add_label(axis_equal_checkbox,
widget_width,
label='Equal scale axes'),
add_label(nbin_x_text, widget_width),
add_label(nbin_y_text, widget_width))
postprocess_tab = column(
add_label(cyl_copies_checkbox,
widget_width,
label='Cylindrical copies'),
add_label(cyl_copies_text, widget_width),
add_label(remove_correlation_checkbox,
widget_width,
label='Remove Correlation'),
add_label(remove_correlation_n_text, widget_width),
add_label(remove_correlation_var1_dropdown, widget_width),
add_label(remove_correlation_var2_dropdown, widget_width),
add_label(take_slice_checkbox,
widget_width,
label='Take slice of data'),
add_label(take_slice_var_dropdown, widget_width),
add_label(take_slice_index_text, widget_width),
add_label(take_slice_nslices_text, widget_width))
tab1 = Panel(child=trends_tab, title='Trends')
tab2 = Panel(child=dist_1d_tab, title='1D Dist.')
tab3 = Panel(child=dist_2d_tab, title='2D Dist.')
tab4 = Panel(child=postprocess_tab, title='Postprocess')
tabs = Tabs(tabs=[tab1, tab2, tab3, tab4])
main_panel = column(row(add_label(plottype_dropdown, widget_width)),
tabs)
# Main plotting function
def create_plot():
#Get current GUI settings
plottype = plottype_dropdown.value.lower()
trend_x = 'mean_' + trend_x_dropdown.value.lower()
trend_y = get_trend_vars(trend_y_dropdown.value.lower())
trend_slice_var = trend_slice_var_dropdown.value
trend_slice_nslices = int(
trend_slice_nslices_text.value
) #constrain_text_input(trend_slice_nslices_text, text_input_params)
screen_z = float(screen_z_dropdown.value)
dist_x_1d = dist_x_1d_dropdown.value
dist_y_1d = dist_type_1d_dropdown.value.lower()
nbins_1d = int(
nbin_1d_text.value
) # constrain_text_input(nbin_1d_text, text_input_params)
dist_x = dist_x_dropdown.value
dist_y = dist_y_dropdown.value
ptype = dist2d_type_dropdown.value.lower()
scatter_color_var = scatter_color_dropdown.value.lower()
is_trend = (plottype == 'trends')
is_slice_trend = any(['slice' in yy for yy in trend_y])
is_dist1d = (plottype == '1d distribution')
is_dist2d = (plottype == '2d distribution')
nbins = [int(nbin_x_text.value), int(nbin_y_text.value)]
axis_equal = (0 in axis_equal_checkbox.active)
cyl_copies_on = (0 in cyl_copies_checkbox.active) and (plottype !=
'trends')
cyl_copies = int(cyl_copies_text.value)
remove_correlation = (0 in remove_correlation_checkbox.active
) and (plottype != 'trends')
remove_correlation_n = int(remove_correlation_n_text.value)
remove_correlation_var1 = remove_correlation_var1_dropdown.value
remove_correlation_var2 = remove_correlation_var2_dropdown.value
take_slice = (0 in take_slice_checkbox.active) and (plottype !=
'trends')
take_slice_var = take_slice_var_dropdown.value
take_slice_nslices = int(take_slice_nslices_text.value)
text_input_params[
take_slice_index_text.id]['max'] = take_slice_nslices - 1
take_slice_index = int(take_slice_index_text.value)
# Disable widgets
trend_x_dropdown.disabled = not is_trend
trend_y_dropdown.disabled = not is_trend
trend_slice_var_dropdown.disabled = not is_slice_trend
trend_slice_nslices_text.disabled = not is_slice_trend
screen_z_dropdown.disabled = not is_dist1d
dist_x_1d_dropdown.disabled = not is_dist1d
dist_type_1d_dropdown.disabled = not is_dist1d
nbin_1d_text.disabled = not is_dist1d
screen_z_dropdown_copy.disabled = not is_dist2d
dist2d_type_dropdown.disabled = not is_dist2d
scatter_color_dropdown.disabled = not (is_dist2d
and ptype == 'scatter')
dist_x_dropdown.disabled = not is_dist2d
dist_y_dropdown.disabled = not is_dist2d
axis_equal_checkbox.disabled = not is_dist2d
nbin_x_text.disabled = not is_dist2d
nbin_y_text.disabled = not is_dist2d
if (is_trend):
params = {}
if (is_slice_trend):
params['slice_key'] = trend_slice_var
params['n_slices'] = trend_slice_nslices
p = gpt_plot(gpt_data,
trend_x,
trend_y,
show_plot=False,
format_input_data=False,
**params)
if (is_dist1d):
ptype_1d = get_dist_plot_type(dist_y_1d)
params = {}
if (cyl_copies_on):
params['cylindrical_copies'] = cyl_copies
if (remove_correlation):
params['remove_correlation'] = (remove_correlation_var1,
remove_correlation_var2,
remove_correlation_n)
if (take_slice):
params['take_slice'] = (take_slice_var, take_slice_index,
take_slice_nslices)
p = gpt_plot_dist1d(gpt_data,
dist_x_1d,
screen_z=screen_z,
plot_type=ptype_1d,
nbins=nbins_1d,
show_plot=False,
format_input_data=False,
**params)
if (is_dist2d):
params = {}
params['color_var'] = scatter_color_var
if (axis_equal):
params['axis'] = 'equal'
if (cyl_copies_on):
params['cylindrical_copies'] = cyl_copies
if (remove_correlation):
params['remove_correlation'] = (remove_correlation_var1,
remove_correlation_var2,
remove_correlation_n)
if (take_slice):
params['take_slice'] = (take_slice_var, take_slice_index,
take_slice_nslices)
p = gpt_plot_dist2d(gpt_data,
dist_x,
dist_y,
screen_z=screen_z,
plot_type=ptype,
nbins=nbins,
show_plot=False,
format_input_data=False,
**params)
p.width = plot_area_width
return p
gui = row(main_panel, create_plot())
doc.add_root(gui)
#callback functions
def just_redraw(attr, old, new):
gui.children[1] = create_plot()
def change_tab(attr, old, new):
new_index = plottype_list.index(new)
if (tabs.active < 3):
tabs.active = new_index
gui.children[1] = create_plot()
# Assign callbacks
plottype_dropdown.on_change('value', change_tab)
trend_x_dropdown.on_change('value', just_redraw)
trend_y_dropdown.on_change('value', just_redraw)
trend_slice_var_dropdown.on_change('value', just_redraw)
trend_slice_nslices_text.on_change('value', just_redraw)
screen_z_dropdown.on_change('value', just_redraw)
dist_x_1d_dropdown.on_change('value', just_redraw)
dist_type_1d_dropdown.on_change('value', just_redraw)
nbin_1d_text.on_change('value', just_redraw)
dist_x_dropdown.on_change('value', just_redraw)
dist_y_dropdown.on_change('value', just_redraw)
dist2d_type_dropdown.on_change('value', just_redraw)
scatter_color_dropdown.on_change('value', just_redraw)
nbin_x_text.on_change('value', just_redraw)
nbin_y_text.on_change('value', just_redraw)
axis_equal_checkbox.on_change('active', just_redraw)
cyl_copies_checkbox.on_change('active', just_redraw)
cyl_copies_text.on_change('value', just_redraw)
remove_correlation_checkbox.on_change('active', just_redraw)
remove_correlation_n_text.on_change('value', just_redraw)
remove_correlation_var1_dropdown.on_change('value', just_redraw)
remove_correlation_var2_dropdown.on_change('value', just_redraw)
take_slice_checkbox.on_change('active', just_redraw)
take_slice_var_dropdown.on_change('value', just_redraw)
take_slice_index_text.on_change('value', just_redraw)
take_slice_nslices_text.on_change('value', just_redraw)
# Run the GUI
show_app(main_gui_fnc,
curstate(),
notebook_address,
port=secondary_gui_port)
def constrain_text_input(widget, params_list):
params = params_list[widget.id]
new = float(widget.value)
if ('min' in params):
if (new < float(params['min'])):
new = float(params['min'])
if ('max' in params):
if (new > float(params['max'])):
new = float(params['max'])
if ('step' in params and 'min' in params):
new = float(params['min']) + float(params['step']) * np.round(
(new - float(params['min'])) / float(params['step']))
if (params['step'] == 1):
new = int(new)
return new
def make_text_input(params, title, min=0, max=1000, value=10, step=1):
p = {}
p['min'] = min
p['max'] = max
p['step'] = step
widget = TextInput(value=f'{value}', title=title)
params[widget.id] = p
return widget
def add_label(w, widget_width, label=None):
label_width = 150
if (label == None):
label = w.title
w.title = ''
return row(Div(text=label, width=label_width), w)