def unrestricted_input(doc):
input_box = AutocompleteInput(css_classes=["foo"],
completions=["100001", "12344556"],
restrict=False)
input_box.on_change('value', counter.increment)
plot = Plot()
doc.add_root(column(input_box, plot))
def modify_doc(doc):
source = ColumnDataSource(dict(x=[1, 2], y=[1, 1], val=["a", "b"]))
plot = Plot(
plot_height=400,
plot_width=400,
x_range=Range1d(0, 1),
y_range=Range1d(0, 1),
min_border=0,
)
plot.add_glyph(source, Circle(x="x", y="y", size=20))
plot.add_tools(
CustomAction(
callback=CustomJS(args=dict(s=source), code=RECORD("data", "s.data"))
)
)
input_box = AutocompleteInput(css_classes=["foo"])
input_box.title = "title"
input_box.value = "400"
input_box.completions = [
"100001",
"12344556",
"12344557",
"3194567289",
"209374209374",
]
def cb(attr, old, new):
source.data["val"] = [old, new]
input_box.on_change("value", cb)
doc.add_root(column(input_box, plot))
def create_document(directory, chat_titles):
(message_df, reacts, title, participants) = parse_json_messages(directory)
# -------------------------------------------------------------------------
# Plot Message Timeseries:
# -------------------------------------------------------------------------
# Create a color palette to use in plotting:
""" Might raise an error when number of people in the group chat is > 20"""
colour_palette = Category20[20][0:len(participants)]
message_panel = create_message_timeseries_panel(message_df, title, participants, colour_palette)
# --------------------------------------------------------------------------+
# Plot Reaction Panel:
# --------------------------------------------------------------------------+
reacts_panel = create_react_breakdown_panel(reacts, title, participants, colour_palette)
# --------------------------------------------------------------------------+
# Create Panel to Summarise Individual Statistics:
# --------------------------------------------------------------------------+
message_log_panel = create_message_log_panel(message_df, title, participants, colour_palette)
# --------------------------------------------------------------------------+
# Compile Bokeh Application:
# --------------------------------------------------------------------------+
tabs = Tabs(tabs=[message_panel, reacts_panel, message_log_panel])
directory_search = AutocompleteInput(completions = list(chat_titles.keys()), width = 400, height = 30, sizing_mode = "fixed", align = 'end')
directory_search.on_change("value", update_data)
search_text = Div(
text = "<i>Search Chats:</i>",
height_policy = "max",
sizing_mode = "scale_both",
align = "end",
style = {"font-family": 'Verdana', "font-size": "17px"}
)
# A title which could be included in the top left of the document
title = Div(
text = "<b>Messenger Analysis</b>",
height_policy = "max",
sizing_mode = "fixed",
align = "start",
style = {"font-family": 'Verdana', "font-size": "16px"}
)
layout = column(row(search_text,directory_search, Spacer(
width=35, height=40, sizing_mode="fixed"), align = "end"), tabs, sizing_mode = "scale_width")
return layout
def modify_doc(doc):
source = ColumnDataSource(dict(x=[1, 2], y=[1, 1], val=["a", "b"]))
plot = Plot(plot_height=400, plot_width=400, x_range=Range1d(0, 1), y_range=Range1d(0, 1), min_border=0)
plot.add_glyph(source, Circle(x='x', y='y', size=20))
plot.add_tools(CustomAction(callback=CustomJS(args=dict(s=source), code=RECORD("data", "s.data"))))
input_box = AutocompleteInput(css_classes=["foo"])
input_box.title = "title"
input_box.value = "400"
input_box.completions = ["100001", "12344556", "12344557", "3194567289", "209374209374"]
def cb(attr, old, new):
source.data['val'] = [old, new]
input_box.on_change('value', cb)
doc.add_root(column(input_box, plot))
def generateAutocompleteWidget(destination_number=1,
initial_value="",
name=None,
placeholder=None):
if name is None:
name = f'Destination {destination_number}'
if placeholder is None:
placeholder = 'Enter Location'
autocomplete = AutocompleteInput(name=name,
completions=['test'],
title=name,
min_characters=3,
value=initial_value,
placeholder=placeholder)
def autocomplete_callback(attr, old, new):
if (len(new) > 0):
pass
autocomplete.on_change('value_input', autocomplete_callback)
return autocomplete
def modify_doc(doc):
#callback function
def autocomplete_update(attrname, old, new):
stream.event(gene=new)
print(autocomplete.value)
#callback function
def dropdown_update(attrname, old, new):
streamSet.event(set=new)
stream.event(set=new)
print(dropdown.value)
#initialize dropdown to select cell type
dropdown = Select(title="Cell Set",
value="all",
options=['all', 'microglia'])
#initialize autocomplete field for querying genes
autocomplete = AutocompleteInput(
title="Type in a gene and select from the dropdown",
value="",
completions=getGenes())
#callbacks
dropdown.on_change('value', dropdown_update)
autocomplete.on_change('value', autocomplete_update)
#get graphs and store in variables
hvplot = renderer.get_plot(dmap_query, doc)
hvplot_full = renderer.get_plot(dmap_cluster, doc)
#create view for HTML
plot = gridplot([[autocomplete, dropdown],
[hvplot.state, hvplot_full.state]])
#add view to HTML doc
doc.add_root(plot)
def bkapp(doc):
# global variables
global flag_control_global
global serial_info
# local variables
flag_control_local = {"start": False}
# the period function
@gen.coroutine
def update(x, y, flag):
global flag_control_global
# source.stream(dict(x=[x], y=[y]))
if (flag_control_local["start"]):
source.data = dict(x=x, y=y)
if (flag_control_global["status"]):
button_open.disabled = True
button_close.disabled = False
else:
button_open.disabled = False
button_close.disabled = True
if (flag):
select_port.options = refresh_com()
def blocking_task():
global data
# global flag_control_global
count = 0
flag_update = False
while True:
# do some blocking computation
time.sleep(0.05)
flag_update = False
count = count + 1
if (count >= 50):
flag_update = True
count = 0
yin = data[:-1]
xin = range(len(yin))
# but update the document from callback
doc.add_next_tick_callback(
partial(update, x=xin, y=yin, flag=flag_update))
def refresh_com():
available_port = ['COM1']
com_available = myserial.SerialConnect.Get_Used_Com()
if (len(com_available) > 0):
for com in com_available:
available_port.append(com["device"])
return available_port
# callback event of the button_open
def callback_button_open():
serial_info["portx"] = select_port.value
serial_info["bps"] = int(text_bps.value)
flag_control_global["connect"] = True
# flag_control_global["disconnect"] = False
button_open.disabled = True
button_close.disabled = False
print("button open successful")
# callback event of the button_close
def callback_button_close():
button_open.disabled = False
button_close.disabled = True
# flag_control_global["connect"] = False
flag_control_global["disconnect"] = True
print("button close successful")
# callback event of the button_start
def callback_button_start():
button_start.disabled = True
button_stop.disabled = False
flag_control_local["start"] = True
print("button start successful")
# callback event of the button_stop
def callback_button_stop():
button_start.disabled = False
button_stop.disabled = True
flag_control_local["start"] = False
print("button stop successful")
# def update_text_port(attrname, old, new):
# pass
def update_select_port(attrnaem, old, new):
pass
def update_text_bps(attrname, old, new):
pass
#------------------- data plot ---------------------------
source = ColumnDataSource(data=dict(x=[], y=[]))
plot = figure(
plot_height=300,
plot_width=1100,
title="serial data wave",
tools="crosshair,pan,reset,save,wheel_zoom",
)
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
# text_port = AutocompleteInput(title="PORT", value='COM1', completions=completions_port)
# text_port.on_change('value', update_text_port)
#------------------- port selector -----------------------
select_port = Select(title="PORT", value='COM1', options=["COM1", "COM2"])
select_port.on_change('value', update_select_port)
#------------------- bps input ---------------------------
completions_bps = ["9600", "115200", "4800"]
text_bps = AutocompleteInput(title="bps",
value='9600',
placeholder="Enter value (auto-complete) ...",
completions=completions_bps)
text_bps.on_change('value', update_text_bps)
#------------------- button on ---------------------------
button_open = Button(label='Open', button_type="success")
button_open.on_click(callback_button_open)
#------------------- button close ------------------------
button_close = Button(label='Close', button_type="success", disabled=True)
button_close.on_click(callback_button_close)
#------------------- button start ------------------------
button_start = Button(label='Start', button_type="success")
button_start.on_click(callback_button_start)
# button_start.js_on_click(CustomJS(code="alert('button: click!')"))
#------------------- button stop ------------------------
button_stop = Button(label='Stop', button_type="success", disabled=True)
button_stop.on_click(callback_button_stop)
#------------------- widgets column ---------------------
serial_control = column(select_port, text_bps, button_open, button_close,
button_start, button_stop)
#--------------------------------------------------------
#------------------- set-parm layout --------------------
#--------------------------------------------------------
text_set_param_1 = TextInput(title="进样时间(s)", value='10')
text_set_param_2 = TextInput(title="分离时间(s)", value='300')
text_set_param_3 = TextInput(title="电极电位(伏)", value='214')
text_set_param_4 = TextInput(title="采样频率(Hz)", value='20')
text_set_param_5 = RadioGroup(labels=["循环伏安扫描", "电泳实验"], active=0)
set_param = column(text_set_param_1, text_set_param_2, text_set_param_3,
text_set_param_4, text_set_param_5)
plot_slider_1 = Slider(title="基线位置", value=10, start=0, end=100, step=0.5)
plot_slider_2 = Slider(title="幅度相调", value=20, start=0, end=100, step=0.5)
plot_slider_3 = Slider(title="幅度粗调", value=60, start=0, end=100, step=0.5)
plot_slider_4 = Slider(title="时间调节", value=40, start=0, end=100, step=0.5)
plot_button_1 = Button(label="滤波", button_type="success")
plot_slider = column(plot_slider_1, plot_slider_2, plot_slider_3,
plot_slider_4, plot_button_1)
ctr_button_0 = Button(label="使用说明",
height=30,
width=100,
button_type="success")
ctr_button_1 = Button(label="保存数据",
height=30,
width=100,
button_type="success")
ctr_button_2 = Button(label="清除数据",
height=30,
width=100,
button_type="success")
ctr_button_3 = Button(label="载入数据",
height=30,
width=100,
button_type="success")
ctr_button_4 = Button(label="加载参数",
height=30,
width=100,
button_type="success")
ctr_button_5 = Button(label="保存图像",
height=30,
width=100,
button_type="success")
ctr_button_6 = Button(label="指令交互",
height=30,
width=100,
button_type="success")
ctr_button_7 = Button(label="配置仪器",
height=30,
width=100,
button_type="success")
ctr_button = column(ctr_button_1, ctr_button_2, ctr_button_3, ctr_button_4,
ctr_button_5, ctr_button_6, ctr_button_7)
#--------------------------------------------------------
#-------------------- Top layout ------------------------
#--------------------------------------------------------
layout_1 = row(plot)
layout_2 = row(ctr_button, serial_control, set_param, plot_slider)
# layout_3 = column(layout_1, layout_2)
# layout_top = row(ctr_button,layout_3)
layout_top = column(layout_1, layout_2)
doc.add_root(layout_top)
thread_update_data = Thread(target=blocking_task)
thread_update_data.start()
'x': xlist,
'y': ylist,
'colors': colors,
'labels': new_ngrams
}
main_line.visible = True
p.legend.visible = True
def clear_lines():
global new_ngrams, lookup_list, box
new_ngrams = []
main_line.visible = False
p.legend.visible = False
lookup_list = list(group.columns)
# set up autocomplete box and trigger
box = AutocompleteInput(completions=lookup_list, placeholder='Enter text')
#box = TextInput(placeholder='Enter text')
box.on_change('value', update_plot)
clear = Button(label='clear all lines')
clear.on_click(clear_lines)
# create layout
box_widget = widgetbox(box)
clear_widget = widgetbox(clear)
layout = column(p, row(box_widget, clear_widget))
curdoc().add_root(layout)
def prepare_server(doc,
input_data,
cell_stack,
cell_markers=None,
default_cell_marker=None):
@lru_cache()
def image_markers(lower=False, mapping=False):
if mapping:
return {
y: j
for j, y in sorted(
((i, x) for i, x in enumerate(
image_markers(lower=lower, mapping=False))),
key=lambda x: x[1].lower(),
)
}
if lower:
return [
x.lower() for x in image_markers(lower=False, mapping=False)
]
return (cell_markers if cell_markers is not None else
[f"Marker {i + 1}" for i in range(cell_stack.shape[1])])
# Data sources
###########################################################################
def prepare_data(input_data):
data = input_data.copy()
if "contour" in data and not all(x in data
for x in ["contour_x", "contour_y"]):
contour = parse_contour(data["contour"])
data["contour_x"] = contour[0]
data["contour_y"] = contour[1]
if "marked" not in data:
data["marked"] = np.full(data.shape[0], "")
source.data = data
source = ColumnDataSource(data={})
prepare_data(input_data)
image_source = ColumnDataSource(
data=dict(image=[], dw=[], dh=[], contour_x=[], contour_y=[]))
# Cell picture plot
###########################################################################
def add_outline():
data = source.data
if all(x in data for x in ["contour_x", "contour_y"]):
cell_outline = cell_figure.patches(
xs="contour_x",
ys="contour_y",
fill_color=None,
line_color="red",
name="cell_outline",
source=image_source,
)
cell_outline.level = "overlay"
else:
cell_outline = cell_figure.select(name="cell_outline")
for x in cell_outline:
cell_figure.renderers.remove(x)
default_cell_marker = (0 if default_cell_marker is None else image_markers(
mapping=True)[default_cell_marker])
cell_markers_select = Select(
value=str(default_cell_marker),
options=list(
(str(i), x) for x, i in image_markers(mapping=True).items()),
title="Marker cell image",
)
cell_marker_input = AutocompleteInput(
completions=list(image_markers()) + list(image_markers(lower=True)),
min_characters=1,
placeholder="Search for marker",
)
cell_slider = RangeSlider(start=0,
end=1,
value=(0, 1),
orientation="vertical",
direction="rtl")
metric_select = RadioButtonGroup(active=0, labels=CELL_IMAGE_METRICS[0])
stats = PreText(text="", width=100)
cell_mapper = bokeh.models.mappers.LinearColorMapper(viridis(20),
low=0,
high=1000,
high_color=None)
cell_color_bar = ColorBar(color_mapper=cell_mapper,
width=12,
location=(0, 0))
cell_figure = figure(
plot_width=450,
plot_height=350,
tools="pan,wheel_zoom,reset",
toolbar_location="left",
)
cell_image = cell_figure.image(
image="image",
color_mapper=cell_mapper,
x=0,
y=0,
dw="dw",
dh="dh",
source=image_source,
)
add_outline()
cell_figure.add_layout(cell_color_bar, "right")
# Edit data of selected cells
###########################################################################
marker_edit_container = column()
marker_edit_instances = []
def add_marker_edit_callback():
editor = ColumnEditor(
source,
marker_edit_container,
log_widget=edit_selecton_log,
editor_delete_callback=delete_marker_edit_callback,
external_edit_callback=edit_selection_callback,
)
marker_edit_instances.append(editor)
def delete_marker_edit_callback(editor):
idx = next(i for i, x in enumerate(marker_edit_instances)
if x is editor)
del marker_edit_instances[idx]
file_name_text = Div()
add_marker_edit_button = Button(label="+",
button_type="success",
align=("start", "end"),
width=50)
add_marker_edit_button.on_click(add_marker_edit_callback)
edit_selection_submit = Button(label="Submit change",
button_type="primary",
align=("start", "end"))
download_button = Button(label="Download edited data",
button_type="success",
align=("start", "end"))
download_button.js_on_click(
CustomJS(args=dict(source=source), code=DOWNLOAD_JS))
edit_selecton_log = TextAreaInput(value="",
disabled=True,
css_classes=["edit_log"],
cols=30,
rows=10)
upload_file_input = FileInput(accept="text/csv", align=("end", "end"))
# Cell table
###########################################################################
default_data_table_cols = [
TableColumn(field="marked", title="Seen", width=20)
]
data_table = DataTable(source=source,
columns=default_data_table_cols,
width=800)
# Callbacks for buttons and widgets
###########################################################################
def cell_slider_change(attrname, old, new):
cell_mapper.low = new[0]
cell_mapper.high = new[1]
def selection_change(attrname, old, new):
selected = source.selected.indices
data = source.data
if not selected:
return
mean_image = CELL_IMAGE_METRICS[1][metric_select.active](
cell_stack[selected,
int(cell_markers_select.value), :, :], axis=0)
image_data = {
"image": [mean_image],
"dw": [cell_stack.shape[2]],
"dh": [cell_stack.shape[3]],
}
for coord in ["contour_x", "contour_y"]:
try:
image_data[coord] = list(data[coord][selected])
except KeyError:
pass
image_source.data = image_data
image_extr = round_signif(mean_image.min()), round_signif(
mean_image.max())
cell_slider.start = image_extr[0]
cell_slider.end = image_extr[1]
cell_slider.step = round_signif((image_extr[1] - image_extr[0]) / 50)
cell_slider.value = image_extr
stats.text = "n cells: " + str(len(selected))
def autocomplete_cell_change(attrname, old, new):
try:
idx = image_markers(mapping=True)[new]
except KeyError:
try:
idx = image_markers(lower=True, mapping=True)[new]
except KeyError:
return
cell_markers_select.value = str(idx)
cell_marker_input.value = None
def data_change(attrname, old, new):
new_keys = [n for n in new.keys() if n not in set(old.keys())]
for n in new_keys:
data_table.columns.append(TableColumn(field=n, title=n))
def edit_selection_submit_click():
for x in marker_edit_instances:
x.edit_callback()
def edit_selection_callback():
idx = source.selected.indices
try:
if len(idx) == 1 and all(
source.data[x.widgets["input_col"].value][idx] != "NA"
for x in marker_edit_instances):
source.selected.indices = [idx[0] + 1]
except KeyError:
pass
def upload_file_callback(attrname, old, new):
try:
data_text = b64decode(new)
data = pd.read_csv(BytesIO(data_text))
except Exception:
file_name_text.text = f"Error loading file {upload_file_input.filename}"
return
file_name_text.text = f"Editing file {upload_file_input.filename}"
# Have to regenerate contours
try:
del data["contour_x"]
del data["contour_y"]
except KeyError:
pass
data_table.columns = default_data_table_cols
prepare_data(data)
add_outline()
source.selected.on_change("indices", selection_change)
source.on_change("data", data_change)
cell_slider.on_change("value", cell_slider_change)
metric_select.on_change("active", selection_change)
cell_markers_select.on_change("value", selection_change)
cell_marker_input.on_change("value", autocomplete_cell_change)
edit_selection_submit.on_click(edit_selection_submit_click)
upload_file_input.on_change("value", upload_file_callback)
style_div = Div(text=CUSTOM_CSS)
# set up layout
layout = column(
row(
column(data_table),
column(
cell_markers_select,
cell_marker_input,
metric_select,
row(cell_figure, cell_slider),
stats,
),
),
file_name_text,
marker_edit_container,
add_marker_edit_button,
row(edit_selection_submit, download_button, upload_file_input),
edit_selecton_log,
style_div,
)
doc.add_root(layout)
doc.title = "Cell classifier"
value='',
case_sensitive=False,
completions=autocomplete_names,
css_classes=['autocomplete'],
placeholder='Search for director, writer, actor')
def update_name(attr, old, new):
global name
if (new != old):
name = new.split(' (')[0]
update_data()
search_bar.on_change('value', update_name)
search_bar_button = Button(name='filter_name_button', label='Clear', width=80)
def clear_name():
global name
if (name != ''):
name = ''
search_bar.value = ''
update_data()
search_bar_button.on_click(clear_name)
def bkapp(doc):
# global variables
global flag_control_global
global serial_info
global Data
# local variables
flag_control_local = {
"start": False,
"exit": False,
"clear": False,
"load": False
}
filename_control = ColumnDataSource(data=dict(
save_flag=[False], save_name=["data0.csv"], load_name=["data0.csv"]))
# { "save" : False,
# "save_name" : "data.csv",
# "load_name" : "data.csv"}
# widegs toolbar
TOOLS = "hover,crosshair,pan,wheel_zoom,zoom_in,zoom_out,box_zoom,undo,redo,reset,tap,save,box_select,poly_select,lasso_select"
# the period function
@gen.coroutine
def update(flag):
global flag_control_global
if (flag_control_local["clear"]):
flag_control_local["clear"] = False
print("Clearing !!!")
source.data = dict(x=[], y=[])
if (flag_control_local["load"]):
flag_control_local["load"] = False
Data.load_data("data.csv")
y = Data.container.copy()
x = list(range(len(y)))
source.data = dict(x=x, y=y)
if (flag_control_local["start"]):
y, base_len = Data.get_buffer()
x = list(range(base_len - len(y), base_len, 1))
if (len(y) > 0):
source.stream(dict(x=x, y=y))
# source.data = dict(x=x, y=y)
if (flag_control_global["status"]):
button_open.disabled = True
button_close.disabled = False
else:
button_open.disabled = False
button_close.disabled = True
if (flag):
select_port.options = refresh_com()
def blocking_task():
count = 0
flag_update = False
while True:
time.sleep(0.05)
flag_update = False
count = count + 1
if (flag_control_local["exit"]):
print("Exiting !!!!!!!")
os._exit(0)
# if(filename_control.data['save_flag'][0]):
# filename_control.data['save_flag'][0] = False
# print("save the data!!!")
if (count >= 40):
print(filename_control.data['save_flag'][0], "\t",
filename_control.data['save_name'][0])
flag_update = True
count = 0
# if (count>=50):
# flag_update = True
# count = 0
# update the document from callback
doc.add_next_tick_callback(partial(update, flag=flag_update))
def refresh_com():
available_port = []
com_available = myserial.SerialConnect.Get_Used_Com()
if (len(com_available) > 0):
for com in com_available:
available_port.append(com["device"])
return available_port
# callback event of the button_open
def callback_button_open():
serial_info["portx"] = select_port.value
serial_info["bps"] = int(text_bps.value)
flag_control_global["connect"] = True
# flag_control_global["disconnect"] = False
button_open.disabled = True
button_close.disabled = False
print("button open")
# callback event of the button_close
def callback_button_close():
button_open.disabled = False
button_close.disabled = True
# flag_control_global["connect"] = False
flag_control_global["disconnect"] = True
print("button close")
# callback event of the button_start
def callback_button_start():
button_start.disabled = True
button_stop.disabled = False
flag_control_local["start"] = True
print("button start")
# callback event of the button_stop
def callback_button_stop():
button_start.disabled = False
button_stop.disabled = True
flag_control_local["start"] = False
print("button stop")
customjs_button_1 = CustomJS(args=dict(source=filename_control),
code="""
var file = window.prompt("Input the file name","data.csv");
var flag = [true];
var name = [file];
source.data['save_flag'] = flag;
source.data['save_name'] = name;
// source.change.emit();
window.alert("Saving !!!");
""")
def callback_ctr_button_1():
Data.save_data("data.csv")
print("save the data")
pass
def callback_ctr_button_2():
flag_control_local["clear"] = True
print("clear the data")
pass
def callback_ctr_button_3():
flag_control_local["load"] = True
print("load local data")
pass
def callback_ctr_button_5():
ctr_button_5.disabled = True
print("Exit the system")
flag_control_local["exit"] = True
def update_select_port(attrnaem, old, new):
pass
def update_text_bps(attrname, old, new):
pass
def mk_tab(type):
plot_tab = figure(
plot_height=300,
plot_width=1100,
tools=TOOLS,
toolbar_location="above") # background_fill_color="lightgrey"
# toolbar_location : "below" "above" "left" "right"
if type == "line":
plot_tab.line('x',
'y',
source=source,
line_width=2,
line_alpha=0.6)
elif type == "scatter":
plot_tab.scatter('x', 'y', source=source, fill_alpha=0.6, size=1)
return Panel(title=type, child=plot_tab)
#------------------- data plot ---------------------------
source = ColumnDataSource(data=dict(x=[], y=[]))
# plot = figure(plot_height=300, plot_width=1100,tools=TOOLS,toolbar_location="above")
# title="serial data wave",
# plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)
#------------------- Plot Tab ---------------------------
tabs = Tabs(tabs=[mk_tab("scatter"), mk_tab("line")])
#------------------- port selector -----------------------
select_port = Select(title="PORT", value='COM1', options=["COM1", "COM2"])
select_port.on_change('value', update_select_port)
#------------------- bps input ---------------------------
completions_bps = ["9600", "115200", "4800"]
text_bps = AutocompleteInput(title="bps",
value='9600',
placeholder="Enter value (auto-complete) ...",
completions=completions_bps)
text_bps.on_change('value', update_text_bps)
#------------------- button on ---------------------------
button_open = Button(label='Open', button_type="success")
button_open.on_click(callback_button_open)
#------------------- button close ------------------------
button_close = Button(label='Close', button_type="success", disabled=True)
button_close.on_click(callback_button_close)
#------------------- button start ------------------------
button_start = Button(label='Start', button_type="success")
button_start.on_click(callback_button_start)
# button_start.js_on_click(CustomJS(code="alert('button: click!')"))
#------------------- button stop ------------------------
button_stop = Button(label='Stop', button_type="success", disabled=True)
button_stop.on_click(callback_button_stop)
#------------------- widgets column ---------------------
serial_control = column(select_port, text_bps, button_open, button_close,
button_start, button_stop)
#--------------------------------------------------------
#------------------- set-parm layout --------------------
#--------------------------------------------------------
text_set_param_1 = TextInput(title="进样时间(s)", value='10')
text_set_param_2 = TextInput(title="分离时间(s)", value='300')
text_set_param_3 = TextInput(title="电极电位(伏)", value='214')
text_set_param_4 = TextInput(title="采样频率(Hz)", value='20')
text_set_param_5 = RadioGroup(labels=["循环伏安扫描", "电泳实验"], active=0)
set_param = column(text_set_param_1, text_set_param_2, text_set_param_3,
text_set_param_4, text_set_param_5)
plot_slider_1 = Slider(title="基线位置", value=10, start=0, end=100, step=0.5)
plot_slider_2 = Slider(title="幅度相调", value=20, start=0, end=100, step=0.5)
plot_slider_3 = Slider(title="幅度粗调", value=60, start=0, end=100, step=0.5)
plot_slider_4 = Slider(title="时间调节", value=40, start=0, end=100, step=0.5)
plot_button_1 = Button(label="滤波", button_type="success")
plot_slider = column(plot_slider_1, plot_slider_2, plot_slider_3,
plot_slider_4, plot_button_1)
ctr_button_0 = Button(label="使用说明",
height=30,
width=100,
button_type="success")
ctr_button_1 = Button(label="保存数据",
height=30,
width=100,
button_type="success")
ctr_button_2 = Button(label="清除数据",
height=30,
width=100,
button_type="success")
ctr_button_3 = Button(label="载入数据",
height=30,
width=100,
button_type="success")
ctr_button_4 = Button(label="加载参数",
height=30,
width=100,
button_type="success")
ctr_button_5 = Button(label="退出系统",
height=30,
width=100,
button_type="success")
ctr_button_6 = Button(label="指令交互",
height=30,
width=100,
button_type="success")
ctr_button_7 = Button(label="配置仪器",
height=30,
width=100,
button_type="success")
ctr_button_1.on_click(callback_ctr_button_1)
# ctr_button_1.js_on_click(customjs_button_1)
# ctr_button_1.js_on_event(events.ButtonClick, customjs_button_1)
ctr_button_2.on_click(callback_ctr_button_2)
ctr_button_3.on_click(callback_ctr_button_3)
ctr_button_5.on_click(callback_ctr_button_5)
ctr_button = column(ctr_button_1, ctr_button_2, ctr_button_3, ctr_button_4,
ctr_button_5, ctr_button_6, ctr_button_7)
#--------------------------------------------------------
#-------------------- Top layout ------------------------
#--------------------------------------------------------
layout_1 = column(tabs)
layout_2 = row(ctr_button, serial_control, plot_slider, set_param)
layout_top = column(layout_1, layout_2)
doc.add_root(layout_top)
thread_update_data = Thread(target=blocking_task)
thread_update_data.start()
def create_plot(doc):
"""Creat a bokeh plot."""
# create a plot and style its properties
# doc = curdoc()
doc.theme = Theme(filename=join(dirname(__file__), 'theme.yaml'))
doc.title = 'Sample bokeh plot'
sp = StockPrices()
plot_width = 600
plot_height = 600
# elements
symbol_selector = AutocompleteInput(completions=list(sp.get_symbols()),
width=150)
period_selector = RadioButtonGroup(labels=[
"Today" if datetime.today().weekday() < 5 else "Friday", "5 days",
"1 month", "6 months", "1 year", "5 years"
],
active=5,
width=400)
selected = ['GOOGL', 'AMZN']
spinner = Div(text='')
overlay = Div(text='')
layout = column(Div(text='<header><h1>Stock Closing Prices</h1></header>',
width=plot_width),
row(column(
widgetbox(Div(text='<h3>Period</h3>'),
period_selector,
width=400)),
column(
widgetbox(Div(text='<h3>Symbols</h3>'),
symbol_selector,
width=plot_width - 400)),
height=95),
plot(period_selector.active, plot_width, plot_height,
get_data(sp, selected, period_selector.active)),
spinner,
overlay,
width=plot_width + 20,
height=plot_height + 120,
sizing_mode='fixed')
# layout.css_classes = ['wrapper']
doc.add_root(layout)
# Set up callbacks
# symbol selector
def update_symbol_list(attr, old, new):
"""Update selected symobls."""
spinner.css_classes = ['loader-spinner']
overlay.css_classes = ['loader-overlay']
if symbol_selector.value is None:
return
if symbol_selector.value in selected:
selected.remove(symbol_selector.value)
else:
selected.append(symbol_selector.value)
if selected is None:
_data = None
else:
_data = get_data(sp, selected, period_selector.active)
layout.children[2] = plot(period_selector.active, plot_width,
plot_height, _data)
symbol_selector.value = None
spinner.css_classes = []
overlay.css_classes = []
symbol_selector.on_change('value', update_symbol_list)
# period selector
def update_period(attr, old, new):
"""Update selected period."""
spinner.css_classes = ['loader-spinner']
overlay.css_classes = ['loader-overlay']
_data = get_data(sp, selected, period_selector.active)
layout.children[2] = plot(period_selector.active, plot_width,
plot_height, _data)
spinner.css_classes = []
overlay.css_classes = []
period_selector.on_change('active', update_period)
def create_message_log_panel(message_df, title, participants, colour_palette):
def filter_for_user(attr, old, new):
df = deepcopy(message_df)
df = df[df['Type'] == 'Message']
if new in participants:
df = df[df['Name'] == new]
message_CDS.data = df
elif new == 'all':
message_CDS.data = df
# Old version, probably not so relevant anymore
type_counts = message_df.groupby(['Name', 'Type']).count().reset_index()
type_counts = ColumnDataSource(type_counts)
type_bar_graph = figure(x_range=[*message_df['Type'].unique()],
plot_height=350,
title="Distribution of Types",
toolbar_location=None,
tools="")
type_bar_graph.vbar(source=type_counts, x='Type', top='Message', width=0.9)
type_bar_graph.xgrid.grid_line_color = None
type_bar_graph.y_range.start = 0
# Create DataTable Widget:
columns = [
TableColumn(field="Message", title="Message"),
TableColumn(field="Name", title="Name", width=10),
TableColumn(field="Date",
title="Date",
formatter=DateFormatter(format="%d/%m/%Y"),
width=10)
]
message_CDS = ColumnDataSource(message_df[message_df['Type'] == 'Message'])
data_table = DataTable(source=message_CDS,
columns=columns,
fit_columns=True,
width=700,
height=350)
directory_search = AutocompleteInput(completions=participants,
width=400,
height=30,
sizing_mode="fixed",
align='start')
directory_search.on_change("value", filter_for_user)
filter_text = Div(text="Filter for a Particular User:"******"max",
sizing_mode="scale_both",
align="end",
style={
"font-family": 'Verdana',
"font-size": "17px"
})
filter_input = row(filter_text, directory_search)
message_log_panel = layout(
[column(filter_input, data_table, sizing_mode="scale_both")],
sizing_mode="scale_both")
message_log_panel = Panel(child=message_log_panel, title='Message Log')
return message_log_panel
def prepare_server(
doc,
input_data,
cell_stack,
cell_markers=None,
default_umap_marker=None,
default_cell_marker=None,
):
@lru_cache()
def get_data(m=None):
d = input_data
if m is not None:
m_v = d[m]
if np.issubdtype(m_v.dtype, np.number):
d["marker_val_num"] = m_v
else:
d["marker_val_cat"] = m_v
if "marker_val_num" not in d:
d["marker_val_num"] = np.arange(d.shape[0])
if "marker_val_cat" not in d:
d["marker_val_cat"] = np.full(d.shape[0], "a")
return d
@lru_cache()
def get_cat_colors(n):
return Colorblind[max(3, n)][:n]
@lru_cache()
def marker_cols(lower=False):
markers = list(sorted(input_data.columns, key=lambda x: x.lower()))
if lower:
return {x.lower(): x for x in markers}
return markers
@lru_cache()
def image_markers(lower=False, mapping=False):
if mapping:
return {
y: j
for j, y in sorted(
(
(i, x)
for i, x in enumerate(image_markers(lower=lower, mapping=False))
),
key=lambda x: x[1].lower(),
)
}
if lower:
return [x.lower() for x in image_markers(lower=False, mapping=False)]
return (
cell_markers
if cell_markers is not None
else [f"Marker {i + 1}" for i in range(cell_stack.shape[1])]
)
input_data = input_data.copy()
# Marker selection for UMAP plots
###########################################################################
if default_umap_marker is None:
default_umap_marker = marker_cols()[0]
marker_select = Select(
value=default_umap_marker, options=marker_cols(), title="Color UMAP by"
)
marker_input = AutocompleteInput(
completions=marker_cols() + list(marker_cols(lower=True).keys()),
min_characters=1,
placeholder="Search for marker",
)
marker_slider = RangeSlider(
start=0, end=1, value=(0, 1), step=0.1, orientation="vertical", direction="rtl"
)
# Data sources
###########################################################################
source = ColumnDataSource(data=get_data(None))
image_source = ColumnDataSource(data=dict(image=[], dw=[], dh=[]))
# UMAP scatter plot for numeric data
###########################################################################
umap_figure = figure(
plot_width=800,
plot_height=500,
tools="pan,wheel_zoom,lasso_select,box_select,tap,reset",
active_scroll="wheel_zoom",
active_drag="box_select",
active_tap="tap",
toolbar_location="left",
)
marker_mapper = linear_cmap(
field_name="marker_val_num",
palette=inferno(10)[:-1],
low=0,
high=500,
high_color=None,
)
umap_scatter_renderer = umap_figure.circle(
"d1",
"d2",
size=8,
source=source,
fill_alpha=0.5,
line_alpha=0.9,
fill_color=marker_mapper,
line_color=marker_mapper,
selection_fill_alpha=0.8,
selection_line_alpha=1,
selection_line_color="black",
nonselection_alpha=0.2,
hover_line_color="black",
)
umap_color_bar = ColorBar(
color_mapper=marker_mapper["transform"], width=12, location=(0, 0)
)
umap_figure.add_layout(umap_color_bar, "right")
umap_figure.add_tools(
HoverTool(tooltips=None, renderers=[umap_scatter_renderer], mode="mouse")
)
# UMAP scatter plot for categorical data
###########################################################################
umap_figure_cat = figure(
plot_width=800,
plot_height=500,
tools="pan,wheel_zoom,lasso_select,box_select,tap,reset",
active_scroll="wheel_zoom",
active_drag="box_select",
active_tap="tap",
x_range=umap_figure.x_range,
y_range=umap_figure.y_range,
toolbar_location="left",
)
marker_mapper_cat = factor_cmap(
field_name="marker_val_cat", palette=["#000000"], factors=["a"]
)
umap_figure_cat.circle(
"d1",
"d2",
size=8,
source=source,
legend_field="marker_val_cat",
alpha=0.7,
fill_color=marker_mapper_cat,
line_color=None,
selection_alpha=0.9,
selection_line_color="black",
nonselection_alpha=0.5,
)
umap_figure_cat.legend.location = "top_right"
umap_figure_cat.legend.orientation = "vertical"
# Cell picture plot
###########################################################################
default_cell_marker = (
0
if default_cell_marker is None
else image_markers(mapping=True)[default_cell_marker]
)
cell_markers_select = Select(
value=str(default_cell_marker),
options=list((str(i), x) for x, i in image_markers(mapping=True).items()),
title="Marker cell image",
)
cell_marker_input = AutocompleteInput(
completions=list(image_markers()) + list(image_markers(lower=True)),
min_characters=1,
placeholder="Search for marker",
)
cell_slider = RangeSlider(
start=0, end=1, value=(0, 1), orientation="vertical", direction="rtl"
)
metric_select = RadioButtonGroup(active=0, labels=CELL_IMAGE_METRICS[0])
stats = PreText(text="", width=100)
cell_mapper = bokeh.models.mappers.LinearColorMapper(
viridis(20), low=0, high=1000, high_color=None
)
cell_color_bar = ColorBar(color_mapper=cell_mapper, width=12, location=(0, 0))
cell_figure = figure(
plot_width=450,
plot_height=350,
tools="pan,wheel_zoom,reset",
toolbar_location="left",
)
cell_image = cell_figure.image(
image="image",
color_mapper=cell_mapper,
x=0,
y=0,
dw="dw",
dh="dh",
source=image_source,
)
cell_figure.add_layout(cell_color_bar, "right")
# Edit data of selected cells
###########################################################################
edit_selection_col = TextInput(title="Column")
edit_selection_val = TextInput(title="Value")
edit_selection_submit = Button(
label="Submit change", button_type="primary", align=("start", "end")
)
edit_selecton_log = PreText(text="")
download_button = Button(
label="Download cell data", button_type="success", align=("start", "end")
)
download_button.js_on_click(CustomJS(args=dict(source=source), code=DOWNLOAD_JS))
# Callbacks for buttons and widgets
###########################################################################
def marker_change(attrname, old, new):
update()
def cell_slider_change(attrname, old, new):
cell_mapper.low = new[0]
cell_mapper.high = new[1]
def marker_slider_change(attrname, old, new):
marker_mapper["transform"].low = new[0]
marker_mapper["transform"].high = new[1]
def update(update_range=True):
m = marker_select.value
d = get_data(m)
source.data = d
numeric_marker = np.issubdtype(d[m].dtype, np.number)
if not numeric_marker:
levels = list(sorted(set(d["marker_val_cat"])))
marker_mapper_cat["transform"].palette = get_cat_colors(len(levels))
marker_mapper_cat["transform"].factors = levels
elif update_range and numeric_marker:
marker_max = round_signif(d["marker_val_num"].max())
marker_min = round_signif(d["marker_val_num"].min())
marker_slider.start = marker_min
marker_slider.end = marker_max
marker_slider.step = round_signif((marker_max - marker_min) / 50)
marker_slider.value = tuple(
map(round_signif, np.percentile(d["marker_val_num"], [5, 95]))
)
umap_figure.visible = numeric_marker
umap_figure_cat.visible = not numeric_marker
marker_slider.visible = numeric_marker
def selection_change(attrname, old, new):
m = marker_select.value
data = get_data(m)
selected = source.selected.indices
if not selected:
return
data = data.iloc[selected, :]
mean_image = CELL_IMAGE_METRICS[1][metric_select.active](
cell_stack[selected, int(cell_markers_select.value), :, :], axis=0
)
image_source.data = {
"image": [mean_image],
"dw": [cell_stack.shape[1]],
"dh": [cell_stack.shape[2]],
}
image_extr = round_signif(mean_image.min()), round_signif(mean_image.max())
cell_slider.start = image_extr[0]
cell_slider.end = image_extr[1]
cell_slider.step = round_signif((image_extr[1] - image_extr[0]) / 50)
cell_slider.value = image_extr
stats.text = "n cells: " + str(len(selected))
def mark_selection():
get_data.cache_clear()
col = edit_selection_col.value
if col is None or col == "":
return
if col not in input_data:
input_data[col] = np.full(input_data.shape[0], "NA")
col_type = input_data[col].dtype
idx = source.selected.indices
try:
val = np.full(len(idx), edit_selection_val.value).astype(col_type)
input_data.loc[input_data.index[idx], col] = val
except Exception as e:
edit_selecton_log.text = (
f'Failed to edit cells. Exception: "{e}"\n' + edit_selecton_log.text
)
else:
edit_selecton_log.text = (
f'Edited {len(source.selected.indices)} cells. {col}="{edit_selection_val.value}"\n'
+ edit_selecton_log.text
)
update(update_range=False)
old_marker_cols = set(marker_cols())
marker_cols.cache_clear()
if old_marker_cols != set(marker_cols()):
marker_select.options = marker_cols()
marker_input.completions = marker_cols() + list(
marker_cols(lower=True).keys()
)
def autocomplete_change(attrname, old, new):
if new not in marker_cols():
try:
new = marker_cols(lower=True)[new]
except KeyError:
return
marker_select.value = new
marker_input.value = None
def autocomplete_cell_change(attrname, old, new):
try:
idx = image_markers(mapping=True)[new]
except KeyError:
try:
idx = image_markers(lower=True, mapping=True)[new]
except KeyError:
return
cell_markers_select.value = str(idx)
cell_marker_input.value = None
source.selected.on_change("indices", selection_change)
marker_select.on_change("value", marker_change)
marker_slider.on_change("value", marker_slider_change)
cell_slider.on_change("value", cell_slider_change)
metric_select.on_change("active", selection_change)
cell_markers_select.on_change("value", selection_change)
edit_selection_submit.on_click(mark_selection)
marker_input.on_change("value", autocomplete_change)
cell_marker_input.on_change("value", autocomplete_cell_change)
# set up layout
layout = column(
row(
column(
marker_select,
marker_input,
row(umap_figure, marker_slider),
umap_figure_cat,
),
column(
cell_markers_select,
cell_marker_input,
metric_select,
row(cell_figure, cell_slider),
stats,
),
),
Div(text="Change data for selected cells"),
row(
edit_selection_col,
edit_selection_val,
edit_selection_submit,
download_button,
),
edit_selecton_log,
)
# initialize
update()
doc.add_root(layout)
doc.title = "UMAP projection"
