def interactive_logistic_regression(X,
y,
target_names=None,
feature_names=None,
stacked: bool = False):
from panel import widgets
import panel as pn
X_train, X_test, y_train, y_test = train_test_split(X,
y,
stratify=y,
random_state=42)
embedding = umap.UMAP(n_components=2, random_state=160290).fit_transform(
np.concatenate([X_train, X_test]))
def interactive_model(C, penalty, fit_intercept, intercept_scaling,
l1_ratio, class_weight):
model = LogisticRegression(
C=C,
penalty=penalty,
solver="saga",
fit_intercept=fit_intercept,
intercept_scaling=intercept_scaling,
l1_ratio=l1_ratio,
class_weight=class_weight,
random_state=42,
).fit(X, y)
return plot_model_evaluation(
model,
X_train,
y_train,
X_test,
y_test,
target_names=target_names,
feature_names=feature_names,
stacked=stacked,
embedding=embedding,
)
c_slider = widgets.LiteralInput(value=1, name="C")
penalty_tog = widgets.RadioButtonGroup(
name="penalty", options=["none", "l1", "l2", "elasticnet"])
fit_intercept = widgets.Toggle(name="fit_intercept")
intercept_scaling = widgets.LiteralInput(value=1, name="intercept_scaling")
l1_ratio = widgets.FloatSlider(end=1.0,
start=0.0,
value=0.5,
name="l1_ratio")
class_weight = widgets.LiteralInput(value=None, name="class_weight")
return pn.interact(
interactive_model,
C=c_slider,
penalty=penalty_tog,
fit_intercept=fit_intercept,
intercept_scaling=intercept_scaling,
l1_ratio=l1_ratio,
class_weight=class_weight,
)
numvals_weight=numvals_weight)
return heatmap_plus_series(seriated, resample=resample)
# In[6]:
from functools import partial
import hvplot.pandas
import param
import panel as pn
from panel.interact import interact, interactive, fixed, interact_manual
from panel import widgets
shift = widgets.FloatSlider(start=0.,
end=5,
step=0.1,
value=0.1,
name="Shift weight")
nums = widgets.FloatSlider(start=0.,
end=5,
step=0.1,
value=0.3,
name="Values weight")
resample = widgets.LiteralInput(value=None, name="Resample")
resample = widgets.Select(options={"Day": "D", "Week": "W", "Month": "M"})
columns = widgets.MultiSelect(options=df.columns.values.tolist(),
value=df.columns.values.tolist(),
name="Series")
columns.height = 300
columns.width = 200
def baseline(self):
self.peak_currents = np.zeros(len(self.dfs))
#eak_left = -0.34
#eak_right = -0.28
#eft_limit = 30
steppp = self.dfs[0]["Potential"][0] - self.dfs[0]["Potential"][1]
first_point = self.dfs[0]["Potential"].iloc[0]
last_point = self.dfs[0]["Potential"].iloc[-1]
peak_left_slider = pnw.FloatSlider(name='Peak Left',
value=-0.35,
start=last_point,
end=first_point,
step=0.01)
peak_right_slider = pnw.FloatSlider(name='Peak Right',
value=-0.25,
start=last_point,
end=first_point,
step=0.01)
limit_left_slider = pnw.IntSlider(name='Limit Left',
value=10,
start=0,
end=len(self.dfs[0]["Potential"]) -
int(0.1 / steppp))
limit_right_slider = pnw.IntSlider(name='Limit Right',
value=10,
start=0,
end=len(self.dfs[0]["Potential"]) -
int(0.1 / steppp))
time_step_slider = pnw.IntSlider(name='Time Step',
value=0,
start=0,
end=len(self.dfs) - 1)
@pn.depends(time_step_slider, peak_left_slider, peak_right_slider,
limit_left_slider, limit_right_slider)
def max_current(time_stamp=time_step_slider.param.value,
a=peak_left_slider,
b=peak_right_slider,
c=limit_left_slider,
d=limit_right_slider):
return pn.pane.Markdown(
"peak current [A]: " +
str("{:.3e}".format(self.peak_currents[0])))
def update_sliders(time_stamp):
peak_left_slider.start = float(
decimal.Decimal(limit_left_slider.value * steppp +
self.dfs[time_stamp]["Potential"].iloc[-1] +
steppp).quantize(decimal.Decimal('.01'),
rounding=decimal.ROUND_UP))
#print(limit_left_slider.value*steppp+dfs[time_stamp]["Potential"].iloc[-1])
#print(float(decimal.Decimal(limit_left_slider.value*steppp+dfs[time_stamp]["Potential"].iloc[-1]+steppp).quantize(decimal.Decimal('.01'), rounding=decimal.ROUND_DOWN)))
#print(dfs[time_stamp]["Potential"].iloc[-(limit_left_slider.value+1)])
peak_left_slider.end = peak_right_slider.value
if (peak_left_slider.value > peak_left_slider.end):
peak_left_slider.value = peak_left_slider.end
if (peak_left_slider.value < peak_left_slider.start):
peak_left_slider.value = peak_left_slider.start
peak_right_slider.end = round(
+self.dfs[time_stamp]["Potential"].iloc[0] -
limit_right_slider.value * steppp, 2)
if (peak_right_slider.value > peak_right_slider.end):
peak_right_slider.value = peak_right_slider.end
if (peak_right_slider.value < peak_right_slider.start):
peak_right_slider.value = peak_right_slider.start
max_current.value = self.peak_currents[time_stamp]
def interact_frame(time_stamp=0,
peak_left=peak_left_slider.value,
peak_right=peak_right_slider.value,
left_limit=limit_left_slider.value,
right_limit=limit_right_slider.value):
peak_removed = [None] * len(self.dfs)
removed = [None] * len(self.dfs)
fit = [None] * len(self.dfs)
baseline = [None] * len(self.dfs)
for i, meas in enumerate(self.dfs):
peak_removed[i] = self.dfs[i].loc[((self.dfs[i].Potential <= peak_left)) | (self.dfs[i].Potential >= peak_right ),\
['Potential', 'Diff']]
removed[i] = pd.concat([
self.dfs[i].iloc[0:right_limit],
self.dfs[i].iloc[-left_limit:]
]) #['Potential', 'Diff'])
baseline[i] = pd.concat([
peak_removed[i].iloc[right_limit:-left_limit],
peak_removed[i].iloc[right_limit:-left_limit]
])
fit[i] = np.polynomial.polynomial.polyfit(
peak_removed[i]['Potential'][right_limit:-left_limit],
peak_removed[i]['Diff'][right_limit:-left_limit], 1)
for j in self.dfs[i].index:
self.dfs[i].at[j,
'Fit'] = np.polynomial.polynomial.polyval(
self.dfs[i].loc[j]['Potential'], fit[i])
if (self.dfs[i].at[j, 'Potential'] > peak_left) and (
self.dfs[i].at[j, 'Potential'] < peak_right):
self.dfs[i].at[
j, 'Peak'] = abs(self.dfs[i].loc[j]['Diff'] -
self.dfs[i].loc[j]['Fit'])
self.peak_currents[i] = self.dfs[i]['Peak'].max()
plot_title = 'Time' + str(self.time_stamps[time_stamp])
measurement_list = [
hv.Points(data=self.dfs[time_stamp],
kdims=[('Potential', 'Potential [V]'),
('Diff', 'Current [A]')],
vdims=[])
]
fit_list = [
hv.Points(data=self.dfs[time_stamp],
kdims=[('Potential', 'Potential [V]'),
('Fit', 'Current [A]')],
vdims=[])
]
fit_list2 = [
hv.Points(data=peak_removed[time_stamp],
kdims=[('Potential', 'Potential [V]'),
('Diff', 'Current [A]')],
vdims=[]).opts(color="r")
]
fit_list3 = [
hv.Points(data=removed[time_stamp],
kdims=[('Potential', 'Potential [V]'),
('Diff', 'Current [A]')],
vdims=[]).opts(color="y")
]
fit_list4 = [
hv.Points(data=baseline[time_stamp],
kdims=[('Potential', 'Potential [V]'),
('Diff', 'Current [A]')],
vdims=[]).opts(color="purple")
]
overlay = hv.Overlay(measurement_list + fit_list + fit_list2 +
fit_list3 + fit_list4)
overlay = overlay.redim.label(x='Potential [V]', y='Current [A]')
update_sliders(time_stamp)
return overlay
reactive_baseline = pn.bind(interact_frame, time_step_slider,
peak_left_slider, peak_right_slider,
limit_left_slider, limit_right_slider)
widgets = pn.Column("<br>\n## Baseline set:", peak_left_slider,
peak_right_slider, limit_left_slider,
limit_right_slider, max_current)
occupancy = pn.Row(reactive_baseline, widgets)
time_column = pn.Column("<br>\n## Time stamp:", time_step_slider)
pn_overlay = pn.Column(time_column, occupancy)
interact_frame()
return pn_overlay
def _update_widgets_panel(self):
self._default_component[self.component_type] = self.component
component = None
controls = None
if self.component is pn.pane.HoloViews:
component = pn.pane.HoloViews(_create_hvplot())
if self.component is pn.pane.ECharts:
# Issue https://github.com/holoviz/panel/issues/1817
component = pn.pane.ECharts(_create_echarts_plot(),
min_height=400,
min_width=200,
sizing_mode="stretch_both")
if self.component is pnw.Ace:
py_code = inspect.getsource(_create_hvplot)
component = pnw.Ace(
value=py_code,
sizing_mode="stretch_width",
language="python",
height=400,
theme=self._ace_theme,
)
elif self.component is pnw.AutocompleteInput:
component = pnw.AutocompleteInput(
name="Autocomplete Input",
options=["Biology", "Chemistry", "Physics"],
placeholder="Write something here",
)
elif self.component is pnw.Button:
component = pnw.Button(name="Click me", button_type="primary")
elif self.component is pnw.CheckBoxGroup:
component = pnw.CheckBoxGroup(
name="Checkbox Group",
value=["Apple", "Pear"],
options=["Apple", "Banana", "Pear", "Strawberry"],
inline=True,
)
elif self.component is pnw.CheckButtonGroup:
component = pnw.CheckButtonGroup(
name="Check Button Group",
value=["Apple", "Pear"],
options=["Apple", "Banana", "Pear", "Strawberry"],
button_type="success",
)
elif self.component is pnw.Checkbox:
component = pnw.Checkbox(name="Checkbox")
elif self.component is pnw.ColorPicker:
component = pnw.ColorPicker(name="Color Picker", value="#DF3874")
elif self.component is pnw.CrossSelector:
component = pnw.CrossSelector(
name="Fruits",
value=["Apple", "Pear"],
options=["Apple", "Banana", "Pear", "Strawberry"],
height=300,
)
elif self.component is pnw.DataFrame:
component = self.component(name="Hello")
component.value = get_dataframe()
component.formatters = get_default_formatters(component.value)
controls = pn.Spacer()
elif self.component is pnw.DatePicker:
component = pnw.DatePicker(name="Date Picker")
# Issue: https://github.com/holoviz/panel/issues/1810
# component.start = date(2020, 1, 20)
# component.end = date(2020, 2, 20)
# component.value = date(2020, 2, 18)
elif self.component is pnw.DateRangeSlider:
component = self.component(name="Hello")
component.start = date(2020, 1, 20)
component.end = date(2020, 2, 20)
component.value = (date(2020, 2, 18), date(2020, 2, 20))
elif self.component is pnw.DateSlider:
component = self.component(name="Hello")
component.start = date(2020, 1, 20)
component.end = date(2020, 2, 20)
component.value = date(2020, 2, 18)
elif self.component is pnw.DatetimeInput:
component = self.component(name="Hello")
component.value = datetime(2020, 2, 18, 1, 2, 3)
elif self.component is pnw.DatetimeRangeInput:
component = self.component(
name="Hello",
start=datetime(2020, 1, 20),
end=datetime(2020, 2, 20),
value=(datetime(2020, 2, 18), datetime(2020, 2, 20)),
)
elif self.component is pnw.DiscretePlayer:
component = pnw.DiscretePlayer(
name="Discrete Player",
options=[2, 4, 8, 16, 32, 64, 128],
value=32,
loop_policy="loop",
)
elif self.component is pnw.DiscreteSlider:
component = pnw.DiscreteSlider(name="Discrete Slider",
options=[2, 4, 8, 16, 32, 64, 128],
value=32)
elif self.component is pnw.FileDownload:
component = pnw.FileDownload(file="README.md",
filename="README.md")
elif self.component is pnw.FileInput:
component = pnw.FileInput(accept=".csv,.json")
elif self.component is pnw.FileSelector:
component = pnw.FileSelector(name="Hello", max_height=400)
elif self.component is pnw.FloatInput:
component = pnw.FloatInput(name="FloatInput",
value=5.0,
step=1e-1,
start=0,
end=1000)
elif self.component is pnw.FloatSlider:
component = pnw.FloatSlider(name="Float Slider",
start=0,
end=3.141,
step=0.01,
value=1.57)
elif self.component is pnw.IntInput:
component = pnw.IntInput(name="IntInput",
value=5,
step=2,
start=0,
end=1000)
elif self.component is pnw.IntRangeSlider:
component = pnw.IntRangeSlider(name="Integer Range Slider",
start=0,
end=100,
value=(8, 40),
step=2)
elif self.component is pnw.IntSlider:
component = pnw.IntSlider(name="Integer Slider",
start=0,
end=20,
step=2,
value=4)
elif self.component is pnw.LiteralInput:
component = pnw.LiteralInput(name="Literal Input (dict)",
value={"key": [1, 2, 3]},
type=dict)
elif self.component is pnw.MenuButton:
menu_items = [
("Option A", "a"),
("Option B", "b"),
("Option C", "c"),
None,
("Help", "help"),
]
component = pnw.MenuButton(name="Dropdown",
items=menu_items,
button_type="primary")
elif self.component is pnw.MultiChoice:
component = pnw.MultiChoice(
name="MultiSelect",
value=["Apple", "Pear"],
options=["Apple", "Banana", "Pear", "Strawberry"],
)
elif self.component is pnw.MultiSelect:
component = pnw.MultiSelect(
name="MultiSelect",
value=["Apple", "Pear"],
options=["Apple", "Banana", "Pear", "Strawberry"],
size=8,
)
elif self.component is pnw.PasswordInput:
component = pnw.PasswordInput(name="Password Input",
placeholder="Enter a string here...")
elif self.component is pnw.Player:
component = pnw.Player(name="Player",
start=0,
end=100,
value=32,
loop_policy="loop")
elif self.component is pnw.Progress:
component = pnw.Progress(name="Progress", value=20, width=200)
elif self.component is pnw.RadioBoxGroup:
component = pnw.RadioBoxGroup(
name="RadioBoxGroup",
options=["Biology", "Chemistry", "Physics"],
inline=True)
elif self.component is pnw.RadioButtonGroup:
component = pnw.RadioButtonGroup(
name="Radio Button Group",
options=["Biology", "Chemistry", "Physics"],
button_type="success",
)
elif self.component is pnw.RangeSlider:
component = pnw.RangeSlider(
name="Range Slider",
start=0,
end=math.pi,
value=(math.pi / 4.0, math.pi / 2.0),
step=0.01,
)
elif self.component is pnw.Select:
component = pnw.Select(name="Select",
options=["Biology", "Chemistry", "Physics"])
elif self.component is pnw.StaticText:
component = pnw.StaticText(name="Static Text", value="A string")
elif self.component is pnw.TextAreaInput:
component = pnw.input.TextAreaInput(
name="Text Area Input", placeholder="Enter a string here...")
elif self.component is pnw.TextInput:
component = pnw.TextInput(name="Text Input",
placeholder="Enter a string here...")
elif self.component == pnw.Toggle:
component = pnw.Toggle(name="Toggle", button_type="success")
elif self.component == pnw.VideoStream:
component = pnw.VideoStream(name="Video Stream",
sizing_mode="stretch_width",
height=300)
if not component:
component = self.component(name="Hello")
if not controls:
controls = component.controls()
controls.margin = 0
self._component_panel[:] = [
pn.pane.Markdown("## " + component.__class__.name + " " +
self.component_type),
component,
pn.layout.Divider(),
pn.pane.Markdown("## Parameters"),
controls,
]
def predictions_dashboard(path):
"""Dashboard for viewing results from epitopepredict runs."""
#folder_input = pn.widgets.TextInput(name='path', value='../zaire_test', width=400,width_policy='fit')
#reload_btn = pn.widgets.Button(name='reload',width=100,button_type='primary')
names = web.get_file_lists(path)
if names is None:
return
preds = web.get_predictors(path, name=names[0])
print(preds)
seqname = pnw.Select(name='name', value=names[0], options=names)
cutoff_slider = pnw.FloatSlider(name='cutoff',
value=.95,
start=.75,
end=.99,
step=0.01)
cutoff_method = pnw.Select(name='cutoff method',
value='default',
options=['default', 'rank'])
n_select = pnw.FloatSlider(name='n', value=1, start=1, end=8, step=1)
plot_select = pnw.Select(name='plot view',
value='tracks',
options=['tracks', 'sequence'])
table_select = pnw.Select(name='table view',
value='promiscuous',
options=['promiscuous', 'binders'])
colorseq_box = pnw.Checkbox(name='color sequences', value=False)
header = pn.pane.Markdown('__total sequences: %s__' % len(names),
css_classes=['main'])
tables = pn.Tabs(width=900)
plot = pn.pane.Bokeh(width=800)
debug = pn.pane.Markdown('test',
style={
'font-size': '10pt',
'background-color': 'yellow'
})
summary_plot = pn.pane.Bokeh()
summary_table_tabs = pn.Tabs()
recalc_button = pnw.Button(name='recalculate', width=200)
def update_banner():
"""Update the banner"""
fullpath = os.path.abspath(path)
banner = pn.Row(
pn.pane.Markdown(
'<h4>epitopepredict: %s</h4> [help](%s) version %s' %
(fullpath, helppage, __version__),
css_classes=['divheader'],
sizing_mode='stretch_width'))
return banner
def update_header(target, event):
names = web.get_file_lists(event.new)
target.object = "_total sequences: %s_" % str(len(names))
return
def callback_getpath(event):
path = os.path.getcwd()
folder.value = path
def update_plot(preds, name, cutoff, n, kind):
"""Plot data view"""
if kind == 'tracks':
p = plotting.bokeh_plot_tracks(preds,
name=name,
cutoff=cutoff,
n=n,
width=1000,
title=name)
plot.object = p
elif kind == 'sequence':
p = plotting.bokeh_plot_sequence(preds,
name=name,
cutoff=cutoff,
n=n,
width=1000,
title=name,
color_sequence=colorseq_box.value)
plot.object = p
return p
def update_tables(preds, name, n):
"""Tabular views of results"""
P = preds[0]
view = table_select.value
tables.clear()
for P in preds:
if view == 'promiscuous':
df = P.promiscuous_binders(n=n, name=name)
else:
df = P.get_binders(name=name)
res = df.to_html(classes="tinytable sortable")
div = '<div class="scrollingArea">%s</div>' % res
tables.append((P.name, div))
#tables.append((P.name,pn.pane.HTML('<p>hddsadsadsasda</p>',width=700)))
return
def update(event):
"""Update all elements"""
name = seqname.value
n = n_select.value
cutoff = cutoff_slider.value
kind = plot_select.value
debug.object = name
preds = web.get_predictors(path, name=name)
update_plot(preds, name=name, cutoff=cutoff, n=n, kind=kind)
update_tables(preds, name, n)
return
def update_summary(path):
"""Summary info for folder"""
data = web.get_summary_tables(path)
df = pd.concat(data, sort=True).reset_index()
#plot = plotting.bokeh_summary_plot(df)
#summary_plot.object = plot
summary_table_tabs.clear()
a = web.aggregate_summary(data)
div = web.get_scrollable_table(a)
summary_table_tabs.append(('all', div))
names = list(data.keys())
for n in names:
df = data[n]
res = df.to_html(classes="tinytable sortable")
div = '<div class="scrollingArea">%s</div>' % res
summary_table_tabs.append((n, div))
return
@pn.depends(seqname.param.value, n_select.param.value)
def download_link(name, n):
if preds is None:
return
df = preds[0].promiscuous_binders(n=n, name=name)
df.to_csv()
return pn.Pane(HTML('<a>download</a>'), width=700)
info = pn.pane.Markdown(web.get_readme())
banner = update_banner()
update_summary(path)
#reload_btn.param.watch(load_predictors, 'clicks')
#reload_btn.param.trigger()
seqname.param.watch(update, 'value')
cutoff_slider.param.watch(update, 'value')
n_select.param.watch(update, 'value')
table_select.param.watch(update, 'value')
plot_select.param.watch(update, 'value')
seqname.param.trigger('options', 'value')
top = pn.Row(header) #,download_link)
left = pn.Column(plot, tables, margin=10, sizing_mode='stretch_width')
right = pn.Column(seqname,
cutoff_slider,
cutoff_method,
n_select,
plot_select,
table_select,
colorseq_box,
css_classes=['widget-box'],
width=200)
center = pn.Row(left, right)
#bottom = pn.Row(table)
main = pn.Column(top, center)
summarypane = pn.Column(recalc_button, (pn.Row(summary_table_tabs)))
tabs = pn.Tabs(('summary', summarypane), ('sequence', main),
('about', info))
#tabs.append()
app = pn.Column(banner, tabs, sizing_mode='stretch_width')
return app