def plot_calibrate_time(self, *args, **kwargs):
"""Experimental viewer for time calibration in a jupyter notebook.
Args:
accepts the same arguments as `SpatialEncoder.calibrate_time` function
"""
scan_pos_fs, edge_pos_pix, fit_coeff = self.calibrate_time(
*args, **kwargs)
source_results = ColumnDataSource(
data=dict(x=scan_pos_fs, y=edge_pos_pix))
source_fit = ColumnDataSource(data=dict(
x=[scan_pos_fs[0], scan_pos_fs[-1]],
y=np.polyval(fit_coeff, [scan_pos_fs[0], scan_pos_fs[-1]]),
))
p_time = figure(
height=400,
width=800,
title='Time calibration',
x_axis_label='Stage position, fs',
y_axis_label='Edge position, pix',
)
p_time.scatter('x', 'y', source=source_results)
p_time.line('x', 'y', line_color='red', source=source_fit)
layout = gridplot([p_time], ncols=1, toolbar_options=dict(logo=None))
handle = show(layout, notebook_handle=True)
# Slider
def slider_callback(change):
left = change['new'][0]
right = change['new'][1]
fit_coeff = np.polyfit(scan_pos_fs[left:right + 1],
edge_pos_pix[left:right + 1], 1)
self.pix_per_fs = fit_coeff[0]
source_fit.data.update(
x=[scan_pos_fs[left], scan_pos_fs[right]],
y=np.polyval(fit_coeff,
[scan_pos_fs[left], scan_pos_fs[right]]),
)
push_notebook(handle=handle)
slider = IntRangeSlider(
min=0,
max=len(scan_pos_fs) - 1,
value=[0, len(scan_pos_fs) - 1],
step=1,
description="Fit range",
continuous_update=False,
layout=Layout(width='800px'),
)
slider.observe(slider_callback, names='value')
return slider
def _init_gui(self):
close = Button(description=' Close', icon='trash', layout=_wlo)
def _close(b):
self.close()
close.on_click(_close)
frame = IntSlider(min=self._df.frame.astype(int).min(),
max=self._df.frame.astype(int).max(),
value=-1,
description='Frame',
layout=_wlo)
cbut = Button(description=' Columns', icon='barcode')
cols = self._df.columns.tolist()
cols = SelectMultiple(options=cols, value=cols)
def _cols(c):
self.columns = c.new
self._update_output()
cols.observe(_cols, names='value')
cfol = Folder(cbut, _ListDict([('cols', cols)]))
rbut = Button(description=' Rows', icon='bars')
rows = IntRangeSlider(min=self.indexes[0],
max=self.indexes[1],
value=[0, 50])
def _rows(c):
self.indexes = c.new
print(self.indexes)
self._update_output()
rows.observe(_rows, names='value')
rfol = Folder(rbut, _ListDict([('rows', rows)]))
return _ListDict([('close', close), ('frame', frame), ('cols', cfol),
('rows', rfol)])
def show_amino_acid_on_protein(self,
assembly_name,
name,
sequence_id=0,
palette_name='Set1',
palette_size=2):
"""
Display visual controls for showing amino acid sequence on a protein of the scene
:param: assembly_name: Name of the assembly containing the protein
:param: name: Name of the protein
:param: sequence_id: ID of the protein sequence
:param: palette_name: Name of the color palette
:param: palette_size: Size of the color palette
"""
sequences = self._be.get_protein_amino_acid_sequences(
assembly_name, name)
if sequence_id >= len(sequences):
raise RuntimeError('Invalid sequence Id')
sequence_as_list = sequences[0].split(',')
value_range = [int(sequence_as_list[0]), int(sequence_as_list[1])]
irs = IntRangeSlider(value=[value_range[0], value_range[1]],
min=value_range[0],
max=value_range[1])
lbl = Label(value="AA sequence")
def update_slider(value):
self._be.set_protein_amino_acid_sequence_as_range(
assembly_name, name, value['new'])
self._be.set_protein_color_scheme(
assembly_name, name, self._be.COLOR_SCHEME_AMINO_ACID_SEQUENCE,
palette_name, palette_size)
lbl.value = sequence_as_list[2][value['new'][0] -
value_range[0]:value['new'][1] -
value_range[0]]
irs.observe(update_slider, 'value')
display(irs)
display(lbl)
def _init_gui(self):
close = Button(description=' Close', icon='trash', layout=_wlo)
def _close(b): self.close()
close.on_click(_close)
frame = IntSlider(min=self._df.frame.astype(int).min(),
max=self._df.frame.astype(int).max(),
value=-1, description='Frame', layout=_wlo)
cbut = Button(description=' Columns', icon='barcode')
cols = self._df.columns.tolist()
cols = SelectMultiple(options=cols, value=cols)
def _cols(c):
self.columns = c.new
self._update_output()
cols.observe(_cols, names='value')
cfol = Folder(cbut, _ListDict([('cols', cols)]))
rbut = Button(description=' Rows', icon='bars')
rows = IntRangeSlider(min=self.indexes[0],
max=self.indexes[1],
value=[0, 50])
def _rows(c):
self.indexes = c.new
print(self.indexes)
self._update_output()
rows.observe(_rows, names='value')
rfol = Folder(rbut, _ListDict([('rows', rows)]))
return _ListDict([('close', close),
('frame', frame),
('cols', cfol),
('rows', rfol)])
