def show(obj):
"""
Displays HoloViews objects in and outside the notebook
Parameters
----------
obj : HoloViews object
HoloViews object to export
"""
if not isinstance(obj, _hv.Dimensioned):
raise ValueError('%s type object not recognized and cannot be shown.' %
type(obj).__name__)
if obj.traverse(lambda x: x, [_hv.HoloMap]):
renderer.app(obj, show=True, new_window=True)
else:
_show(renderer.get_plot(obj).state)
def show(obj, filename=None):
"""
Displays HoloViews objects in and outside the notebook
Parameters
----------
obj : HoloViews object
HoloViews object to export
"""
if not isinstance(obj, _hv.core.Dimensioned):
raise ValueError('%s type object not recognized and cannot be shown.' %
type(obj).__name__)
if obj.traverse(lambda x: x, [_hv.HoloMap]):
renderer.app(obj, show=True, new_window=True)
else:
from bokeh.io import output_file
output_file(filename or 'default.html')
_show(renderer.get_plot(obj).state)
def visualize(k_mers,
target_freqs,
optimized_freqs,
original_freqs=None,
title="Freqgen Optimization Results",
plot_height=400,
plot_width=1200,
show=True,
filepath="freqgen.html",
codons=False):
'''Creates a visualization of the results of a Freqgen optimization.
Note:
Currently, this function does not support the visualization of codon
optimization *and* *k*-mer optimization simultaneously.
Args:
k_mers (list): A list of the *k*-mers to use as the labels for the *x*-axis.
target_freqs (list): A list of the target frequencies in the same order as the `k_mers` argument.
optimized_freqs (list): A list of the resultant frequencies in the same order as the `k_mers` argument.
original_freqs (list, optional): A list of the original frequencies in the same order as the `k_mers` argument.
title (str, optional): A title to use for the graph. Defaults to "Freqgen Optimization Results".
plot_height (int, optional): The height for the graph. Defaults to 400.
plot_width (int, optional): The width for the graph. Defaults to 1200.
show (bool, optional): Whether to show the plot or simply return it. Defaults to True.
filepath (str, optional): The output filepath. Defaults to "freqgen.html".
codons (bool, optional): Whether codons are included in the input vectors. If they are, the *x*-axis legend will updated accordingly.
Note:
Codons must be denoted with a ``*`` in the ``k_mers`` argument. For example, the codon GAG should be passed as ``GAG*``
Returns:
bokeh.plotting.figure.Figure: A Bokeh figure containing the bar graph.
'''
# validate that all the codons that should be there are there
if codons and len([k_mer for k_mer in k_mers if k_mer.endswith("*")]) != 64:
raise ValueError("You appear to be passing an incomplete list of codons.")
codons_only = False
if all([k_mer.endswith("*") for k_mer in k_mers]) and codons:
k_mers = [k_mer[:-1] for k_mer in k_mers]
codons_only = True
output_file(filepath)
categories = ['Original', 'Target', 'Optimized']
data = {'k_mers': k_mers,
'Target': target_freqs,
'Optimized': optimized_freqs}
# adjust spacing depending on if there's three bars or two
if not isinstance(original_freqs, type(None)):
offset = 0.25
data["Original"] = original_freqs
else:
offset = 0.15
# identify the greatest y value for setting bounds
y_max = max((max(target_freqs), max(optimized_freqs)))
if not isinstance(original_freqs, type(None)):
y_max = max((max(original_freqs), y_max))
source = ColumnDataSource(data=data)
p = figure(x_range=k_mers,
plot_height=plot_height,
plot_width=plot_width,
title=title,
y_range=(0, 1.2 * y_max))
if not isinstance(original_freqs, type(None)):
p.vbar(x=dodge('k_mers', -0.25, range=p.x_range), top='Original', width=0.2, source=source,
color=Set2_3[0], legend=value("Original"))
p.vbar(x=dodge('k_mers', 0.0 if not isinstance(original_freqs, type(None)) else -offset, range=p.x_range), top='Target', width=0.2, source=source,
color=Set2_3[1], legend=value("Target"))
p.vbar(x=dodge('k_mers', offset, range=p.x_range), top='Optimized', width=0.2, source=source,
color=Set2_3[2], legend=value("Optimized"))
p.x_range.range_padding = 0.05
p.xgrid.grid_line_color = None
p.legend.location = "top_right"
p.legend.orientation = "horizontal"
p.legend.click_policy = "hide"
# decide the x-axis label
if codons_only:
p.xaxis.axis_label = "codon"
elif codons:
p.xaxis.axis_label = "k-mer (* denotes codon)"
else:
p.xaxis.axis_label = 'k-mer'
if len(k_mers) >= 32:
p.xaxis.major_label_orientation = math.pi / 2
p.yaxis.axis_label = 'frequency'
if show:
_show(p)
else:
save(p, filename=filepath)
return p