def _repr_html_(self):
from mako.template import Template
from mako.lookup import TemplateLookup
template = Template(filename=html.SELF_TEMPLATE(__file__),
lookup=TemplateLookup(directories=['/']))
return template.render(fit=self,
roc_plot=plot_to_html_img(self.plot_ROC),
cmx_plot=plot_to_html_img(
self.plot_confusion_matrix))
def _repr_html_(self):
from mako.template import Template
path = os.path.dirname(os.path.abspath(__file__))
file = os.path.join(path, 'html',
'weighted_classification_summary.html')
template = Template(filename=file)
# TODO add min premium field -> sum all losses / nr_of_trades
return template.render(
summary=self,
gmx_plot=plot_to_html_img(self.plot_gross_confusion),
roc_plot=plot_to_html_img(self.plot_ROC),
cmx_plot=plot_to_html_img(self.plot_confusion_matrix),
samples_plot=plot_to_html_img(self.plot_samples))
def _repr_html_(self):
from mako.template import Template
path = os.path.dirname(os.path.abspath(__file__))
file = os.path.join(path, 'html',
'binary_weighted_classification_summary.html')
template = Template(filename=file)
return template.render(
summary=self,
gross_confusion=self.gross_confusion(),
roc_plot=plot_to_html_img(self.plot_ROC),
cmx_plot=plot_to_html_img(self.plot_confusion_matrix),
gross_distribution_plot=plot_to_html_img(
self.plot_gross_distribution),
)
def _repr_html_(self):
from mako.template import Template
from mako.lookup import TemplateLookup
template = Template(filename=html.SELF_TEMPLATE(__file__),
lookup=TemplateLookup(directories=['/']))
return template.render(true_pred_scatter_plot=plot_to_html_img(
self.plot_true_pred_scatter))
def _repr_html_(self):
from mako.template import Template
from mako.lookup import TemplateLookup
template = Template(filename=html.FIT_TEMPLATE,
lookup=TemplateLookup(directories=['/']))
return template.render(fit=self,
loss_plot=plot_to_html_img(
self.model.plot_loss, **self._kwargs))
def _repr_html_(self):
from mako.template import Template
from mako.lookup import TemplateLookup
template = Template(filename=html.SELF_TEMPLATE(__file__),
lookup=TemplateLookup(directories=['/']))
return template.render(fit=self,
recon_plot=plot_to_html_img(
self.reconstruction_plot))
def _repr_html_(self):
from mako.template import Template
path = os.path.dirname(os.path.abspath(__file__))
file = os.path.join(
path, 'html', 'multi_binary_weighted_classification_summary.html')
template = Template(filename=file)
return template.render(
summary=self,
gross_confusions=[
bs.gross_confusion() for bs in self.binary_summaries
],
roc_plots=[
plot_to_html_img(bs.plot_ROC) for bs in self.binary_summaries
],
cmx_plots=[
plot_to_html_img(bs.plot_confusion_matrix)
for bs in self.binary_summaries
],
# gross_loss_plot=[plot_to_html_img(bs.plot_classification) for bs in self.binary_summaries],
)
def _repr_html_(self):
from mako.template import Template
from mako.lookup import TemplateLookup
plot = "<class 'matplotlib.figure.Figure'>"
figures = [arg(self.df, model=self.model) for arg in self.args]
figures = [("img", plot_to_html_img(f)) if str(type(f)) == plot else
("html",
f._repr_html_() if hasattr(f, "_repr_html_") else str(f))
for f in figures]
template = Template(filename=html.SELF_TEMPLATE(__file__),
lookup=TemplateLookup(directories=['/']))
return template.render(summary=self,
figures=figures,
layout=self.layout,
laypout_nr_columns=self.laypout_nr_columns)