def bokeh_heatmap(index=['Date', 'Representative']):
#return three retention matrices
percent_MRR, actual_MRR, contract_MRR = pivot_tables(combo=generate_data(
n_sample=100, periods=30),
index=index)
#reformat data to column sparse matrix and place into dictionary
x = []
y = []
vals = []
[(y.append(i[0]), x.append(i[1]), vals.append(v))
for i, v in np.ndenumerate(percent_MRR)]
data = {'x': x, 'y': y, 'vals': vals}
#heatmap instantiate
hm = HeatMap(data=data,
x='x',
y='y',
values='vals',
stat=None,
title='Revenue Retention by {}'.format(','.join(index)),
ygrid=True,
xgrid=True,
xlabel='months',
ylabel='contract start',
yscale='categorical',
palette=brewer['RdYlGn'][11],
title_text_font_size='20pt')
#add value labels to heat map
# create formatted column of values for annotation labels
data['labels'] = [
'{:.0%}'.format(round(i, 2)) if i >= 0 else '' for i in data['vals']
]
#dropping vals which are not json compliant
del data['vals']
source = ColumnDataSource(data=data)
labels = LabelSet(x='x',
y='y',
text='labels',
level='glyph',
x_offset=-2,
y_offset=-4,
source=source,
render_mode='canvas',
text_font_size='7pt',
text_color='white')
hm.add_layout(labels)
# customize y-axis text
# new_index=actual_MRR.sum(axis=1).reset_index()
# new_index.rename(columns={0: 'Actual MRR'}, inplace=True)
# new_index['Contract MRR']=contract_MRR.sum(axis=1).reset_index()[0]
y_label_dict = {}
for index, groups in enumerate(list(percent_MRR.index)):
y_label_dict[index] = '-'.join(groups)
#reverse y-axis order
hm.y_range.start = max(y_label_dict.keys())
hm.y_range.end = min(y_label_dict.keys())
hm.x_range = Range1d(0, 12)
#generate javascript code to reformat y-axis
hm.yaxis.formatter = FuncTickFormatter(code="""var labels = {};
return labels[tick];
""".format(y_label_dict))
# fix ticks to display all values
hm.yaxis[0].ticker = FixedTicker(ticks=list(y_label_dict.keys()))
total_contract_mrr = contract_MRR.sum(axis=1)
total_actual_mrr = actual_MRR.sum(axis=1)
yaxis2_text = pd.concat([total_actual_mrr, total_contract_mrr], axis=1)
yaxis2_text.reset_index(drop=True, inplace=True)
yaxis2_text.columns = ['Actual MRR', 'Contract MRR']
yaxis2_text['text'] = yaxis2_text.apply(
lambda row: '{:,.0f}/{:,.0f} \t ({:.0%})'.format(
row['Actual MRR'], row['Contract MRR'], row['Actual MRR'] / row[
'Contract MRR']),
axis=1)
yaxis2_text = yaxis2_text['text'].to_dict()
#add right hand y-axis for additional information
top = max(yaxis2_text.keys())
bottom = min(yaxis2_text.keys())
print(top, bottom)
hm.extra_y_ranges = {'mrr': Range1d(top, bottom)}
hm.add_layout(LinearAxis(y_range_name="mrr"), 'right')
hm.yaxis[1].formatter = FuncTickFormatter(code="""var labels = {};
return labels[tick];
""".format(yaxis2_text))
hm.yaxis[1].ticker = FixedTicker(ticks=list(yaxis2_text.keys()))
hm.yaxis[1].axis_label = 'Actual and Contract MRR'
hm.yaxis[1].major_label_standoff = 30
# #help(hm.legend)
# legend_items=list(hm.legend)[0].items
#
hm.legend.location = 'bottom_right'
# exit()
output_file('interactive.html')
show(hm)
def process_file(self, file_path):
"""
Process the file given. This read from the file
and add it to the codec. The codec will then decode
the data and pass it to the UDP port.
"""
# Check if the file exist
if os.path.exists(file_path):
logger.info("Open file: " + file_path)
# Open the file
f = open(file_path, "rb")
# Add the data from the file to the codec
data = f.read(4096)
while len(data) > 0:
# Add data to codec
self.codec.add(data)
# Read next block from the file
data = f.read(4096)
# Close the file
f.close()
# Display the Heatmap and save it to HTML file
output_file('test.html')
hover = HoverTool(tooltips=[
("index", "$index"),
("(x,y)", "($x, $y)"),
("desc", "@desc"),
])
TOOLS = "hover,save,pan,box_zoom,reset,wheel_zoom"
hm = HeatMap(
self.df_mag_ens,
x='ens',
y='bin',
values='mag',
stat=None,
sort_dim={'x': False},
width=1000,
spacing_ratio=0.9,
tools=TOOLS,
toolbar_location="above", # Move toolbar to top
toolbar_sticky=False) # Make toolbar not to close to plot
# Set min and max axis and invert axis
xmin = self.df_mag_ens['ens'].min()
xmax = self.df_mag_ens['ens'].max()
ymax = self.df_mag_ens['bin'].min() # Swap Min and Max for y axis
ymin = self.df_mag_ens['bin'].max() # Swap Min and Max for y axis
hm.x_range = Range1d(
xmin, xmax) # Set the min and max, so no gaps on edges
hm.y_range = Range1d(
ymin, ymax) # Set the min and max, so no gaps on edges
show(hm)
while True:
input("Press enter to continue")
break
else:
logger.error("File does not exist")
