def dashboard():
"""
Creates the main app objects
"""
# TODO: Should find a better design and remove those global objs...
global source
global csource
source = ColumnDataSource(df)
source.tags = ['main_source']
csource = ColumnDataSource(cdf)
csource.tags = ['crash_source']
select_sec = Select.create(options=SECURITIES, name='select_sec', title="")
asel = Select.create(options=df.columns, name='field_to_add', title="")
chart_sel = Select.create(options=chart_types, name='chart_to_add', title="")
msel = MultiSelect.create(options=[], name='ms')
abutton = Button(label="add", type="success", name='add_button')
rbutton = Button(label="remove", type="danger", name='remove_button')
add_chart_button = Button(label="add chart", type="success", name='add_chart')
data_table = DataTable(source=source, editable=True, width=500, height=400)
ccolumns = [TableColumn(field=x, title=x, editor=NumberEditor()) for x in cdf.columns]
crashes_table = DataTable(source=csource, editable=True, width=1200, height=400, columns=ccolumns)
charts_box = AppVBox(children=[], name='charts_box')
counts = cdf['crashes']
crashes_hist = charts.Histogram({'crash_counts': counts}, bins=20, height=300, title="# Crashes per Symbol")
crashes_scatter = create_crashes_scatter()
main_tab = VBox(children=[], name='d_box')
dlg = Dialog(buttons=[], content=main_tab , visible=False)
options = CheckboxGroup(
labels=['Show peaks', 'Show Std. Dev.', 'Bolinger Bands'],
name='new_chart_options'
)
select_palette = Select.create(options=brewer.keys(), name='select_palette', title="Palette")
return {
# security tab
'select_sec': select_sec,
'field_to_add': asel,
'chart_to_add': chart_sel,
'ms': msel,
'dt': data_table,
'add_button': abutton,
'remove_button': rbutton,
'add_chart': add_chart_button,
'charts_box': charts_box,
'dlg': dlg,
# Crashes tab objs
'crashes_hist': crashes_hist,
'crashes_scatter': crashes_scatter,
'crashes_table': crashes_table,
'crash_stats': PreText(text="NO CRASHES FOR SYMBOL %s" % SYMBOL, width=300),
#
'chart_values': MultiSelect.create(options=df.columns, name="chart_values", title="Values"),
'new_chart_index': Select.create(options=['---']+list(df.columns), title="Chart index", name="new_chart_index"),
'new_chart_title': TextInput(title="Chart Title", name='new_chart_title', value=''),
'new_chart_options': options,
'select_palette': select_palette,
# ANNOTATIONS
"annotations": MultiSelect.create(options=[], name="annotations", title="Annotations"),
"add_annotation": Button(label="add", type="success", name='add_annotation'),
"delete_annotation": Button(label="remove", type="danger", name='delete_annotation'),
"show_annotation": Button(label="Show", type="link", name='show_annotation'),
'new_annotation_dlg': Dialog(buttons=[], content=main_tab , visible=False),
'annotation_txt': TextInput(title="New Annotation", name='annotation_txt', value=''),
'new_annotation_options': CheckboxGroup(labels=[], name='new_annotation_options'),
}
def portalDynamicity(df):
def getWeekString(yearweek):
if yearweek is None or len(str(yearweek)) == 0:
return ''
year = "'" + str(yearweek)[:2]
week = int(str(yearweek)[2:])
# d = d - timedelta(d.weekday())
# dd=(week)*7
# dlt = timedelta(days = dd)
# first= d + dlt
# dlt = timedelta(days = (week)*7)
# last= d + dlt + timedelta(days=6)
return 'W' + str(week) + '-' + str(year)
bp = figure(plot_width=600, plot_height=300, y_axis_type="datetime", responsive=True,
tools='') # ,toolbar_location=None
bp.toolbar.logo = None
bp.toolbar_location = None
label_dict={}
for i, s in enumerate(df['snapshot']):
label_dict[i] = getWeekString1(s)
bp.yaxis[0].formatter = NumeralTickFormatter(format="0.0%")
bp.xaxis[0].axis_label = 'Snapshots'
bp.yaxis[0].axis_label = '% of portals'
li = bp.line(df.index.values.tolist(), df['dyratio'], line_width=2, line_color='red', legend="dyratio")
c = bp.circle(df.index.values.tolist(), df['dyratio'], line_width=2, line_color='red', legend="dyratio")
li1 = bp.line(df.index.values.tolist(), df['adddelratio'], line_width=2, line_color='blue', legend="adddelratio")
c = bp.circle(df.index.values.tolist(), df['adddelratio'], line_width=2, line_color='blue', legend="adddelratio")
legend = bp.legend[0].legends
bp.legend[0].legends = []
l = Legend(location=(0, -30))
l.items = legend
bp.add_layout(l, 'right')
labels=["staticRatio","updatedRatio","addRatio","delRatio"]
#for l in labels:
# df[l]= df[l]*100
print brewer.keys()
colors = brewer["Pastel2"][len(labels)]
bar = Bar(df,
values=blend("staticRatio","updatedRatio","addRatio","delRatio", name='medals', labels_name='medal'),
label=cat(columns='snapshot', sort=False),
stack=cat(columns='medal', sort=False),
color=color(columns='medal', palette=colors,
sort=False),
legend='top_right',
bar_width=0.5, responsive=True,
tooltips=[('ratio', '@medal'), ('snapshot', '@snapshot'),('Value of Total',' @height{0.00%}')])
legend = bar.legend[0].legends
bar.legend[0].legends = []
l = Legend(location=(0, -30))
l.items = legend
bar.add_layout(l, 'right')
bar.xaxis[0].axis_label = 'Snapshots'
bar.yaxis[0].axis_label = '% of datasets'
bar.width=600
bar.height=300
bar.xaxis[0].formatter = FuncTickFormatter.from_py_func(getWeekStringTick)
bar.toolbar.logo = None
bar.toolbar_location = None
bar.yaxis[0].formatter = NumeralTickFormatter(format="0.0%")
return {'bar':bar,'lines':bp}
from StringIO import StringIO from collections import OrderedDict import numpy as np import pandas as pd from bokeh.plotting import * from bokeh.palettes import brewer from bokeh.objects import HoverTool import pdb import click palettes = u', '.join(sorted(brewer.keys())) help = u"""Colors palette to use. The following palettes are available: %s You can also provide your own custom palette by specifying a list colors. I.e.: "#a50026,#d73027,#f46d43,#fdae61,#fee08b,#ffffbf,#d9ef8b,#a6d96a,#66bd63" """ % palettes @click.command()
from StringIO import StringIO
from collections import OrderedDict
import numpy as np
import pandas as pd
from bokeh.plotting import *
from bokeh.palettes import brewer
from bokeh.objects import HoverTool
import pdb
import click
palettes = u', '.join(sorted(brewer.keys()))
help = u"""Colors palette to use. The following palettes are available:
%s
You can also provide your own custom palette by specifying a list colors. I.e.:
"#a50026,#d73027,#f46d43,#fdae61,#fee08b,#ffffbf,#d9ef8b,#a6d96a,#66bd63"
""" % palettes
@click.command()
@click.option('--source_filename',
type=click.Path(dir_okay=False, writable=True),
default="heatmap.html",
show_default=True,
)
@click.option(
"-d",
"--delim",
help="Delimiter used in the matrix. [ default: '\\t']",
default="\t",
# show_default=True,
)
@click.option(
"-p",
"--palette",
help="ColorBrewer palette to use for heatmap.",
type=click.Choice(choices=brewer.keys(), case_sensitive=True),
default="RdBu",
show_default=True,
)
@click.option("-t",
"--title",
help="Title for the heatmap.",
default=TITLE,
show_default=True)
@click.option("--width",
help="Plot width in pixels",
default=WIDTH,
show_default=True)
@click.option("--height",
help="Plot height in pixels",
default=HEIGHT,
counterclock=not rot_clock,
ax=ax,
**kwargs)
if ax:
ax.set(aspect="equal")
if title:
ax.set_title(title, fontsize=14)
else:
plt.axis('equal')
if title:
plt.title(title, fontsize=14)
# 色板
CMAP = ','.join(sorted(brewer.keys()))
pal = brewer
temp = {}
## 添加 反转 cmap
for cols in brewer:
temp[cols + "_r"] = {}
for i in brewer[cols]:
temp[cols + "_r"][i] = brewer[cols][i] #bokeh 的色板顺序和 seaborn 相反
brewer[cols][i] = list(reversed(brewer[cols][i]))
brewer.update(temp)
del temp
def showPal(cmp=None):