def Violin(dfs, measurement, configs, analysisType, **addConfigs):
"""Plots a measurement from all df as boxwisker"""
newConfigs = addConfigs
log.info("Generating Violin Plot for {}".format(measurement))
try:
plot = hv.Violin(
dfs["All"],
kdims="Name",
vdims=measurement,
label="Violin: {}".format(measurement),
group="Violin: {}".format(measurement),
)
# get labels from the configs
# ylabel = "{} [{}]".format(measurement, dfs[dfs["keys"][0]]["units"][dfs[dfs["keys"][0]]["measurements"].index(measurement)])
try:
ylabel = "{} [{}]".format(
measurement,
dfs[dfs["keys"][0]]["units"][dfs[
dfs["keys"][0]]["measurements"].index(measurement)],
)
except Exception as err:
log.error(
"Label could not be generated for violin plot {}. Error: {}".
format(measurement, err))
ylabel = "Y-Axis"
plot.opts(
box_alpha=0.3,
xrotation=80,
box_color="blue",
height=500,
show_legend=False,
width=600,
ylabel=ylabel, # inner='quartiles'
)
# Update the plot specific options if need be
generalOptions = configs[analysisType].get("General", {})
newConfigs.update(generalOptions.copy())
data_options = (configs[analysisType].get(measurement, {}).get(
"Violin", {}).get("PlotOptions", {}))
newConfigs.update(configs[analysisType].get(
"{}Options".format("Violin"), {}))
newConfigs.update(data_options)
plot = customize_plot(plot, "", configs[analysisType], **newConfigs)
except Exception as err:
log.error(
"Unexpected error happened during violin plot generation {}. Error: {}"
.format(measurement, err))
return None
return plot
def create_dist_plot(ds, fold):
df = ds.data
df['absolute error'] = (df.y - df.y_pred).abs()
df_selected = df.loc[df['data_split'] == fold].copy()
df_selected['selected'] = fold
df_all = df.groupby(['data_split', 'in_train_set']).mean().reset_index()
df_all['selected'] = 'all'
ds_dist = hv.Dataset(pd.concat([df_selected, df_all]),
kdims=['selected', 'in_train_set'],
vdims=['absolute error'])
opts = dict(width=600, height=540)
boxWhisker = (ds_dist.to(hv.BoxWhisker,
kdims=['selected', 'in_train_set'],
groupby=[]).opts(**opts, ylim=(0, 4)))
violin = hv.Violin(boxWhisker).opts(**opts)
return (boxWhisker + violin).opts(tabs=True)
print('CpG', CpG, sep='\t', file=Violin_out)
GpC = float(columns[6])
print('GpC', GpC, sep='\t', file=Violin_out)
violin_plot(out_file)
#==============================plot 1 = violin plot==============================
violin_data = 'arranged_data_violin.txt'
#loading the data
df = pd.read_csv(violin_data, sep='\t')
# Declearing the data
#plot
violin = hv.Violin(df, ('Dinucleotide', 'Dinucleotides'),
('ratio', 'Ratio')).redim.range(ratio=(0, 2))
violin.opts(height=500,
width=900,
violin_fill_color=dim('Dinucleotides').str(),
cmap='Set1')
#save plot
hv.save(violin, 'Promo_violin_plot.png', fmt='png')
#========================making the line plot with guassian filter=========================
count_CpG = {}
count_GpC = {}
with open('promoters_output.txt') as fh:
header = fh.readline()
for line in fh:
def holoviews_violinPlot_large(self):
import holoviews as hv
from holoviews import dim
from bokeh.sampledata.autompg import autompg
from bokeh.layouts import row, widgetbox
from bokeh.models import Select
from bokeh.plotting import curdoc
#### Bokeh Imports
from bokeh.plotting import figure, show, output_file
from bokeh.embed import components
from bokeh.resources import CDN
df_for_bokeh = pd.read_pickle("./df_holoviewPlots.pkl")
hv.extension('bokeh')
### OWN EXPERI STARTS === businesstravel dailyrate
# label = "WATSON ANALYTICS EMPLOYEE ATTRITION"
#TBD-- ##label=label
# violin_plot ==1 ---- BUSINESS_TRAVEL..'DAILY_RATE
violin_plot = hv.Violin(
df_for_bokeh, ('businesstravel', 'BUSINESS_TRAVEL'),
('dailyrate', 'DAILY_RATE')).redim.range(dailyrate=(120, 1300))
violin_plot.opts(height=500,
width=900,
show_legend=True,
violin_fill_color=dim('BUSINESS_TRAVEL').str(),
cmap='Set1')
violin_plot = hv.render(violin_plot)
print("---------type(violin_plot)--------", type(violin_plot))
##<class 'bokeh.plotting.figure.Figure'>
js_violin_plot, div_violin_plot = components(violin_plot)
cdn_js_violin_plot = CDN.js_files[0] # NOT REQD ??
cdn_css_violin_plot = CDN.css_files[0] # NOT REQD ??
# violin_plot ==2 ---- BUSINESS_TRAVEL..ATTRITTION -- attrition
violin_plot1 = hv.Violin(
df_for_bokeh, ('businesstravel', 'BUSINESS_TRAVEL'),
('attrition', 'ATTRITION')).redim.range(attrition=(0, 1))
violin_plot1.opts(height=500,
width=900,
show_legend=True,
violin_fill_color=dim('BUSINESS_TRAVEL').str(),
cmap='Set1')
violin_plot1 = hv.render(violin_plot1)
print("---------type(violin_plot)--------", type(violin_plot1))
##<class 'bokeh.plotting.figure.Figure'>
js_violin_plot1, div_violin_plot1 = components(violin_plot1)
cdn_js_violin_plot1 = CDN.js_files[0] # NOT REQD ??
cdn_css_violin_plot1 = CDN.css_files[0] # NOT REQD ??
return js_violin_plot, div_violin_plot, cdn_js_violin_plot, cdn_css_violin_plot, js_violin_plot1, div_violin_plot1, cdn_js_violin_plot1, cdn_css_violin_plot1
# def holoviews_plot_1(self):
# #
# """
# #Working Code - OK -- ORIGINAL -- Cars MPG Example -Not Reqd-- dc_holoviews_plotview
# """
# import holoviews as hv
# from bokeh.layouts import row, widgetbox
# from bokeh.models import Select
# from bokeh.plotting import curdoc
# from bokeh.sampledata.autompg import autompg
# #### Bokeh Imports
# from bokeh.plotting import figure, show, output_file
# from bokeh.embed import components
# from bokeh.resources import CDN
# df = autompg.copy()
# SIZES = list(range(6, 22, 3))
# ORIGINS = ['North America', 'Europe', 'Asia']
# # data cleanup
# df.cyl = [str(x) for x in df.cyl]
# df.origin = [ORIGINS[x-1] for x in df.origin]
# df['year'] = [str(x) for x in df.yr]
# del df['yr']
# df['mfr'] = [x.split()[0] for x in df.name]
# df.loc[df.mfr=='chevy', 'mfr'] = 'chevrolet'
# df.loc[df.mfr=='chevroelt', 'mfr'] = 'chevrolet'
# df.loc[df.mfr=='maxda', 'mfr'] = 'mazda'
# df.loc[df.mfr=='mercedes-benz', 'mfr'] = 'mercedes'
# df.loc[df.mfr=='toyouta', 'mfr'] = 'toyota'
# df.loc[df.mfr=='vokswagen', 'mfr'] = 'volkswagen'
# df.loc[df.mfr=='vw', 'mfr'] = 'volkswagen'
# del df['name']
# columns = sorted(df.columns)
# print("---------COLUMNS ==-----",columns)
# discrete = [x for x in columns if df[x].dtype == object]
# continuous = [x for x in columns if x not in discrete]
# quantileable = [x for x in continuous if len(df[x].unique()) > 20]
# print("---------quantileable----",quantileable)
# renderer = hv.renderer('bokeh')
# print("----------HOLOVIEWS -----",renderer)
# ## BokehRenderer()
# #
# options = hv.Store.options(backend='bokeh')
# options.Points = hv.Options('plot', width=800, height=500, size_index=None,) ## OK works
# options.Points = hv.Options('style', cmap='rainbow', line_color='black')
# def create_figure():
# x = Select(title='X-Axis', value='mpg', options=quantileable)
# ## Select == /home/dhankar/anaconda2/lib/python2.7/site-packages/bokeh/models/widgets/inputs.py
# #x.on_change('value', update)
# y = Select(title='Y-Axis', value='hp', options=quantileable)
# #y.on_change('value', update)
# #size = Select(title='Size', value='None', options=['None'] + quantileable)
# size = Select(title='Size', value='None', options=['None'] + quantileable)
# #size.on_change('value', update)
# color = Select(title='Color', value='None', options=['None'] + quantileable)
# #color.on_change('value', update)
# label = "Plot MAIN TITLE == %s vs %s" % (x.value.title(), y.value.title())
# kdims = [x.value, y.value]
# print("---------TYPE === kdims----------",type(kdims)) ##<class 'list'>
# print("--------- kdims----------",kdims) ## ['mpg', 'hp']
# opts, style = {}, {}
# opts['color_index'] = color.value if color.value != 'None' else None
# if size.value != 'None': ## DHANKAR --- CHANGED --- != TO ==
# opts['size_index'] = size.value
# opts['scaling_factor'] = (1./df[size.value].max())*200
# print("-----------AAAA--opts--",opts) ## This line Doesnt print --- this Code doesnt get into this -- - if -- Statement
# print("-----------TYPE--opts--",type(opts)) ## <class 'dict'>
# print("-----------BBBB--opts--",opts) ## {'color_index': None} ## Dict value printed outside the -- if -- Statement
# #points = hv.Points(df, kdims=kdims, label=label).opts(plot=opts, style=style) ## Original Code
# #points = hv.Points(df, vdims=['mfr', 'size'] , tools=['hover'] , kdims=kdims, label=label).opts(color='mfr')
# """
# Supplied data does not contain specified dimensions, the following dimensions were not found: ['size']
# PandasInterface expects tabular data, for more information on supported datatypes see http://holoviews.org/user_guide/Tabular_Datasets.html
# """
# #points = hv.Points(df, vdims=['mfr'] , tools=['hover'] , kdims=kdims, label=label).opts(color='mfr')
# ## WARNING:param.Points01326: Setting non-parameter attribute tools=['hover'] using a mechanism intended only for parameters
# points = hv.Points(df, vdims=['mfr'] , kdims=kdims, label=label).opts(color='mfr')
# """
# File "pandas/_libs/hashtable_class_helper.pxi", line 1500, in pandas._libs.hashtable.PyObjectHashTable.get_item
# KeyError: 'None'
# """
# # FOO--- Dhankar Code
# from bokeh.io import show
# from bokeh.models.tickers import FixedTicker
# from bokeh.themes import built_in_themes
# from bokeh.io import curdoc
# curdoc().theme = 'dark_minimal'
# bokeh_plot = hv.render(points)
# print("---------type(bokeh_plot)--------",type(bokeh_plot))
# ##<class 'bokeh.plotting.figure.Figure'>
# #bokeh_plot -- SHOW
# #show(bokeh_plot)
# #
# #hv.save(bokeh_plot, 'bokeh_plot.png')
# #return renderer.get_plot(points).state ## Original Code
# #return renderer.get_plot(points).state , bokeh_plot ## ERROR - we are intentionally Returning a TUPLE
# return bokeh_plot #OWN EXPERI ## ERROR - we are intentionally Returing a TUPLE
# bokeh_plot = create_figure()
# js_boxplot, div_boxplot = components(bokeh_plot)
# cdn_js_boxplot=CDN.js_files[0] # NOT REQD ??
# cdn_css_boxplot=CDN.css_files[0] # NOT REQD ??
# return js_boxplot,div_boxplot ,cdn_js_boxplot,cdn_css_boxplot
"""
### Original Code BElow ----------- OK
def update(attr, old, new):
layout.children[1] = create_figure()
x = Select(title='X-Axis', value='mpg', options=quantileable)
x.on_change('value', update)
y = Select(title='Y-Axis', value='hp', options=quantileable)
y.on_change('value', update)
size = Select(title='Size', value='None', options=['None'] + quantileable)
size.on_change('value', update)
color = Select(title='Color', value='None', options=['None'] + quantileable)
color.on_change('value', update)
controls = widgetbox([x, y, color, size], width=200)
layout = row(controls, create_figure()) ## Original Code --- Commented Out as gives ERROR - we are intentionally Returing a TUPLE
print("----------layout---------",layout)
print("------TYPE----layout---------",type(layout))
#----------layout--------- Row(id='1138', ...)
#------TYPE----layout--------- <class 'bokeh.models.layouts.Row'>
curdoc().add_root(layout) ## Original Code --- Commented Out as gives ERROR - we are intentionally Returing a TUPLE
curdoc().title = "Crossfilter" ## Original Code --- Commented Out as gives ERROR - we are intentionally Returing a TUPLE
print("---curdoc()--------------",curdoc()) ## <bokeh.document.document.Document object at
### FOO_ERROR --- Some issue with -- curdoc() == https://github.com/bokeh/bokeh/issues/8020
"""
# ---curdoc()-------------- <bokeh.document.document.Document object at 0x7f778e77f6d8>
# WARNING:bokeh.embed.util:
# You are generating standalone HTML/JS output, but trying to use real Python
# callbacks (i.e. with on_change or on_event). This combination cannot work.
# Only JavaScript callbacks may be used with standalone output. For more
# information on JavaScript callbacks with Bokeh, see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/interaction/callbacks.html
# Alternatively, to use real Python callbacks, a Bokeh server application may
# be used. For more information on building and running Bokeh applications, see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/server.html
"""
def holoviews_violinPlot_small(self):
"""
holoviews_violinPlot_small
"""
try:
#
import holoviews as hv
from holoviews import dim
from bokeh.sampledata.autompg import autompg
from bokeh.layouts import row, widgetbox
from bokeh.models import Select, HoverTool
#from bokeh.models import HoverTool , WheelZoomTool , LassoSelectTool ,BoxZoomTool, ResetTool , PanTool
from bokeh.plotting import curdoc
#### Bokeh Imports
from bokeh.plotting import figure, show, output_file
from bokeh.embed import components
from bokeh.resources import CDN
#
df_for_bokeh = pd.read_pickle("./df_holoviewPlots.pkl")
hv.extension('bokeh')
### OWN EXPERI STARTS === businesstravel dailyrate
# label = "WATSON ANALYTICS EMPLOYEE ATTRITION"
#TBD-- ##label=label
# violin_plot ==1 ---- BUSINESS_TRAVEL..'DAILY_RATE
violin_plot = hv.Violin(
df_for_bokeh, ('businesstravel', 'BUSINESS_TRAVEL'),
('dailyrate', 'DAILY_RATE')).redim.range(dailyrate=(120, 1300))
violin_plot.opts(height=200,
width=210,
show_legend=False,
tools=['hover'],
violin_fill_color=dim('BUSINESS_TRAVEL').str(),
cmap='Set1')
violin_plot = hv.render(violin_plot)
#plot_width=150, plot_height=170
print("---------type(violin_plot)--------", type(violin_plot))
##<class 'bokeh.plotting.figure.Figure'>
violin_plot.toolbar.logo = None
violin_plot.toolbar_location = None
js_violin_plot, div_violin_plot = components(violin_plot)
cdn_js_violin_plot = CDN.js_files[0] # NOT REQD ??
cdn_css_violin_plot = CDN.css_files[0] # NOT REQD ??
# violin_plot ==2 ---- BUSINESS_TRAVEL..ATTRITTION -- attrition
violin_plot1 = hv.Violin(
df_for_bokeh, ('businesstravel', 'BUSINESS_TRAVEL'),
('attrition', 'ATTRITION')).redim.range(attrition=(0, 1))
violin_plot1.opts(height=200,
width=210,
show_legend=False,
tools=['hover'],
violin_fill_color=dim('BUSINESS_TRAVEL').str(),
cmap='Set1')
violin_plot1 = hv.render(violin_plot1)
print("---------type(violin_plot)--------", type(violin_plot1))
##<class 'bokeh.plotting.figure.Figure'>
violin_plot1.toolbar.logo = None
violin_plot1.toolbar_location = None
js_violin_plot1, div_violin_plot1 = components(violin_plot1)
cdn_js_violin_plot1 = CDN.js_files[0] # NOT REQD ??
cdn_css_violin_plot1 = CDN.css_files[0] # NOT REQD ??
return js_violin_plot, div_violin_plot, cdn_js_violin_plot, cdn_css_violin_plot, js_violin_plot1, div_violin_plot1, cdn_js_violin_plot1, cdn_css_violin_plot1
except Exception as e:
print(
"--except Exception as e:---FROM ===>>-dc_holoviews.py--==--def holoviews_violinPlot_small(self)------",
e)
#return >>> ## Custom HTML to come here ...
"""
def violin_sueldos(df):
violin = hv.Violin(df, ('valor_cargo', 'Valor de Cargo'),
('sueldo_basico', 'Sueldo'))
violin.options(height=500, width=500)
return hv.renderer('bokeh').instance(mode='server').get_plot(violin).state
def violin_areas(df):
violin = hv.Violin(df, ('nombre_area', 'Area'), ('edad', 'Edad'))
violin.options(height=500, width=500)
return hv.renderer('bokeh').instance(mode='server').get_plot(violin).state