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Cleanup plots
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‎dashboard/plots.py‎

Lines changed: 65 additions & 145 deletions
Original file line numberDiff line numberDiff line change
@@ -13,143 +13,6 @@
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from bokeh.transform import dodge
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# for tests
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#import pandas as pd
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#import random
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#from bokeh.io import output_notebook, show, push_notebook
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#x = [str(i) for i in range(7)]
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#xs = [x,x,x,x,x]
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#xlabels = [[f'1 pli bla blub {i}' for i in x], [f'2 pli bla blub {i}' for i in x], [f'3 pli bla blub {i}' for i in x], [f'4 pli bla blub {i}' for i in x], [f'5 pli bla blub {i}' for i in x]]
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#ys = [[random.randint(0, 1200) for i in x], [random.randint(0, 1200) for i in x], [random.randint(0, 1200) for i in x],[random.randint(0, 1200) for i in x], [random.randint(0, 1200) for i in x]]
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# bokeh bar plot
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'''
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def bokeh_barchart(df, x='value', y='counts', factors=None, figure=None, title='This is a title', width=0.9, xlabel='Answers', ylabel='Number of answers', palette=Category20c, fill_color='color', description='For more information about the HMC survey click here.', redirect='https://helmholtz-metadaten.de/en/pages/structure-governance'):
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"""Plot an interactive bar chart with bokeh"""
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legend_it = []
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if isinstance(df, ColumnDataSource):
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xdata = df.data[x]
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if not 'color' in df.column_names:
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if not len(xdata) > 20:
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df.data['color'] = Category20c[len(xdata)] # ! if len(xdata)>20 this fails
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else:
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xdata = df[x]
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if not 'color' in df.columns:
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df['color'] = Category20c[len(xdata)] # ! if len(xdata)>20 this fails
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help_t = HelpTool(description=description, redirect=redirect)
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tools = 'hover,wheel_zoom,box_zoom,undo,reset,save'
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if figure is None:
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if factors is not None:
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fig = bokeh_figure(plot_height=600, plot_width=600,
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title=title,
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toolbar_location='above',
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x_range=FactorRange(factors=factors),
50-
tools=tools,#'hover',
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tooltips=[('Data', f'@{x}'), ('Count', f'@{y}')])
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else:
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fig = bokeh_figure(plot_height=600, plot_width=600,
54-
title=title,
55-
toolbar_location='above',
56-
tools=tools,#'hover',
57-
tooltips=[('Data', f'@{x}'), ('Count', f'@{y}')])
58-
else:
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fig = figure
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#if factors is not None:
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# fig.x_range=FactorRange(factors=factors)
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63-
fig.add_tools(help_t)
64-
fig.vbar(x=x, top=y, width=width, source=df, line_color="white", fill_color=fill_color)#factor_cmap('x', palette=palette, factors=factors, start=1, end=2))
65-
fig.y_range.start = 0
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fig.x_range.range_padding = 0.1
67-
fig.toolbar.logo = None
68-
fig.xaxis.major_label_orientation = 1
69-
fig.xgrid.grid_line_color = None
70-
fig.yaxis.axis_label = ylabel
71-
fig.xaxis.axis_label = xlabel
72-
fig.xgrid.grid_line_color = None
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#fig.legend.location = "left"
76-
#fig.legend.orientation = "horizontal"
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#fig.legend.click_policy="hide"
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return fig
80-
81-
def bokeh_barchart2(df, x=['value'], y=['counts'], factors=None, figure=None, data_visible=[True], title='', width=0.9, xlabel='Answers', ylabel='Number of answers', palette=Category20c, fill_color='color', legend_labels=None):
82-
"""Plot an interactive bar chart with bokeh"""
83-
84-
if figure is None:
85-
if factors is not None:
86-
fig = bokeh_figure(plot_height=600, plot_width=600,
87-
title=title,
88-
toolbar_location='above',
89-
#x_range=FactorRange(factors=factors),
90-
tools='',#'hover',
91-
tooltips=[('Data', f'@{x}'), ('Count', f'@{y}')])
92-
else:
93-
fig = bokeh_figure(plot_height=600, plot_width=600,
94-
title=title,
95-
toolbar_location='above',
96-
tools='',#'hover',
97-
tooltips=[('Data', f'@{x}'), ('Count', f'@{y}')])
98-
else:
99-
fig = figure
100-
101-
if isinstance(x, list):
102-
if not 'color' in df.column_names:
103-
if isinstance(palette, dict):
104-
x_color = palette[len(x)]
105-
else:
106-
x_color = df.data['color']
107-
position = []
108-
step = width + 0.05
109-
nvisible = data_visible.count(True)
110-
if nvisible%2 == 0:
111-
start = -step*nvisible/2 + step/2.0
112-
elif nvisible==1:
113-
start = 0.0
114-
else:
115-
start = nvisible//2 * -step
116-
displayed_pos = [start + i*step for i in range(nvisible)]
117-
ind = 0
118-
for visible in data_visible:
119-
if not visible:
120-
position.append(0.0)
121-
else:
122-
position.append(displayed_pos[ind])
123-
ind = ind+1
124-
for i, data in enumerate(x):
125-
fig.vbar(x=dodge(data, position[i], range=fig.x_range), top=y[i], source=df,
126-
width=width, color=x_color[i], legend_label=data, visible=data_visible[i])
127-
else:
128-
if isinstance(df, ColumnDataSource):
129-
xdata = df.data[x]
130-
if not 'color' in df.column_names:
131-
df.data['color'] = palette[len(xdata)]
132-
else:
133-
xdata = df[x]
134-
if not 'color' in df.columns:
135-
df['color'] = palette[len(xdata)]
136-
fig.vbar(x=x, top=y, width=width, source=df, line_color="white", fill_color=fill_color)#factor_cmap('x', palette=palette, factors=factors, start=1, end=2))
137-
138-
fig.y_range.start = 0
139-
fig.x_range.range_padding = 0.1
140-
fig.xaxis.major_label_orientation = 1
141-
fig.xgrid.grid_line_color = None
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fig.yaxis.axis_label = ylabel
143-
fig.xaxis.axis_label = xlabel
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fig.xgrid.grid_line_color = None
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fig.toolbar.logo = None
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#fig.legend.location = "left"
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#fig.legend.orientation = "horizontal"
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#fig.legend.click_policy="hide"
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return fig
152-
'''
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15417
def add_legend_outside(fig):
15518
"""
@@ -161,6 +24,8 @@ def add_legend_outside(fig):
16124
legend = fig.legend
16225
fig.add_layout(legend, 'right')
16326
return fig
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28+
16429
# test
16530
#df_test = pd.DataFrame(data=dict(value=xs[0], counts=ys[0]))
16631
#fig = bokeh_barchart(df_test, factors=xs[0])
@@ -173,12 +38,66 @@ def add_legend_outside(fig):
17338
#palette = Category20c[len(ys[0])]
17439
#fig = bokeh_barchart(df_test3, factors=factors, fill_color=factor_cmap('value', palette=palette, factors=xs[0], start=1, end=2))
17540
#show(fig)
41+
def preprocess_bokeh_input(func):
42+
"""Decorator function to preprocess, modify any bokeh plotting functions
43+
44+
:param func: the function to be decorated
45+
:type func: function
46+
"""
47+
def modified_plot(*args, **kwargs):
48+
"""Modifed plot functions"""
49+
50+
# check if pandas data frame, if yes convert
51+
# figure_kwargs
52+
# plot function kwargs
53+
func(*args, **kwargs)
54+
17655

56+
return modified_plot
17757

58+
59+
@preprocess_bokeh_input
17860
def bokeh_barchart(df, x='x_value', y=['y_value'], factors=None, figure=None, data_visible=[True], title='',
17961
width=0.1, xlabel='', ylabel='Number of answers', palette=Category20c,
180-
fill_color=None, legend_labels=None, description='For more information about the HMC survey click here.', redirect='https://helmholtz-metadaten.de/en/pages/structure-governance'):
62+
fill_color=None, legend_labels=None, description='For more information about the HMC survey click here.',
63+
redirect='https://helmholtz-metadaten.de/en/pages/structure-governance', **kwargs):
64+
"""Create an interactive bar chart with bokeh
65+
66+
:param df: [description]
67+
:type df: bokeh.models.ColumnDataSource
68+
:param x: [description], defaults to 'x_value'
69+
:type x: str, optional
70+
:param y: [description], defaults to ['y_value']
71+
:type y: list, optional
72+
:param factors: [description], defaults to None
73+
:type factors: [type], optional
74+
:param figure: [description], defaults to None
75+
:type figure: [type], optional
76+
:param data_visible: [description], defaults to [True]
77+
:type data_visible: list, optional
78+
:param title: [description], defaults to ''
79+
:type title: str, optional
80+
:param width: [description], defaults to 0.1
81+
:type width: float, optional
82+
:param xlabel: [description], defaults to ''
83+
:type xlabel: str, optional
84+
:param ylabel: [description], defaults to 'Number of answers'
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:type ylabel: str, optional
86+
:param palette: [description], defaults to Category20c
87+
:type palette: [type], optional
88+
:param fill_color: [description], defaults to None
89+
:type fill_color: [type], optional
90+
:param legend_labels: [description], defaults to None
91+
:type legend_labels: [type], optional
92+
:param description: [description], defaults to 'For more information about the HMC survey click here.'
93+
:type description: str, optional
94+
:param redirect: [description], defaults to 'https://helmholtz-metadaten.de/en/pages/structure-governance'
95+
:type redirect: str, optional
96+
:return: [description]
97+
:rtype: [type]
98+
"""
18199
y_keys = y
100+
182101
source = df
183102

184103
help_t = HelpTool(description=description, redirect=redirect)
@@ -202,7 +121,7 @@ def bokeh_barchart(df, x='x_value', y=['y_value'], factors=None, figure=None, da
202121
bars = []
203122
for i, y in enumerate(y_keys):
204123
bar = fig.vbar(x=dodge(x, position[i], range=fig.x_range), top=y, source=source,
205-
width=width, color=fill_color[i], legend_label=y)
124+
width=width, color=fill_color[i], legend_label=y, **kwargs)
206125
tooltips.append((f'{y}', '@{' + str(y) + '}'))
207126
bars.append(bar)
208127

@@ -226,8 +145,9 @@ def bokeh_barchart(df, x='x_value', y=['y_value'], factors=None, figure=None, da
226145

227146

228147

229-
# bokeh piechart
230-
def bokeh_piechart(df, x='value', y='counts', figure=None, radius=0.8, title=''):
148+
# bokeh piechart
149+
@preprocess_bokeh_input
150+
def bokeh_piechart(df, x='value', y='counts', figure=None, radius=0.8, title='', **kwargs):
231151
"""Draw an interactive piechart with bokeh"""
232152

233153
from math import pi
@@ -265,7 +185,7 @@ def bokeh_piechart(df, x='value', y='counts', figure=None, radius=0.8, title='')
265185
line_color='white',
266186
fill_color='color',
267187
legend_field=x,
268-
source=df)
188+
source=df, **kwargs)
269189
fig.toolbar.logo = None
270190
fig.axis.axis_label = None
271191
fig.axis.visible = False
@@ -281,8 +201,8 @@ def bokeh_piechart(df, x='value', y='counts', figure=None, radius=0.8, title='')
281201
#fig = bokeh_piechart(df_test)
282202
#show(fig)
283203

284-
285-
def bokeh_corr_plot(df, x='x_values', y='y_values', figure=None, title='', markersize='markersize', xlabel='Answers', ylabel='Number of answers', alpha=None):
204+
@preprocess_bokeh_input
205+
def bokeh_corr_plot(df, x='x_values', y='y_values', figure=None, title='', markersize='markersize', xlabel='Answers', ylabel='Number of answers', alpha=None, **kwargs):
286206
"""Plot an interactive circle with bokeh"""
287207

288208
if figure is None:
@@ -297,7 +217,7 @@ def bokeh_corr_plot(df, x='x_values', y='y_values', figure=None, title='', mark
297217
alpha = 1.0
298218
colors = ["#75968f", "#a5bab7", "#c9d9d3", "#e2e2e2", "#dfccce", "#ddb7b1", "#cc7878", "#933b41", "#550b1d"]
299219
mapper = LinearColorMapper(palette=colors, low=df.data[y].min(), high=df.data[y].max())
300-
fig.circle(source=df, x=x, y=y, radius = 0.9)#size=markersize, fill_color={'field': 'region', 'transform': color_mapper}, fill_alpha=alpha)
220+
fig.circle(source=df, x=x, y=y, radius = 0.9, **kwargs)#size=markersize, fill_color={'field': 'region', 'transform': color_mapper}, fill_alpha=alpha)
301221
#line_color='#7c7e71',
302222
#line_width=0.5,
303223
#line_alpha=0.5,

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