def violin_colorscale(data, data_header, group_header, colors, use_colorscale,
group_stats, rugplot, sort, height, width,
title):
"""
Refer to FigureFactory.create_violin() for docstring.
Returns fig for violin plot with colorscale.
"""
# collect all group names
group_name = []
for name in data[group_header]:
if name not in group_name:
group_name.append(name)
if sort:
group_name.sort()
# make sure all group names are keys in group_stats
for group in group_name:
if group not in group_stats:
raise exceptions.PlotlyError("All values/groups in the index "
"column must be represented "
"as a key in group_stats.")
gb = data.groupby([group_header])
group_name = list(gb.median().sort_values(data_header,
ascending=False).index)
L = len(group_name)
fig = make_subplots(rows=1, cols=L,
shared_yaxes=True,
horizontal_spacing=0.025,
print_grid=False)
# prepare low and high color for colorscale
lowcolor = utils.color_parser(colors[0], utils.unlabel_rgb)
highcolor = utils.color_parser(colors[1], utils.unlabel_rgb)
# find min and max values in group_stats
group_stats_values = []
for key in group_stats:
group_stats_values.append(group_stats[key])
max_value = max(group_stats_values)
min_value = min(group_stats_values)
for k, gr in enumerate(group_name):
vals = np.asarray(gb.get_group(gr)[data_header], np.float)
# find intermediate color from colorscale
intermed = (group_stats[gr] - min_value) / (max_value - min_value)
intermed_color = utils.find_intermediate_color(
lowcolor, highcolor, intermed
)
plot_data, plot_xrange = violinplot(
vals,
fillcolor='rgb{}'.format(intermed_color),
rugplot=rugplot
)
layout = graph_objs.Layout()
for item in plot_data:
fig.append_trace(item, 1, k + 1)
fig['layout'].update(
{'xaxis{}'.format(k + 1): make_XAxis(group_name[k], plot_xrange)}
)
# add colorbar to plot
trace_dummy = graph_objs.Scatter(
x=[0],
y=[0],
mode='markers',
marker=dict(
size=2,
cmin=min_value,
cmax=max_value,
colorscale=[[0, colors[0]],
[1, colors[1]]],
showscale=True),
showlegend=False,
)
fig.append_trace(trace_dummy, 1, L)
# set the sharey axis style
fig['layout'].update({'yaxis{}'.format(1): make_YAxis(data_header)})
fig['layout'].update(
title=title,
showlegend=False,
hovermode='closest',
autosize=True,
height=height,
margin=graph_objs.Margin(l=50, b=100)
)
return fig
def gantt_colorscale(chart,
colors,
title,
index_col,
show_colorbar,
bar_width,
showgrid_x,
showgrid_y,
height,
width,
tasks=None,
task_names=None,
data=None,
group_tasks=False):
"""
Refer to FigureFactory.create_gantt() for docstring
"""
if tasks is None:
tasks = []
if task_names is None:
task_names = []
if data is None:
data = []
showlegend = False
for index in range(len(chart)):
task = dict(x0=chart[index]['Start'],
x1=chart[index]['Finish'],
name=chart[index]['Task'])
if 'Description' in chart[index]:
task['description'] = chart[index]['Description']
tasks.append(task)
shape_template = {
'type': 'rect',
'xref': 'x',
'yref': 'y',
'opacity': 1,
'line': {
'width': 0,
}
}
# compute the color for task based on indexing column
if isinstance(chart[0][index_col], Number):
# check that colors has at least 2 colors
if len(colors) < 2:
raise exceptions.PlotlyError(
"You must use at least 2 colors in 'colors' if you "
"are using a colorscale. However only the first two "
"colors given will be used for the lower and upper "
"bounds on the colormap.")
# create the list of task names
for index in range(len(tasks)):
tn = tasks[index]['name']
# Is added to task_names if group_tasks is set to False,
# or if the option is used (True) it only adds them if the
# name is not already in the list
if not group_tasks or tn not in task_names:
task_names.append(tn)
# Guarantees that for grouped tasks the tasks that are inserted
# first are shown at the top
if group_tasks:
task_names.reverse()
for index in range(len(tasks)):
tn = tasks[index]['name']
del tasks[index]['name']
tasks[index].update(shape_template)
# If group_tasks is True, all tasks with the same name belong
# to the same row.
groupID = index
if group_tasks:
groupID = task_names.index(tn)
tasks[index]['y0'] = groupID - bar_width
tasks[index]['y1'] = groupID + bar_width
# unlabel color
colors = utils.color_parser(colors, utils.unlabel_rgb)
lowcolor = colors[0]
highcolor = colors[1]
intermed = (chart[index][index_col]) / 100.0
intermed_color = utils.find_intermediate_color(
lowcolor, highcolor, intermed)
intermed_color = utils.color_parser(intermed_color,
utils.label_rgb)
tasks[index]['fillcolor'] = intermed_color
# relabel colors with 'rgb'
colors = utils.color_parser(colors, utils.label_rgb)
# add a line for hover text and autorange
entry = dict(x=[tasks[index]['x0'], tasks[index]['x1']],
y=[groupID, groupID],
name='',
marker={'color': 'white'})
if "description" in tasks[index]:
entry['text'] = tasks[index]['description']
del tasks[index]['description']
data.append(entry)
if show_colorbar is True:
# generate dummy data for colorscale visibility
data.append(
dict(x=[tasks[index]['x0'], tasks[index]['x0']],
y=[index, index],
name='',
marker={
'color': 'white',
'colorscale': [[0, colors[0]], [1, colors[1]]],
'showscale': True,
'cmax': 100,
'cmin': 0
}))
if isinstance(chart[0][index_col], str):
index_vals = []
for row in range(len(tasks)):
if chart[row][index_col] not in index_vals:
index_vals.append(chart[row][index_col])
index_vals.sort()
if len(colors) < len(index_vals):
raise exceptions.PlotlyError(
"Error. The number of colors in 'colors' must be no less "
"than the number of unique index values in your group "
"column.")
# make a dictionary assignment to each index value
index_vals_dict = {}
# define color index
c_index = 0
for key in index_vals:
if c_index > len(colors) - 1:
c_index = 0
index_vals_dict[key] = colors[c_index]
c_index += 1
# create the list of task names
for index in range(len(tasks)):
tn = tasks[index]['name']
# Is added to task_names if group_tasks is set to False,
# or if the option is used (True) it only adds them if the
# name is not already in the list
if not group_tasks or tn not in task_names:
task_names.append(tn)
# Guarantees that for grouped tasks the tasks that are inserted
# first are shown at the top
if group_tasks:
task_names.reverse()
for index in range(len(tasks)):
tn = tasks[index]['name']
del tasks[index]['name']
tasks[index].update(shape_template)
# If group_tasks is True, all tasks with the same name belong
# to the same row.
groupID = index
if group_tasks:
groupID = task_names.index(tn)
tasks[index]['y0'] = groupID - bar_width
tasks[index]['y1'] = groupID + bar_width
tasks[index]['fillcolor'] = index_vals_dict[chart[index]
[index_col]]
# add a line for hover text and autorange
entry = dict(x=[tasks[index]['x0'], tasks[index]['x1']],
y=[groupID, groupID],
name='',
marker={'color': 'white'})
if "description" in tasks[index]:
entry['text'] = tasks[index]['description']
del tasks[index]['description']
data.append(entry)
if show_colorbar is True:
# generate dummy data to generate legend
showlegend = True
for k, index_value in enumerate(index_vals):
data.append(
dict(x=[tasks[index]['x0'], tasks[index]['x0']],
y=[k, k],
showlegend=True,
name=str(index_value),
hoverinfo='none',
marker=dict(color=colors[k], size=1)))
layout = dict(
title=title,
showlegend=showlegend,
height=height,
width=width,
shapes=[],
hovermode='closest',
yaxis=dict(
showgrid=showgrid_y,
ticktext=task_names,
tickvals=list(range(len(task_names))),
range=[-1, len(task_names) + 1],
autorange=False,
zeroline=False,
),
xaxis=dict(
showgrid=showgrid_x,
zeroline=False,
rangeselector=dict(buttons=list([
dict(count=7, label='1w', step='day', stepmode='backward'),
dict(count=1, label='1m', step='month', stepmode='backward'),
dict(count=6, label='6m', step='month', stepmode='backward'),
dict(count=1, label='YTD', step='year', stepmode='todate'),
dict(count=1, label='1y', step='year', stepmode='backward'),
dict(step='all')
])),
type='date'))
layout['shapes'] = tasks
fig = dict(data=data, layout=layout)
return fig
def violin_colorscale(data, data_header, group_header, colors, use_colorscale,
group_stats, rugplot, sort, height, width,
title):
"""
Refer to FigureFactory.create_violin() for docstring.
Returns fig for violin plot with colorscale.
"""
# collect all group names
group_name = []
for name in data[group_header]:
if name not in group_name:
group_name.append(name)
if sort:
group_name.sort()
# make sure all group names are keys in group_stats
for group in group_name:
if group not in group_stats:
raise exceptions.PlotlyError("All values/groups in the index "
"column must be represented "
"as a key in group_stats.")
gb = data.groupby([group_header])
L = len(group_name)
fig = make_subplots(rows=1, cols=L,
shared_yaxes=True,
horizontal_spacing=0.025,
print_grid=False)
# prepare low and high color for colorscale
lowcolor = utils.color_parser(colors[0], utils.unlabel_rgb)
highcolor = utils.color_parser(colors[1], utils.unlabel_rgb)
# find min and max values in group_stats
group_stats_values = []
for key in group_stats:
group_stats_values.append(group_stats[key])
max_value = max(group_stats_values)
min_value = min(group_stats_values)
for k, gr in enumerate(group_name):
vals = np.asarray(gb.get_group(gr)[data_header], np.float)
# find intermediate color from colorscale
intermed = (group_stats[gr] - min_value) / (max_value - min_value)
intermed_color = utils.find_intermediate_color(
lowcolor, highcolor, intermed
)
plot_data, plot_xrange = violinplot(
vals,
fillcolor='rgb{}'.format(intermed_color),
rugplot=rugplot
)
layout = graph_objs.Layout()
for item in plot_data:
fig.append_trace(item, 1, k + 1)
fig['layout'].update(
{'xaxis{}'.format(k + 1): make_XAxis(group_name[k], plot_xrange)}
)
# add colorbar to plot
trace_dummy = graph_objs.Scatter(
x=[0],
y=[0],
mode='markers',
marker=dict(
size=2,
cmin=min_value,
cmax=max_value,
colorscale=[[0, colors[0]],
[1, colors[1]]],
showscale=True),
showlegend=False,
)
fig.append_trace(trace_dummy, 1, L)
# set the sharey axis style
fig['layout'].update({'yaxis{}'.format(1): make_YAxis('')})
fig['layout'].update(
title=title,
showlegend=False,
hovermode='closest',
autosize=False,
height=height,
width=width
)
return fig
def gantt_colorscale(chart, colors, title, index_col, show_colorbar, bar_width,
showgrid_x, showgrid_y, height, width, tasks=None,
task_names=None, data=None, group_tasks=False):
"""
Refer to FigureFactory.create_gantt() for docstring
"""
if tasks is None:
tasks = []
if task_names is None:
task_names = []
if data is None:
data = []
showlegend = False
for index in range(len(chart)):
task = dict(x0=chart[index]['Start'],
x1=chart[index]['Finish'],
name=chart[index]['Task'])
if 'Description' in chart[index]:
task['description'] = chart[index]['Description']
tasks.append(task)
shape_template = {
'type': 'rect',
'xref': 'x',
'yref': 'y',
'opacity': 1,
'line': {
'width': 0,
}
}
# compute the color for task based on indexing column
if isinstance(chart[0][index_col], Number):
# check that colors has at least 2 colors
if len(colors) < 2:
raise exceptions.PlotlyError(
"You must use at least 2 colors in 'colors' if you "
"are using a colorscale. However only the first two "
"colors given will be used for the lower and upper "
"bounds on the colormap."
)
# create the list of task names
for index in range(len(tasks)):
tn = tasks[index]['name']
# Is added to task_names if group_tasks is set to False,
# or if the option is used (True) it only adds them if the
# name is not already in the list
if not group_tasks or tn not in task_names:
task_names.append(tn)
# Guarantees that for grouped tasks the tasks that are inserted
# first are shown at the top
if group_tasks:
task_names.reverse()
for index in range(len(tasks)):
tn = tasks[index]['name']
del tasks[index]['name']
tasks[index].update(shape_template)
# If group_tasks is True, all tasks with the same name belong
# to the same row.
groupID = index
if group_tasks:
groupID = task_names.index(tn)
tasks[index]['y0'] = groupID - bar_width
tasks[index]['y1'] = groupID + bar_width
# unlabel color
colors = utils.color_parser(colors, utils.unlabel_rgb)
lowcolor = colors[0]
highcolor = colors[1]
intermed = (chart[index][index_col]) / 100.0
intermed_color = utils.find_intermediate_color(
lowcolor, highcolor, intermed
)
intermed_color = utils.color_parser(
intermed_color, utils.label_rgb
)
tasks[index]['fillcolor'] = intermed_color
# relabel colors with 'rgb'
colors = utils.color_parser(colors, utils.label_rgb)
# add a line for hover text and autorange
entry = dict(
x=[tasks[index]['x0'], tasks[index]['x1']],
y=[groupID, groupID],
name='',
marker={'color': 'white'}
)
if "description" in tasks[index]:
entry['text'] = tasks[index]['description']
del tasks[index]['description']
data.append(entry)
if show_colorbar is True:
# generate dummy data for colorscale visibility
data.append(
dict(
x=[tasks[index]['x0'], tasks[index]['x0']],
y=[index, index],
name='',
marker={'color': 'white',
'colorscale': [[0, colors[0]], [1, colors[1]]],
'showscale': True,
'cmax': 100,
'cmin': 0}
)
)
if isinstance(chart[0][index_col], str):
index_vals = []
for row in range(len(tasks)):
if chart[row][index_col] not in index_vals:
index_vals.append(chart[row][index_col])
index_vals.sort()
if len(colors) < len(index_vals):
raise exceptions.PlotlyError(
"Error. The number of colors in 'colors' must be no less "
"than the number of unique index values in your group "
"column."
)
# make a dictionary assignment to each index value
index_vals_dict = {}
# define color index
c_index = 0
for key in index_vals:
if c_index > len(colors) - 1:
c_index = 0
index_vals_dict[key] = colors[c_index]
c_index += 1
# create the list of task names
for index in range(len(tasks)):
tn = tasks[index]['name']
# Is added to task_names if group_tasks is set to False,
# or if the option is used (True) it only adds them if the
# name is not already in the list
if not group_tasks or tn not in task_names:
task_names.append(tn)
# Guarantees that for grouped tasks the tasks that are inserted
# first are shown at the top
if group_tasks:
task_names.reverse()
for index in range(len(tasks)):
tn = tasks[index]['name']
del tasks[index]['name']
tasks[index].update(shape_template)
# If group_tasks is True, all tasks with the same name belong
# to the same row.
groupID = index
if group_tasks:
groupID = task_names.index(tn)
tasks[index]['y0'] = groupID - bar_width
tasks[index]['y1'] = groupID + bar_width
tasks[index]['fillcolor'] = index_vals_dict[
chart[index][index_col]
]
# add a line for hover text and autorange
entry = dict(
x=[tasks[index]['x0'], tasks[index]['x1']],
y=[groupID, groupID],
name='',
marker={'color': 'white'}
)
if "description" in tasks[index]:
entry['text'] = tasks[index]['description']
del tasks[index]['description']
data.append(entry)
if show_colorbar is True:
# generate dummy data to generate legend
showlegend = True
for k, index_value in enumerate(index_vals):
data.append(
dict(
x=[tasks[index]['x0'], tasks[index]['x0']],
y=[k, k],
showlegend=True,
name=str(index_value),
hoverinfo='none',
marker=dict(
color=colors[k],
size=1
)
)
)
layout = dict(
title=title,
showlegend=showlegend,
height=height,
width=width,
shapes=[],
hovermode='closest',
yaxis=dict(
showgrid=showgrid_y,
ticktext=task_names,
tickvals=list(range(len(task_names))),
range=[-1, len(task_names) + 1],
autorange=False,
zeroline=False,
),
xaxis=dict(
showgrid=showgrid_x,
zeroline=False,
rangeselector=dict(
buttons=list([
dict(count=7,
label='1w',
step='day',
stepmode='backward'),
dict(count=1,
label='1m',
step='month',
stepmode='backward'),
dict(count=6,
label='6m',
step='month',
stepmode='backward'),
dict(count=1,
label='YTD',
step='year',
stepmode='todate'),
dict(count=1,
label='1y',
step='year',
stepmode='backward'),
dict(step='all')
])
),
type='date'
)
)
layout['shapes'] = tasks
fig = dict(data=data, layout=layout)
return fig