def __init__(self, scheduler, width=600, **kwargs):
with log_errors():
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource({'nprocessing': [1, 2],
'nprocessing-half': [0.5, 1],
'nprocessing-color': ['red', 'blue'],
'nbytes': [1, 2],
'nbytes-half': [0.5, 1],
'worker': ['a', 'b'],
'y': [1, 2],
'nbytes-color': ['blue', 'blue'],
'bokeh_address': ['', '']})
processing = figure(title='Tasks Processing', tools='resize', id='bk-nprocessing-plot',
width=int(width / 2), **kwargs)
processing.rect(source=self.source,
x='nprocessing-half', y='y',
width='nprocessing', height=1,
color='nprocessing-color')
processing.x_range.start = 0
nbytes = figure(title='Bytes stored', tools='resize',
id='bk-nbytes-worker-plot', width=int(width / 2),
**kwargs)
nbytes.rect(source=self.source,
x='nbytes-half', y='y',
width='nbytes', height=1,
color='nbytes-color')
nbytes.xaxis[0].formatter = NumeralTickFormatter(format='0.0 b')
nbytes.xaxis.major_label_orientation = -math.pi / 12
nbytes.x_range.start = 0
for fig in [processing, nbytes]:
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
tap = TapTool(callback=OpenURL(url='http://@bokeh_address/'))
fig.add_tools(tap)
fig.toolbar.logo = None
fig.toolbar_location = None
fig.yaxis.visible = False
hover = HoverTool()
hover.tooltips = "@worker : @nprocessing tasks. Click for worker page"
hover.point_policy = 'follow_mouse'
processing.add_tools(hover)
hover = HoverTool()
hover.tooltips = "@worker : @nbytes bytes. Click for worker page"
hover.point_policy = 'follow_mouse'
nbytes.add_tools(hover)
self.processing_figure = processing
self.nbytes_figure = nbytes
processing.y_range = nbytes.y_range
self.root = row(nbytes, processing, sizing_mode='scale_width')
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.steal = scheduler.extensions['stealing']
self.last = 0
self.source = ColumnDataSource({'time': [time() - 20, time()],
'level': [0, 15],
'color': ['white', 'white'],
'duration': [0, 0], 'radius': [1, 1],
'cost_factor': [0, 10], 'count': [1, 1]})
x_range = DataRange1d(follow='end', follow_interval=20000, range_padding=0)
fig = figure(title="Stealing Events",
x_axis_type='datetime', y_axis_type='log',
height=250, tools='', x_range=x_range, **kwargs)
fig.circle(source=self.source, x='time', y='cost_factor', color='color',
size='radius', alpha=0.5)
fig.yaxis.axis_label = "Cost Multiplier"
hover = HoverTool()
hover.tooltips = "Level: @level, Duration: @duration, Count: @count, Cost factor: @cost_factor"
hover.point_policy = 'follow_mouse'
fig.add_tools(
hover,
ResetTool(reset_size=False),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width")
)
self.root = fig
def __init__(self, **kwargs):
data = self.processing_update({'processing': {}, 'ncores': {}})
self.source = ColumnDataSource(data)
x_range = Range1d(-1, 1)
fig = figure(
title='Processing and Pending', tools='resize',
x_range=x_range, id='bk-processing-stacks-plot', **kwargs)
fig.quad(source=self.source, left=0, right='right', color=Spectral9[0],
top='top', bottom='bottom')
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Host:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Processing:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@processing</span>
</div>
"""
hover.point_policy = 'follow_mouse'
self.root = fig
def __init__(self, scheduler, **kwargs):
with log_errors():
self.scheduler = scheduler
self.source = ColumnDataSource({
'occupancy': [0, 0],
'worker': ['a', 'b'],
'x': [0.0, 0.1],
'y': [1, 2],
'ms': [1, 2]
})
fig = figure(title='Occupancy',
tools='resize',
id='bk-occupancy-plot',
x_axis_type='datetime',
**kwargs)
fig.rect(source=self.source,
x='x',
width='ms',
y='y',
height=1,
color='blue')
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
# fig.xaxis[0].formatter = NumeralTickFormatter(format='0.0s')
fig.x_range.start = 0
hover = HoverTool()
hover.tooltips = "@worker : @occupancy s"
hover.point_policy = 'follow_mouse'
fig.add_tools(hover)
self.root = fig
def __init__(self, scheduler, **kwargs):
with log_errors():
self.scheduler = scheduler
self.source = ColumnDataSource({'occupancy': [0, 0],
'worker': ['a', 'b'],
'x': [0.0, 0.1],
'y': [1, 2],
'ms': [1, 2],
'color': ['red', 'blue'],
'bokeh_address': ['', '']})
fig = figure(title='Occupancy', tools='', id='bk-occupancy-plot',
x_axis_type='datetime', **kwargs)
rect = fig.rect(source=self.source, x='x', width='ms', y='y', height=1,
color='color')
rect.nonselection_glyph = None
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
# fig.xaxis[0].formatter = NumeralTickFormatter(format='0.0s')
fig.x_range.start = 0
tap = TapTool(callback=OpenURL(url='http://@bokeh_address/'))
hover = HoverTool()
hover.tooltips = "@worker : @occupancy s."
hover.point_policy = 'follow_mouse'
fig.add_tools(hover, tap)
self.root = fig
def nbytes_plot(**kwargs):
data = {'name': [], 'left': [], 'right': [], 'center': [], 'color': [],
'percent': [], 'MB': [], 'text': []}
source = ColumnDataSource(data)
fig = figure(title='Memory Use', tools='', toolbar_location=None, **kwargs)
fig.quad(source=source, top=1, bottom=0,
left='left', right='right', color='color', alpha=1)
fig.grid.grid_line_color = None
fig.grid.grid_line_color = None
fig.axis.visible = None
fig.outline_line_color = None
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Percent:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@percent</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">MB:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@MB</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def nbytes_plot(**kwargs):
data = {'name': [], 'left': [], 'right': [], 'center': [], 'color': [],
'percent': [], 'MB': [], 'text': []}
source = ColumnDataSource(data)
fig = figure(title='Memory Use', tools='', toolbar_location=None, **kwargs)
fig.quad(source=source, top=1, bottom=0,
left='left', right='right', color='color', alpha=0.8)
fig.text(source=source, x='center', y=0.5, text='text',
text_baseline='middle', text_align='center')
fig.grid.grid_line_color = None
fig.grid.grid_line_color = None
fig.axis.visible = None
fig.outline_line_color = None
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Percent:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@percent</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">MB:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@MB</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def nbytes_plot(**kwargs):
data = {"name": [], "left": [], "right": [], "center": [], "color": [], "percent": [], "MB": [], "text": []}
source = ColumnDataSource(data)
fig = figure(title="Memory Use", tools="", toolbar_location=None, id="bk-nbytes-plot", **kwargs)
fig.quad(source=source, top=1, bottom=0, left="left", right="right", color="color", alpha=1)
fig.grid.grid_line_color = None
fig.grid.grid_line_color = None
fig.axis.visible = None
fig.outline_line_color = None
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Percent:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@percent</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">MB:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@MB</span>
</div>
"""
hover.point_policy = "follow_mouse"
return source, fig
def __init__(self, scheduler, **kwargs):
with log_errors():
self.scheduler = scheduler
self.source = ColumnDataSource({'occupancy': [0, 0],
'worker': ['a', 'b'],
'x': [0.0, 0.1],
'y': [1, 2],
'ms': [1, 2]})
fig = figure(title='Occupancy', tools='resize', id='bk-occupancy-plot',
x_axis_type='datetime', **kwargs)
fig.rect(source=self.source, x='x', width='ms', y='y', height=1,
color='blue')
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
# fig.xaxis[0].formatter = NumeralTickFormatter(format='0.0s')
fig.x_range.start = 0
hover = HoverTool()
hover.tooltips = "@worker : @occupancy s"
hover.point_policy = 'follow_mouse'
fig.add_tools(hover)
self.root = fig
def task_stream_plot(height=400, width=800, follow_interval=5000, **kwargs):
data = {
'start': [],
'duration': [],
'key': [],
'name': [],
'color': [],
'worker': [],
'y': [],
'worker_thread': [],
'alpha': []
}
source = ColumnDataSource(data)
if follow_interval:
x_range = DataRange1d(follow='end',
follow_interval=follow_interval,
range_padding=0)
else:
x_range = None
fig = figure(width=width,
height=height,
x_axis_type='datetime',
tools=['xwheel_zoom', 'xpan', 'reset', 'resize', 'box_zoom'],
responsive=True,
x_range=x_range,
**kwargs)
fig.rect(x='start',
y='y',
width='duration',
height=0.9,
fill_color='color',
line_color='gray',
alpha='alpha',
source=source)
if x_range:
fig.circle(x=[1, 2], y=[1, 2], alpha=0.0)
fig.xaxis.axis_label = 'Time'
fig.yaxis.axis_label = 'Worker Core'
fig.min_border_right = 10
fig.ygrid.grid_line_alpha = 0.4
fig.xgrid.grid_line_alpha = 0.0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Key:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Duration:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@duration</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def data_usage_plot(df):
def create_data_source(df):
return ColumnDataSource(data=dict(filesystem=df['filesystem'],total_size=df['total_size'],used=df['used'],available=df['available'],use_percent=df['use_percent'],mounted=['mounted'],submittime=[x.strftime("%Y-%m-%d") for x in df['submittime']]))
hover = HoverTool(names=['points'])
TOOLS = [BoxZoomTool(),PanTool(),ResetTool(),WheelZoomTool(),hover]
Colors = ['red','navy','olive','firebrick','lightskyblue','yellowgreen','lightcoral','yellow', 'green','blue','gold']
# Change percents to format bokeh can use
fp_list = []
for row in df['use_percent']:
fp_list.append(float(row.replace('%','')))
df['f_percent'] = fp_list
# Begin Plotting
x_max = datetime.now()
p = figure(height=500, width=1000, x_axis_type="datetime", x_range=((x_max-timedelta(14)),x_max), y_axis_label='Percent Full', tools=TOOLS, title='Data Usage by Filesystem')
# Points with hover info
p.scatter(x=df['submittime'], y=df['f_percent'], name='points', source=create_data_source(df), color='black', size=6)
df = df.groupby(by = ['filesystem'])
# Connecting lines
count = 0
for filesystem, group in df:
count += 1
p.line(x=group['submittime'] ,y=group['f_percent'], color=Colors[count], legend=str(filesystem), line_width=3)
# Formating
p.legend.orientation = "top_left"
hover.point_policy = "follow_mouse"
hover.tooltips = [("Filesystem", "@filesystem"),("Size","@total_size"),("Available","@available"),("Percent Used","@use_percent"),("Time","@submittime")]
return p
def __init__(self, **kwargs):
data = self.processing_update({'processing': {}, 'ncores': {}})
self.source = ColumnDataSource(data)
x_range = Range1d(-1, 1)
fig = figure(title='Processing and Pending', tools='',
x_range=x_range, id='bk-processing-stacks-plot', **kwargs)
fig.quad(source=self.source, left=0, right='right', color=Spectral9[0],
top='top', bottom='bottom')
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Host:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Processing:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@processing</span>
</div>
"""
hover.point_policy = 'follow_mouse'
self.root = fig
def plot_coords(df, filename):
lat = 'Latitude|"Degrees"|-180.0|180.0|10'
long = 'Longitude|"Degrees"|-180.0|180.0|10'
speed = 'Speed|"mph"|0.0|150.0|10'
df.loc[df[lat] == 0, lat] = np.nan
df.loc[df[long] == 0, long] = np.nan
coord_source = ColumnDataSource(df)
coord_source.add(df['Interval|"ms"|0|0|1'], name='Time')
coord = figure(sizing_mode='scale_both',
width=700,
height=600,
title='GPS Data_{}'.format(filename))
# TODO figure out why this is broken
# mapper = linear_cmap(field_name='Speed"|"mph"|0.0|150.0|10', palette=Spectral6, low=min(speed), high=max(speed))
coord.circle(x=lat, y=long, source=coord_source, size=3, color='darkcyan')
# TODO figure out how to make the points be connected
# coord.line(x=lat, y=long, source=coord_source, line_width=2, color='red')
# Tools
hover = HoverTool()
hover.tooltips = [('Lat', '$x{0.000000}'), ('Long', '$y{0.000000}'),
('Time', '@Time')]
hover.point_policy = 'follow_mouse'
coord.add_tools(hover)
return coord
def __init__(self, scheduler, name, height=150, **kwargs):
self.scheduler = scheduler
self.action_ys = dict()
self.last = 0
self.name = name
self.source = ColumnDataSource({'time': [], 'action': [], 'hover': [],
'y': [], 'color': []})
x_range = DataRange1d(follow='end', follow_interval=200000)
fig = figure(title=name, x_axis_type='datetime',
height=height, tools='', x_range=x_range, **kwargs)
fig.circle(source=self.source, x='time', y='y', color='color',
size=50, alpha=0.5, legend='action')
fig.yaxis.axis_label = "Action"
fig.legend.location = 'top_left'
hover = HoverTool()
hover.tooltips = "@action<br>@hover"
hover.point_policy = 'follow_mouse'
fig.add_tools(
hover,
ResetTool(reset_size=False),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width")
)
self.root = fig
def task_stream_plot(sizing_mode="scale_width", **kwargs):
data = {
"start": [],
"duration": [],
"key": [],
"name": [],
"color": [],
"worker": [],
"y": [],
"worker_thread": [],
"alpha": [],
}
source = ColumnDataSource(data)
x_range = DataRange1d(range_padding=0)
fig = figure(
x_axis_type="datetime",
title="Task stream",
tools="xwheel_zoom,xpan,reset,box_zoom",
toolbar_location="above",
sizing_mode=sizing_mode,
x_range=x_range,
id="bk-task-stream-plot",
**kwargs
)
fig.rect(
x="start",
y="y",
width="duration",
height=0.8,
fill_color="color",
line_color="color",
line_alpha=0.6,
alpha="alpha",
line_width=3,
source=source,
)
fig.xaxis.axis_label = "Time"
fig.yaxis.axis_label = "Worker Core"
fig.ygrid.grid_line_alpha = 0.4
fig.xgrid.grid_line_color = None
fig.min_border_right = 35
fig.yaxis[0].ticker.num_minor_ticks = 0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 12px; font-weight: bold;">@name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@duration</span>
<span style="font-size: 10px;">ms</span>
</div>
"""
hover.point_policy = "follow_mouse"
return source, fig
def worker_table_plot(**kwargs):
""" Column data source and plot for host table """
with log_errors():
# names = ['host', 'cpu', 'memory_percent', 'memory', 'cores', 'processes',
# 'processing', 'latency', 'last-seen', 'disk-read', 'disk-write',
# 'network-send', 'network-recv']
names = ['processes', 'disk-read', 'cores', 'cpu', 'disk-write',
'memory', 'last-seen', 'memory_percent', 'host']
source = ColumnDataSource({k: [] for k in names})
columns = {name: TableColumn(field=name,
title=name.replace('_percent', ' %'))
for name in names}
cnames = ['host', 'cores', 'processes', 'memory', 'cpu', 'memory_percent']
formatters = {'cpu': NumberFormatter(format='0.0 %'),
'memory_percent': NumberFormatter(format='0.0 %'),
'memory': NumberFormatter(format='0 b'),
'latency': NumberFormatter(format='0.00000'),
'last-seen': NumberFormatter(format='0.000'),
'disk-read': NumberFormatter(format='0 b'),
'disk-write': NumberFormatter(format='0 b'),
'net-send': NumberFormatter(format='0 b'),
'net-recv': NumberFormatter(format='0 b')}
table = DataTable(source=source, columns=[columns[n] for n in cnames],
**kwargs)
for name in cnames:
if name in formatters:
table.columns[cnames.index(name)].formatter = formatters[name]
x_range = Range1d(0, 1)
y_range = Range1d(-.1, .1)
mem_plot = figure(title="Memory Usage (%)",
tools='box_select', height=90, width=600,
x_range=x_range, y_range=y_range, toolbar_location=None)
mem_plot.circle(source=source, x='memory_percent', y=0, size=10,
alpha=0.5)
mem_plot.yaxis.visible = False
mem_plot.xaxis.minor_tick_line_width = 0
mem_plot.ygrid.visible = False
mem_plot.xaxis.minor_tick_line_alpha = 0
hover = HoverTool()
mem_plot.add_tools(hover)
hover = mem_plot.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 10px; font-family: Monaco, monospace;">@host: </span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory_percent</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, [mem_plot, table]
def progress_plot(height=300, width=800, **kwargs):
from ..diagnostics.progress_stream import progress_quads
data = progress_quads({'all': {}, 'in_memory': {},
'erred': {}, 'released': {}})
source = ColumnDataSource(data)
fig = figure(width=width, height=height, tools=['resize'],
responsive=True, **kwargs)
fig.quad(source=source, top='top', bottom='bottom',
left=0, right=1, color='#aaaaaa', alpha=0.2)
fig.quad(source=source, top='top', bottom='bottom',
left=0, right='released_right', color='#0000FF', alpha=0.4)
fig.quad(source=source, top='top', bottom='bottom',
left='released_right', right='in_memory_right',
color='#0000FF', alpha=0.8)
fig.quad(source=source, top='top', bottom='bottom',
left='erred_left', right=1,
color='#000000', alpha=0.3)
fig.text(source=source, text='fraction', y='center', x=-0.01,
text_align='right', text_baseline='middle')
fig.text(source=source, text='name', y='center', x=1.01,
text_align='left', text_baseline='middle')
fig.scatter(x=[-0.2, 1.4], y=[0, 5], alpha=0)
fig.xgrid.grid_line_color = None
fig.ygrid.grid_line_color = None
fig.axis.visible = None
fig.min_border_left = 0
fig.min_border_right = 10
fig.min_border_top = 0
fig.min_border_bottom = 0
fig.outline_line_color = None
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">In Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@in_memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def task_stream_plot(sizing_mode='scale_width', **kwargs):
data = {
'start': [],
'duration': [],
'key': [],
'name': [],
'color': [],
'worker': [],
'y': [],
'worker_thread': [],
'alpha': []
}
source = ColumnDataSource(data)
x_range = DataRange1d(range_padding=0)
fig = figure(x_axis_type='datetime',
title="Task stream",
tools='xwheel_zoom,xpan,reset,box_zoom',
toolbar_location='above',
sizing_mode=sizing_mode,
x_range=x_range,
id='bk-task-stream-plot',
**kwargs)
fig.rect(x='start',
y='y',
width='duration',
height=0.8,
fill_color='color',
line_color='color',
line_alpha=0.6,
alpha='alpha',
line_width=3,
source=source)
fig.xaxis.axis_label = 'Time'
fig.yaxis.axis_label = 'Worker Core'
fig.ygrid.grid_line_alpha = 0.4
fig.xgrid.grid_line_color = None
fig.min_border_right = 35
fig.yaxis[0].ticker.num_minor_ticks = 0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 12px; font-weight: bold;">@name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@duration</span>
<span style="font-size: 10px;">ms</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def progress_plot(**kwargs):
from ..diagnostics.progress_stream import progress_quads
data = progress_quads({'all': {}, 'in_memory': {},
'erred': {}, 'released': {}})
x_range = Range1d(-0.5, 1.5)
y_range = Range1d(5.1, -0.1)
source = ColumnDataSource(data)
fig = figure(tools='', toolbar_location=None, y_range=y_range, x_range=x_range, **kwargs)
fig.quad(source=source, top='top', bottom='bottom',
left=0, right=1, color='#aaaaaa', alpha=0.2)
fig.quad(source=source, top='top', bottom='bottom',
left=0, right='released_right', color=Spectral9[0], alpha=0.4)
fig.quad(source=source, top='top', bottom='bottom',
left='released_right', right='in_memory_right',
color=Spectral9[0], alpha=0.8)
fig.quad(source=source, top='top', bottom='bottom',
left='erred_left', right=1,
color='#000000', alpha=0.3)
fig.text(source=source, text='fraction', y='center', x=-0.01,
text_align='right', text_baseline='middle')
fig.text(source=source, text='name', y='center', x=1.01,
text_align='left', text_baseline='middle')
fig.xgrid.grid_line_color = None
fig.ygrid.grid_line_color = None
fig.axis.visible = None
fig.outline_line_color = None
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">In Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@in_memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def _draw_contigCirclePlot(self):
hover = HoverTool(tooltips=[('Length', '@contigs')])
hover.point_policy = "follow_mouse"
plot = figure(x_axis_type=None, y_axis_type=None, tools=[hover], title='Contig lengths')
plot.annular_wedge(x=0, y=0, inner_radius=0.5, outer_radius=0.7,
start_angle='start', end_angle='stop',
color='colors', alpha=0.9, source=self.contig_dist_src)
plot.yaxis.axis_label_text_font_size = '14pt'
plot.xaxis.axis_label_text_font_size = '14pt'
plot.yaxis.major_label_text_font_size = '14pt'
plot.xaxis.major_label_text_font_size = '14pt'
plot.title.text_font_size = '16pt'
return plot
def progress_plot(**kwargs):
with log_errors():
from ..diagnostics.progress_stream import progress_quads
data = progress_quads({'all': {}, 'memory': {},
'erred': {}, 'released': {}})
y_range = Range1d(-8, 0)
source = ColumnDataSource(data)
fig = figure(tools='', toolbar_location=None, y_range=y_range, **kwargs)
fig.quad(source=source, top='top', bottom='bottom',
left='left', right='right', color='#aaaaaa', alpha=0.2)
fig.quad(source=source, top='top', bottom='bottom',
left='left', right='released-loc', color=Spectral9[0], alpha=0.4)
fig.quad(source=source, top='top', bottom='bottom',
left='released-loc', right='memory-loc', color=Spectral9[0], alpha=0.8)
fig.quad(source=source, top='top', bottom='bottom',
left='erred-loc', right='erred-loc', color='#000000', alpha=0.3)
fig.text(source=source, text='show-name', y='bottom', x='left',
x_offset=5, text_font_size='10pt')
fig.text(source=source, text='done', y='bottom', x='right', x_offset=-5,
text_align='right', text_font_size='10pt')
fig.xaxis.visible = False
fig.yaxis.visible = False
fig.grid.grid_line_alpha = 0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def progress_plot(**kwargs):
with log_errors():
from ..diagnostics.progress_stream import progress_quads
data = progress_quads({"all": {}, "memory": {}, "erred": {}, "released": {}})
y_range = Range1d(-8, 0)
source = ColumnDataSource(data)
fig = figure(tools="", toolbar_location=None, y_range=y_range, id="bk-progress-plot", **kwargs)
fig.quad(source=source, top="top", bottom="bottom", left="left", right="right", color="#aaaaaa", alpha=0.2)
fig.quad(source=source, top="top", bottom="bottom", left="left", right="released-loc", color="color", alpha=0.6)
fig.quad(
source=source, top="top", bottom="bottom", left="released-loc", right="memory-loc", color="color", alpha=1
)
fig.quad(
source=source, top="top", bottom="bottom", left="erred-loc", right="erred-loc", color="#000000", alpha=0.3
)
fig.text(source=source, text="show-name", y="bottom", x="left", x_offset=5, text_font_size="10pt")
fig.text(
source=source, text="done", y="bottom", x="right", x_offset=-5, text_align="right", text_font_size="10pt"
)
fig.xaxis.visible = False
fig.yaxis.visible = False
fig.grid.grid_line_alpha = 0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
"""
hover.point_policy = "follow_mouse"
return source, fig
def progress_plot(**kwargs):
with log_errors():
from ..diagnostics.progress_stream import progress_quads
data = progress_quads({'all': {}, 'memory': {},
'erred': {}, 'released': {}})
y_range = Range1d(-8, 0)
source = ColumnDataSource(data)
fig = figure(tools='', toolbar_location=None, y_range=y_range, **kwargs)
fig.quad(source=source, top='top', bottom='bottom',
left='left', right='right', color='#aaaaaa', alpha=0.2)
fig.quad(source=source, top='top', bottom='bottom',
left='left', right='released-loc', color='color', alpha=0.6)
fig.quad(source=source, top='top', bottom='bottom',
left='released-loc', right='memory-loc', color='color', alpha=1)
fig.quad(source=source, top='top', bottom='bottom',
left='erred-loc', right='erred-loc', color='#000000', alpha=0.3)
fig.text(source=source, text='show-name', y='bottom', x='left',
x_offset=5, text_font_size='10pt')
fig.text(source=source, text='done', y='bottom', x='right', x_offset=-5,
text_align='right', text_font_size='10pt')
fig.xaxis.visible = False
fig.yaxis.visible = False
fig.grid.grid_line_alpha = 0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def createHoverTool(simg, cols):
"""
"""
# Make the hovertool only follow the patches (still a hack)
htline = simg
ht = HoverTool()
ht.tooltips = [("Time", "@index{%F %T}")]
for col in cols:
fStr = "@%s{0.00}" % (col)
ht.tooltips.append((col, fStr))
ht.formatters = {'index': 'datetime'}
ht.show_arrow = False
ht.point_policy = 'follow_mouse'
ht.line_policy = 'nearest'
ht.renderers = [htline]
return ht
def task_stream_plot(height=400, width=800, follow_interval=5000, **kwargs):
data = {'start': [], 'duration': [],
'key': [], 'name': [], 'color': [],
'worker': [], 'y': [], 'worker_thread': []}
source = ColumnDataSource(data)
if follow_interval:
x_range = DataRange1d(follow='end', follow_interval=follow_interval,
range_padding=0)
else:
x_range = None
fig = figure(width=width, height=height, x_axis_type='datetime',
tools=['xwheel_zoom', 'xpan', 'reset', 'resize', 'box_zoom'],
responsive=True, x_range=x_range, **kwargs)
fig.rect(x='start', width='duration',
y='y', height=0.9,
fill_color='color', line_color='gray', source=source)
if x_range:
fig.circle(x=[1, 2], y=[1, 2], alpha=0.0)
fig.xaxis.axis_label = 'Time'
fig.yaxis.axis_label = 'Worker Core'
fig.min_border_right = 10
fig.ygrid.grid_line_alpha = 0.4
fig.xgrid.grid_line_alpha = 0.0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Key:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Duration:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@duration</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def task_stream_plot(sizing_mode='scale_width', **kwargs):
data = {'start': [], 'duration': [],
'key': [], 'name': [], 'color': [],
'worker': [], 'y': [], 'worker_thread': [], 'alpha': []}
source = ColumnDataSource(data)
x_range = DataRange1d(range_padding=0)
fig = figure(
x_axis_type='datetime', title="Task stream",
tools='xwheel_zoom,xpan,reset,box_zoom', toolbar_location='above',
sizing_mode=sizing_mode, x_range=x_range, **kwargs
)
fig.rect(
x='start', y='y', width='duration', height=0.8,
fill_color='color', line_color='color', line_alpha=0.6, alpha='alpha',
line_width=3, source=source
)
fig.xaxis.axis_label = 'Time'
fig.yaxis.axis_label = 'Worker Core'
fig.ygrid.grid_line_alpha = 0.4
fig.xgrid.grid_line_color = None
fig.min_border_right = 35
fig.yaxis[0].ticker.num_minor_ticks = 0
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Key:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Duration:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@duration</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
def plot_stats():
"""Creates and returns a figure."""
pos = [positions[i] for i in select_position.active]
team = select_team.value
ds = create_ds(team, pos)
source = ColumnDataSource(ds)
p = figure(plot_height=600,
plot_width=800,
title=f'{x.value} vs {y.value}',
tools='pan,box_zoom,reset')
p.circle(x=x.value,
y=y.value,
size='Size',
color='Color',
alpha=0.5,
source=source,
hover_color='navy')
hover = HoverTool(tooltips=[('Player', '@name'), (
'Team',
'@team'), (f'{x.value}',
f'@{{{x.value}}}'), (
f'{y.value}',
f'@{{{y.value}}}'), (f'Opponent', f'@Opponent')])
if size.value != 'None':
hover.tooltips.append((f'{size.value}', f'@{{{size.value}}}'))
if color.value != 'None':
hover.tooltips.append((f'{color.value}', f'@{{{color.value}}}'))
hover.point_policy = 'follow_mouse'
p.add_tools(hover)
p.xaxis.axis_label = x.value
p.yaxis.axis_label = y.value
return p
def _draw_contigCirclePlot(self):
hover = HoverTool(tooltips=[('Length', '@contigs')])
hover.point_policy = "follow_mouse"
plot = figure(x_axis_type=None,
y_axis_type=None,
tools=[hover],
title='Contig lengths')
plot.annular_wedge(x=0,
y=0,
inner_radius=0.5,
outer_radius=0.7,
start_angle='start',
end_angle='stop',
color='colors',
alpha=0.9,
source=self.contig_dist_src)
plot.yaxis.axis_label_text_font_size = '14pt'
plot.xaxis.axis_label_text_font_size = '14pt'
plot.yaxis.major_label_text_font_size = '14pt'
plot.xaxis.major_label_text_font_size = '14pt'
plot.title.text_font_size = '16pt'
return plot
def plot_filtering(time, raw, filtered):
"""
:param time:
:param raw:
:param filtered:
:return:
"""
hover = HoverTool()
hover.point_policy = 'snap_to_data'
hover.line_policy = 'nearest'
TOOLS = ['pan,wheel_zoom,box_zoom']
time = np.arange(0, raw.size)
p1 = figure(title="Timeseries SSH (raw vs filtered)",
tools=TOOLS,
plot_width=1000)
p1.grid.grid_line_alpha = 0.3
p1.xaxis.axis_label = 'Date (Julian days)'
p1.yaxis.axis_label = 'SSH'
p1.circle(time, raw, color='lightseagreen')
p1.line(time, raw, legend='raw', color='lightseagreen')
p1.circle(time, filtered, color='royalblue')
p1.line(time, filtered, legend='filtered',
color='royalblue') #, line_width=4)
p1.add_tools(
HoverTool(tooltips=[
('date', '@x'),
('SSH', '@y m'),
], mode='mouse'))
p1.legend.location = "top_left"
# output_file("Hss_timeseries.html", title="Hss_timeseries")
show(p1, plot_width=1000, plot_height=400)
def progress_plot(height=300, width=800, **kwargs):
from ..diagnostics.progress_stream import progress_quads
data = progress_quads({
'all': {},
'in_memory': {},
'erred': {},
'released': {}
})
source = ColumnDataSource(data)
fig = figure(width=width,
height=height,
tools=['resize'],
responsive=True,
**kwargs)
fig.quad(source=source,
top='top',
bottom='bottom',
left=0,
right=1,
color='#aaaaaa',
alpha=0.2)
fig.quad(source=source,
top='top',
bottom='bottom',
left=0,
right='released_right',
color='#0000FF',
alpha=0.4)
fig.quad(source=source,
top='top',
bottom='bottom',
left='released_right',
right='in_memory_right',
color='#0000FF',
alpha=0.8)
fig.quad(source=source,
top='top',
bottom='bottom',
left='erred_left',
right=1,
color='#000000',
alpha=0.3)
fig.text(source=source,
text='fraction',
y='center',
x=-0.01,
text_align='right',
text_baseline='middle')
fig.text(source=source,
text='name',
y='center',
x=1.01,
text_align='left',
text_baseline='middle')
fig.scatter(x=[-0.2, 1.4], y=[0, 5], alpha=0)
fig.xgrid.grid_line_color = None
fig.ygrid.grid_line_color = None
fig.axis.visible = None
fig.min_border_left = 0
fig.min_border_right = 10
fig.min_border_top = 0
fig.min_border_bottom = 0
fig.outline_line_color = None
hover = HoverTool()
fig.add_tools(hover)
hover = fig.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">In Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@in_memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, fig
x = [0, 1, 2, 3, 4, 5]
y = [0, 1, 4, 9, 16, 25]
# set output to static HTML file
output_file("quad.html")
# create a new plot with a title and axis labels
p = figure(title="x^2 example",
x_axis_label='x',
y_axis_label='y',
active_scroll="wheel_zoom")
# add a line renderer with legend and line thickness
p.line(x, y, legend_label="x-val legend label", line_width=2)
# customize the hover_tool/tooltip
hover_tool = HoverTool(tooltips=[("x val", "$x"), ("y val", "$y")])
hover_tool.point_policy = "snap_to_data"
hover_tool.line_policy = "interp" # interpolate if between data points, makes it more continuous
hover_tool.mode = "vline" #shows value if in line vertically (no need to be directly on top of graph line)
p.add_tools(hover_tool)
# remove tools on the right and logo for clean look
p.toolbar.logo = None
p.toolbar_location = None
# show graph
show(p)
#leitura do arquivo de dados
df = pd.DataFrame()
df = pd.read_csv('/home/bh/Documentos/DoubleMuRun2011A.csv',
engine='python') #Lê o arquivo com os dados.
btn_bin = Button(label="calcular fit")
options = [("Breit-Wigner", "Breit-Wigner"),
("Duas Gaussianas + Exponencial", "Duas Gaussianas + Exponencial"),
("CrystalBall + Exponencial", "CrystalBall + Exponencial")]
dropdown = Dropdown(label="fit selection", button_type="warning", menu=options)
#add hover
hover = HoverTool(tooltips=[('Counts',
'@inv_mass'), ('Invariant mass (GeV)', '$x')])
hover.point_policy = "follow_mouse"
bins = 500
def plot(newbin, begin, end, y_type='linear'):
weights = []
for i in df["M"]:
weights.append(newbin / np.log(10) / i)
#create histogram
hist, edges = np.histogram(df["M"],
bins=np.logspace(begin, end, num=newbin + 1),
weights=weights)
# Put the information in a dataframe
def plot_coadd(all_df, processed_df, band_df, tag):
def create_processed_data_source(df):
return ColumnDataSource(data=dict(tilename=df['tilename'],status=df['status'],attnum=df['attnum'],reqnum=df['reqnum'],id=df['id'],dmedian=df['dmedian']))
def create_all_data_source(df):
return ColumnDataSource(data=dict(tilename=df['tilename'],dmedian=df['dmedian']))
Colors=['green','blue','blue','blue','blue','blue','blue','blue','blue','blue']
### All_df data prep ###
new_all_df = pd.DataFrame()
xlist, ylist, tilelist =[],[],[]
for i, row in all_df.iterrows():
# Fixes wrapping issue
if (row['rac3']-row['rac4']) > 100:
row['rac4']=360 + row['rac4']
row['rac1']=360 + row['rac1']
# Shifts image so that tank is visable
if row['rac3'] < 180:
row['rac1'] = row['rac1']+360
row['rac2'] = row['rac2']+360
row['rac3'] = row['rac3']+360
row['rac4'] = row['rac4']+360
xlist.append([row['rac1'], row['rac2'], row['rac3'], row['rac4']])
ylist.append([row['decc1'], row['decc2'], row['decc3'], row['decc4']])
tilelist.append(row['tilename'])
new_all_df['x']=xlist
new_all_df['y']=ylist
new_all_df['tilename']=tilelist
# Band_df data prep
band_df = band_df.groupby(by = ['tilename'])
new_band_df = pd.DataFrame()
maxdepth=20
tilelist, depthlist, alphalist = [],[],[]
for tile,group in band_df:
depth,count = 0,0
for i,row in group.iterrows():
count += 1
depth += row['dmedian']
depth = depth/count
#if depth > 3:
tilelist.append(tile)
alphalist.append(depth/maxdepth)
depthlist.append(depth)
new_band_df['tilename'] = tilelist
new_band_df['dmedian'] = depthlist
new_band_df['alphas'] = alphalist
# Merge all dfs
new_all_df = pd.merge(new_all_df, new_band_df, how='outer', on=['tilename'])
new_all_df.fillna(0, inplace=True)
fn_df = pd.merge(new_all_df, processed_df, how='inner', on=['tilename'])
fn_df.fillna('None', inplace=True)
### Avg band plot ###
all_hover = HoverTool(names=['all'])
TOOLS = [BoxZoomTool(),PanTool(),ResetTool(),WheelZoomTool(),all_hover]
p = figure(height=1000, width=1000, x_axis_label='RA (Deg)', y_axis_label='DEC (Deg)', tools=TOOLS, title=str(tag)+
' Coadd Map')
p.patches(xs=new_all_df['x'], ys=new_all_df['y'], source=create_all_data_source(new_all_df), name='all', fill_color='blue', fill_alpha=new_all_df['alphas'], line_color='black')
### Add each unitname to plot ###
p.patches(xs=fn_df['x'], ys=fn_df['y'], source=create_processed_data_source(fn_df), name='all', fill_color='green', fill_alpha=0.95, line_color='black')
all_hover.point_policy = "follow_mouse"
all_hover.tooltips = [("Tilename", "@tilename"),('Pfw_attempt_id','@id'),("Depth","@dmedian")]
return p
def contour_plot_bokeh(
model,
xlabel=None,
ylabel=None,
main=None,
xlim=(-3.2, 3.2),
ylim=(-3.2, 3.2),
colour_function="terrain",
show=True,
show_expt_data=True,
figsize=(10, 10),
dpi=50,
other_factors=None,
):
# TODO: show labels of contour plot
# https://stackoverflow.com/questions/33533047/how-to-make-a-contour-plot-in-python-using-bokeh-or-other-libs
dpi_max = dpi**3.5
N = min(dpi, np.power(dpi_max, 0.5))
h_grid = np.linspace(xlim[0], xlim[1], num=N)
v_grid = np.linspace(ylim[0], ylim[1], num=N)
H, V = np.meshgrid(h_grid, v_grid)
h_grid, v_grid = H.ravel(), V.ravel()
pure_factors = model.get_factor_names(level=1)
if xlabel is None:
xlabel = pure_factors[0]
else:
xlabel = str(xlabel)
if ylabel is None:
ylabel = pure_factors[1]
else:
ylabel = str(ylabel)
kwargs = {xlabel: h_grid, ylabel: v_grid}
if other_factors is not None and isinstance(other_factors, dict):
kwargs = kwargs.update(other_factors)
# Look at which factors are included, and pop them out. The remaining
# factors are specified at their zero level
unspecified_factors = [i for i in pure_factors if i not in kwargs.keys()]
for factor in unspecified_factors:
kwargs[factor] = np.zeros_like(h_grid)
assert sorted(kwargs.keys()) == sorted(pure_factors), ("Not all factors "
"were specified.")
Z = predict(model, **kwargs)
Z = Z.values.reshape(N, N)
z_min, z_max = Z.min(), Z.max()
levels = np.linspace(z_min, z_max, N)
from matplotlib.pyplot import contour, clabel
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use("Agg")
# Turn interactive plotting off
plt.ioff()
CS = contour(H, V, Z, levels=levels, linestyles="dotted")
clabel(CS, inline=True, fontsize=10, fmt="%1.0f")
# contour_labels = [(float(q._x), float(q._y), float(q._text))\
# for q in CS.labelTexts]
# Convert the Matplotlib colour mapper to Bokeh
# https://stackoverflow.com/questions/49931311/using-matplotlibs-colormap-for-bokehs-color-bar
mapper = getattr(cm, colour_function)
colours = (255 * mapper(range(256))).astype("int")
colour_palette = [RGB(*tuple(rgb)).to_hex() for rgb in colours]
color_mapper = LinearColorMapper(palette=colour_palette,
low=z_min,
high=z_max)
# Another alternative:
# https://stackoverflow.com/questions/35315259/using-colormap-with-bokeh-scatter
# colors = ["#%02x%02x%02x" % (int(r), int(g), int(b)) for \
# r, g, b, _ in 255*mpl.cm.viridis(mpl.colors.Normalize()(radii))]
p = figure(
x_range=xlim,
y_range=ylim,
# https://github.com/bokeh/bokeh/issues/2351
tools="pan,wheel_zoom,box_zoom,box_select,lasso_select,reset,save",
)
# Create the image layer
source = {"Xax": [h_grid], "Yax": [v_grid], "predictions": [Z]}
h_image = p.image(
source=source,
image="predictions",
x=xlim[0],
y=ylim[0],
dw=xlim[1] - xlim[0],
dh=ylim[1] - ylim[0],
color_mapper=color_mapper,
global_alpha=0.5, # with some transparency
name="contour_image",
)
h1 = HoverTool(
tooltips=[
(xlabel, "@{Xax}{0.4g}"),
(ylabel, "@{Yax}{0.4f}"),
("Predicted", "@{predictions}{0.4g}"),
],
renderers=[h_image],
formatters={
"Predicted": "printf",
xlabel: "printf",
ylabel: "printf"
},
)
color_bar = ColorBar(
color_mapper=color_mapper,
major_label_text_font_size="8pt",
ticker=BasicTicker(max_interval=(z_max - z_min) / N * 2),
formatter=PrintfTickFormatter(format="%.2f"),
label_standoff=6,
border_line_color=None,
location=(0, 0),
)
p.add_layout(color_bar, "right")
# Contour lines using Scipy:
# scaler_y = (ylim[1] - ylim[0]) / (N - 1)
# scaler_x = (xlim[1] - xlim[0]) / (N - 1)
# for level in levels:
# contours = measure.find_contours(Z, level)
# for contour in contours:
# x = contour[:, 1] * scaler_y + ylim[0]
# y = contour[:, 0] * scaler_x + xlim[0]
for _, cccontour in enumerate(CS.allsegs):
if cccontour:
x = cccontour[0][:, 0]
y = cccontour[0][:, 1]
p.line(x, y, line_dash="dashed", color="darkgrey", line_width=1)
# TODO: bigger experimental markers
# TODO: hover for the data point shows the factor settings for the data point
if show_expt_data:
source = ColumnDataSource(data=dict(
x=model.data[xlabel],
y=model.data[ylabel],
output=model.data[model.get_response_name()].to_list(),
))
h_expts = p.circle(
x="x",
y="y",
color="black",
source=source,
# linestyle='',
# marker='o',
size=10,
line_width=2,
name="experimental_points",
)
# custom tooltip for the experimental points
h2 = HoverTool(
tooltips=[
(xlabel, "$x{0.4g}"),
(ylabel, "$y{0.4g}"),
("Actual value", "@{output}{0.4g}"), # why not working???
],
renderers=[h_expts],
formatters={
"Actual value": "printf",
xlabel: "printf",
ylabel: "printf"
},
)
h2.point_policy = "snap_to_data"
h2.line_policy = "none"
# Axis labels:
p.xaxis.axis_label_text_font_size = "14pt"
p.xaxis.axis_label = xlabel
p.xaxis.major_label_text_font_size = "14pt"
p.xaxis.axis_label_text_font_style = "bold"
p.xaxis.bounds = (xlim[0], xlim[1])
p.yaxis.major_label_text_font_size = "14pt"
p.yaxis.axis_label = ylabel
p.yaxis.axis_label_text_font_size = "14pt"
p.yaxis.axis_label_text_font_style = "bold"
p.yaxis.bounds = (ylim[0], ylim[1])
# Add the hover tooltips:
p.add_tools(h1)
p.add_tools(h2)
if show:
show_plot(p)
return p
def rca2(functionNode):
logger = functionNode.get_logger()
logger.info("==>>>> in rca2 (root cause analysis " +
functionNode.get_browse_path())
progressNode = functionNode.get_child("control").get_child("progress")
progressNode.set_value(0.1)
m = functionNode.get_model()
report = '<i>REPORT</i><br><div style="font-size:85%">'
annotations = functionNode.get_child("annotations").get_leaves()
#order = ["Step"+str(no) for no in range(1,19)]
order = ["Phase" + str(no) for no in range(3, 28)]
order = functionNode.get_child("annotationsOrder").get_value()
annotations = data_cleaning(annotations, order=order,
logger=logger) #Step1,Step2,...Step18
report += (f"found {len(annotations)} valid processes <br>")
#for now, flatten them out
annotations = [
subprocess for process in annotations for subprocess in process
]
algo = functionNode.get_child("selectedAlgorithm").get_value()
target = functionNode.get_child("selectedTarget").get_target()
progressNode.set_value(0.3)
#now we are building up the table by iterating all the children in "selection"
entries = functionNode.get_child("selection").get_children()
table = {"target": []}
firstVariable = True
for entry in entries:
logger.debug(f"entry {entry.get_name()}")
#each entry is a combination of variable, tags and feature
vars = entry.get_child("selectedVariables").get_targets()
tags = entry.get_child("selectedTags").get_value()
features = entry.get_child("selectedFeatures").get_value()
#for iterate over variables
for var in vars:
logger.debug(
f"processing variable: {var.get_name()} with tags {tags} and features {features}"
)
#columnName = var.get_name()+str(tags)+m.getRandomId()
for tag in tags:
row = 0
#table[columnName]=[]# make a column
for idx, anno in enumerate(annotations):
if anno.get_child("type").get_value() != "time":
continue
if tag in anno.get_child("tags").get_value():
startTime = anno.get_child("startTime").get_value()
endTime = anno.get_child("endTime").get_value()
data = var.get_time_series(startTime,
endTime)["values"]
#we take only the values "inside" the annotation
if len(data) > 2:
data = data[1:-1]
#now create the features
for feature in features:
feat = calc_feature(data, feature)
columnName = var.get_name(
) + "_" + tag + "_" + feature
if not columnName in table:
table[columnName] = []
table[columnName].append(feat)
targetValue = get_target(
target,
(date2secs(startTime) + date2secs(endTime)) / 2)
if targetValue:
if firstVariable:
#for the first variable we also write the target
table["target"].append(targetValue)
else:
#for all others we make sure we have the same target value for that case (sanity check)
if table["target"][row] != targetValue:
logger.warning(
f'problem target {table["target"][row]} !=> {targetValue}'
)
row = row + 1
else:
logger.warning(
f"no corrrect target value for {startTime} - {endTime}"
)
firstVariable = False
#now we have the table, plot it
import json
#print(json.dumps(table,indent=2))
progressNode.set_value(0.5)
#try a model
algo = functionNode.get_child("selectedAlgorithm").get_value()
if algo == "lasso":
reg = linear_model.LassoCV()
report += " using lasso Regression with auto-hyperparams <br>"
else:
#default
report += " using linear Regression <br>"
reg = linear_model.LinearRegression() #try rigde, lasso
columnNames = []
dataTable = []
for k, v in table.items():
if k == "target":
continue
dataTable.append(v)
columnNames.append(k)
dataTable = numpy.asarray(dataTable)
x = dataTable.T
y = table["target"]
x_train, x_test, y_train, y_test = train_test_split(x, y)
reg.fit(x_train, y_train)
print(reg.coef_)
y_hat = reg.predict(x_test)
y_repeat = reg.predict(x_train)
print(f"predict: {y_hat} vs real: {y_test}")
#check over/underfitting
r_train = r2_score(y_train, y_repeat)
r_test = r2_score(y_test, y_hat)
report += "R<sup>2</sup> train= %.4g, R<sup>2</sup> test = %.4g <br>" % (
r_train, r_test)
pearsons = []
for col in x.T:
pearsons.append(pearsonr(col, y)[0])
#and finally the correlations between y and yhat
y_pearson_train = pearsonr(y_train, y_repeat)[0]
y_pearson_test = pearsonr(y_test, y_hat)[0]
report += "pearsonCorr y/y_hat train:%.4g , test:%.4g <br>" % (
y_pearson_train, y_pearson_test)
report += "regression coefficients, pearsons correlations:<br>"
for col, coef, pear in zip(columnNames, reg.coef_, pearsons):
report += "    %s:%.4g,   %.4g <br>" % (col, coef, pear)
#write report
progressNode.set_value(0.8)
report += "<div>" #close the style div
functionNode.get_child("report").set_value(report)
#make a plot
hover1 = HoverTool(tooltips=[('x,y', '$x,$y')], mode='mouse')
hover1.point_policy = 'snap_to_data'
hover1.line_policy = "nearest"
tools = [
PanTool(),
WheelZoomTool(),
BoxZoomTool(),
ResetTool(),
SaveTool(), hover1
]
title = "prediction results on " + functionNode.get_child(
"selectedAlgorithm").get_value()
fig = figure(title=title, tools=tools, plot_height=400, plot_width=500)
fig.toolbar.logo = None
curdoc().theme = Theme(json=themes.darkTheme)
fig.xaxis.major_label_text_color = themes.darkTickColor
fig.yaxis.major_label_text_color = themes.darkTickColor
fig.xaxis.axis_label = target.get_name()
fig.xaxis.axis_label_text_color = "white"
fig.yaxis.axis_label = "predicted Values for " + target.get_name()
fig.yaxis.axis_label_text_color = "white"
fig.circle(y_train,
y_repeat,
size=4,
line_color="white",
fill_color="white",
name="train",
legend_label="train")
fig.circle(y_test,
y_hat,
line_color="#d9b100",
fill_color="#d9b100",
size=4,
name="test",
legend_label="test")
fileName = functionNode.get_child("outputFileName").get_value()
filePath = os.path.join(myDir, './../web/customui/' + fileName)
fig.legend.location = "top_left"
output_file(filePath, mode="inline")
save(fig)
return True
def worker_table_plot(**kwargs):
""" Column data source and plot for host table """
with log_errors():
# names = ['host', 'cpu', 'memory_percent', 'memory', 'cores', 'processes',
# 'processing', 'latency', 'last-seen', 'disk-read', 'disk-write',
# 'network-send', 'network-recv']
names = [
'processes', 'disk-read', 'cores', 'cpu', 'disk-write', 'memory',
'last-seen', 'memory_percent', 'host'
]
source = ColumnDataSource({k: [] for k in names})
columns = {
name: TableColumn(field=name, title=name.replace('_percent', ' %'))
for name in names
}
cnames = [
'host', 'cores', 'processes', 'memory', 'cpu', 'memory_percent'
]
formatters = {
'cpu': NumberFormatter(format='0.0 %'),
'memory_percent': NumberFormatter(format='0.0 %'),
'memory': NumberFormatter(format='0 b'),
'latency': NumberFormatter(format='0.00000'),
'last-seen': NumberFormatter(format='0.000'),
'disk-read': NumberFormatter(format='0 b'),
'disk-write': NumberFormatter(format='0 b'),
'net-send': NumberFormatter(format='0 b'),
'net-recv': NumberFormatter(format='0 b')
}
table = DataTable(source=source,
columns=[columns[n] for n in cnames],
**kwargs)
for name in cnames:
if name in formatters:
table.columns[cnames.index(name)].formatter = formatters[name]
x_range = Range1d(0, 1)
y_range = Range1d(-.1, .1)
mem_plot = figure(title="Memory Usage (%)",
tools='box_select',
height=90,
width=600,
x_range=x_range,
y_range=y_range,
toolbar_location=None)
mem_plot.circle(source=source,
x='memory_percent',
y=0,
size=10,
alpha=0.5)
mem_plot.yaxis.visible = False
mem_plot.xaxis.minor_tick_line_width = 0
mem_plot.ygrid.visible = False
mem_plot.xaxis.minor_tick_line_alpha = 0
hover = HoverTool()
mem_plot.add_tools(hover)
hover = mem_plot.select(HoverTool)
hover.tooltips = """
<div>
<span style="font-size: 10px; font-family: Monaco, monospace;">@host: </span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory_percent</span>
</div>
"""
hover.point_policy = 'follow_mouse'
return source, [mem_plot, table]
# instantiate shared generic plot settings
# hover tool
hoverm = HoverTool(tooltips=[
("Age", "(@Age)"),
("Incidents", "(@Males{0,0.000})"),
],
mode='vline')
hoverf = HoverTool(tooltips=[
("Age", "(@Age)"),
("Incidents", "(@Females{0,0.000})"),
],
mode='hline')
hoverm.point_policy = 'snap_to_data'
hoverm.line_policy = 'nearest'
# graph tool bar
toolsm = ["box_select", hoverm, "reset"]
toolsf = ["box_select", hoverf, "reset"]
#create the main plot
def create_figure(*args):
#create new plot with sizing & labels
mplot = figure(x_range=label,
plot_width=900,
plot_height=400,
tools=toolsm,
title="Cancer Incidents in Males 2016")
def map(self, func, x=None, y=None, tooltips=[], rotate=0, **kwargs):
is_new = (len(self.plots) == 0)
if not isinstance(x, list):
x = [x]
if self.hue is not None:
x += [self.hue]
self.update_cmap(self.data)
self.data['color'] = [
self.cmap[lvl] for lvl in self.data[self.hue]
]
kwargs['fill_color'] = 'color'
kwargs['hue_order'] = self.ordering['hue']
(factor_combs, factor_values) = self.get_row_col_combs()
for i, pair in enumerate(factor_combs):
data = self.data.loc[(factor_values == pair)].copy()
if data.size == 0:
self.plots.append(None)
continue
prev_plot = None
if not is_new: prev_plot = self.plots[i]
if self.hue is not None:
tooltips = np.append(tooltips, self.hue)
if is_new:
kwargs['legend_field'] = self.hue
x = [xi for xi in x if xi is not None]
if len(x) == 1 and 'legend_field' in kwargs:
kwargs.pop('legend_field')
p = func(x=x,
y=y,
data=data,
p=prev_plot,
width=self.width,
height=self.height,
name=func.__name__,
**kwargs)
if rotate != 0:
p.xaxis.major_label_orientation = rotate
tooltips_fmt = pd.Series(tooltips,
dtype='object').drop_duplicates()
tooltips_fmt = list(zip(tooltips_fmt, '@' + tooltips_fmt))
hover_tool = HoverTool(tooltips=tooltips_fmt,
names=[func.__name__])
hover_tool.point_policy = 'snap_to_data'
p.add_tools(hover_tool)
# Add facet info in subtitle
if is_new and pair != True:
subtitle = Title(text=', '.join(
'{}: {}'.format(*it)
for it in zip(factor_combs.names, pair)),
text_font_size=CFG['subtitle_fs'],
text_font_style="italic")
p.add_layout(subtitle, 'above')
# Format legend and put in outside the plot area
if 'legend_field' in kwargs:
legends = format_legend(p)
p.legend.items.clear()
for legend in legends:
p.add_layout(legend, 'right')
if len(self.plots) < len(factor_combs):
self.plots.append(p)
test_list = []
x_range = []
# for level in range (1,7):
# search_str_list.append ("LTE.*RSSI Level " + str(level))
#
# print (search_str_list)
hover = HoverTool(tooltips=[
("index", "$index"),
("Power", "@y"),
("desc", "@desc"),
],
names=["foo"],
mode='vline')
hover.point_policy = "snap_to_data"
hover.line_policy = "nearest"
p = figure(
plot_width=800,
plot_height=800,
title="LTE RSSI",
tools=[hover,
BoxZoomTool(),
ResetTool(),
PanTool(),
BoxSelectTool()])
for row in reader:
if row['Product'] == "Upper Limits----->":
for field in search_fieldlist:
def plot_classification_probabilities(
x,
y,
cv_results,
output_html=None,
width=500,
height=500,
sizing_mode="stretch_both",
):
"""Plot the classification probabilities for each cross-validation split
Parameters
----------
x : numpy.ndarray
The original feature matrix
y : numpy.ndarray
The target array (i.e. "ground truth")
cv_results : list of SGLResult namedtuples
Results of each cross-validation split
output_html : string or None, default=None
Filename for bokeh html output. If None, figure will not be saved
width : int, default=500
Width of each beta plot (in pixels)
height : int, default=500
Height of each beta plot (in pixels)
sizing_mode : string
One of ("fixed", "stretch_both", "scale_width", "scale_height",
"scale_both"). Specifies how will the items in the layout resize to
fill the available space. Default is "stretch_both". For more
information on the different modes see
https://bokeh.pydata.org/en/latest/docs/reference/models/layouts.html#bokeh.models.layouts.LayoutDOM
"""
p = figure(plot_width=width, plot_height=height, toolbar_location="above")
p.title.text = "Classification probabilities for each CV split"
p.add_layout(
Title(
text="Click on legend entries to hide/show corresponding lines",
align="left",
),
"right",
)
names = ["cv_idx = {i:d}".format(i=i) for i in range(len(cv_results))]
hover = HoverTool(tooltips=[("Subject", "$index")], mode="vline")
hover.point_policy = "snap_to_data"
hover.line_policy = "nearest"
for res, color, name in zip(cv_results, Spectral10, names):
p.line(
np.arange(len(y)),
_sigmoid(x.dot(res.beta_hat)),
line_width=2,
color=color,
alpha=0.8,
legend=name,
)
p.line(np.arange(len(y)), y, line_width=3, alpha=0.8, legend="ground truth")
p.line(
np.arange(len(y)),
0.5 * np.ones(len(y)),
line_width=2,
line_dash="dashed",
alpha=0.8,
legend="threshold",
)
p.add_tools(hover)
p.legend.location = "top_right"
p.legend.click_policy = "hide"
p.xaxis.axis_label = "Subject ID"
p.xaxis.major_tick_line_color = None # turn off x-axis major ticks
p.xaxis.minor_tick_line_color = None # turn off x-axis minor ticks
p.xaxis.major_label_text_font_size = "0pt" # turn off x-axis tick labels
p.yaxis.axis_label = "Classification Probability"
p.sizing_mode = sizing_mode
if output_html is not None:
html = file_html(p, CDN, "my plot")
with open(op.abspath(output_html), "w") as fp:
fp.write(html)
else:
show(p)
def bokehTile(tileFile,
jsonFile,
TT=[0, 0, 0],
DD=[2019, 10, 1],
dynamic=False,
plotTitle=''):
citls, h = fitsio.read(tileFile, header=True)
w = (np.where(citls['IN_DESI'] == 1)[0])
inci = citls[w]
if jsonFile is not None:
with open(jsonFile, "r") as read_file:
data = json.load(read_file)
## Coloring scheme
palette = ['green', 'red', 'white']
dye = []
for tile in citls['TILEID']:
rang = 2 # 'orange'
if jsonFile is not None:
if str(tile) in data:
rang = 0 # 'green' #green default
if len(data[str(tile)]
['unassigned']) > 0: # not assigned (red)
rang = 1 # 'red' #'red'
if (0 in data[str(tile)]['gfa_stars_percam']):
print(data[str(tile)]['gfa_stars_percam'])
rang = 1 # 'cyan'
else:
rang = 0 # green if qa.json is not provided
dye.append(rang)
dye = np.asarray(dye)
w = (np.where(dye < 2)[0])
citls = citls[w]
dye = dye[w]
mapper = linear_cmap(field_name='DYE', palette=palette, low=0, high=2)
#########################################################
TOOLS = [
'pan', 'tap', 'wheel_zoom', 'box_zoom', 'reset', 'save', 'box_select'
]
obsTime = dt(DD[0], DD[1], DD[2], TT[0], TT[1], TT[2])
# print(get_kp_twilights(TT,DD))
if plotTitle == '' or plotTitle is None:
PTITLE = ''
else:
PTITLE = 'Program: ' + plotTitle
p = figure(tools=TOOLS,
toolbar_location="right",
plot_width=800,
plot_height=450,
title=PTITLE,
active_drag='box_select') # str(DD[1])+" - 2019")
p.title.text_font_size = '16pt'
p.title.text_color = 'black'
p.grid.grid_line_color = "gainsboro"
############################### adding ecliptic plane+ hour grid ####################3
add_plane(p, color='red', plane='ecliptic', projection='equatorial')
tiledata = dict(
RA=citls['RA'],
DEC=citls['DEC'],
TILEID=citls['TILEID'],
BRIGHTRA=citls['BRIGHTRA'][:, 0],
BRIGHTDEC=citls['BRIGHTDEC'][:, 0],
BRIGHTVTMAG=citls['BRIGHTVTMAG'][:, 0],
EBV_MED=np.round(citls['EBV_MED'], 3),
STAR_DENSITY=citls['STAR_DENSITY'],
DYE=dye,
program=citls['PROGRAM'],
selected=np.ones(len(citls), dtype=bool),
)
for colname in ['STAR_DENSITY', 'EBV_MED']:
if colname in citls.dtype.names:
tiledata[colname] = citls[colname]
tiles = ColumnDataSource(data=tiledata)
colformat = bktables.NumberFormatter(format='0,0.00')
columns = [
bktables.TableColumn(field='TILEID', title='TILEID', width=80),
bktables.TableColumn(field='RA', title='RA', formatter=colformat),
bktables.TableColumn(field='DEC', title='DEC', formatter=colformat),
]
for colname in ['STAR_DENSITY', 'EBV_MED']:
if colname in tiledata:
columns.append(
bktables.TableColumn(field=colname,
title=colname,
formatter=colformat))
columns.append(bktables.TableColumn(field='selected', title='Selected'))
tiletable = bktables.DataTable(columns=columns, source=tiles, width=800)
tiles.selected.js_on_change(
'indices',
CustomJS(args=dict(s1=tiles),
code="""
var inds = cb_obj.indices;
var d1 = s1.data;
for (var i=0; i<d1['selected'].length; i++) {
d1['selected'][i] = false;
}
for (var i = 0; i < inds.length; i++) {
d1['selected'][inds[i]] = true;
}
s1.change.emit();
"""))
render = p.circle(
'RA',
'DEC',
source=tiles,
size=9,
line_color='chocolate',
color=mapper,
alpha=0.4,
hover_color='orange',
hover_alpha=1,
hover_line_color='red',
# set visual properties for selected glyphs
selection_fill_color='orange',
selection_line_color='white',
# set visual properties for non-selected glyphs
nonselection_fill_alpha=0.4,
nonselection_fill_color=mapper)
p.xaxis.axis_label = 'RA [deg]'
p.yaxis.axis_label = 'Dec. [deg]'
p.xaxis.axis_label_text_font_size = "14pt"
p.yaxis.axis_label_text_font_size = "14pt"
p.grid.grid_line_color = "gainsboro"
p.yaxis.major_label_text_font_size = "12pt"
p.xaxis.major_label_text_font_size = "12pt"
p.x_range = Range1d(360, 0)
p.y_range = Range1d(-40, 95)
p.toolbar.logo = None
p.toolbar_location = None
# mytext = Label(x=180, y=-35, text="S", text_color='gray', text_font_size='12pt') ; p.add_layout(mytext)
# mytext = Label(x=180, y=88, text="N", text_color='gray', text_font_size='12pt') ; p.add_layout(mytext)
# mytext = Label(x=350, y=45, text="E", text_color='gray', text_font_size='12pt', angle=np.pi/2) ; p.add_layout(mytext)
# mytext = Label(x=4, y=45, text="W", text_color='gray', text_font_size='12pt', angle=np.pi/2) ; p.add_layout(mytext)
## Javascript code to open up custom html pages, once user click on a tile
code = """
var index_selected = source.selected['1d']['indices'][0];
var tileID = source.data['TILEID'][index_selected];
if (tileID!==undefined) {
var win = window.open("http://www.astro.utah.edu/~u6022465/cmx/ALL_SKY/dr8/allSKY_ci_tiles/sub_pages/tile-"+tileID+".html", " ");
try {win.focus();} catch (e){} }
"""
taptool = p.select(type=TapTool)
taptool.callback = CustomJS(args=dict(source=tiles), code=code)
## The html code for the hover window that contain tile infrormation
ttp = """
<div>
<div>
<span style="font-size: 14px; color: blue;">Tile ID:</span>
<span style="font-size: 14px; font-weight: bold;">@TILEID{int}</span>
</div>
<div>
<span style="font-size: 14px; color: blue;">RA:</span>
<span style="font-size: 14px; font-weight: bold;">@RA</span>
</div>
<div>
<span style="font-size: 14px; color: blue;">Dec:</span>
<span style="font-size: 14px; font-weight: bold;">@DEC</span>
</div>
<div>
<span style="font-size: 14px; color: blue;">EBV_MED:</span>
<span style="font-size: 14px; font-weight: bold;">@EBV_MED{0.000}</span>
</div>
<div>
<span style="font-size: 14px; color: blue;">STAR_DENSITY:</span>
<span style="font-size: 14px; font-weight: bold;">@STAR_DENSITY{0}</span>
</div>
<div>
<span style="font-size: 14px; color: blue;">BRIGHTEST_STAR_VTMAG:</span>
<span style="font-size: 14px; font-weight: bold;">@BRIGHTVTMAG</span>
</div>
<div>
<span style="font-size: 14px; color: blue;">BRIGHTEST_STAR_LOC:</span>
<span style="font-size: 14px; font-weight: bold;">(@BRIGHTRA, @BRIGHTDEC)</span>
</div>
</div>
"""
hover = HoverTool(tooltips=ttp, renderers=[render])
hover.point_policy = 'snap_to_data'
hover.line_policy = 'nearest'
# hover.mode='vline'
p.add_tools(hover)
cross = CrosshairTool()
# cross.dimensions='height'
cross.line_alpha = 0.3
cross.line_color = 'gray'
p.add_tools(cross)
# Setting the second y axis range name and range
p.extra_y_ranges = {"foo": p.y_range}
p.extra_x_ranges = {"joo": p.x_range}
# Adding the second axis to the plot.
p.add_layout(LinearAxis(y_range_name="foo"), 'right')
p.add_layout(LinearAxis(x_range_name="joo"), 'above')
p.xaxis.major_label_text_font_size = "12pt"
p.yaxis.major_label_text_font_size = "12pt"
if dynamic:
# twilight_source = get_kp_twilights(TT,DD) # evening and morning twilights at every TT and DD
circleSource_1 = skyCircle(TT, DD, 1.5)
p.circle('RA', 'DEC', source=circleSource_1, size=1.5, color='black')
circleSource_2 = skyCircle(TT, DD, 2.0)
p.circle('RA', 'DEC', source=circleSource_2, size=0.5, color='gray')
else:
circleSource = skyCircle(TT, DD, 1.5)
p.circle('RA', 'DEC', source=circleSource, size=1.5, color=None)
### Dealing with the Moon and Jupiter
inFile = 'moonLoc_jupLoc_fracPhase.csv' # 'moon_loc_jup_loc_fracPhase_namePhase.csv'
tbl_moon_jup = np.genfromtxt(inFile,
delimiter=',',
filling_values=-1,
names=True,
dtype=None) # , dtype=np.float)
loc = EarthLocation.of_site('Kitt Peak')
kp_lat = 31, 57, 48
kp_lon = -111, 36, 00
mooninfo_obj = pylunar.MoonInfo((kp_lat), (kp_lon))
m_ra, m_dec, frac_phase, name_phase = moonLoc(TT, DD, loc, mooninfo_obj)
j_ra, j_dec = jupLoc(TT, DD, loc)
#moonSource = ColumnDataSource({"moon_RAS": tbl_moon_jup['moon_ra'], "moon_DECS": tbl_moon_jup['moon_dec'],
# "Phase_frac": tbl_moon_jup['moon_phase_frac']})
moonSource = ColumnDataSource({
"moon_RAS":
tbl_moon_jup['moon_ra'],
"moon_DECS":
tbl_moon_jup['moon_dec'],
"Phase_frac":
np.round(100 * tbl_moon_jup['moon_phase_frac'])
})
####moon_RADEC = ColumnDataSource({"moon_ra": [m_ra.deg], "moon_dec": [m_dec.deg], "phase_frac": [frac_phase]})
moon_RADEC_ = ColumnDataSource({
"moon_ra": [m_ra.deg - 360],
"moon_dec": [m_dec.deg],
"phase_frac": [frac_phase]
})
moon_RADEC = ColumnDataSource({
"moon_ra": [m_ra.deg],
"moon_dec": [m_dec.deg],
"phase_frac": [frac_phase]
})
render_moon = p.circle('moon_ra',
'moon_dec',
source=moon_RADEC,
size=170,
color='cyan',
alpha=0.2)
render_moon = p.circle('moon_ra',
'moon_dec',
source=moon_RADEC,
size=4,
color='blue')
render_moon = p.circle('moon_ra',
'moon_dec',
source=moon_RADEC_,
size=170,
color='cyan',
alpha=0.2)
render_moon = p.circle('moon_ra',
'moon_dec',
source=moon_RADEC_,
size=4,
color='blue')
jupSource = ColumnDataSource({
"jup_RAS": tbl_moon_jup['jup_ra'],
"jup_DECS": tbl_moon_jup['jup_dec']
})
jup_RADEC = ColumnDataSource({
"jup_ra": [j_ra.deg],
"jup_dec": [j_dec.deg]
})
twilight = get_kp_twilights(
TT, DD) # evening and morning twilights at every TT and DD
twilight_source = ColumnDataSource({
"eve_twilight": [twilight[0]],
"mor_twilight": [twilight[1]]
})
render_jup = p.circle('jup_ra',
'jup_dec',
source=jup_RADEC,
size=5,
color='blue')
render_jup = p.circle('jup_ra',
'jup_dec',
source=jup_RADEC,
size=4,
color='gold')
from bokeh.models.glyphs import Text
TXTsrc = ColumnDataSource(
dict(x=[350],
y=[85],
text=['Moon Phase: ' + "%.0f" % (frac_phase * 100) + "%"]))
glyph = Text(x="x", y="y", text="text", angle=0, text_color="black")
p.add_glyph(TXTsrc, glyph)
TXTsrc_moon = ColumnDataSource(
dict(x=[m_ra.deg + 10], y=[m_dec.deg - 10], text=['Moon']))
glyph = Text(x="x",
y="y",
text="text",
angle=0,
text_color="blue",
text_alpha=0.3,
text_font_size='10pt')
p.add_glyph(TXTsrc_moon, glyph)
TXTsrc_jup = ColumnDataSource(
dict(x=[j_ra.deg + 5], y=[j_dec.deg - 8], text=['Jup.']))
glyph = Text(x="x",
y="y",
text="text",
angle=0,
text_color="black",
text_alpha=0.3,
text_font_size='10pt')
p.add_glyph(TXTsrc_jup, glyph)
callback = CustomJS(args=dict(source_sky1=circleSource_1,
source_sky2=circleSource_2,
source_moon=moonSource,
source_moon_RADEC=moon_RADEC,
source_moon_RADEC_=moon_RADEC_,
source_jup=jupSource,
source_jup_RADEC=jup_RADEC,
sourceTXT=TXTsrc,
sourceTXTmoon=TXTsrc_moon,
sourceTXTjup=TXTsrc_jup),
code="""
// First set times as if they were UTC
var t = new Date(time_slider.value);
var d = new Date(date_slider.value);
var data1 = source_sky1.data;
var ra_1 = data1['RA'];
var ra0_1 = data1['RA0'];
var data2 = source_sky2.data;
var ra_2 = data2['RA'];
var ra0_2 = data2['RA0'];
var data_moon = source_moon.data;
var ras_moon = data_moon['moon_RAS'];
var decs_moon = data_moon['moon_DECS'];
var phase_frac = data_moon['Phase_frac'];
var moonRADEC = source_moon_RADEC.data;
var moon_ra = moonRADEC['moon_ra'];
var moon_dec = moonRADEC['moon_dec'];
var moonRADEC_ = source_moon_RADEC_.data;
var moon_ra_ = moonRADEC_['moon_ra'];
var moon_dec_ = moonRADEC_['moon_dec'];
var data_jup = source_jup.data;
var ras_jup = data_jup['jup_RAS'];
var decs_jup = data_jup['jup_DECS'];
var jupRADEC = source_jup_RADEC.data;
var jup_ra = jupRADEC['jup_ra'];
var jup_dec = jupRADEC['jup_dec'];
var Hour = t.getUTCHours();
var Day = d.getDate();
var Month = d.getMonth();
var Year = new Array(31,28,31,30,31,30,31,31,30,31,30,31);
var all_FULdays = 0;
for (var i = 0; i < Month; i++)
all_FULdays=all_FULdays+Year[i];
all_FULdays = all_FULdays + (Day-1);
if (Hour<12) all_FULdays=all_FULdays+1;
var all_minutes = all_FULdays*24+Hour;
if (all_minutes<8800) {
moon_ra[0] = ras_moon[all_minutes];
moon_dec[0] = decs_moon[all_minutes];
moon_ra_[0] = ras_moon[all_minutes]-360.;
moon_dec_[0] = decs_moon[all_minutes];
}
var jupTXTdata = sourceTXTjup.data;
var x_jup = jupTXTdata['x'];
var y_jup = jupTXTdata['y'];
var text_jup = jupTXTdata['text'];
if (all_minutes<8800) {
jup_ra[0] = ras_jup[all_minutes];
jup_dec[0] = decs_jup[all_minutes];
x_jup[0] = jup_ra[0]+5;
y_jup[0] = jup_dec[0]-8;
}
if (t.getUTCHours() < 12) {
d.setTime(date_slider.value + 24*3600*1000);
} else {
d.setTime(date_slider.value);
}
d.setUTCHours(t.getUTCHours());
d.setUTCMinutes(t.getUTCMinutes());
d.setUTCSeconds(0);
// Correct to KPNO local time
// d object still thinks in UTC, which is 7 hours ahead of KPNO
d.setTime(d.getTime() + 7*3600*1000);
// noon UT on 2000-01-01
var reftime = new Date();
reftime.setUTCFullYear(2000);
reftime.setUTCMonth(0); // Months are 0-11 (!)
reftime.setUTCDate(1); // Days are 1-31 (!)
reftime.setUTCHours(12);
reftime.setUTCMinutes(0);
reftime.setUTCSeconds(0);
// time difference in days (starting from milliseconds)
var dt = (d.getTime() - reftime.getTime()) / (24*3600*1000);
// Convert to LST
var mayall_longitude_degrees = -(111 + 35/60. + 59.6/3600);
var LST_hours = ((18.697374558 + 24.06570982441908 * dt) + mayall_longitude_degrees/15) % 24;
var LST_degrees = LST_hours * 15;
for (var i = 0; i < ra_1.length; i++) {
ra_1[i] = (ra0_1[i] + LST_degrees) % 360;
}
for (var i = 0; i < ra_2.length; i++) {
ra_2[i] = (ra0_2[i] + LST_degrees) % 360;
}
//// Here we gtake care of the moon phasde text
var TXTdata = sourceTXT.data;
var x = TXTdata['x'];
var y = TXTdata['y'];
var text = TXTdata['text'];
var moonTXTdata = sourceTXTmoon.data;
var x_moon = moonTXTdata['x'];
var y_moon = moonTXTdata['y'];
var text_moon = moonTXTdata['text'];
// x[0] = 1;
// y[0] = 40;
if (all_minutes<8800) {
text[0] = 'Moon Phase: ' + phase_frac[all_minutes]+'%';
x_moon[0] = moon_ra[0]+10;
y_moon[0] = moon_dec[0]-10;
}
sourceTXT.change.emit();
/////////////////////////////// Moon phase code ends.
source_sky1.change.emit();
source_sky2.change.emit();
//source_moon_RADEC.change.emit();
//source_moon_RADEC_.change.emit();
//source_jup_RADEC.change.emit();
sourceTXTmoon.change.emit();
sourceTXTjup.change.emit();
//alert(d);
""")
if dynamic:
### TIME
Timeslider = DateSlider(start=dt(2019, 9, 1, 16, 0, 0),
end=dt(2019, 9, 2, 8, 0, 0),
value=dt(2019, 9, 1, 16, 0, 0),
step=1,
title="KPNO local time(hh:mm)",
format="%H:%M",
width=800)
## DATE
Dateslider = DateSlider(start=dt(2019, 9, 1, 16, 0, 0),
end=dt(2020, 8, 31, 8, 0, 0),
value=dt(2019, 10, 1, 16, 0, 0),
step=1,
title="Date of sunset(4pm-8am)",
format="%B:%d",
width=800)
callback.args['time_slider'] = Timeslider
callback.args['date_slider'] = Dateslider
Dateslider.js_on_change('value', callback)
Timeslider.js_on_change('value', callback)
layout = column(p, Dateslider, Timeslider, tiletable)
# show(p)
return layout
return p
def plot_model(
model,
x_column,
y_column=None,
fig=None,
x_slider=None,
y_slider=None,
show_expt_data=True,
figsize=(10, 10),
dpi=100,
**kwargs,
):
"""
Plots a `model` object with a given model input as `x_column` against
the model's output: `y_column`. If `y_column` is not specified, then it
found from the `model`.
For model's with more than 1 inputs, the `y_column` is the variable to be
plotted on the y-axis, and then the plot type is a contour plot.
"""
pure_factors = model.get_factor_names(level=1)
dpi_max = dpi**3.5 # should be reasonable for most modern computers
per_axis_points = min(dpi, np.power(dpi_max, 1 / len(pure_factors)))
# `oneD=True`: the x-variable is a model input, and the y-axis is a response
oneD = False
if y_column and y_column not in pure_factors:
oneD = True
y_column = model.get_response_name()
param_names = [
model.get_response_name(),
]
param_names.extend(model.get_factor_names())
# Not always a great test: y = I(1/d) does not pick up that "d" is the model
# even though it is via the term encapsulated in I(...)
# assert x_column in param_names, "x_column must exist in the model."
assert y_column in param_names, "y_column must exist in the model."
xrange = model.data[x_column].min(), model.data[x_column].max()
xdelta = xrange[1] - xrange[0]
xlim = kwargs.get("xlim",
(xrange[0] - xdelta * 0.05, xrange[1] + xdelta * 0.05))
h_grid = np.linspace(xlim[0], xlim[1], num=per_axis_points)
plotdata = {x_column: h_grid}
if not oneD:
yrange = model.data[y_column].min(), model.data[y_column].max()
ydelta = yrange[1] - yrange[0]
ylim = kwargs.get(
"ylim", (yrange[0] - ydelta * 0.05, yrange[1] + ydelta * 0.05))
v_grid = np.linspace(ylim[0], ylim[1], num=per_axis_points)
H, V = np.meshgrid(h_grid, v_grid)
h_grid, v_grid = H.ravel(), V.ravel()
plotdata[x_column] = h_grid
plotdata[y_column] = v_grid
# TODO: handle the 2D case later
# if other_factors is not None and isinstance(other_factors, dict):
# plotdata = kwargs.update(other_factors)
## Look at which factors are included, and pop them out. The remaining
## factors are specified at their zero level
# unspecified_factors = [i for i in pure_factors if i not in kwargs.keys()]
# for factor in unspecified_factors:
# plotdata[factor] = np.zeros_like(h_grid)
# assert sorted(kwargs.keys()) == sorted(pure_factors), ("Not all factors "
# "were specified.")
Z = predict(model, **plotdata)
if not oneD:
assert False
else:
plotdata[y_column] = Z
yrange = Z.min(), Z.max()
ydelta = yrange[1] - yrange[0]
ylim = kwargs.get(
"ylim", (yrange[0] - ydelta * 0.05, yrange[1] + ydelta * 0.05))
if fig:
p = fig
prior_figure = True
else:
prior_figure = False
p = figure(
x_range=xlim,
y_range=ylim,
# https://github.com/bokeh/bokeh/issues/2351
tools="pan,wheel_zoom,box_zoom, box_select,lasso_select,reset,save",
)
h_line = p.line(
plotdata[x_column],
plotdata[y_column],
line_dash="solid",
color=kwargs.get("color", "black"),
line_width=kwargs.get("line_width", 2),
)
y_units = model.data.pi_units[y_column]
tooltips = [(x_column, "$x")]
if y_units:
tooltips.append((f"Prediction of {y_column} [{y_units}]", "$y"))
else:
tooltips.append((f"Prediction of {y_column}", "$y"))
tooltips.append(("Source", model.name or ""))
# custom tooltip for the predicted prediction line
h1 = HoverTool(tooltips=tooltips, renderers=[h_line])
h1.line_policy = "nearest"
if show_expt_data:
source = ColumnDataSource(data=dict(
x=model.data[x_column],
y=model.data[y_column],
output=model.data[model.get_response_name()].to_list(),
))
h_expts = p.circle(
x="x",
y="y",
color="black",
source=source,
size=10,
line_width=2,
name="Experimental_points",
)
h2 = HoverTool(
tooltips=[
(x_column, "$x"),
(y_column, "$y"),
("Experimental value", "@output"),
],
renderers=[h_expts],
)
h2.point_policy = "snap_to_data"
h2.line_policy = "none"
# Axis labels:
p.xaxis.axis_label_text_font_size = "14pt"
p.xaxis.axis_label = x_column
p.xaxis.major_label_text_font_size = "14pt"
p.xaxis.axis_label_text_font_style = "bold"
p.yaxis.major_label_text_font_size = "14pt"
p.yaxis.axis_label = y_column
p.yaxis.axis_label_text_font_size = "14pt"
p.yaxis.axis_label_text_font_style = "bold"
if prior_figure:
# p.xaxis.bounds =
p.x_range = Range1d(
min(xlim[0], p.x_range.start, min(model.data[x_column])),
max(xlim[1], p.x_range.end, max(model.data[x_column])),
)
p.y_range = Range1d(
min(ylim[0], p.y_range.start, min(model.data[y_column])),
max(ylim[1], p.y_range.end, max(model.data[y_column])),
)
else:
p.x_range = Range1d(xlim[0], xlim[1])
p.y_range = Range1d(ylim[0], ylim[1])
# Add the hover tooltips:
p.add_tools(h1)
p.add_tools(h2)
show_plot(p)
return p
source_rc = ColumnDataSource(data=dict(x=x, y=y6))
source_im = ColumnDataSource(data=dict(x=x, y=y7))
source_na = ColumnDataSource(data=dict(x=x, y=y8))
source_ra = ColumnDataSource(data=dict(x=x, y=y9))
source_da = ColumnDataSource(data=dict(x=x, y=y10))
source_ic = ColumnDataSource(data=dict(x=x, y=y11))
source_pr = ColumnDataSource(data=dict(x=x, y=y12))
# Incidence vs Rt
source_phase_space = ColumnDataSource(data=dict(x=y5, y=y11))
# plot 1
hover = HoverTool(tooltips=[(PLOT_X_LABEL, "@x{0}"), (PLOT_Y_LABEL, "@y{0}")],
mode="vline")
hover.point_policy = 'snap_to_data'
hover.line_policy = 'nearest'
plot = figure(
plot_height=PLOT_HEIGHT,
plot_width=PLOT_WIDTH,
title=PLOT_TITLE,
tools=PLOT_TOOLS,
x_range=[0, DAYS],
)
plot.line('x',
'y',
source=source_active,
line_width=PLOT_LINE_WIDTH,
line_alpha=PLOT_LINE_ALPHA,
def __init__(self, scheduler, width=600, **kwargs):
with log_errors():
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource({
"memory": [1, 2],
"memory-half": [0.5, 1],
"memory_text": ["1B", "2B"],
"utilization": [1, 2],
"utilization-half": [0.5, 1],
"worker": ["a", "b"],
"gpu-index": [0, 0],
"y": [1, 2],
"escaped_worker": ["a", "b"],
})
memory = figure(title="GPU Memory",
tools="",
id="bk-gpu-memory-worker-plot",
width=int(width / 2),
name="gpu_memory_histogram",
**kwargs)
rect = memory.rect(
source=self.source,
x="memory-half",
y="y",
width="memory",
height=1,
color="#76B900",
)
rect.nonselection_glyph = None
utilization = figure(title="GPU Utilization",
tools="",
id="bk-gpu-utilization-worker-plot",
width=int(width / 2),
name="gpu_utilization_histogram",
**kwargs)
rect = utilization.rect(
source=self.source,
x="utilization-half",
y="y",
width="utilization",
height=1,
color="#76B900",
)
rect.nonselection_glyph = None
memory.axis[0].ticker = BasicTicker(mantissas=[1, 256, 512],
base=1024)
memory.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
memory.xaxis.major_label_orientation = -math.pi / 12
memory.x_range.start = 0
for fig in [memory, utilization]:
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
tap = TapTool(callback=OpenURL(
url="./info/worker/@escaped_worker.html"))
fig.add_tools(tap)
fig.toolbar.logo = None
fig.toolbar_location = None
fig.yaxis.visible = False
hover = HoverTool()
hover.tooltips = "@worker : @utilization %"
hover.point_policy = "follow_mouse"
utilization.add_tools(hover)
hover = HoverTool()
hover.tooltips = "@worker : @memory_text"
hover.point_policy = "follow_mouse"
memory.add_tools(hover)
self.memory_figure = memory
self.utilization_figure = utilization
self.utilization_figure.y_range = memory.y_range
self.utilization_figure.x_range.start = 0
self.utilization_figure.x_range.end = 100
color = loc_color,
rprice = price,
dis = distance,
addr = address,
restaurant = food,
cafe = cafes,
pub = pubs,
size = sqft,
)
)
circle = Circle(x = 'lon', y = 'lat', fill_color = 'color', size = 10, fill_alpha=0.6, line_color=None)
plot.add_glyph(source, circle)
# Hover
hover = HoverTool()
hover.point_policy = "follow_mouse"
hover.tooltips = [
("Address", "@addr"),
("Price per Room", "@rprice"),
("Distance to Campus", "@dis"),
("Food Quality", "@restaurant"),
("Number of cafes", "@cafe"),
("Number of pubs", "@pub"),
("Room size", "@size"),
]
tools = [PanTool(), WheelZoomTool(), hover]
plot.add_tools(*tools)
output_file("gmap_plot.html")
show(plot)
def plot_team_stat(comparison_stat, agg_func):
"""Creates figures with bars plots of teams stats.
:param comparison_stat: str. Statistic to plot.
:param agg_func: str. 'mean' or 'sum'.
:return: bokeh figures.
"""
map_agg_func = ('mean', 'sum')
data = create_data_source(comparison_stat, map_agg_func[agg_func])
source = ColumnDataSource(data=data)
teams = list(source.data['team'])
# Plot avg stat per game
p_1 = figure(x_range=FactorRange(factors=teams),
plot_height=400,
plot_width=700)
hover = HoverTool(tooltips=[('', '@{Total}')])
hover.point_policy = 'follow_mouse'
p_1.add_tools(hover)
p_1.vbar(x='team',
top='Total',
source=source,
width=0.4,
color=Spectral4[0])
p_1.x_range.range_padding = 0.05
p_1.xaxis.major_label_orientation = 1
p_1.xaxis.major_label_text_font_size = "10pt"
p_1.toolbar_location = None
# Plot breakdown by match result
p_2 = figure(x_range=FactorRange(factors=teams),
plot_height=400,
plot_width=700,
tools='hover',
tooltips='@$name',
title='Breakdown by Match Result')
w = p_2.vbar(x=dodge('team', -0.25, range=p_2.x_range),
top='w',
width=0.2,
source=source,
color=Spectral4[1],
name='w')
d = p_2.vbar(x=dodge('team', 0.0, range=p_2.x_range),
top='d',
width=0.2,
source=source,
color=Spectral4[2],
name='d')
l = p_2.vbar(x=dodge('team', 0.25, range=p_2.x_range),
top='l',
width=0.2,
source=source,
color=Spectral4[3],
name='l')
legend_it = [('Won', [w]), ('Drew', [d]), ('Lost', [l])]
legend = Legend(items=legend_it, location=(0, 155))
p_2.add_layout(legend, 'right')
p_2.title.text_font_size = '12pt'
p_2.x_range.range_padding = 0.05
p_2.xgrid.grid_line_color = None
p_2.xaxis.major_label_text_font_size = "10pt"
p_2.xaxis.major_label_orientation = 1
p_2.toolbar_location = None
return p_1, p_2