def get_plottag(script_path):
""" Saves js in script_path and returns tag for embedding in html
"""
import numpy as np
import pandas as pd
import os
y_data = np.random.randn(100)
x_data = pd.date_range('31-Aug-2014', periods=len(y_data))
figure(x_axis_type='datetime',
tools='pan,wheel_zoom,box_zoom,reset,previewsave,crosshair',
name='test plot')
hold()
line(x_data, y_data,
line_color="#D95B43", line_width=4, alpha=0.7,
legend='random',
background_fill= '#cccccc')
circle(x_data, y_data,
color='red', fill_color=None, size=6,
legend='random')
curplot().title = 'Test Plot'
xaxis().axis_label='date'
yaxis().axis_label='some random numbers'
grid().grid_line_color='white'
grid().grid_line_alpha = 0.5
plotid = curplot()._id
script_path = os.path.join(script_path, plotid+'.js')
js, tag = autoload_static(curplot(), CDN, script_path=script_path)
with open(script_path, 'w') as f:
f.write(js)
return tag
def build_timeplot(data):
output_file('distribution.html', title='distribution')#, js="relative", css="relative")
x,y=[],[]
if len(data)>0:
x,y=zip(*[(k, data[k]) for k in sorted(data)])
line([pd.DatetimeIndex([dt])[0] for dt in x] , [int(yt) for yt in y],x_axis_type='datetime', tools="pan,zoom,resize", width=400,height=300, title = 'voorkomens')
xaxis()[0].axis_label = "Datum"
yaxis()[0].axis_label = "# artikels"
# Create an HTML snippet of our plot.
snippet = curplot().create_html_snippet(embed_base_url='/static/plots/', embed_save_loc=plotdir)
# Return the snippet we want to place in our page.
return snippet
def draw(self, x, y, z, title, func, **kwargs):
import bokeh.plotting as bk
#TODO: change colors if y is of list type
y = (y if type(y) == list else [y]) # wrap y to a list so that we can iterate
kwargs.update({ "outline_line_color":"black", #FIXME refactor
"plot_width":300,
"plot_height":300,
})
bk.hold(True)
for yi in y:
x_data, y_data = self[x], self[yi]
func(x=x_data,
y=y_data,
title=title,
**kwargs)
bk.hold(False)
ret = bk.curplot()
def _label(axis, field):
label = kwargs.get(axis + '_label', False)
if label:
self.properties.plot_properties.insert(field, {axis + '_label':label})
else:
label = self.properties.plot_properties.select(field, axis + '_label', "None")
return label
def _range(axis, field):
from bokeh.objects import Range1d
p_range_args = kwargs.get(axis + '_range', False)
if p_range_args:
self.properties.plot_properties.insert(field, {axis + '_range': p_range})
else:
p_range = self.properties.plot_properties.select(field, axis + '_range')
if not p_range:
return False
else:
return Range1d(start=p_range[0], end=p_range[1])
bk.xaxis().axis_label = _label('x', x)
if _range('x', x):
ret.x_range = _range('x', x)
bk.yaxis().axis_label = _label('y', y[0]) #TODO can this make sense for multiplots?
if _range('y', y[0]):
ret.y_range = _range('y', y[0])
return ret
def create_histogram(releases):
number_of_bidders_list = []
frequency_list = []
for number_of_bidders, corresponding_releases in get_releases_by_amount_of_bidders(releases).items():
number_of_bidders_list.append(number_of_bidders)
frequency_list.append(len(corresponding_releases))
zeros = [0]*len(frequency_list)
right = [x+1 for x in number_of_bidders_list]
histogram = quad(top=frequency_list, bottom=zeros, left=number_of_bidders_list, right=right)
histogram.title = "Frequency of releases vs. Number of Bidders"
xaxis()[0].axis_label = "Number of Bidders"
yaxis()[0].axis_label = "Frequency of Releases"
show()
def bokeh_kin(kin_env, m_signal, color='#DF4949', alpha=1.0, **kwargs):
m_vector = tools.to_vector(m_signal, kin_env.m_channels)
s_signal = kin_env._multiarm.forward_kin(m_vector)
xs, ys = [0.0], [0.0]
for i in range(kin_env.cfg.dim):
xs.append(s_signal['x{}'.format(i + 1)])
ys.append(s_signal['y{}'.format(i + 1)])
xs, ys = ys, xs # we swap x and y for a more symmetrical look
if isinstance(kin_env.cfg.lengths, numbers.Real):
total_length = kin_env.cfg.lengths * kin_env.cfg.dim
else:
total_length = sum(kin_env.cfg.lengths)
total_length += 0.0
kwargs = {
'plot_height': int(350 * 1.60),
'plot_width': int(350 * 1.60),
'x_range': [-1.0, 1.0],
'y_range': [-1.0, 1.0],
'line_color': color,
'line_alpha': alpha,
'fill_color': color,
'fill_alpha': alpha,
'title': ''
}
plotting.hold()
plotting.line(xs, ys, **kwargs)
plotting.grid().grid_line_color = None
plotting.xaxis().major_tick_in = 0
plotting.ygrid().grid_line_color = None
plotting.yaxis().major_tick_in = 0
plotting.circle(xs[:1], ys[:1], radius=0.015, **kwargs)
plotting.circle(xs[1:-1], ys[1:-1], radius=0.008, **kwargs)
plotting.circle(xs[-1:], ys[-1:], radius=0.01, color='red')
plotting.hold(False)
def bokeh_kin(kin_env, m_signal, color='#DF4949', alpha=1.0, **kwargs):
m_vector = tools.to_vector(m_signal, kin_env.m_channels)
s_signal = kin_env._multiarm.forward_kin(m_vector)
xs, ys = [0.0], [0.0]
for i in range(kin_env.cfg.dim):
xs.append(s_signal['x{}'.format(i+1)])
ys.append(s_signal['y{}'.format(i+1)])
xs, ys = ys, xs # we swap x and y for a more symmetrical look
if isinstance(kin_env.cfg.lengths, numbers.Real):
total_length = kin_env.cfg.lengths*kin_env.cfg.dim
else:
total_length = sum(kin_env.cfg.lengths)
total_length += 0.0
kwargs ={'plot_height' : int(350*1.60),
'plot_width' : int(350*1.60),
'x_range' : [-1.0, 1.0],
'y_range' : [-1.0, 1.0],
'line_color' : color,
'line_alpha' : alpha,
'fill_color' : color,
'fill_alpha' : alpha,
'title':''
}
plotting.hold()
plotting.line(xs, ys, **kwargs)
plotting.grid().grid_line_color = None
plotting.xaxis().major_tick_in = 0
plotting.ygrid().grid_line_color = None
plotting.yaxis().major_tick_in = 0
plotting.circle(xs[ : 1], ys[ : 1], radius=0.015, **kwargs)
plotting.circle(xs[ 1:-1], ys[ 1:-1], radius=0.008, **kwargs)
plotting.circle(xs[-1: ], ys[-1: ], radius=0.01, color='red')
plotting.hold(False)
def create_scatter_plot(releases):
number_of_bidders = []
delta_time = []
for release in releases:
start = get_start_date(release)
award = get_award_date(release)
delta = get_difference_in_days(start, award)
delta_time.append(delta)
number_of_bidders.append(get_number_of_bidders(release))
scatter_plot = scatter(delta_time, number_of_bidders,
fill_alpha=0.2, size=10,
name="period between start of tender period and award date vs amount of bidders")
scatter_plot.title = "period vs. bidders"
xaxis()[0].axis_label = "Days"
yaxis()[0].axis_label = "Number of Bidders"
show()
def test_yaxis(self):
plt.figure()
p = plt.circle([1,2,3], [1,2,3])
self.assertEqual(len(plt.yaxis()), 1)
expected = set(plt.yaxis())
ax = LinearAxis()
expected.add(ax)
p.right.append(ax)
self.assertEqual(set(plt.yaxis()), expected)
ax2 = LinearAxis()
expected.add(ax2)
p.right.append(ax2)
self.assertEqual(set(plt.yaxis()), expected)
p.above.append(LinearAxis())
self.assertEqual(set(plt.yaxis()), expected)
p.below.append(LinearAxis())
self.assertEqual(set(plt.yaxis()), expected)
def test_yaxis(self):
plt.figure()
p = plt.circle([1,2,3], [1,2,3])
self.assertEqual(len(plt.yaxis()), 1)
expected = set(plt.yaxis())
ax = LinearAxis()
expected.add(ax)
p.right.append(ax)
self.assertEqual(set(plt.yaxis()), expected)
ax2 = LinearAxis()
expected.add(ax2)
p.right.append(ax2)
self.assertEqual(set(plt.yaxis()), expected)
p.above.append(LinearAxis())
self.assertEqual(set(plt.yaxis()), expected)
p.below.append(LinearAxis())
self.assertEqual(set(plt.yaxis()), expected)
import numpy as np
import bokeh.plotting as bk
from bokeh.objects import Glyph
import time
t = 0
time_x = np.array([0])
pres_y = np.array([20])
bk.output_server('Pressure')
bk.line(time_x, pres_y, color='#0000FF',
tools='pan,wheel_zoom,box_zoom,reset,resize,crosshair,select,previewsave,embed',
width=1200,height=300)
bk.xaxis()[0].axis_label = 'Time'
bk.yaxis()[0].axis_label = 'Pressure'
renderer = [r for r in bk.curplot().renderers if isinstance(r, Glyph)][0]
ds = renderer.data_source
while True:
ds.data["x"] = time_x
ds.data["y"] = pres_y
ds._dirty = True
bk.session().store_obj(ds)
time.sleep(1)
t = t + 1
time_x = np.append(time_x,
time_x[t-1]+1)
def plotting_axis():
plotting.xaxis().minor_tick_line_color = None
plotting.xaxis().major_tick_in = 0
plotting.yaxis().minor_tick_line_color = None
plotting.yaxis().major_tick_in = 0
def plotting_axis():
plotting.xaxis().minor_tick_line_color = None
plotting.xaxis().major_tick_in = 0
plotting.yaxis().minor_tick_line_color = None
plotting.yaxis().major_tick_in = 0
# text(x, y, text=inds, alpha=0.5, text_font_size="5pt", text_baseline="middle", text_align="center", angle=0)
### find hover tool, and tell it what to look for
hover = [t for t in bplt.curplot().tools if isinstance(t, HoverTool)][0]
hover.tooltips = OrderedDict([
#("index", "$index"),
("(x,y)", "($x, $y)"),
("stefilename", "@stefilename"),
("Nmodes","@Nmodes"),
("Ntriples","@Ntriples"),
("Ngens","@Ngens"),
])
### label axes
bplt.xaxis().axis_label=xlabel
bplt.yaxis().axis_label=ylabel
# bplt.show()
#=================================================
if opts.special_plots:
axes_loc = [0.15,0.15,0.6,0.8]
cb_loc = [0.8, 0.15, 0.05, 0.8]
### Ng1 vs Ng2
if opts.verbose: print "Ng1 vs Ng2"
Ng1 = []
Ng2 = []
cfg.lengths = 1/cfg.dim
cfg.full_sensors = True
kin_env = Environment.create(cfg)
# Arm with decreasing lenghts segments
cfg2 = cfg._deepcopy()
cfg2.lengths = np.array([0.9**i for i in range(cfg2.dim)])
#cfg2.lengths = np.array([random.random() for i in range(cfg2.dim)])
cfg2.lengths = cfg2.lengths/sum(cfg2.lengths)
kin_env2 = Environment.create(cfg2)
m_signals = [{'j0': -31.23, 'j1': -44.21, 'j2': -20.18, 'j3': +31.55, 'j4': +35.66, 'j5': +5.19, 'j6': +17.34, 'j7': +24.51, 'j8': -2.69, 'j9': +26.52, 'j10': -34.87, 'j11': +10.72, 'j12': -19.38, 'j13': -33.49, 'j14': +13.78, 'j15': -22.43, 'j16': +33.61, 'j17': -28.95, 'j18': +34.31, 'j19': 45.75},
{'j0': -53.66, 'j1': -56.20, 'j2': -56.67, 'j3': -34.83, 'j4': -20.29, 'j5': +7.51, 'j6': +20.92, 'j7': +25.51, 'j8': -17.59, 'j9': +6.51, 'j10': -9.65, 'j11': +45.70, 'j12': +20.88, 'j13': +24.25, 'j14': +28.65, 'j15': -42.79, 'j16': +34.45, 'j17': -39.90, 'j18': +2.74, 'j19': -11.12},
{'j0': +58.13, 'j1': +45.43, 'j2': -21.01, 'j3': +2.35, 'j4': -38.90, 'j5': -39.23, 'j6': +45.14, 'j7': -57.58, 'j8': +39.49, 'j9': +29.01, 'j10': -0.09, 'j11': -56.19, 'j12': +56.07, 'j13': +5.91, 'j14': +36.61, 'j15': -52.65, 'j16': -58.60, 'j17': +32.45, 'j18': +43.69, 'j19': -120.77},
{'j0': +53.09, 'j1': +55.83, 'j2': -51.08, 'j3': +41.44, 'j4': +44.43, 'j5': +4.67, 'j6': +2.15, 'j7': +37.23, 'j8': -3.77, 'j9': -46.70, 'j10': +56.41, 'j11': -21.08, 'j12': +13.73, 'j13': +47.23, 'j14': +7.94, 'j15': -27.26, 'j16': +56.54, 'j17': -7.77, 'j18': -18.98, 'j19': +149.46}]
plotting.output_file('arm_vizu.html')
for i, m_signal in enumerate(m_signals):
bokeh_kin(kin_env, m_signal, alpha=0.2 + i*0.15)
plotting.hold(True)
bokeh_kin(kin_env2, m_signal, color='#91C46C', alpha=0.2 + i*0.15)
plotting.hold(True)
plotting.xaxis().minor_tick_line_color = None
plotting.xaxis().major_tick_in = 0
plotting.yaxis().minor_tick_line_color = None
plotting.yaxis().major_tick_in = 0
plotting.show()
t = 0
time_x = np.array([0])
pres_y = np.array([20])
bk.output_server('Pressure')
bk.line(
time_x,
pres_y,
color='#0000FF',
tools=
'pan,wheel_zoom,box_zoom,reset,resize,crosshair,select,previewsave,embed',
width=1200,
height=300)
bk.xaxis()[0].axis_label = 'Time'
bk.yaxis()[0].axis_label = 'Pressure'
renderer = [r for r in bk.curplot().renderers if isinstance(r, Glyph)][0]
ds = renderer.data_source
while True:
ds.data["x"] = time_x
ds.data["y"] = pres_y
ds._dirty = True
bk.session().store_obj(ds)
time.sleep(1)
t = t + 1
time_x = np.append(time_x, time_x[t - 1] + 1)
pres_y = np.append(