def alert(duration=2):
""" makes sound on client using javascript (works with remote server) """
framerate = 44100
freq=300
t = np.linspace(0,duration,framerate*duration)
data = np.sin(2*np.pi*freq*t)
d(Audio(data,rate=framerate, autoplay=True))
d(HTML("<style>audio{display:none}</style>"))
def alert():
""" makes sound on client using javascript (works with remote server) """
framerate = 44100
duration = .05
freq = 300
t = np.linspace(0, duration, framerate * duration)
data = np.sin(2 * np.pi * freq * t)
d(Audio(data, rate=framerate, autoplay=True))
def playSoundOnColab():
print("Colab plays sound")
# Create a sound
framerate = 44100
t = np.linspace(0,5,framerate*5)
data = np.sin(2*np.pi*220*t) + np.sin(2*np.pi*224*t)
# Generate a player for mono sound
d(Audio(data,rate=framerate, autoplay=True))
def alert():
""" makes sound using javascript
works on any os and on local notebook with remote kernel """
framerate = 44100
duration=.05
freq=300
t = np.linspace(0,duration,framerate*duration)
data = np.sin(2*np.pi*freq*t)
d(Audio(data,rate=framerate, autoplay=True))
# hide the audio control
d(HTML("<style>audio{display:none}</style>"))
def stable(*args, **kwargs):
""" survival table showing counts and %lived
args[0] is row target died/lived
args[1] is list of column variables
"""
# enable assign to args
args = list(args)
# if args[1] is single column then make it a list
if not isinstance(args[1], list):
args[1] = [args[1]]
title = ", ".join([col.name for col in args[1]])
d(HTML("<h4>%s</h4>"%title))
table = pd.crosstab(*args, **kwargs)
table.index = ["died", "lived"]
table.loc["rate"] = table.iloc[-1] / table.sum()
ftable = table.style.format("{:.0%}", subset=pd.IndexSlice["rate",:])
d(ftable)
def optimise(self, num_evals, target=None,
search_space=None, verbose=20,
metrics=["score"], **params):
""" optimises score returned from target
verbose
0=no output
10=score and charts on completion
20=score every iteration
"""
# set defaults
if not target:
target = self._target_crossval
if not search_space:
search_space = get_search_space(self.clf)
# optimize
o = Optuner()
runs = o.maximise(target, search_space, num_evals=num_evals,
verbose=verbose, **params)
best_run = runs.get_best()
best_params = runs.get_best_params()
self.clf.set_params(**best_params)
# report
if verbose >= 10:
clear_output()
# best run
best_params = ', '.join("{!s}={!r}".format(k,v)
for (k,v) in best_params.items())
print("Best model:\n%s\n%s"%(best_run["clf"], best_params))
print("CV=%s TT=%s"%(best_run["score"], self.score()))
# plots
for metric in metrics:
d(HTML("<h6>%s %s</>"%(best_run["clf"], metric)))
runs.plot(metric)
def wide():
""" makes notebook fill screen width """
d(HTML("<style>.container { width:100% !important; }</style>"))
def hide_audio():
""" hide the audio control """
d(HTML("<style>audio{display:none}</style>"))
def wide():
""" makes notebook fill screen width """
d(HTML("<style>.container { width:100% !important; }</style>"))
