def distributionPlot(mode, median, maximum, color):
"""
Plot data from a randomly generated LogNornal distribution.
@param mode: distribution mode
@type mode: L{float}
@param median: distribution median
@type median: L{float}
@param maximum: highest x-value to allow
@type maximum: L{float}
@param color: color to use for line in plot
@type color: L{str}
"""
distribution = LogNormalDistribution(mode=mode,
median=median,
maximum=maximum)
result = defaultdict(int)
for _ignore in range(1000000):
s = int(distribution.sample()) + 0.5
result[s] += 1
x, y = zip(*sorted(result.items()))
plt.plot(x, y, color=color)
peak_y = LogNormal.fn(distribution._scale, distribution._mu,
distribution._sigma, distribution._scale, 1.0)
scale_y = sum(sorted(y, reverse=True)[0:100]) / 100.0 / peak_y
return (
x,
y,
LogNormal.Params(distribution._mu, distribution._sigma,
distribution._scale, scale_y),
)
def setParameters(
self,
enabled=True,
sendInvitationDistribution=NormalDistribution(600, 60),
inviteeDistribution=UniformDiscreteDistribution(range(-10, 11)),
inviteeClumping=True,
inviteeCountDistribution=LogNormalDistribution(1.2, 1.2),
eventStartDistribution=NearFutureDistribution(),
eventDurationDistribution=UniformDiscreteDistribution([
15 * 60, 30 * 60,
45 * 60, 60 * 60,
120 * 60
]),
recurrenceDistribution=RecurrenceDistribution(False),
fileAttachPercentage=30,
fileSizeDistribution=NormalDistribution(1024, 1),
inviteeLookupPercentage=50,
):
self.enabled = enabled
self._sendInvitationDistribution = sendInvitationDistribution
self._inviteeDistribution = inviteeDistribution
self._inviteeClumping = inviteeClumping
self._inviteeCountDistribution = inviteeCountDistribution
self._eventStartDistribution = eventStartDistribution
self._eventDurationDistribution = eventDurationDistribution
self._recurrenceDistribution = recurrenceDistribution
self._fileAttachPercentage = fileAttachPercentage
self._fileSizeDistribution = fileSizeDistribution
self._inviteeLookupPercentage = inviteeLookupPercentage