random.gauss

All Samples(550) | Call(514) | Derive(0) | Import(36)

Gaussian distribution.

mu is the mean, and sigma is the standard deviation.  This is
slightly faster than the normalvariate() function.

Not thread-safe without a lock around calls.

src/g/r/grease-0.2/examples/blasteroids3.py grease(Download)

            debris.shape.verts = segment
            debris.position.position = self.position.position
            debris.movement.velocity = self.movement.velocity
            debris.movement.velocity += segment[0].normalized() * random.gauss(50, 20)
            debris.movement.rotation = random.gauss(0, 45)
            debris.renderable.color = self.renderable.color

                random.choice([-1, 1]) * random.randint(50, window.height / 2))
        else:
            self.position.position = position
        self.movement.velocity = (random.gauss(0, 700 / radius), random.gauss(0, 700 / radius))
        if parent_velocity is not None:
            self.movement.velocity += parent_velocity
        self.movement.rotation = random.gauss(0, 15)
        verts = [(random.gauss(x*radius, radius / 7), random.gauss(y*radius, radius / 7))

src/g/r/grease-0.2/examples/blasteroids2.py grease(Download)

            debris.shape.verts = segment
            debris.position.position = self.position.position
            debris.movement.velocity = self.movement.velocity
            debris.movement.velocity += segment[0].normalized() * random.gauss(50, 20)
            debris.movement.rotation = random.gauss(0, 45)
            debris.renderable.color = self.renderable.color

    def __init__(self, world, radius=45):
        self.position.position = (
            random.choice([-1, 1]) * random.randint(50, window.width / 2), 
            random.choice([-1, 1]) * random.randint(50, window.height / 2))
        self.movement.velocity = (random.gauss(0, 700 / radius), random.gauss(0, 700 / radius))
        self.movement.rotation = random.gauss(0, 15)
        verts = [(random.gauss(x * radius, radius / 7), random.gauss(y * radius, radius / 7))

src/l/e/lepton-1.0b2/examples/fireworks.py lepton(Download)

 
import os
import math
from random import expovariate, uniform, gauss
from pyglet import image
from pyglet.gl import *

				position=(uniform(-50, 50), uniform(-30, 30), uniform(-30, 30)), 
				color=color), 
			deviation=Particle(
				velocity=(gauss(0, 5), gauss(0, 5), gauss(0, 5)),
				age=1.5),
			velocity=domain.Sphere((0, gauss(40, 20), 0), 60, 60))

				ColorBlender([(0, (1,1,1,1)), (2, color), (self.lifetime, color)]),
				Fader(fade_out_start=1.0, fade_out_end=self.lifetime * 0.5),
			],
			renderer=PointRenderer(abs(gauss(10, 3)), spark_texturizer))
 
		spark_emitter.emit(int(gauss(60, 40)) + 50, self.sparks)
 
		spread = abs(gauss(0.4, 1.0))

				Lifetime(self.lifetime * 1.5),
				Movement(damping=0.83),
				ColorBlender([(0, (1,1,1,1)), (1, color), (self.lifetime, color)]),
				Fader(max_alpha=0.75, fade_out_start=0, fade_out_end=gauss(self.lifetime, self.lifetime*0.3)),
				self.trail_emitter
			],
			renderer=PointRenderer(10, trail_texturizer))

src/g/r/grease-0.2/examples/blasteroids1.py grease(Download)

    def __init__(self, world, radius=45):
        self.position.position = (
            random.choice([-1, 1]) * random.randint(50, window.width / 2), 
            random.choice([-1, 1]) * random.randint(50, window.height / 2))
        self.movement.velocity = (random.gauss(0, 700 / radius), random.gauss(0, 700 / radius))
        self.movement.rotation = random.gauss(0, 15)
        verts = [(random.gauss(x * radius, radius / 7), random.gauss(y * radius, radius / 7))

src/a/t/atma-HEAD/trunk/examples/basics/root/samplejson.py atma(Download)

 
        a = dict()
        a['alpha'] = random.random()
        a['bravo'] = random.gauss(1,1)
        a['charlie'] = random.sample(range(30),random.randint(10,20))
 
        return pprint.pformat(a)

src/a/t/atma-HEAD/examples/basics/root/samplejson.py atma(Download)

 
        a = dict()
        a['alpha'] = random.random()
        a['bravo'] = random.gauss(1,1)
        a['charlie'] = random.sample(range(30),random.randint(10,20))
 
        return pprint.pformat(a)

src/v/i/vispa-HEAD/vispa/trunk/examples/AnalysisDesigner/withROOT/smear_script.py vispa(Download)

            name=particle.getName()
            (pt,eta,phi,m)=(particle.getPt(),particle.getEta(),particle.getPhi(),particle.getMass())
            if name in rel_resolutions_pt.keys():
                pt*=random.gauss(1,rel_resolutions_pt[name])
            if name in rel_resolutions_eta.keys():
                eta*=random.gauss(1,rel_resolutions_eta[name])
            if name in rel_resolutions_eta.keys():
                phi*=random.gauss(1,rel_resolutions_phi[name])

src/b/r/brian-HEAD/trunk/examples/misc/pulsepacket.py brian(Download)

'''
This example basically replicates what the Brian PulsePacket object does,
and then compares to that object.
'''
 
from brian import *
from random import gauss, shuffle
 
# Generator for pulse packet
def pulse_packet(t, n, sigma):
    # generate a list of n times with Gaussian distribution, sort them in time, and
    # then randomly assign the neuron numbers to them
    times = [gauss(t, sigma) for i in range(n)]

src/b/r/brian-HEAD/examples/misc/pulsepacket.py brian(Download)

'''
This example basically replicates what the Brian PulsePacket object does,
and then compares to that object.
'''
 
from brian import *
from random import gauss, shuffle
 
# Generator for pulse packet
def pulse_packet(t, n, sigma):
    # generate a list of n times with Gaussian distribution, sort them in time, and
    # then randomly assign the neuron numbers to them
    times = [gauss(t, sigma) for i in range(n)]

src/l/a/Langtangen-HEAD/src/py/examples/efficiency/pyefficiency.py Langtangen(Download)

    def list_append3(n):
        import random
        r = []
        for i in xrange(n):
            r.append(random.gauss(0,1))
        return r
 
    def list_chunk2(n):
        import random
        r = [0.0]*n
        for i in xrange(n):
            r[i] = random.gauss(0,1)

    def list_append5(n):
        import random
        return [random.gauss(0,1) for i in xrange(n)]
 
    def list_chunk3(n):
        import random
        g = random.gauss

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