All Samples(1983) | Call(1850) | Derive(0) | Import(133)
pow(x, y) Return x**y (x to the power of y).
src/p/y/pylon-HEAD/examples/national_grid/tikz.py pylon(Download)
sinphi=math.sin(phi)
con=eccent*sinphi
com=.5*eccent
con=math.pow(((1.0-con)/(1.0+con)),com)
ts=math.tan(.5*((math.pi*0.5)-phi))/con
y=0-r_major*math.log(ts)
return y
src/v/t/VT-USRP-daughterboard-drivers_python-HEAD/gnuradio-examples/python/apps/hf_explorer/hfx2.py VT-USRP-daughterboard-drivers_python(Download)
if self.active_button == 8:
new = max(0, min(500, self.slider_4.GetValue() + event.delta))
self.slider_4.SetValue(new)
self.scale.set_k(math.pow(10.,((self.slider_4.GetValue()-500.)/100.)))
if self.active_button == 9:
if self.PLAY_FROM_USRP == False:
if event.delta == -1:
def set_volume(self, event):
self.scale.set_k(math.pow(10.,((self.slider_4.GetValue()-500.)/100.)))
def set_pga(self,event):
if self.PLAY_FROM_USRP:
self.subdev.set_gain(self.slider_5.GetValue())
def am_carrier(self,event):
scale = math.pow(10,(self.slider_6.GetValue())/50.)
self.pll_carrier_scale.set_k(complex(scale,0))
# Reset AT data and start calibrate over
def AT_reset(self, event):
self.xdata = []
if ( int(new) >= 0 ) & ( int(new) <= 500 ):
self.volume = int(new)
self.slider_4.SetValue(self.volume)
self.scale.set_k(math.pow(10.,((self.slider_4.GetValue()-500.)/100.)))
else: # no new web commands, update state
fh = open("/var/www/cgi-bin/state/freq","w")
src/q/u/quickflash-HEAD/branch_tags/octave-swig/QuickFlash-1.0.0-Octave-1.0/examples/boxcount/plot_boxcounts.py quickflash(Download)
log_mid_width = 0.5 * (p1_log_width + p2_log_width)
geom_mid_width = math.pow(10.0, log_mid_width)
mid_widths.append(geom_mid_width)
slopes.append(delta_log_count / delta_log_oneOver_width)
log_mid_width = 0.5 * (p1_log_width + p2_log_width)
geom_mid_width = math.pow(10.0, log_mid_width)
mid_widths.append(geom_mid_width)
slopes.append(delta_log_count / delta_log_oneOver_width)
src/p/y/pyjamas-0.7/examples/gwtcanvas/SuiteDemo.py Pyjamas(Download)
else:
dy = -25.0
self.canvas.lineTo( (math.pow(i, 1.5) * 2.0), 75 + dy)
self.canvas.stroke()
self.canvas.restoreContext()
src/c/o/copads-HEAD/copads/copads/samplestatistics.py copads(Download)
"""
mult = 1.0
one_over_n = 1.0 / len(inlist)
for item in inlist: mult = mult * math.pow(item, one_over_n)
return mult
def harmonicMean(self, inlist):
Usage: skew(inlist)
"""
return self.moment(inlist, 3) / math.pow(self.moment(inlist, 2), 1.5)
def kurtosis(self, inlist):
"""
Returns the kurtosis of a distribution, as defined in Numerical
Recipies (alternate defn in CRC Standard Probability and Statistics,
p.6.)
Usage: kurtosis(inlist)
"""
return self.moment(inlist, 4) / math.pow(self.moment(inlist, 2), 2.0)
src/p/y/pyjamas-0.7/examples/gcharttestapp/GChartExample04.py Pyjamas(Download)
# add (log10-transformed) powers of 2 from 1/4 to 8
for i in range(-2, 4):
self.getCurve().addPoint(i,log10(math.pow(2,i)))
# GChart's "=10^" NumberFormat prefix inverts the log10
# transform
src/c/a/cantera-HEAD/language_interfaces/python/examples/surface_chemistry/catcomb.py cantera(Download)
# chemistry on slowly
sim.surface.setCoverageEqs('on')
for iter in range(6):
mult = math.pow(10.0,(iter - 5));
surf_phase.setMultiplier(mult);
gas.setMultiplier(mult);
print 'Multiplier = ',mult
src/h/e/heatsource-HEAD/src/Stream/PyHeatsource.py heatsource(Download)
from __future__ import division from math import pow, sqrt, sin, log, atan, sin, cos, pi, tan, acos, exp,radians, degrees, log10 from random import randint from bisect import bisect class HeatSourceError(Exception): pass
Dummy1 = sin(toRadians*Obliquity) * sin(toRadians*SunApparentLong)
Declination = toDegrees*(atan(Dummy1 / sqrt(-Dummy1 * Dummy1 + 1)))
SunRadVector = (1.000001018 * (1 - pow(Eccentricity,2))) / (1 + Eccentricity * cos(toRadians*(GeoMeanAnomalySun + SunEqofCenter)))
#======================================================
#Equation of time (minutes)
Dummy = pow((tan(Obliquity * pi / 360)),2)
Dummy1 = sin(toRadians*(2 * GeoMeanLongSun))
Dummy2 = sin(toRadians*(GeoMeanAnomalySun))
Dummy3 = cos(toRadians*(2 * GeoMeanLongSun))
Dummy4 = sin(toRadians*(4 * GeoMeanLongSun))
Dummy5 = sin(toRadians*(2 * GeoMeanAnomalySun))
Et = toDegrees*(4 * (Dummy * Dummy1 - 2 * Eccentricity * Dummy2 + 4 * Eccentricity * Dummy * Dummy2 * Dummy3 - 0.5 * pow(Dummy,2) * Dummy4 - 1.25 * pow(Eccentricity,2) * Dummy5))
else:
Dummy = tan(toRadians*(AtmElevation))
if AtmElevation > 5:
RefractionCorrection = 58.1 / Dummy - 0.07 / pow(Dummy,3) + 0.000086 / pow(Dummy,5)
elif AtmElevation > -0.575:
RefractionCorrection = 1735 + AtmElevation * (-518.2 + AtmElevation * (103.4 + AtmElevation * (-12.79 + AtmElevation * 0.711)))
else:
# then adds a slight change to the depth and solves it again. It should iterate for a solution to depth
# within about 5-6 solutions.
while Converge > 1e-7:
Fy = (D_est * (W_b + z * D_est)) * pow(((D_est * (W_b + z * D_est)) / (W_b + 2 * D_est * sqrt(1+ pow(z,2)))),power) - ((n * Q_est) / sqrt(S))
thed = D_est + dy
Fyy = (thed * (W_b + z * thed)) * pow((thed * (W_b + z * thed))/ (W_b + 2 * thed * sqrt(1+ pow(z,2))),power) - (n * Q_est) / sqrt(S)
dFy = (Fyy - Fy) / dy
count += 1
# Use the calculated wetted depth to calculate new channel characteristics
A = (D_est * (W_b + z * D_est))
Pw = (W_b + 2 * D_est * sqrt(1+ pow(z,2)))
Rh = A/Pw
Ww = W_b + 2 * z * D_est
U = Q_est / A
# THis is a sheer velocity estimate, followed by an estimate of numerical dispersion
if S == 0.0:
Shear_Velocity = U
else:
Shear_Velocity = sqrt(9.8 * D_est * S)
Dispersion = (0.011 * pow(U,2.0) * pow(Ww,2.0)) / (D_est * Shear_Velocity)
else:
Shear_Velocity = sqrt(9.8 * D_est * S)
Dispersion = (0.011 * pow(U,2.0) * pow(Ww,2.0)) / (D_est * Shear_Velocity)
if (Dispersion * dt / pow(dx,2.0)) > 0.5:
Dispersion = (0.45 * pow(dx,2)) / dt
#Dispersion = 50
return D_est, A, Pw, Rh, Ww, U, Dispersion
src/p/y/pytrafikanten-HEAD/trafikanten/util.py pytrafikanten(Download)
k0 = 0.9996
arc = northing / k0
mu = arc / (a * (1 - math.pow(e, 2) / 4.0 - 3 * math.pow(e, 4) / 64.0 - 5 * math.pow(e, 6) / 256.0))
ei = (1 - math.pow((1 - e * e), (1 / 2.0))) / (1 + math.pow((1 - e * e), (1 / 2.0)))
ca = 3 * ei / 2 - 27 * math.pow(ei, 3) / 32.0
cb = 21 * math.pow(ei, 2) / 16 - 55 * math.pow(ei, 4) / 32
cc = 151 * math.pow(ei, 3) / 96
cd = 1097 * math.pow(ei, 4) / 512
cd = 1097 * math.pow(ei, 4) / 512
phi1 = mu + ca * math.sin(2 * mu) + cb * math.sin(4 * mu) + cc * math.sin(6 * mu) + cd * math.sin(8 * mu)
n0 = a / math.pow((1 - math.pow((e * math.sin(phi1)), 2)), (1 / 2.0))
r0 = a * (1 - e * e) / math.pow((1 - math.pow((e * math.sin(phi1)), 2)), (3 / 2.0))
fact1 = n0 * math.tan(phi1) / r0
_a1 = 500000 - easting
dd0 = _a1 / (n0 * k0)
fact2 = dd0 * dd0 / 2
t0 = math.pow(math.tan(phi1), 2)
Q0 = e1sq * math.pow(math.cos(phi1), 2)
t0 = math.pow(math.tan(phi1), 2)
Q0 = e1sq * math.pow(math.cos(phi1), 2)
fact3 = (5 + 3 * t0 + 10 * Q0 - 4 * Q0 * Q0 - 9 * e1sq) * math.pow(dd0, 4) / 24
fact4 = (61 + 90 * t0 + 298 * Q0 + 45 * t0 * t0 - 252 * e1sq - 3 * Q0 * Q0) * math.pow(dd0, 6) / 720
lof1 = _a1 / (n0 * k0)
lof2 = (1 + 2 * t0 + Q0) * math.pow(dd0, 3) / 6.0
lof3 = (5 - 2 * Q0 + 28 * t0 - 3 * math.pow(Q0, 2) + 8 * e1sq + 24 * math.pow(t0, 2)) * math.pow(dd0, 5) / 120
src/a/n/analyticgeom-HEAD/trunk/modulos/Cuadricas.py analyticgeom(Download)
from pivy.coin import * from PyQt4 import QtGui, QtCore, uic from modulos.util import main, lee, conecta from math import sqrt, cos, sin, asin, pi, pow from MallaBase2 import MallaBase, ParametricPlot3D, creaVars, Eq, creaVarParam, creaOpParam from Visor import Visor #import psyco
def rangox(self,w=0):
a = sqrt(16 - 16*w + pow(w,2))
return (
(2*sqrt(pow(-2 + w,2)))/a,
(2*sqrt(40 - 40*w + pow(w,2)))/a, 40)
def rangox2(self,w=0):
a = sqrt(16 - 16*w + pow(w,2))
return ((2*sqrt(pow(-2 + w,2)))/a,3, 40)
def func1(w, r, t):
a = 16 -16*w +w**2
b = -1 + w
return (
.25*r*sqrt(a/(1 - w))*cos(t),
.25*sqrt(abs(((-a)*pow(r,2) + 4*pow(-2 + w,2))/b)),
(2*w + sqrt(a/pow(b,2))*b*r*sin(t))/(4*b))
def func2(w, r, t):
a = 16 -16*w +w**2
b = -1 + w
return (
.25*r*sqrt(a/(1 - w))*cos(t),
-.25*sqrt(abs(((-a)*pow(r,2) + 4*pow(-2 + w,2))/b)),
(2*w + sqrt(a/pow(b,2))*b*r*sin(t))/(4*b))
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