def plotError():
print('Plotting error..')
#func = lambda x: 1.0 / (x + 1.0)
func = sinSqr
remez = remezFit('Sin', func, func, (epsilon, 1.0), 4)
# remez = remezFit('Rcp', func, func, (1.0, 2.0), 3)
print('err:', remez.maxError)
est = remezToPoly(remez)
err = lambda x: (func(x) - est(x)) / func(x)
mp.plot([err], [0.0, 1.0])
def main():
parser = argparse.ArgumentParser(description='Design Serial Diode')
parser.add_argument('Vs', type=float, help='Voltage supply')
parser.add_argument('Id',
type=float,
help='Desired current over the diode in Amps')
parser.add_argument(
'Is',
type=float,
nargs='?',
default=1e-12,
help='Diode Saturation current in Amps (default = 1e-12)')
parser.add_argument('N',
type=float,
nargs='?',
default=1,
help='Emission Coefficient (default = 1)')
parser.add_argument('--Vt',
type=float,
default=0.026,
help='Thermal Voltage in Volts (default = 0.026)')
parser.add_argument('-g',
'--graph',
action='store_true',
help='Draw a graph')
parser.add_argument('-v',
'--verbose',
action='store_true',
help='Print debug')
args = parser.parse_args()
Vs = args.Vs
Id = args.Id
Is = args.Is
N = args.N
Vt = args.Vt
nVt = N * Vt
if args.verbose:
logging.basicConfig(format='%(levelname)s|%(message)s',
level=logging.INFO)
logging.info(f'Vs: {Vs}, Id: {Id}, Is: {Is}, N: {N}, Vt: {Vt}')
Vd = fmul(log(fadd(fdiv(Id, Is), mpf(1))), nVt)
VR = fsub(Vs, Vd)
IR = Id
R = fdiv(VR, IR)
print("VR: {}, IR: {}, R: {}".format(VR, IR, R))
print("Vd: {}, Id: {}, Rd: {}".format(Vd, Id, fdiv(Vd, Id)))
if args.graph:
plot([
lambda x: fsub(Vs, fmul(x, R)),
lambda x: fmul(nVt, log(fadd(fdiv(x, Is), 1)))
], [0, fdiv(Vs, R)], [0, Vs])
def main():
parser = argparse.ArgumentParser(
description='Analyse charge % vs cycles of tau')
parser.add_argument(
'value',
type=float,
help=
'Value of cycles or Vratio (the value for which we are not solving)')
parser.add_argument(
'-c',
'--cycles',
action='store_true',
help='Solve for cycles (if the flag is not set, solve for Vratio)')
parser.add_argument('-g',
'--graph',
action='store_true',
help='Draw a graph')
parser.add_argument('-v',
'--verbose',
action='store_true',
help='Print debug')
args = parser.parse_args()
value = args.value
cycles = args.cycles
if args.verbose:
logging.basicConfig(format='%(levelname)s|%(message)s',
level=logging.INFO)
logging.info(f'value: {value}, cycles: {cycles}')
if cycles:
Vratio = value
cycles = fsub(0, log(fsub(1, Vratio)))
print("cycles: {}".format(cycles))
else:
cycles = value
Vratio = fsub(1, exp(fsub(0, cycles)))
print("Vratio: {}".format(Vratio))
if args.graph:
plot([lambda x: fsub(1, exp(fsub(0, x)))], [0, cycles], [0, 1])
def main(argv):
if len(argv) != 4:
print "Analyse Serial Diode"
print "Usage: asd <Vcc> <R> <Is> <nVt>"
else:
Vcc = mpf(argv[0])
R = mpf(argv[1])
Is = mpf(argv[2])
nVt = mpf(argv[3])
x = fdiv(fmul(fmul(Is, R), fsub(exp(fdiv(Vcc, nVt)), mpf(1))), nVt)
w = lambertw(x)
Id = fdiv(fmul(w, nVt), R)
Vd = fmul(log(fadd(fdiv(Id, Is), mpf(1))), nVt)
VR = fsub(Vcc, Vd)
IR = fdiv(VR, R)
print "VR: {}, IR: {}".format(VR, IR)
print "Vd: {}, Id: {}".format(Vd, Id)
plot([
lambda x: fsub(Vcc, fmul(x, R)),
lambda x: fmul(nVt, log(fadd(fdiv(x, Is), 1)))
], [0, fdiv(Vcc, R)], [0, Vcc])
def plot_in_terminal(expr, *args, prec=None, logname=None, file=None, **kwargs):
"""
Run mpmath.plot() but show in terminal if possible
"""
from mpmath import plot
if logname:
os.makedirs('plots', exist_ok=True)
file = 'plots/%s.png' % logname
if prec:
mpmath.mp.dps = prec
if isinstance(expr, (list, tuple)):
f = [lambdify(t, i, 'mpmath') for i in expr]
else:
f = lambdify(t, expr, 'mpmath')
try:
if hasattr(sys.stdout, 'isatty') and sys.stdout.isatty():
from iterm2_tools.images import display_image_bytes
else:
raise ImportError
except ImportError:
plot(f, *args, file=file, **kwargs)
else:
# mpmath.plot ignores the axes argument if file is given, so let
# file=False, disable this.
if 'axes' in kwargs:
file=False
if file is not False:
from io import BytesIO
b = BytesIO()
else:
b = None
plot(f, *args, **kwargs, file=b)
if file:
with open(file, 'wb') as f:
f.write(b.getvalue())
if b:
print(display_image_bytes(b.getvalue()))
def main():
parser = argparse.ArgumentParser(description='Analyse Parallel Diode')
parser.add_argument('Vs', type=float, help='Voltage supply')
parser.add_argument('R1', type=float, help='Resistor 1 value in Ohms')
parser.add_argument('R2', type=float, help='Resistor 2 value in Ohms')
parser.add_argument('Is', type=float, nargs='?', default=1e-12, help='Diode Saturation current in Amps (default = 1e-12)')
parser.add_argument('N', type=float, nargs='?', default=1, help='Emission Coefficient (default = 1)')
parser.add_argument('--Vt', type=float, default=0.026, help='Thermal Voltage in Volts (default = 0.026)')
parser.add_argument('-g', '--graph', action='store_true', help='Draw a graph')
parser.add_argument('-v', '--verbose', action='store_true', help='Print debug')
args = parser.parse_args()
Vs = args.Vs
R1 = args.R1
R2 = args.R2
Is = args.Is
N = args.N
Vt = args.Vt
nVt = N*Vt
if args.verbose:
logging.basicConfig(format='%(levelname)s|%(message)s', level=logging.INFO)
logging.info(f'Vs: {Vs}, R1: {R1}, R2: {R2}, Is: {Is}, N: {N}, Vt: {Vt}')
x = fdiv(fmul(fmul(fmul(R1,R2),Is),exp(fdiv(fmul(R2,fadd(Vs,fmul(Is,R1))),(fmul(nVt,fadd(R1,R2)))))),fmul(nVt,fadd(R1,R2)))
w = lambertw(x)
Id = fsub(fdiv(fmul(fmul(nVt,w),fadd(R1,R2)),fmul(R1,R2)),Is)
Vd = fmul(log(fadd(fdiv(Id,Is),mpf(1))),nVt)
Rd = fdiv(Vd,Id)
Rd2 = fdiv(fmul(Rd,R2),fadd(Rd,R2))
VR2 = Vd
IR2 = fdiv(VR2,R2)
VR1 = fsub(Vs,Vd)
IR1 = fdiv(VR1,R1)
print("VR1: {}, IR1: {}".format(VR1, IR1))
print("VR2: {}, IR2: {}".format(VR2, IR2))
print("Vd: {}, Id: {}".format(Vd, Id))
if args.graph:
plot([lambda x: fsub(Vs,fmul(fadd(x,fdiv(fmul(nVt,log(fadd(fdiv(x,Is),mpf(1)))),R2)),R1)), lambda x: fmul(nVt,log(fadd(fdiv(x,Is),mpf(1))))], [0, fdiv(Vs,fadd(R1,Rd2))], [0, Vs])
def main(argv):
if len(argv) != 5:
print "Design Parallel Diode"
print "Usage: apd <Vcc> <Id> <R2Mul> <Is> <nVt>"
else:
Vcc = mpf(argv[0])
Id = mpf(argv[1])
R2Mul = mpf(argv[2])
Is = mpf(argv[3])
nVt = mpf(argv[4])
Vd = fmul(log(fadd(fdiv(Id,Is),mpf(1))),nVt)
Rd = fdiv(Vd,Id)
VR2 = Vd
IR2 = fmul(Id,R2Mul)
R2 = fdiv(VR2,IR2)
Rd2 = fdiv(fmul(Rd,R2),fadd(Rd,R2))
VR1 = fsub(Vcc,Vd)
IR1 = fadd(Id,IR2)
R1 = fdiv(VR1,IR1)
print "VR1: {}, IR1: {}, R1: {}".format(VR1, IR1, R1)
print "VR2: {}, IR2: {}, R2: {}".format(VR2, IR2, R2)
print "Vd: {}, Id: {}, Rd: {}".format(Vd, Id, Rd)
plot([lambda x: fsub(Vcc,fmul(fadd(x,fdiv(fmul(nVt,log(fadd(fdiv(x,Is),mpf(1)))),R2)),R1)), lambda x: fmul(nVt,log(fadd(fdiv(x,Is),mpf(1))))], [0, fdiv(Vcc,fadd(R1,Rd2))], [0, Vcc])
def main(argv):
if len(argv) != 5:
print "Analyse Parallel Diode"
print "Usage: apd <Vcc> <R1> <R2> <Is> <nVt>"
else:
Vcc = mpf(argv[0])
R1 = mpf(argv[1])
R2 = mpf(argv[2])
Is = mpf(argv[3])
nVt = mpf(argv[4])
x = fdiv(
fmul(
fmul(fmul(R1, R2), Is),
exp(
fdiv(fmul(R2, fadd(Vcc, fmul(Is, R1))),
(fmul(nVt, fadd(R1, R2)))))), fmul(nVt, fadd(R1, R2)))
w = lambertw(x)
Id = fsub(fdiv(fmul(fmul(nVt, w), fadd(R1, R2)), fmul(R1, R2)), Is)
Vd = fmul(log(fadd(fdiv(Id, Is), mpf(1))), nVt)
Rd = fdiv(Vd, Id)
Rd2 = fdiv(fmul(Rd, R2), fadd(Rd, R2))
VR2 = Vd
IR2 = fdiv(VR2, R2)
VR1 = fsub(Vcc, Vd)
IR1 = fdiv(VR1, R1)
print "VR1: {}, IR1: {}".format(VR1, IR1)
print "VR2: {}, IR2: {}".format(VR2, IR2)
print "Vd: {}, Id: {}".format(Vd, Id)
plot([
lambda x: fsub(
Vcc,
fmul(
fadd(x, fdiv(fmul(nVt, log(fadd(fdiv(x, Is), mpf(1)))), R2)
), R1)),
lambda x: fmul(nVt, log(fadd(fdiv(x, Is), mpf(1))))
], [0, fdiv(Vcc, fadd(R1, Rd2))], [0, Vcc])
#!/usr/bin/python
# import mpmath module
import mpmath as mp
# trick to show & save with the same function:
# if file is None, it shows the plot, else it saves to the filename
for file in [None, '7900_09_08.png']:
# plot a sine between -6 and 6
mp.plot(mp.sin, [-6, 6], file=file)
# same trick as above
for file in [None, '7900_09_09.png']:
# plot square root (to show complex plotting)
# and a custom function (made with lambda expression)
mp.plot([mp.sqrt, lambda x: -0.1 * x**3 + x - 0.5], [-3, 3], file=file)
import numpy as np
import matplotlib.pyplot as plt
from mpmath import j
from mpmath import plot
plot(lambda n: 3.0 / (2 * np.pi) - 1.0 / (2 * np.pi * (j * n)**2), [-10, 10])
plot(lambda n: 3.0 / (2 * np.pi) - 1.0 / (2 * np.pi * (j * 2 * n)**2),
[-10, 10])
plot(lambda n: 3.0 / (2 * np.pi) - 1.0 / (2 * np.pi * (j * 4 * n)**2),
[-10, 10])
plot(lambda n: 3.0 / (2 * np.pi) - 1.0 / (2 * np.pi * (j * (n / 2.0))**2),
[-10, 10])
plot(lambda n: 3.0 / (2 * np.pi) - 1.0 / (2 * np.pi * (j * (n / 4.0))**2),
[-10, 10])
# [x0, x1] - function implements on the interval
# q - Polinomials maximum degree for choosing Galerkin method basis
# 0th degree basis function is fixed to the initial value
# ode - ordinary differential equation
# x - function argument
# u0 - initial value
# Assume that the solution can be approximated as a linear combination of the basis functions
def galerkin(ode, x, x0, x1, u0, q):
basis = [x**k for k in range(q+1)]
# Coefficients for the basis monomials
xi = [Symbol("xi_%i" % k) for k in range(q+1)]
# Solution function ansatz
u = u0 + sum(xi[k]*basis[k] for k in range(1,q+1))
# Form system of linear equations
equations = [integrate(ode(u)*basis[k], (x, x0, x1)) \
for k in range(1,q+1)]
coeffs = solve(equations, xi[1:])
return u.subs(coeffs)
if __name__ == "__main__":
x = Symbol('x')
ode = lambda u: u.diff(x) - u
for q in range(1,6):
pprint(galerkin(ode, x, 0, 1, 1, q))
u1 = Lambda(x, galerkin(ode, x, 0, 1, 1, 1))
u2 = Lambda(x, galerkin(ode, x, 0, 1, 1, 2))
u3 = Lambda(x, galerkin(ode, x, 0, 1, 1, 3))
plot([exp, u1, u2, u3], [0, 2])
#coding=utf-8 import math import pandas from mpmath import arange, plot print(math.factorial(4)) plot(arange(5))
import numpy as np import matplotlib.pyplot as plt from mpmath import j from mpmath import plot plot(lambda n: 3.0/(2*np.pi) - 1.0/(2*np.pi*(j*n)**2), [-10, 10]) plot(lambda n: 3.0/(2*np.pi) - 1.0/(2*np.pi*(j*2*n)**2), [-10, 10]) plot(lambda n: 3.0/(2*np.pi) - 1.0/(2*np.pi*(j*4*n)**2), [-10, 10]) plot(lambda n: 3.0/(2*np.pi) - 1.0/(2*np.pi*(j*(n/2.0))**2), [-10, 10]) plot(lambda n: 3.0/(2*np.pi) - 1.0/(2*np.pi*(j*(n/4.0))**2), [-10, 10])
# mp.plot([lambda t: S_double_hol_conn(x1, x2, t, s, b),lambda t: S_double_hol_disconn(x1, x2, t, s, b)],[0,maxtime],points=plotpoints)
"""
plot of SINGLE SPLITTING QUENCH
"""
# s,b=3.37,50
a = cutoff(s, b)
# print(a)
# maxtime = 200
# plotpoints = 1000
# mp.plot(lambda x: cutoff(x,50)/50,[0.9,10],points=100)
# x1, x2 = 50, 150
# mp.plot(lambda t: S_single_dirac(x1, x2, t, a),[0,maxtime],points=plotpoints)
# x1, x2 = -20, 50
# mp.plot(lambda t: S_single_dirac(x1, x2, t, a),[0,maxtime],points=plotpoints)
# x1, x2 = 50, 150
# mp.plot([lambda t: S_single_hol_conn(x1, x2, t, a),lambda t: S_single_hol_disconn(x1, x2, t, a)],[0,maxtime],points=plotpoints)
# x1, x2 = -20, 50
# mp.plot([lambda t: S_single_hol_conn(x1, x2, t, a),lambda t: S_single_hol_disconn(x1, x2, t, a)],[0,maxtime],points=plotpoints)
"""
difference
"""
x1 = 30
x2 = 40
# mp.plot( [lambda t: S_double_dirac(x1, x2, t, s, b)/(S_single_dirac(x1-b, x2-b, t, a)+S_single_dirac(x1+b, x2+b, t, a))], [0,400],points=200 )
mp.plot([
lambda t: S_double_hol(x1, x2, t, s, b) / (S_single_hol(
x1 - b, x2 - b, t, a) + S_single_hol(x1 + b, x2 + b, t, a))
], [0, 100],
points=100)
from mpmath import zeta, plot, gamma, sin, pi
# real-plot.py zeichnet zwei reelle Graphen der Riemannschen
# Zetafunktion. Der Graph wird erst im Bereich mit x zwischen -4 und
# 6 betrachtet, dann mit x zwischen -49 und 51.
plot(zeta, [-4, 6],
ylim=[-20, 20],
points=1000,
file="real-plot-1.pdf",
singularities=[1])
plot(zeta, [-49, 51],
ylim=[-20, 20],
points=10000,
file="real-plot-2.pdf",
singularities=[1])
#!/usr/bin/python
# import mpmath module
import mpmath as mp
# trick to show & save with the same function:
# if file is None, it shows the plot, else it saves to the filename
for file in [None, '7900_09_08.png']:
# plot a sine between -6 and 6
mp.plot(mp.sin, [-6, 6], file=file)
# same trick as above
for file in [None, '7900_09_09.png']:
# plot square root (to show complex plotting)
# and a custom function (made with lambda expression)
mp.plot([mp.sqrt, lambda x: -0.1*x**3 + x-0.5], [-3, 3],
file=file)
