DanHickstein

for i in range(1,10):
    print i

DanHickstein

import numpy as np
import matplotlib.pyplot as plt
from scipy.linalg import circulant
from scipy.optimize import curve_fit, brentq
from scipy.interpolate import interp1d
from scipy.ndimage import gaussian_filter
import scipy.ndimage as nd

def gaussian(x, a, mu, sigma, c):
    """

DanHickstein

import numpy as np
import matplotlib.pyplot as plt
import abel

sizes = np.logspace(np.log10(50), np.log10(1e4), 20)
n_max_bs   = 2001
n_max_slow = 2001
transform_repeat = 4 # for less than 400

results = {'basex' :         [], 

DanHickstein

import numpy as np
import abel
import matplotlib.pyplot as plt
import time

# nps = np.logspace(1,9,12)
nps = [10,20,2e9]

print nps
times1 = []

DanHickstein

import numpy as np
import scipy
import time
import matplotlib.pyplot as plt

print np.__file__


ax = plt.subplot(111)

DanHickstein

7.946976846400634440e-05 8.667642234809308478e-05 9.450443003223845827e-05 1.030043386224856205e-04 1.122305339989060352e-04 1.222415087244265548e-04 1.331001466999138366e-04 1.448740254584019566e-04 1.576357370272610443e-04 1.714632283235950107e-04 1.864401620851679976e-04 2.026562993765587868e-04 2.202079047479936881e-04 2.391981751623455208e-04 2.597376938439263346e-04 2.819449102409028979e-04 3.059466473313294643e-04 3.318786375406693146e-04 3.598860885763137266e-04 3.901242805216768991e-04 4.227591955688852869e-04 4.579681818047371213e-04 4.959406524991876548e-04 5.368788223790569615e-04 5.809984824016828321e-04 6.285298145735682780e-04 6.797182483876665002e-04 7.348253604793540889e-04 7.941298191251164491e-04 8.579283752295608452e-04 9.265369014647428531e-04 1.000291481241133039e-03 1.079549549201436025e-03 1.164691084936236897e-03 1.256119861624400503e-03 1.354264751300345276e-03 1.459581088444606616e-03 1.572552093583458755e-03 1.693690358566635884e-03 1.823539395169958711e-03 1.962675248640656338e-03

DanHickstein

import numpy as np
import matplotlib.pyplot as plt
import pynlo
import matplotlib.cm as cm

FWHM    = 0.2  # pulse duration (ps)
pulseWL = 1550   # pulse central wavelength (nm)
EPP     = 200e-12 # Energy per pulse (J)
GDD     = 0.0    # Group delay dispersion (ps^2)
TOD     = 0.0    # Third order dispersion (ps^3)

DanHickstein

# -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function

import numpy as np
import abel
import matplotlib.pyplot as plt
import scipy

def direct1d(n=51):

DanHickstein

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec

import abel
from scipy.ndimage import zoom
from scipy import signal

import peakutils

DanHickstein

import numpy as np
import matplotlib.pyplot as plt
import abel
import scipy.interpolate, scipy.ndimage.interpolation
import time

global X,Y,R,T

size = 301