def llspace(xmin, xmax, n=None, log=False, dx=None, dex=None):
    '\n    llspace(xmin, xmax, n = None, log = False, dx = None, dex = None)\n    get values evenly spaced in linear or log spaced\n    n [10] -- Optional -- number of steps\n    log [false] : switch for log spacing\n    dx : spacing for linear bins\n    dex : spacing for log bins (in base 10)\n    dx and dex override n\n    '
    (xmin, xmax) = (float(xmin), float(xmax))
    nisNone = (n is None)
    dxisNone = (dx is None)
    dexisNone = (dex is None)
    if ((nisNone & dxisNone) & dexisNone):
        print('Error: Defaulting to 10 linears steps')
        n = 10.0
        nisNone = False
    log = (log or (dxisNone and (not dexisNone)))
    if log:
        if (xmin == 0):
            print('log(0) is -inf. xmin must be > 0 for log spacing')
        (xmin, xmax) = (np.log10(xmin), np.log10(xmax))
    if (not nisNone):
        if (log and dexisNone):
            dex = ((xmax - xmin) / n)
        elif ((not log) and dxisNone):
            dx = ((xmax - xmin) / n)
    if log:
        return np.power(10, np.arange(xmin, (xmax + dex), dex))
    else:
        return np.arange(xmin, (xmax + dx), dx)
llspace(xmin, xmax, n = None, log = False, dx = None, dex = None)
get values evenly spaced in linear or log spaced
n [10] -- Optional -- number of steps
log [false] : switch for log spacing
dx : spacing for linear bins
dex : spacing for log bins (in base 10)
dx and dex override n
def llspace(xmin, xmax, n=None, log=False, dx=None, dex=None):
    '\n    llspace(xmin, xmax, n = None, log = False, dx = None, dex = None)\n    get values evenly spaced in linear or log spaced\n    n [10] -- Optional -- number of steps\n    log [false] : switch for log spacing\n    dx : spacing for linear bins\n    dex : spacing for log bins (in base 10)\n    dx and dex override n\n    '
    (xmin, xmax) = (float(xmin), float(xmax))
    nisNone = (n is None)
    dxisNone = (dx is None)
    dexisNone = (dex is None)
    if ((nisNone & dxisNone) & dexisNone):
        print('Error: Defaulting to 10 linears steps')
        n = 10.0
        nisNone = False
    log = (log or (dxisNone and (not dexisNone)))
    if log:
        if (xmin == 0):
            print('log(0) is -inf. xmin must be > 0 for log spacing')
        (xmin, xmax) = (np.log10(xmin), np.log10(xmax))
    if (not nisNone):
        if (log and dexisNone):
            dex = ((xmax - xmin) / n)
        elif ((not log) and dxisNone):
            dx = ((xmax - xmin) / n)
    if log:
        return np.power(10, np.arange(xmin, (xmax + dex), dex))
    else:
        return np.arange(xmin, (xmax + dx), dx)