sefd_summary

Module Contents

Functions

arg_init()
fitfunc2(p, x)
errfunc2(p, x, y)
linfunc(p, x)
linerr(p, x, y)
fit_g(x, y, p0[, fkey])
find_mode(data, parameters)	Estimates and returns the mode of those input data that lie within the limits set by the parameters.
dual_half_circle(center, radius[, angle, ax, colors])	Add two half circles to the axes ax (or the current axes) with the
bsect(x, z)	Find position in array x of value z; assumes x sorted in increasing order.
get_footprint_pa_zero(name, pitch)
make_cmap(ssl, ssu)
main()

Attributes

big
funcs
fmt

sefd_summary.big = 1e+20

sefd_summary.arg_init()

sefd_summary.fitfunc2(p, x)

sefd_summary.errfunc2(p, x, y)

sefd_summary.linfunc(p, x)

sefd_summary.linerr(p, x, y)

sefd_summary.funcs

sefd_summary.fit_g(x, y, p0, fkey='gau')

sefd_summary.find_mode(data, parameters)

Estimates and returns the mode of those input data that lie within the limits set by the parameters. The mode is determined by fitting a guassian function to the peak of the histogram of the logarithms of the values.

Parameters:

• data – np.array of real values

• parameters – dictionary giving the data value bounds

Returns:

sefd_summary.dual_half_circle(center, radius, angle=0, ax=None, colors=('w', 'k'), **kwargs)

Add two half circles to the axes ax (or the current axes) with the specified facecolors colors rotated at angle (in degrees).

sefd_summary.bsect(x, z)

Find position in array x of value z; assumes x sorted in increasing order. Returns j such that x[j] <= z < x[j+1]

sefd_summary.get_footprint_pa_zero(name, pitch)

sefd_summary.make_cmap(ssl, ssu)

sefd_summary.main()

sefd_summary.fmt = '%(asctime)s %(levelname)s  %(name)s %(message)s'