The sherpa.utils moduleΒΆ
Functions
Knuth_close(x, y, tol[, myop]) |
Check whether two floating-point numbers are close together. |
_guess_ampl_scale |
float(x) -> floating point number |
apache_muller(fcn, xa, xb[, fa, fb, args, ...]) |
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bisection(fcn, xa, xb[, fa, fb, args, ...]) |
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bool_cast(val) |
Converts a string (true|False|on|OFF|etc...) to a boolean value |
calc_ftest(dof1, stat1, dof2, stat2) |
Compare two models using the F test. |
calc_mlr(delta_dof, delta_stat) |
Compare two models using the Maximum Likelihood Ratio test. |
calc_total_error([staterror, syserror]) |
Add statistical and systematic errors in quadrature. |
create_expr(vals[, mask, format, delim]) |
collapse a list of channels into an expression using hyphens |
dataspace1d(start, stop[, step, numbins]) |
Populates an integrated grid |
dataspace2d(dim) |
Populates a blank image dataset |
demuller(fcn, xa, xb, xc[, fa, fb, fc, ...]) |
A root-finding algorithm using Muller’s method [1]_. |
erf |
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export_method(meth[, name, modname]) |
Given a bound instance method, return a simple function that wraps it. |
extract_kernel |
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filter_bins(mins, maxes, axislist) |
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gamma(z) |
Calculate the Gamma function. |
get_error_estimates(x[, sorted]) |
Compute the median and (-1,+1) sigma values for the data. |
get_fwhm(y, x[, xhi]) |
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get_keyword_defaults(func[, skip]) |
Return the keyword arguments and their default values. |
get_keyword_names(func[, skip]) |
Return the names of the keyword arguments. |
get_midpoint(a) |
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get_num_args(func) |
Return the number of arguments for a function. |
get_peak(y, x[, xhi]) |
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get_position(y, x[, xhi]) |
Get 1D model parameter positions pos (val, min, max) |
get_valley(y, x[, xhi]) |
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guess_amplitude(y, x[, xhi]) |
Guess model parameter amplitude (val, min, max) |
guess_amplitude2d(y, x0lo, x1lo[, x0hi, x1hi]) |
Guess 2D model parameter amplitude (val, min, max) |
guess_amplitude_at_ref(r, y, x[, xhi]) |
Guess model parameter amplitude (val, min, max) |
guess_bounds(x[, xhi]) |
Guess model parameters xlo, xhi (val, min, max) |
guess_fwhm(y, x[, xhi, scale]) |
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guess_position(y, x0lo, x1lo[, x0hi, x1hi]) |
Guess 2D model parameter positions xpos, ypos ({val0, min0, max0}, |
guess_radius(x0lo, x1lo[, x0hi, x1hi]) |
Guess 2D model parameter radius (val, min, max) |
guess_reference(pmin, pmax, x[, xhi]) |
Guess model parameter reference (val, min, max) |
histogram1d(x, x_lo, x_hi) |
Create a 1D histogram from a binned grid (x_lo, xhi) and array of samples (x). |
histogram2d(x, y, x_grid, y_grid) |
Create 21D histogram from a binned grid (x_grid, y_grid) and array of samples (x, and y). |
igam(a,x) |
Calculate the regularized incomplete Gamma function (lower). |
igamc(a,x) |
Calculate the complement of the regularized incomplete Gamma function (upper). |
incbet(a,b,x) |
Calculate the incomplete Beta function |
interpolate(xout, xin, yin[, function]) |
One-dimensional interpolation. |
is_binary_file(filename) |
Estimate if a file is a binary file. |
lgam(z) |
Calculate the log (base e) of the Gamma function. |
linear_interp(xout, xin, yin) |
Linear one-dimensional interpolation. |
multinormal_pdf(x, mu, sigma) |
The PDF of a multivariate-normal. |
multit_pdf(x, mu, sigma, dof) |
The PDF of a multivariate student-t. |
nearest_interp(xout, xin, yin) |
Nearest-neighbor one-dimensional interpolation. |
neville(xout, xin, yin) |
Polynomial one-dimensional interpolation using Neville’s method [1]_. |
neville2d(xinterp, yinterp, x, y, fval) |
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new_muller(fcn, xa, xb[, fa, fb, args, ...]) |
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normalize |
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numpy_convolve(a, b) |
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pad_bounding_box |
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parallel_map(function, sequence[, numcores]) |
A parallelized version of the native Python map function that utilizes the Python multiprocessing module to divide and conquer sequence. |
param_apply_limits(param_limits, par[, ...]) |
apply the dictionary of guess values to parameter, also, save the |
parse_expr(expr) |
parse a filter expression into numerical components for notice/ignore |
poisson_noise(x) |
Draw samples from a Poisson distribution. |
print_fields(names, vals[, converters]) |
Given a list of strings names and mapping vals, where names is a subset of vals.keys(), return a listing of name/value pairs printed one per line in the format ‘<name> = <value>’. |
quantile(sorted_array, f) |
Return the quantile element from sorted_array, where f is [0,1] using linear interpolation. |
rebin(y0, x0lo, x0hi, x1lo, x1hi) |
Rebin a histogram. |
sao_arange |
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sao_fcmp(x, y, tol) |
Compare y to x, using an absolute tolerance. |
set_origin |
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sum_intervals |
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zeroin(fcn, xa, xb[, fa, fb, args, maxfev, tol]) |
Obtain a zero of a function of one variable using Brent’s root finder. |
Classes
NoNewAttributesAfterInit() |
Prevents attribute deletion and setting of new attributes after __init__ has been called. |