Class: CArray

Inherits:
Object
  • Object
show all
Defined in:
lib/carray-gsl/core.rb,
lib/carray-gsl/core.rb

Instance Method Summary collapse

Instance Method Details

#cholesky_decomp ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 181

def cholesky_decomp
  attach {
    c = GSL::Linalg::Cholesky.decomp(self.gm)
    out = c.ca.m
    out["@cholesky"] = c
    return out
  }
end

#cholesky_solve(b) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 190

def cholesky_solve (b)
  CArray.attach(self, b) {
    return GSL::Linalg::Cholesky.solve(self.gm, b.gv).ca.v
  }
end

#eigen_herm ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 215

def eigen_herm
  attach {
    return GSL::Eigen.herm(self.gm).ca.v
  }
end

#eigen_hermv ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 221

def eigen_hermv
  attach {
    e, v = *GSL::Eigen.hermv(self.gm)
    return e.ca.v, v.ca.m
  }
end

#eigen_nonsymm ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 228

def eigen_nonsymm 
  attach {
    return GSL::Eigen.nonsymm(self.gm).ca.v
  }
end

#eigen_nonsymm_Z ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 234

def eigen_nonsymm_Z 
  attach {
    e, z = *GSL::Eigen.nonsymm_Z(self.gm)
    return e.ca.v, z.ca.m
  }
end

#eigen_nonsymmv ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 241

def eigen_nonsymmv 
  attach {
    e, v = *GSL::Eigen.nonsymmv(self.gm)
    return e.ca.v, v.ca.m
  }
end

#eigen_symm ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 202

def eigen_symm 
  attach {
    return GSL::Eigen.symm(self.gm).ca.v
  }
end

#eigen_symmv ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 208

def eigen_symmv
  attach {
    e, v = *GSL::Eigen.symmv(self.gm)
    return e.ca.v, v.ca.m
  }
end

#fit_builtin(*args) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 305

def fit_builtin (*args)
  if args[1].is_a?(String)
    x, func, guess = *args
    CArray.attach(self, x) {
      if guess
        coef, err, chi2, dof =
          *GSL::MultiFit::FdfSolver.fit(x.gv, self.gv, func, guess)
      else
        coef, err, chi2, dof =
          *GSL::MultiFit::FdfSolver.fit(x.gv, self.gv, func)
      end
      return coef.to_a, err.to_a, chi2, dof
    }
  elsif args[2].is_a?(String)
    x, w, func, guess = *args
    CArray.attach(self, x, w) {
      if guess
        coef, err, chi2, dof =
          *GSL::MultiFit::FdfSolver.fit(x.gv, w.gv, self.gv, func, guess)
      else
        coef, err, chi2, dof =
          *GSL::MultiFit::FdfSolver.fit(x.gv, w.gv, self.gv, func)
      end
      return coef.to_a, err.to_a, chi2, dof
    }
  else
    raise ArgumentError, "invalid built-in function specifier"
  end
end

#fit_linear(x) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 248

def fit_linear (x)
  CArray.attach(self, x) {
    c0, c1, c00, c01, c11, chi2, status = 
                       *GSL::Fit.linear(x.gv, self.gv)
    dof   = self.elements - 2
    covar = CA_DOUBLE([[c00, c01],[c01, c11]])
    err   = Array.new(2){|i| Math::sqrt(chi2/dof*covar[i,i]) }
    return [c0, c1], err, chi2, dof, covar
  }
end

#fit_nonlinear(xx, sigma, procf, procdf, parms, errs) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 270

def fit_nonlinear (xx, sigma, procf, procdf, parms, errs)
  n  = self.elements
  np = parms.size
  parms = GSL::Vector[*parms]
  gf = Proc.new { |a, x, y, sigma, f|
    f.ca[] = (procf.call(x, a.to_a) - y) / sigma
  }
  gdf = Proc.new { |a, x, y, sigma, jac| 
    cjac = jac.ca
    df   = procdf.call(x, a.to_a)
    a.size.times do |i|
      cjac[nil, i] = df[i] / sigma
    end
  }
  func   = GSL::MultiFit::Function_fdf.alloc(gf, gdf, np)
  func.set_data(xx, self, sigma)
  lmsder = GSL::MultiFit::FdfSolver::LMSDER
  solver = GSL::MultiFit::FdfSolver.alloc(lmsder, n, np)
  solver.set(func, parms)

  iter = 0
  begin
    iter += 1
    status = solver.iterate
    status = solver.test_delta(*errs)
  end while status == GSL::CONTINUE and iter < 500

  coef  = solver.position.to_a
  chi2  = GSL::pow_2(solver.f.dnrm2)
  dof   = n - np
  covar = solver.covar(0.0).ca
  err   = Array.new(np){|i| Math::sqrt(chi2/dof*covar[i,i]) }
  return coef, err, chi2, dof, covar
end

#fit_wlinear(x, w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 259

def fit_wlinear (x, w)
  CArray.attach(self, x, w) {
    c0, c1, c00, c01, c11, chi2, status = 
                       *GSL::Fit.wlinear(x.gv, w.gv, self.gv)
    dof   = self.elements - 2
    covar = CA_DOUBLE([[c00, c01],[c01, c11]])
    err   = Array.new(2){|i| Math::sqrt(chi2/dof*covar[i,i]) }
    return [c0, c1], err, chi2, dof, covar
  }
end

#hh_solve(b) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 196

def hh_solve (b)
  CArray.attach(self, b) {
    return GSL::Linalg::HH.solve(self.gm, b.gv).ca.v
  }
end

#lu_decomp ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 96

def lu_decomp
  attach {
    lu, perm, sign = *GSL::Linalg::LU.decomp(self.gm)
    out = lu.ca.m
    out.attribute["@A"]    = self.gm
    out.attribute["@LU"]   = lu
    out.attribute["@perm"] = perm
    out.attribute["@sign"] = sign
    return out
  }
end

#lu_det ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 137

def lu_det
  attach {
    return GSL::Linalg::LU.det(self.gm)
  }
end

#lu_invert ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 131

def lu_invert
  attach {
    return GSL::Linalg::LU.invert(self.gm).ca.m
  }
end

#lu_refine(b, x) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 122

def lu_refine (b, x)
  CArray.attach(self, b, x) {
    a    = self["@A"]
    lu   = self["@LU"]
    perm = self["@perm"]
    return GSL::Linalg::LU.refine(a, lu, perm, b.gv, x.gv).first.ca.v
  }
end

#lu_solve(b) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 108

def lu_solve (b)
  if self["@LU"]
    CArray.attach(self, b) {
      lu   = self["@LU"]
      perm = self["@perm"]
      return GSL::Linalg::LU.solve(lu, perm, b.gv).ca.v
    }
  else
    CArray.attach(self, b) {
      return GSL::Linalg::LU.solve(self.gm, b.gv).ca.v
    }
  end
end

#qr_decomp ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 143

def qr_decomp
  attach {
    qr, tau = *GSL::Linalg::QR.decomp(self.gm)
    out = qr.ca.m
    out["@qr"] = qr
    out["@tau"] = tau
    return out
  }
end

#qr_solve(b) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 153

def qr_solve (b)
  CArray.attach(self, b) {
    return GSL::Linalg::QR.solve(self.gm, b.gv).ca.v
  }
end

#qr_unpack ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 159

def qr_unpack 
  attach {
    qr  = self["@qr"]
    tau = self["@tau"]
    q, r = *GSL::Linalg::QR.unpack(qr, tau)
    return q.ca.m, r.ca.m
  }
end

#stats_absdev ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 389

def stats_absdev 
  attach {
    return GSL::Stats.absdev(self.gv)
  }
end

#stats_absdev_m(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 395

def stats_absdev_m (mean)
  attach {
    return GSL::Stats.absdev_m(self.gv, mean)
  }
end

#stats_kurtosis ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 413

def stats_kurtosis 
  attach {
    return GSL::Stats.kurtosis(self.gv)
  }
end

#stats_kurtosis_m_sd(mean, sd) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 419

def stats_kurtosis_m_sd (mean, sd)
  attach {
    return GSL::Stats.kurtosis(self.gv, mean, sd)
  }
end

#stats_lag1_autocorrelation ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 425

def stats_lag1_autocorrelation 
  attach {
    return GSL::Stats.lag1_autocorrelation(self.gv)
  }
end

#stats_lag1_autocorrelation_m(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 431

def stats_lag1_autocorrelation_m (mean)
  attach {
    return GSL::Stats.lag1_autocorrelation(self.gv, mean)
  }
end

#stats_max ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 528

def stats_max 
  attach {
    return GSL::Stats.max(self.gv)
  }
end

#stats_max_index ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 546

def stats_max_index
  attach {
    return GSL::Stats.max_index(self.gv)
  }
end

#stats_mean ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 335

def stats_mean 
  attach {
    return GSL::Stats.mean(self.gv)
  }
end

#stats_median_from_sorted_data ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 564

def stats_median_from_sorted_data
  attach {
    return GSL::Stats.median_from_sorted_data(self.gv)
  }
end

#stats_min ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 534

def stats_min 
  attach {
    return GSL::Stats.min(self.gv)
  }
end

#stats_min_index ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 552

def stats_min_index
  attach {
    return GSL::Stats.min_index(self.gv)
  }
end

#stats_minmax ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 540

def stats_minmax
  attach {
    return GSL::Stats.minmax(self.gv)
  }
end

#stats_minmax_index ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 558

def stats_minmax_index
  attach {
    return GSL::Stats.minmax_index(self.gv)
  }
end

#stats_quantile_from_sorted_data ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 570

def stats_quantile_from_sorted_data
  attach {
    return GSL::Stats.quantile_from_sorted_data(self.gv)
  }
end

#stats_sd ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 353

def stats_sd 
  attach {
    return GSL::Stats.sd(self.gv)
  }
end

#stats_sd_m(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 359

def stats_sd_m (mean)
  attach {
    return GSL::Stats.sd_m(self.gv, mean)
  }
end

#stats_sd_with_fixed_mean(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 383

def stats_sd_with_fixed_mean (mean)
  attach {
    return GSL::Stats.sd_with_fixed_mean(self.gv, mean)
  }
end

#stats_skew ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 401

def stats_skew 
  attach {
    return GSL::Stats.skew(self.gv)
  }
end

#stats_skew_m_sd(mean, sd) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 407

def stats_skew_m_sd (mean, sd)
  attach {
    return GSL::Stats.skew(self.gv, mean, sd)
  }
end

#stats_tss ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 365

def stats_tss 
  attach {
    return GSL::Stats.tss(self.gv)
  }
end

#stats_tss_m(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 371

def stats_tss_m (mean)
  attach {
    return GSL::Stats.tss_m(self.gv, mean)
  }
end

#stats_variance ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 341

def stats_variance 
  attach {
    return GSL::Stats.variance(self.gv)
  }
end

#stats_variance_m(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 347

def stats_variance_m (mean)
  attach {
    return GSL::Stats.variance_m(self.gv, mean)
  }
end

#stats_variance_with_fixed_mean(mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 377

def stats_variance_with_fixed_mean (mean)
  attach {
    return GSL::Stats.variance_with_fixed_mean(self.gv, mean)
  }
end

#stats_wabsdev(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 492

def stats_wabsdev (w)
  CArray.attach(self, w) {
    return GSL::Stats.wabsdev(self.gv, w.gv)
  }
end

#stats_wabsdev_m(w, mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 498

def stats_wabsdev_m (w, mean)
  CArray.attach(self, w) {
    return GSL::Stats.wabsdev_m(self.gv, w.gv, mean)
  }
end

#stats_wkurtosis(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 516

def stats_wkurtosis (w)
  CArray.attach(self, w) {
    return GSL::Stats.wkurtosis(self.gv, w.gv)
  }
end

#stats_wkurtosis_m_sd(w, mean, sd) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 522

def stats_wkurtosis_m_sd (w, mean, sd)
  CArray.attach(self, w) {
    return GSL::Stats.wkurtosis(self.gv, w.gv, mean, sd)
  }
end

#stats_wmean(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 438

def stats_wmean (w)
  CArray.attach(self, w) {
    return GSL::Stats.wmean(self.gv, w.gv)
  }
end

#stats_wsd(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 456

def stats_wsd (w)
  CArray.attach(self, w) {
    return GSL::Stats.wsd(self.gv, w.gv)
  }
end

#stats_wsd_m(w, mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 462

def stats_wsd_m (w, mean)
  CArray.attach(self, w) {
    return GSL::Stats.wsd_m(self.gv, w.gv, mean)
  }
end

#stats_wsd_with_fixed_mean(w, mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 486

def stats_wsd_with_fixed_mean (w, mean)
  CArray.attach(self, w) {
    return GSL::Stats.wsd_with_fixed_mean(self.gv, w.gv, mean)
  }
end

#stats_wskew(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 504

def stats_wskew (w)
  CArray.attach(self, w) {
    return GSL::Stats.wskew(self.gv, w.gv)
  }
end

#stats_wskew_m_sd(w, mean, sd) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 510

def stats_wskew_m_sd (w, mean, sd)
  CArray.attach(self, w) {
    return GSL::Stats.wskew(self.gv, w.gv, mean, sd)
  }
end

#stats_wtss(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 468

def stats_wtss (w)
  CArray.attach(self, w) {
    return GSL::Stats.wtss(self.gv, w.gv)
  }
end

#stats_wtss_m(w, mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 474

def stats_wtss_m (w, mean)
  CArray.attach(self, w) {
    return GSL::Stats.wtss_m(self.gv, w.gv, mean)
  }
end

#stats_wvariance(w) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 444

def stats_wvariance (w)
  CArray.attach(self, w) {
    return GSL::Stats.wvariance(self.gv, w.gv)
  }
end

#stats_wvariance_m(w, mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 450

def stats_wvariance_m (w, mean)
  CArray.attach(self, w) {
    return GSL::Stats.wvariance_m(self.gv, w.gv, mean)
  }
end

#stats_wvariance_with_fixed_mean(w, mean) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 480

def stats_wvariance_with_fixed_mean (w, mean)
  CArray.attach(self, w) {
    return GSL::Stats.wvariance_with_fixed_mean(self.gv, w.gv, mean)
  }
end

#sv_decomp ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 168

def sv_decomp
  attach {
    u, v, s = *GSL::Linalg::SV.decomp(self.gm)
    return u.ca.m, v.ca.m, s.ca.v
  }
end

#sv_solve(b) ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 175

def sv_solve (b)
  CArray.attach(self, b) {
    return GSL::Linalg::SV.solve(self.gm, b.gv).ca.v
  }
end

#vt ⇒ Object 



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# File 'lib/carray-gsl/core.rb', line 763

def vt
  return v.t
end