+001: import numpy as np

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 002: cimport numpy as np

+003: import math

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 004: cimport cython

 005: 

 006: from libc.math cimport sqrt, log, M_PI, fmax, isnan

 007: cimport cost_function

 008: from cost_function cimport mll_mean, mll_var, mll_meanvar, mll_meanvar_exp, mll_meanvar_poisson, mbic_var, mbic_meanvar, mbic_mean, mbic_meanvar_exp, mbic_meanvar_poisson

 009: from cost_function cimport mll_nonparametric_ed, mll_nonparametric_ed_mbic

 010: 

 011: cimport utils

 012: from utils cimport order_vec

 013: from cython.parallel import prange

 014: 

 015: 

+016: DTYPE = np.float64

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+017: ITYPE = np.int64

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+018: ctypedef np.float64_t DTYPE_t

typedef __pyx_t_5numpy_float64_t __pyx_t_14pychangepoints_11cython_pelt_DTYPE_t;

 019: ctypedef np.int64_t ITYPE_t

 020: 

 021: 

 022: """

 023: def cpelt2 (np.ndarray[DTYPE_t, ndim=3] sumstat, double pen, int minseglen):

 024:     cdef int n = sumstat.shape[0] 

 025:     cdef int error = 0

 026:     cdef int nchecklist

 027: 

 028:     cdef int [:] cptsout = np.zeros(n+1).astype(int)

 029:     cdef int [:] lastchangecpts = np.zeros(2*(n + 1)).astype(int)

 030:     cdef double [:] lastchangelike = np.zeros(n+1)

 031:     cdef int [:] checklist = np.zeros(n+1).astype(int)

 032:     cdef double [:] tmplike = np.zeros(n+1)

 033:     cdef int [:] tmpt = np.zeros(n+1).astype(int)

 034:     cdef int [:] numchangecpts = np.zeros(n+1).astype(int)

 035:     cdef int tstar,i,j,k,whichout,nchecktmp

 036:     cdef double minout

 037: 

 038:     lastchangelike[0] = -pen

 039:     lastchangecpts[0] = 0

 040:     lastchangecpts[n + 0] = 0

 041:     lastchangecpts[n + 1] = 1

 042:     lastchangecpts[n + 2] = 2

 043:     lastchangecpts[n + 3] = 3

 044:     for j in range(minseglen, 2 * minseglen):

 045:         lastchangelike[j] = mll_mean(sumstat[j, 0], sumstat[j, 1], j)

 046:         lastchangecpts[j] = 0

 047:     nchecklist = 2

 048:     checklist[0] = 0

 049:     checklist[1] = minseglen

 050:     for tstar in range(2 * minseglen, n + 1):

 051:         for i in range(0,nchecklist):

 052:             print(tstar-checklist[i])

 053:             tmplike[i]=lastchangelike[checklist[i]] + mll_mean(sumstat[tstar,0]-sumstat[checklist[i],0],sumstat[tstar,1]-sumstat[checklist[i],1], tstar-checklist[i])+pen

 054:         whichout = np.argmin(tmplike[0:nchecklist])

 055:         minout = tmplike[whichout]

 056:         lastchangelike[tstar] = minout

 057:         lastchangecpts[tstar] = checklist[whichout]

 058:         lastchangecpts[n + tstar] = tstar

 059:         nchecktmp = 0

 060:         for k in range(0,nchecklist):

 061:             if (tmplike[k]<=lastchangelike[tstar] + pen):

 062:                 checklist[nchecktmp]=checklist[k]

 063:                 nchecktmp+=1

 064:         checklist[nchecktmp] = (tstar - (minseglen - 1))

 065:         nchecktmp += 1

 066:         nchecklist = nchecktmp

 067: 

 068:     cdef int ncpts = 0

 069:     cdef int last = n

 070:     changepoints = np.array(0)

 071:     while (last != 0):

 072:         if (last != n):

 073:             changepoints = np.append(changepoints, last)

 074:         last = int(lastchangecpts[last])

 075:         ncpts += 1

 076:     changepoints = np.sort(changepoints)

 077:     return changepoints

 078: """

 079: @cython.wraparound(False)

 080: @cython.boundscheck(False)

+081: def cpelt(np.ndarray[DTYPE_t, ndim=1] sumstat, double pen, int minseglen, int n, str method):

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/* … */
    goto __pyx_L3;
  }

+117:         current_cost = mll_meanvar_exp

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mll_meanvar_exp;

+118:     elif method == "mll_meanvar_poisson":

  __pyx_t_11 = (__Pyx_PyString_Equals(__pyx_v_method, __pyx_n_s_mll_meanvar_poisson, Py_EQ)); if (unlikely(__pyx_t_11 < 0)) __PYX_ERR(0, 118, __pyx_L1_error)
  __pyx_t_12 = (__pyx_t_11 != 0);
  if (__pyx_t_12) {
/* … */
    goto __pyx_L3;
  }

+119:         current_cost = mll_meanvar_poisson

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mll_meanvar_poisson;

+120:     elif method == "mbic_var":

  __pyx_t_12 = (__Pyx_PyString_Equals(__pyx_v_method, __pyx_n_s_mbic_var, Py_EQ)); if (unlikely(__pyx_t_12 < 0)) __PYX_ERR(0, 120, __pyx_L1_error)
  __pyx_t_11 = (__pyx_t_12 != 0);
  if (__pyx_t_11) {
/* … */
    goto __pyx_L3;
  }

+121:         current_cost = mbic_var

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mbic_var;

+122:     elif method == "mbic_meanvar":

  __pyx_t_11 = (__Pyx_PyString_Equals(__pyx_v_method, __pyx_n_s_mbic_meanvar, Py_EQ)); if (unlikely(__pyx_t_11 < 0)) __PYX_ERR(0, 122, __pyx_L1_error)
  __pyx_t_12 = (__pyx_t_11 != 0);
  if (__pyx_t_12) {
/* … */
    goto __pyx_L3;
  }

+123:         current_cost = mbic_meanvar

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mbic_meanvar;

+124:     elif method == "mbic_mean":

  __pyx_t_12 = (__Pyx_PyString_Equals(__pyx_v_method, __pyx_n_s_mbic_mean, Py_EQ)); if (unlikely(__pyx_t_12 < 0)) __PYX_ERR(0, 124, __pyx_L1_error)
  __pyx_t_11 = (__pyx_t_12 != 0);
  if (__pyx_t_11) {
/* … */
    goto __pyx_L3;
  }

+125:         current_cost = mbic_mean

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mbic_mean;

+126:     elif method == "mbic_meanvar_exp":

  __pyx_t_11 = (__Pyx_PyString_Equals(__pyx_v_method, __pyx_n_s_mbic_meanvar_exp, Py_EQ)); if (unlikely(__pyx_t_11 < 0)) __PYX_ERR(0, 126, __pyx_L1_error)
  __pyx_t_12 = (__pyx_t_11 != 0);
  if (__pyx_t_12) {
/* … */
    goto __pyx_L3;
  }

+127:         current_cost = mbic_meanvar_exp

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mbic_meanvar_exp;

+128:     elif method == "mbic_meanvar_poisson":

  __pyx_t_12 = (__Pyx_PyString_Equals(__pyx_v_method, __pyx_n_s_mbic_meanvar_poisson, Py_EQ)); if (unlikely(__pyx_t_12 < 0)) __PYX_ERR(0, 128, __pyx_L1_error)
  __pyx_t_11 = (__pyx_t_12 != 0);
  if (__pyx_t_11) {
/* … */
    goto __pyx_L3;
  }

+129:         current_cost = mbic_meanvar_poisson

    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mbic_meanvar_poisson;

 130:     else:

+131:         current_cost = mbic_meanvar

  /*else*/ {
    __pyx_v_current_cost = __pyx_f_14pychangepoints_13cost_function_mbic_meanvar;
  }
  __pyx_L3:;

 132: 

 133:     cdef int j

+134:     for j in range(minseglen, 2*minseglen):

  __pyx_t_13 = (2 * __pyx_v_minseglen);
  __pyx_t_14 = __pyx_t_13;
  for (__pyx_t_15 = __pyx_v_minseglen; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) {
    __pyx_v_j = __pyx_t_15;

+135:         lastchangelike[j] = current_cost(sumstat[j], sumstat[j+n+1], sumstat[j+2*(n+1)], j)

    __pyx_t_16 = __pyx_v_j;
    __pyx_t_17 = ((__pyx_v_j + __pyx_v_n) + 1);
    __pyx_t_18 = (__pyx_v_j + (2 * (__pyx_v_n + 1)));
    __pyx_t_19 = __pyx_v_j;
    *((double *) ( /* dim=0 */ (__pyx_v_lastchangelike.data + __pyx_t_19 * __pyx_v_lastchangelike.strides[0]) )) = __pyx_v_current_cost((*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_16, __pyx_pybuffernd_sumstat.diminfo[0].strides)), (*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_17, __pyx_pybuffernd_sumstat.diminfo[0].strides)), (*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_18, __pyx_pybuffernd_sumstat.diminfo[0].strides)), __pyx_v_j);
  }

+136:     for j in range(minseglen, 2*minseglen):

  __pyx_t_13 = (2 * __pyx_v_minseglen);
  __pyx_t_14 = __pyx_t_13;
  for (__pyx_t_15 = __pyx_v_minseglen; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) {
    __pyx_v_j = __pyx_t_15;

+137:         numchangecpts[j] = 1

    __pyx_t_18 = __pyx_v_j;
    *((int *) ( /* dim=0 */ (__pyx_v_numchangecpts.data + __pyx_t_18 * __pyx_v_numchangecpts.strides[0]) )) = 1;
  }

+138:     for j in range(minseglen, 2*minseglen):

  __pyx_t_13 = (2 * __pyx_v_minseglen);
  __pyx_t_14 = __pyx_t_13;
  for (__pyx_t_15 = __pyx_v_minseglen; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) {
    __pyx_v_j = __pyx_t_15;

+139:         lastchangecpts[j] = 1

    __pyx_t_17 = __pyx_v_j;
    *((int *) ( /* dim=0 */ (__pyx_v_lastchangecpts.data + __pyx_t_17 * __pyx_v_lastchangecpts.strides[0]) )) = 1;
  }

 140:     cdef DTYPE_t a1 , a2, a3

 141: 

+142:     nchecklist = 2

  __pyx_v_nchecklist = 2;

+143:     checklist[0] = 0

  __pyx_t_16 = 0;
  *((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_16 * __pyx_v_checklist.strides[0]) )) = 0;

+144:     checklist[1] = minseglen

  __pyx_t_20 = 1;
  *((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_20 * __pyx_v_checklist.strides[0]) )) = __pyx_v_minseglen;

+145:     for tstar in range(2*minseglen, n+1):

  __pyx_t_13 = (__pyx_v_n + 1);
  __pyx_t_14 = __pyx_t_13;
  for (__pyx_t_15 = (2 * __pyx_v_minseglen); __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) {
    __pyx_v_tstar = __pyx_t_15;

+146:         if lastchangelike[tstar] == 0:

    __pyx_t_21 = __pyx_v_tstar;
    __pyx_t_11 = (((*((double *) ( /* dim=0 */ (__pyx_v_lastchangelike.data + __pyx_t_21 * __pyx_v_lastchangelike.strides[0]) ))) == 0.0) != 0);
    if (__pyx_t_11) {
/* … */
    }

+147:             for i in range(0, nchecklist+1):

      __pyx_t_22 = (__pyx_v_nchecklist + 1);
      __pyx_t_23 = __pyx_t_22;
      for (__pyx_t_24 = 0; __pyx_t_24 < __pyx_t_23; __pyx_t_24+=1) {
        __pyx_v_i = __pyx_t_24;

+148:                 a1 = sumstat[tstar]-sumstat[checklist[i]]

        __pyx_t_21 = __pyx_v_tstar;
        __pyx_t_25 = __pyx_v_i;
        __pyx_t_26 = (*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_25 * __pyx_v_checklist.strides[0]) )));
        __pyx_v_a1 = ((*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_sumstat.diminfo[0].strides)) - (*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_sumstat.diminfo[0].strides)));

+149:                 a2 = sumstat[tstar+n+1]-sumstat[checklist[i]+n+1]

        __pyx_t_25 = ((__pyx_v_tstar + __pyx_v_n) + 1);
        __pyx_t_26 = __pyx_v_i;
        __pyx_t_21 = (((*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_26 * __pyx_v_checklist.strides[0]) ))) + __pyx_v_n) + 1);
        __pyx_v_a2 = ((*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_25, __pyx_pybuffernd_sumstat.diminfo[0].strides)) - (*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_sumstat.diminfo[0].strides)));

+150:                 a3 = sumstat[tstar+2*(n+1)]-sumstat[checklist[i]+2*(n+1)]

        __pyx_t_26 = (__pyx_v_tstar + (2 * (__pyx_v_n + 1)));
        __pyx_t_21 = __pyx_v_i;
        __pyx_t_25 = ((*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_21 * __pyx_v_checklist.strides[0]) ))) + (2 * (__pyx_v_n + 1)));
        __pyx_v_a3 = ((*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_sumstat.diminfo[0].strides)) - (*__Pyx_BufPtrStrided1d(__pyx_t_14pychangepoints_11cython_pelt_DTYPE_t *, __pyx_pybuffernd_sumstat.rcbuffer->pybuffer.buf, __pyx_t_25, __pyx_pybuffernd_sumstat.diminfo[0].strides)));

+151:                 tmplike[i] = lastchangelike[checklist[i]] + current_cost(a1, a2, a3, tstar-checklist[i])+pen

        __pyx_t_21 = __pyx_v_i;
        __pyx_t_25 = (*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_21 * __pyx_v_checklist.strides[0]) )));
        __pyx_t_26 = __pyx_v_i;
        __pyx_t_27 = __pyx_v_i;
        *((double *) ( /* dim=0 */ (__pyx_v_tmplike.data + __pyx_t_27 * __pyx_v_tmplike.strides[0]) )) = (((*((double *) ( /* dim=0 */ (__pyx_v_lastchangelike.data + __pyx_t_25 * __pyx_v_lastchangelike.strides[0]) ))) + __pyx_v_current_cost(__pyx_v_a1, __pyx_v_a2, __pyx_v_a3, (__pyx_v_tstar - (*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_26 * __pyx_v_checklist.strides[0]) )))))) + __pyx_v_pen);
      }

+152:             minout = tmplike[0]

      __pyx_t_26 = 0;
      __pyx_v_minout = (*((double *) ( /* dim=0 */ (__pyx_v_tmplike.data + __pyx_t_26 * __pyx_v_tmplike.strides[0]) )));

+153:             whichout = 0

      __pyx_v_whichout = 0;

+154:             for i in range(0, nchecklist):

      __pyx_t_24 = __pyx_v_nchecklist;
      __pyx_t_28 = __pyx_t_24;
      for (__pyx_t_29 = 0; __pyx_t_29 < __pyx_t_28; __pyx_t_29+=1) {
        __pyx_v_i = __pyx_t_29;

+155:                 if tmplike[i] <= minout:

        __pyx_t_26 = __pyx_v_i;
        __pyx_t_11 = (((*((double *) ( /* dim=0 */ (__pyx_v_tmplike.data + __pyx_t_26 * __pyx_v_tmplike.strides[0]) ))) <= __pyx_v_minout) != 0);
        if (__pyx_t_11) {
/* … */
        }
      }

+156:                     minout = tmplike[i]

          __pyx_t_26 = __pyx_v_i;
          __pyx_v_minout = (*((double *) ( /* dim=0 */ (__pyx_v_tmplike.data + __pyx_t_26 * __pyx_v_tmplike.strides[0]) )));

+157:                     whichout = i

          __pyx_v_whichout = __pyx_v_i;

+158:             lastchangelike[tstar] = minout

      __pyx_t_26 = __pyx_v_tstar;
      *((double *) ( /* dim=0 */ (__pyx_v_lastchangelike.data + __pyx_t_26 * __pyx_v_lastchangelike.strides[0]) )) = __pyx_v_minout;

+159:             lastchangecpts[tstar] = checklist[whichout]

      __pyx_t_21 = __pyx_v_whichout;
      __pyx_t_25 = __pyx_v_tstar;
      *((int *) ( /* dim=0 */ (__pyx_v_lastchangecpts.data + __pyx_t_25 * __pyx_v_lastchangecpts.strides[0]) )) = (*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_21 * __pyx_v_checklist.strides[0]) )));

+160:             numchangecpts[tstar] = numchangecpts[lastchangecpts[tstar]]+1

      __pyx_t_21 = __pyx_v_tstar;
      __pyx_t_30 = (*((int *) ( /* dim=0 */ (__pyx_v_lastchangecpts.data + __pyx_t_21 * __pyx_v_lastchangecpts.strides[0]) )));
      __pyx_t_31 = __pyx_v_tstar;
      *((int *) ( /* dim=0 */ (__pyx_v_numchangecpts.data + __pyx_t_31 * __pyx_v_numchangecpts.strides[0]) )) = ((*((int *) ( /* dim=0 */ (__pyx_v_numchangecpts.data + __pyx_t_30 * __pyx_v_numchangecpts.strides[0]) ))) + 1);

+161:             nchecktmp = 0

      __pyx_v_nchecktmp = 0;

+162:             for i in range(0, nchecklist):

      __pyx_t_24 = __pyx_v_nchecklist;
      __pyx_t_28 = __pyx_t_24;
      for (__pyx_t_29 = 0; __pyx_t_29 < __pyx_t_28; __pyx_t_29+=1) {
        __pyx_v_i = __pyx_t_29;

+163:                 if(tmplike[i] <= (lastchangelike[tstar]+pen)):

        __pyx_t_21 = __pyx_v_i;
        __pyx_t_30 = __pyx_v_tstar;
        __pyx_t_11 = (((*((double *) ( /* dim=0 */ (__pyx_v_tmplike.data + __pyx_t_21 * __pyx_v_tmplike.strides[0]) ))) <= ((*((double *) ( /* dim=0 */ (__pyx_v_lastchangelike.data + __pyx_t_30 * __pyx_v_lastchangelike.strides[0]) ))) + __pyx_v_pen)) != 0);
        if (__pyx_t_11) {
/* … */
        }
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+164:                     checklist[nchecktmp] = checklist[i]

          __pyx_t_30 = __pyx_v_i;
          __pyx_t_21 = __pyx_v_nchecktmp;
          *((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_21 * __pyx_v_checklist.strides[0]) )) = (*((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_30 * __pyx_v_checklist.strides[0]) )));

+165:                     nchecktmp = nchecktmp+1

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+166:             nchecklist = nchecktmp

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+167:         checklist[nchecklist] = tstar-(minseglen-1)

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    *((int *) ( /* dim=0 */ (__pyx_v_checklist.data + __pyx_t_30 * __pyx_v_checklist.strides[0]) )) = (__pyx_v_tstar - (__pyx_v_minseglen - 1));

+168:         nchecklist += 1

    __pyx_v_nchecklist = (__pyx_v_nchecklist + 1);
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 169: 

+170:     cdef int ncpts = 0

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+171:     cdef int last = n

  __pyx_v_last = __pyx_v_n;

+172:     while (last != 0):

  while (1) {
    __pyx_t_11 = ((__pyx_v_last != 0) != 0);
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+173:         cptsout[ncpts] = last

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    *((int *) ( /* dim=0 */ (__pyx_v_cptsout.data + __pyx_t_32 * __pyx_v_cptsout.strides[0]) )) = __pyx_v_last;

+174:         last = lastchangecpts[last]

    __pyx_t_33 = __pyx_v_last;
    __pyx_v_last = (*((int *) ( /* dim=0 */ (__pyx_v_lastchangecpts.data + __pyx_t_33 * __pyx_v_lastchangecpts.strides[0]) )));

+175:         ncpts += 1

    __pyx_v_ncpts = (__pyx_v_ncpts + 1);
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+176:     return np.array(cptsout)[0:(ncpts)], ncpts

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 177: 

 178: 

 179: @cython.wraparound(False)

 180: @cython.boundscheck(False)

+181: def cbin_seg(np.ndarray[DTYPE_t, ndim=2] sumstat, ITYPE_t Q, ITYPE_t minseglen, str method):

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static PyObject *__pyx_pw_14pychangepoints_11cython_pelt_3cbin_seg(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
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/* … */
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+228:                 null = (-0.5)*current_cost(sumstat[end, 0]-sumstat[st-1, 0], sumstat[end, 1]-sumstat[st-1, 1], sumstat[end, 2]-sumstat[st-1, 2], end - st + 1)

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 229:             else:

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/* … */
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