diff --git a/causalml/inference/tree/causaltree.html b/causalml/inference/tree/causaltree.html deleted file mode 100644 index a07ba4e7..00000000 --- a/causalml/inference/tree/causaltree.html +++ /dev/null @@ -1,3588 +0,0 @@ - - - - - - Cython: causaltree.pyx - - - -

Generated by Cython 0.29.24

-

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Raw output: causaltree.c

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+001: # cython: cdivision=True
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 002: # cython: boundscheck=False
-
 003: # cython: wraparound=False
-
 004:
-
 005:
-
+006: import logging
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+007: import numbers
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+008: import numpy as np
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+009: import pandas as pd
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 010:
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+011: from math import ceil
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+012: from scipy.sparse import issparse
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+013: from scipy.stats import norm
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 014: from sklearn.tree._criterion cimport RegressionCriterion
-
 015: from sklearn.tree._criterion cimport SIZE_t, DOUBLE_t
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+016: from sklearn.tree._splitter import BestSplitter
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+017: from sklearn.tree._tree import DepthFirstTreeBuilder, DOUBLE, DTYPE, Tree
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+018: from sklearn.utils import check_array, check_random_state
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 019:
-
+020: from causalml.inference.meta.utils import check_treatment_vector
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 021:
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+022: logger = logging.getLogger('causalml')
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 023:
-
 024:
-
+025: cdef class CausalMSE(RegressionCriterion):
-
struct __pyx_obj_8causalml_9inference_4tree_10causaltree_CausalMSE {
-  struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion __pyx_base;
-};
-/* … */
-struct __pyx_vtabstruct_8causalml_9inference_4tree_10causaltree_CausalMSE {
-  struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion __pyx_base;
-};
-static struct __pyx_vtabstruct_8causalml_9inference_4tree_10causaltree_CausalMSE *__pyx_vtabptr_8causalml_9inference_4tree_10causaltree_CausalMSE;
-
-
 026:     """Causal Tree mean squared error impurity criterion.
-
 027:
-
 028:         CausalTreeMSE = right_effect + left_effect
-
 029:
-
 030:         where,
-
 031:
-
 032:         effect = alpha * tau^2 - (1 - alpha) * (1 + train_to_est_ratio) * (VAR_tr / p + VAR_cont / (1 - p))
-
 033:     """
-
 034:
-
+035:     cdef void node_value(self, double* dest) nogil:
-
static void __pyx_f_8causalml_9inference_4tree_10causaltree_9CausalMSE_node_value(struct __pyx_obj_8causalml_9inference_4tree_10causaltree_CausalMSE *__pyx_v_self, double *__pyx_v_dest) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_is_treated;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_y_ik;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight;
-  double __pyx_v_node_ct;
-  double __pyx_v_node_tr;
-  double __pyx_v_node_ct_sum;
-  double __pyx_v_node_tr_sum;
-  double __pyx_v_one_over_eps;
-/* … */
-  /* function exit code */
-  goto __pyx_L0;
-  __pyx_L1_error:;
-  __Pyx_WriteUnraisable("causalml.inference.tree.causaltree.CausalMSE.node_value", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 1);
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-}
-
 036:         """Compute the node value of samples[start:end] into dest."""
-
 037:
-
+038:         cdef SIZE_t start = self.start
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  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.start;
-  __pyx_v_start = __pyx_t_1;
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+039:         cdef SIZE_t end = self.end
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  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_1;
-
 040:
-
 041:         cdef SIZE_t i
-
 042:         cdef SIZE_t p
-
 043:         cdef DOUBLE_t is_treated
-
 044:         cdef DOUBLE_t y_ik
-
 045:
-
+046:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_2;
-
+047:         cdef DOUBLE_t* sample_weight = self.sample_weight
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.sample_weight;
-  __pyx_v_sample_weight = __pyx_t_3;
-
 048:
-
+049:         cdef double node_ct = 0.0
-
  __pyx_v_node_ct = 0.0;
-
+050:         cdef double node_tr = 0.0
-
  __pyx_v_node_tr = 0.0;
-
+051:         cdef double node_ct_sum = 0.0
-
  __pyx_v_node_ct_sum = 0.0;
-
+052:         cdef double node_tr_sum = 0.0
-
  __pyx_v_node_tr_sum = 0.0;
-
+053:         cdef double one_over_eps = 1e5
-
  __pyx_v_one_over_eps = 1e5;
-
 054:
-
+055:         for p in range(start, end):
-
  __pyx_t_1 = __pyx_v_end;
-  __pyx_t_4 = __pyx_t_1;
-  for (__pyx_t_5 = __pyx_v_start; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
-    __pyx_v_p = __pyx_t_5;
-
+056:             i = samples[p]
-
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);
-
 057:
-
+058:             if sample_weight != NULL:
-
    __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
-    if (__pyx_t_6) {
-/* … */
-    }
-
 059:                 # the weights of 1 and 1 + eps are used for treatment and control respectively
-
+060:                 is_treated = (sample_weight[i] - 1.0) * one_over_eps
-
      __pyx_v_is_treated = (((__pyx_v_sample_weight[__pyx_v_i]) - 1.0) * __pyx_v_one_over_eps);
-
 061:
-
 062:             # assume that there is only one output (k = 0)
-
+063:             y_ik = self.y[i, 0]
-
    if (unlikely(!__pyx_v_self->__pyx_base.__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 63, __pyx_L1_error)}
-    __pyx_t_7 = __pyx_v_i;
-    __pyx_t_8 = 0;
-    __pyx_v_y_ik = (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.__pyx_base.y.strides[0]) )) + __pyx_t_8)) )));
-
 064:
-
+065:             node_tr += is_treated
-
    __pyx_v_node_tr = (__pyx_v_node_tr + __pyx_v_is_treated);
-
+066:             node_ct += 1. - is_treated
-
    __pyx_v_node_ct = (__pyx_v_node_ct + (1. - __pyx_v_is_treated));
-
+067:             node_tr_sum += y_ik * is_treated
-
    __pyx_v_node_tr_sum = (__pyx_v_node_tr_sum + (__pyx_v_y_ik * __pyx_v_is_treated));
-
+068:             node_ct_sum += y_ik * (1. - is_treated)
-
    __pyx_v_node_ct_sum = (__pyx_v_node_ct_sum + (__pyx_v_y_ik * (1. - __pyx_v_is_treated)));
-  }
-
 069:
-
 070:         # save the average of treatment effects within a node as a value for the node
-
+071:         dest[0] = node_tr_sum / node_tr - node_ct_sum / node_ct
-
  (__pyx_v_dest[0]) = ((__pyx_v_node_tr_sum / __pyx_v_node_tr) - (__pyx_v_node_ct_sum / __pyx_v_node_ct));
-
 072:
-
+073:     cdef double node_impurity(self) nogil:
-
static double __pyx_f_8causalml_9inference_4tree_10causaltree_9CausalMSE_node_impurity(struct __pyx_obj_8causalml_9inference_4tree_10causaltree_CausalMSE *__pyx_v_self) {
-  CYTHON_UNUSED double *__pyx_v_sum_total;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_is_treated;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_y_ik;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight;
-  double __pyx_v_node_tr;
-  double __pyx_v_node_ct;
-  double __pyx_v_node_sum;
-  double __pyx_v_node_tr_sum;
-  double __pyx_v_node_sq_sum;
-  double __pyx_v_node_tr_sq_sum;
-  double __pyx_v_tr_var;
-  double __pyx_v_ct_var;
-  double __pyx_v_one_over_eps;
-  double __pyx_v_node_tau;
-  double __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
-  __Pyx_WriteUnraisable("causalml.inference.tree.causaltree.CausalMSE.node_impurity", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 1);
-  __pyx_r = 0;
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 074:         """Evaluate the impurity of the current node, i.e. the impurity of
-
 075:            samples[start:end]."""
-
 076:
-
+077:         cdef double* sum_total = self.sum_total
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.sum_total;
-  __pyx_v_sum_total = __pyx_t_1;
-
 078:         cdef double impurity
-
+079:         cdef SIZE_t start = self.start
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start;
-  __pyx_v_start = __pyx_t_2;
-
+080:         cdef SIZE_t end = self.end
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_2;
-
 081:
-
 082:         cdef SIZE_t i
-
 083:         cdef SIZE_t p
-
 084:         cdef DOUBLE_t is_treated
-
 085:         cdef DOUBLE_t y_ik
-
 086:
-
+087:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_3;
-
+088:         cdef DOUBLE_t* sample_weight = self.sample_weight
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.sample_weight;
-  __pyx_v_sample_weight = __pyx_t_4;
-
 089:
-
+090:         cdef double node_tr = 0.0
-
  __pyx_v_node_tr = 0.0;
-
+091:         cdef double node_ct = 0.0
-
  __pyx_v_node_ct = 0.0;
-
+092:         cdef double node_sum = self.sum_total[0]
-
  __pyx_v_node_sum = (__pyx_v_self->__pyx_base.__pyx_base.sum_total[0]);
-
+093:         cdef double node_tr_sum = 0.0
-
  __pyx_v_node_tr_sum = 0.0;
-
+094:         cdef double node_sq_sum = 0.0
-
  __pyx_v_node_sq_sum = 0.0;
-
+095:         cdef double node_tr_sq_sum = 0.0
-
  __pyx_v_node_tr_sq_sum = 0.0;
-
 096:         cdef double tr_var
-
 097:         cdef double ct_var
-
+098:         cdef double one_over_eps = 1e5
-
  __pyx_v_one_over_eps = 1e5;
-
 099:
-
+100:         for p in range(start, end):
-
  __pyx_t_2 = __pyx_v_end;
-  __pyx_t_5 = __pyx_t_2;
-  for (__pyx_t_6 = __pyx_v_start; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
-    __pyx_v_p = __pyx_t_6;
-
+101:             i = samples[p]
-
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);
-
 102:
-
+103:             if sample_weight != NULL:
-
    __pyx_t_7 = ((__pyx_v_sample_weight != NULL) != 0);
-    if (__pyx_t_7) {
-/* … */
-    }
-
 104:                 # the weights of 1 and 1 + eps are used for treatment and control respectively
-
+105:                 is_treated = (sample_weight[i] - 1.0) * one_over_eps
-
      __pyx_v_is_treated = (((__pyx_v_sample_weight[__pyx_v_i]) - 1.0) * __pyx_v_one_over_eps);
-
 106:
-
 107:             # assume that there is only one output (k = 0)
-
+108:             y_ik = self.y[i, 0]
-
    if (unlikely(!__pyx_v_self->__pyx_base.__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 108, __pyx_L1_error)}
-    __pyx_t_8 = __pyx_v_i;
-    __pyx_t_9 = 0;
-    __pyx_v_y_ik = (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.__pyx_base.y.strides[0]) )) + __pyx_t_9)) )));
-
 109:
-
+110:             node_tr += is_treated
-
    __pyx_v_node_tr = (__pyx_v_node_tr + __pyx_v_is_treated);
-
+111:             node_ct += (1. - is_treated)
-
    __pyx_v_node_ct = (__pyx_v_node_ct + (1. - __pyx_v_is_treated));
-
+112:             node_tr_sum += y_ik * is_treated
-
    __pyx_v_node_tr_sum = (__pyx_v_node_tr_sum + (__pyx_v_y_ik * __pyx_v_is_treated));
-
+113:             node_sq_sum += y_ik * y_ik
-
    __pyx_v_node_sq_sum = (__pyx_v_node_sq_sum + (__pyx_v_y_ik * __pyx_v_y_ik));
-
+114:             node_tr_sq_sum += y_ik * y_ik * is_treated
-
    __pyx_v_node_tr_sq_sum = (__pyx_v_node_tr_sq_sum + ((__pyx_v_y_ik * __pyx_v_y_ik) * __pyx_v_is_treated));
-  }
-
 115:
-
+116:         node_tau = node_tr_sum / node_tr - (node_sum - node_tr_sum) / node_ct
-
  __pyx_v_node_tau = ((__pyx_v_node_tr_sum / __pyx_v_node_tr) - ((__pyx_v_node_sum - __pyx_v_node_tr_sum) / __pyx_v_node_ct));
-
+117:         tr_var = node_tr_sq_sum / node_tr - node_tr_sum * node_tr_sum / (node_tr * node_tr)
-
  __pyx_v_tr_var = ((__pyx_v_node_tr_sq_sum / __pyx_v_node_tr) - ((__pyx_v_node_tr_sum * __pyx_v_node_tr_sum) / (__pyx_v_node_tr * __pyx_v_node_tr)));
-
+118:         ct_var = ((node_sq_sum - node_tr_sq_sum) / node_ct -
-
  __pyx_v_ct_var = (((__pyx_v_node_sq_sum - __pyx_v_node_tr_sq_sum) / __pyx_v_node_ct) - (((__pyx_v_node_sum - __pyx_v_node_tr_sum) * (__pyx_v_node_sum - __pyx_v_node_tr_sum)) / (__pyx_v_node_ct * __pyx_v_node_ct)));
-
 119:                   (node_sum - node_tr_sum) * (node_sum - node_tr_sum) / (node_ct * node_ct))
-
 120:
-
+121:         return  (tr_var / node_tr + ct_var / node_ct) - node_tau * node_tau
-
  __pyx_r = (((__pyx_v_tr_var / __pyx_v_node_tr) + (__pyx_v_ct_var / __pyx_v_node_ct)) - (__pyx_v_node_tau * __pyx_v_node_tau));
-  goto __pyx_L0;
-
 122:
-
 123:
-
+124:     cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil:
-
static void __pyx_f_8causalml_9inference_4tree_10causaltree_9CausalMSE_children_impurity(struct __pyx_obj_8causalml_9inference_4tree_10causaltree_CausalMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) {
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
-  double *__pyx_v_sum_left;
-  double *__pyx_v_sum_right;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_is_treated;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_y_ik;
-  double __pyx_v_right_tr;
-  double __pyx_v_right_ct;
-  double __pyx_v_right_sum;
-  double __pyx_v_right_tr_sum;
-  double __pyx_v_right_sq_sum;
-  double __pyx_v_right_tr_sq_sum;
-  double __pyx_v_right_tr_var;
-  double __pyx_v_right_ct_var;
-  double __pyx_v_left_tr;
-  double __pyx_v_left_ct;
-  double __pyx_v_left_sum;
-  double __pyx_v_left_tr_sum;
-  double __pyx_v_left_sq_sum;
-  double __pyx_v_left_tr_sq_sum;
-  double __pyx_v_left_tr_var;
-  double __pyx_v_left_ct_var;
-  double __pyx_v_one_over_eps;
-  double __pyx_v_right_tau;
-  double __pyx_v_left_tau;
-/* … */
-  /* function exit code */
-  goto __pyx_L0;
-  __pyx_L1_error:;
-  __Pyx_WriteUnraisable("causalml.inference.tree.causaltree.CausalMSE.children_impurity", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 1);
-  __pyx_L0:;
-}
-
 125:         """Evaluate the impurity in children nodes, i.e. the impurity of the
-
 126:            left child (samples[start:pos]) and the impurity the right child
-
 127:            (samples[pos:end])."""
-
 128:
-
+129:         cdef DOUBLE_t* sample_weight = self.sample_weight
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.sample_weight;
-  __pyx_v_sample_weight = __pyx_t_1;
-
+130:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_2;
-
+131:         cdef SIZE_t start = self.start
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.start;
-  __pyx_v_start = __pyx_t_3;
-
+132:         cdef SIZE_t pos = self.pos
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.pos;
-  __pyx_v_pos = __pyx_t_3;
-
+133:         cdef SIZE_t end = self.end
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_3;
-
 134:
-
+135:         cdef double* sum_left = self.sum_left
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.sum_left;
-  __pyx_v_sum_left = __pyx_t_4;
-
+136:         cdef double* sum_right = self.sum_right
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.sum_right;
-  __pyx_v_sum_right = __pyx_t_4;
-
 137:
-
 138:         cdef SIZE_t i
-
 139:         cdef SIZE_t p
-
 140:         cdef DOUBLE_t is_treated
-
 141:         cdef DOUBLE_t y_ik
-
 142:
-
+143:         cdef double right_tr = 0.0
-
  __pyx_v_right_tr = 0.0;
-
+144:         cdef double right_ct = 0.0
-
  __pyx_v_right_ct = 0.0;
-
+145:         cdef double right_sum = 0.0
-
  __pyx_v_right_sum = 0.0;
-
+146:         cdef double right_tr_sum = 0.0
-
  __pyx_v_right_tr_sum = 0.0;
-
+147:         cdef double right_sq_sum = 0.0
-
  __pyx_v_right_sq_sum = 0.0;
-
+148:         cdef double right_tr_sq_sum = 0.0
-
  __pyx_v_right_tr_sq_sum = 0.0;
-
 149:         cdef double right_tr_var
-
 150:         cdef double right_ct_var
-
 151:
-
+152:         cdef double left_tr = 0.0
-
  __pyx_v_left_tr = 0.0;
-
+153:         cdef double left_ct = 0.0
-
  __pyx_v_left_ct = 0.0;
-
+154:         cdef double left_sum = 0.0
-
  __pyx_v_left_sum = 0.0;
-
+155:         cdef double left_tr_sum = 0.0
-
  __pyx_v_left_tr_sum = 0.0;
-
+156:         cdef double left_sq_sum = 0.0
-
  __pyx_v_left_sq_sum = 0.0;
-
+157:         cdef double left_tr_sq_sum = 0.0
-
  __pyx_v_left_tr_sq_sum = 0.0;
-
 158:         cdef double left_tr_var
-
 159:         cdef double left_ct_var
-
 160:
-
+161:         cdef double one_over_eps = 1e5
-
  __pyx_v_one_over_eps = 1e5;
-
 162:
-
+163:         for p in range(start, end):
-
  __pyx_t_3 = __pyx_v_end;
-  __pyx_t_5 = __pyx_t_3;
-  for (__pyx_t_6 = __pyx_v_start; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
-    __pyx_v_p = __pyx_t_6;
-
+164:             i = samples[p]
-
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);
-
 165:
-
+166:             if sample_weight != NULL:
-
    __pyx_t_7 = ((__pyx_v_sample_weight != NULL) != 0);
-    if (__pyx_t_7) {
-/* … */
-    }
-
 167:                 # the weights of 1 and 1 + eps are used for control and treatment respectively
-
+168:                 is_treated = (sample_weight[i] - 1.0) * one_over_eps
-
      __pyx_v_is_treated = (((__pyx_v_sample_weight[__pyx_v_i]) - 1.0) * __pyx_v_one_over_eps);
-
 169:
-
 170:             # assume that there is only one output (k = 0)
-
+171:             y_ik = self.y[i, 0]
-
    if (unlikely(!__pyx_v_self->__pyx_base.__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 171, __pyx_L1_error)}
-    __pyx_t_8 = __pyx_v_i;
-    __pyx_t_9 = 0;
-    __pyx_v_y_ik = (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.__pyx_base.y.strides[0]) )) + __pyx_t_9)) )));
-
 172:
-
+173:             if p < pos:
-
    __pyx_t_7 = ((__pyx_v_p < __pyx_v_pos) != 0);
-    if (__pyx_t_7) {
-/* … */
-      goto __pyx_L6;
-    }
-
+174:                 left_tr += is_treated
-
      __pyx_v_left_tr = (__pyx_v_left_tr + __pyx_v_is_treated);
-
+175:                 left_ct += 1. - is_treated
-
      __pyx_v_left_ct = (__pyx_v_left_ct + (1. - __pyx_v_is_treated));
-
+176:                 left_sum += y_ik
-
      __pyx_v_left_sum = (__pyx_v_left_sum + __pyx_v_y_ik);
-
+177:                 left_tr_sum += y_ik * is_treated
-
      __pyx_v_left_tr_sum = (__pyx_v_left_tr_sum + (__pyx_v_y_ik * __pyx_v_is_treated));
-
+178:                 left_sq_sum += y_ik * y_ik
-
      __pyx_v_left_sq_sum = (__pyx_v_left_sq_sum + (__pyx_v_y_ik * __pyx_v_y_ik));
-
+179:                 left_tr_sq_sum += y_ik * y_ik * is_treated
-
      __pyx_v_left_tr_sq_sum = (__pyx_v_left_tr_sq_sum + ((__pyx_v_y_ik * __pyx_v_y_ik) * __pyx_v_is_treated));
-
 180:             else:
-
+181:                 right_tr += is_treated
-
    /*else*/ {
-      __pyx_v_right_tr = (__pyx_v_right_tr + __pyx_v_is_treated);
-
+182:                 right_ct += 1. - is_treated
-
      __pyx_v_right_ct = (__pyx_v_right_ct + (1. - __pyx_v_is_treated));
-
+183:                 right_sum += y_ik
-
      __pyx_v_right_sum = (__pyx_v_right_sum + __pyx_v_y_ik);
-
+184:                 right_tr_sum += y_ik * is_treated
-
      __pyx_v_right_tr_sum = (__pyx_v_right_tr_sum + (__pyx_v_y_ik * __pyx_v_is_treated));
-
+185:                 right_sq_sum += y_ik * y_ik
-
      __pyx_v_right_sq_sum = (__pyx_v_right_sq_sum + (__pyx_v_y_ik * __pyx_v_y_ik));
-
+186:                 right_tr_sq_sum += y_ik * y_ik * is_treated
-
      __pyx_v_right_tr_sq_sum = (__pyx_v_right_tr_sq_sum + ((__pyx_v_y_ik * __pyx_v_y_ik) * __pyx_v_is_treated));
-    }
-    __pyx_L6:;
-  }
-
 187:
-
+188:         right_tau = right_tr_sum / right_tr - (sum_right[0] - right_tr_sum) / right_ct
-
  __pyx_v_right_tau = ((__pyx_v_right_tr_sum / __pyx_v_right_tr) - (((__pyx_v_sum_right[0]) - __pyx_v_right_tr_sum) / __pyx_v_right_ct));
-
+189:         right_tr_var = right_tr_sq_sum / right_tr - right_tr_sum * right_tr_sum / (right_tr * right_tr)
-
  __pyx_v_right_tr_var = ((__pyx_v_right_tr_sq_sum / __pyx_v_right_tr) - ((__pyx_v_right_tr_sum * __pyx_v_right_tr_sum) / (__pyx_v_right_tr * __pyx_v_right_tr)));
-
+190:         right_ct_var = ((right_sq_sum - right_tr_sq_sum) / right_ct -
-
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diff --git a/causalml/inference/tree/uplift.html b/causalml/inference/tree/uplift.html deleted file mode 100644 index eb93d071..00000000 --- a/causalml/inference/tree/uplift.html +++ /dev/null @@ -1,13953 +0,0 @@ - - - - - - Cython: uplift.pyx - - - -

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 0005: Forest of trees-based ensemble methods for Uplift modeling on Classification
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 0006: Problem. Those methods include random forests and extremely randomized trees.
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 0008: The module structure is the following:
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 0009: - The ``UpliftRandomForestClassifier`` base class implements different
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static float __pyx_f_8causalml_9inference_4tree_6uplift_kl_divergence(float __pyx_v_pk, float __pyx_v_qk) {
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 0051:
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 0053:     ----
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