674 lines
23 KiB
Cython
674 lines
23 KiB
Cython
# cython: cdivision=True
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# cython: boundscheck=False
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# cython: wraparound=False
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# Authors: Gilles Louppe <g.louppe@gmail.com>
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# Peter Prettenhofer <peter.prettenhofer@gmail.com>
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# Arnaud Joly <arnaud.v.joly@gmail.com>
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# Jacob Schreiber <jmschreiber91@gmail.com>
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# Nelson Liu <nelson@nelsonliu.me>
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#
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#
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# License: BSD 3 clause
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from libc.stdlib cimport free
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from libc.stdlib cimport malloc
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from libc.stdlib cimport calloc
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from libc.stdlib cimport realloc
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from libc.math cimport log as ln
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import numpy as np
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cimport numpy as np
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np.import_array()
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# =============================================================================
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# Helper functions
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# =============================================================================
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cdef realloc_ptr safe_realloc(realloc_ptr* p, size_t nelems) except *:
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# sizeof(realloc_ptr[0]) would be more like idiomatic C, but causes Cython
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# 0.20.1 to crash.
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cdef size_t nbytes = nelems * sizeof(p[0][0])
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if nbytes / sizeof(p[0][0]) != nelems:
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# Overflow in the multiplication
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raise MemoryError("could not allocate (%d * %d) bytes"
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% (nelems, sizeof(p[0][0])))
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cdef realloc_ptr tmp = <realloc_ptr>realloc(p[0], nbytes)
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if tmp == NULL:
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raise MemoryError("could not allocate %d bytes" % nbytes)
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p[0] = tmp
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return tmp # for convenience
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def _realloc_test():
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# Helper for tests. Tries to allocate <size_t>(-1) / 2 * sizeof(size_t)
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# bytes, which will always overflow.
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cdef SIZE_t* p = NULL
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safe_realloc(&p, <size_t>(-1) / 2)
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if p != NULL:
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free(p)
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assert False
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# rand_r replacement using a 32bit XorShift generator
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# See http://www.jstatsoft.org/v08/i14/paper for details
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cdef inline UINT32_t our_rand_r(UINT32_t* seed) nogil:
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seed[0] ^= <UINT32_t>(seed[0] << 13)
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seed[0] ^= <UINT32_t>(seed[0] >> 17)
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seed[0] ^= <UINT32_t>(seed[0] << 5)
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return seed[0] % (<UINT32_t>RAND_R_MAX + 1)
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cdef inline np.ndarray sizet_ptr_to_ndarray(SIZE_t* data, SIZE_t size):
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"""Encapsulate data into a 1D numpy array of intp's."""
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cdef np.npy_intp shape[1]
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shape[0] = <np.npy_intp> size
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return np.PyArray_SimpleNewFromData(1, shape, np.NPY_INTP, data)
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cdef inline SIZE_t rand_int(SIZE_t low, SIZE_t high,
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UINT32_t* random_state) nogil:
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"""Generate a random integer in [0; end)."""
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return low + our_rand_r(random_state) % (high - low)
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cdef inline double rand_uniform(double low, double high,
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UINT32_t* random_state) nogil:
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"""Generate a random double in [low; high)."""
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return ((high - low) * <double> our_rand_r(random_state) /
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<double> RAND_R_MAX) + low
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cdef inline double log(double x) nogil:
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return ln(x) / ln(2.0)
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# =============================================================================
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# Stack data structure
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# =============================================================================
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cdef class Stack:
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"""A LIFO data structure.
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Attributes
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----------
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capacity : SIZE_t
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The elements the stack can hold; if more added then ``self.stack_``
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needs to be resized.
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top : SIZE_t
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The number of elements currently on the stack.
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stack : StackRecord pointer
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The stack of records (upward in the stack corresponds to the right).
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"""
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def __cinit__(self, SIZE_t capacity):
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self.capacity = capacity
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self.top = 0
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self.stack_ = <StackRecord*> malloc(capacity * sizeof(StackRecord))
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if self.stack_ == NULL:
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raise MemoryError()
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def __dealloc__(self):
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free(self.stack_)
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cdef bint is_empty(self) nogil:
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return self.top <= 0
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cdef int push(self, SIZE_t start, SIZE_t end, SIZE_t depth, SIZE_t parent,
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bint is_left, double impurity,
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SIZE_t n_constant_features) nogil:
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"""Push a new element onto the stack.
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Returns 0 if successful; -1 on out of memory error.
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"""
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cdef SIZE_t top = self.top
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cdef StackRecord* stack = NULL
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# Resize if capacity not sufficient
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if top >= self.capacity:
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self.capacity *= 2
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stack = <StackRecord*> realloc(self.stack_,
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self.capacity * sizeof(StackRecord))
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if stack == NULL:
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# no free; __dealloc__ handles that
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return -1
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self.stack_ = stack
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stack = self.stack_
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stack[top].start = start
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stack[top].end = end
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stack[top].depth = depth
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stack[top].parent = parent
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stack[top].is_left = is_left
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stack[top].impurity = impurity
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stack[top].n_constant_features = n_constant_features
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# Increment stack pointer
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self.top = top + 1
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return 0
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cdef int pop(self, StackRecord* res) nogil:
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"""Remove the top element from the stack and copy to ``res``.
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Returns 0 if pop was successful (and ``res`` is set); -1
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otherwise.
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"""
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cdef SIZE_t top = self.top
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cdef StackRecord* stack = self.stack_
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if top <= 0:
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return -1
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res[0] = stack[top - 1]
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self.top = top - 1
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return 0
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# =============================================================================
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# PriorityHeap data structure
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# =============================================================================
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cdef void heapify_up(PriorityHeapRecord* heap, SIZE_t pos) nogil:
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"""Restore heap invariant parent.improvement > child.improvement from
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``pos`` upwards. """
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if pos == 0:
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return
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cdef SIZE_t parent_pos = (pos - 1) / 2
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if heap[parent_pos].improvement < heap[pos].improvement:
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heap[parent_pos], heap[pos] = heap[pos], heap[parent_pos]
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heapify_up(heap, parent_pos)
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cdef void heapify_down(PriorityHeapRecord* heap, SIZE_t pos,
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SIZE_t heap_length) nogil:
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"""Restore heap invariant parent.improvement > children.improvement from
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``pos`` downwards. """
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cdef SIZE_t left_pos = 2 * (pos + 1) - 1
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cdef SIZE_t right_pos = 2 * (pos + 1)
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cdef SIZE_t largest = pos
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if (left_pos < heap_length and
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heap[left_pos].improvement > heap[largest].improvement):
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largest = left_pos
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if (right_pos < heap_length and
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heap[right_pos].improvement > heap[largest].improvement):
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largest = right_pos
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if largest != pos:
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heap[pos], heap[largest] = heap[largest], heap[pos]
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heapify_down(heap, largest, heap_length)
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cdef class PriorityHeap:
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"""A priority queue implemented as a binary heap.
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The heap invariant is that the impurity improvement of the parent record
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is larger then the impurity improvement of the children.
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Attributes
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----------
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capacity : SIZE_t
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The capacity of the heap
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heap_ptr : SIZE_t
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The water mark of the heap; the heap grows from left to right in the
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array ``heap_``. The following invariant holds ``heap_ptr < capacity``.
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heap_ : PriorityHeapRecord*
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The array of heap records. The maximum element is on the left;
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the heap grows from left to right
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"""
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def __cinit__(self, SIZE_t capacity):
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self.capacity = capacity
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self.heap_ptr = 0
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self.heap_ = <PriorityHeapRecord*> malloc(capacity * sizeof(PriorityHeapRecord))
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if self.heap_ == NULL:
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raise MemoryError()
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def __dealloc__(self):
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free(self.heap_)
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cdef bint is_empty(self) nogil:
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return self.heap_ptr <= 0
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cdef int push(self, SIZE_t node_id, SIZE_t start, SIZE_t end, SIZE_t pos,
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SIZE_t depth, bint is_leaf, double improvement,
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double impurity, double impurity_left,
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double impurity_right) nogil:
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"""Push record on the priority heap.
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Returns 0 if successful; -1 on out of memory error.
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"""
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cdef SIZE_t heap_ptr = self.heap_ptr
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cdef PriorityHeapRecord* heap = NULL
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# Resize if capacity not sufficient
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if heap_ptr >= self.capacity:
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self.capacity *= 2
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heap = <PriorityHeapRecord*> realloc(self.heap_,
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self.capacity *
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sizeof(PriorityHeapRecord))
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if heap == NULL:
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# no free; __dealloc__ handles that
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return -1
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self.heap_ = heap
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# Put element as last element of heap
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heap = self.heap_
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heap[heap_ptr].node_id = node_id
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heap[heap_ptr].start = start
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heap[heap_ptr].end = end
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heap[heap_ptr].pos = pos
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heap[heap_ptr].depth = depth
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heap[heap_ptr].is_leaf = is_leaf
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heap[heap_ptr].impurity = impurity
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heap[heap_ptr].impurity_left = impurity_left
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heap[heap_ptr].impurity_right = impurity_right
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heap[heap_ptr].improvement = improvement
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# Heapify up
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heapify_up(heap, heap_ptr)
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# Increase element count
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self.heap_ptr = heap_ptr + 1
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return 0
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cdef int pop(self, PriorityHeapRecord* res) nogil:
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"""Remove max element from the heap. """
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cdef SIZE_t heap_ptr = self.heap_ptr
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cdef PriorityHeapRecord* heap = self.heap_
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if heap_ptr <= 0:
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return -1
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# Take first element
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res[0] = heap[0]
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# Put last element to the front
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heap[0], heap[heap_ptr - 1] = heap[heap_ptr - 1], heap[0]
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# Restore heap invariant
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if heap_ptr > 1:
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heapify_down(heap, 0, heap_ptr - 1)
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self.heap_ptr = heap_ptr - 1
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return 0
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# =============================================================================
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# WeightedPQueue data structure
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# =============================================================================
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cdef class WeightedPQueue:
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"""A priority queue class, always sorted in increasing order.
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Attributes
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----------
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capacity : SIZE_t
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The capacity of the priority queue.
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array_ptr : SIZE_t
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The water mark of the priority queue; the priority queue grows from
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left to right in the array ``array_``. ``array_ptr`` is always
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less than ``capacity``.
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array_ : WeightedPQueueRecord*
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The array of priority queue records. The minimum element is on the
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left at index 0, and the maximum element is on the right at index
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``array_ptr-1``.
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"""
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def __cinit__(self, SIZE_t capacity):
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self.capacity = capacity
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self.array_ptr = 0
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safe_realloc(&self.array_, capacity)
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if self.array_ == NULL:
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raise MemoryError()
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def __dealloc__(self):
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free(self.array_)
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cdef void reset(self) nogil:
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"""Reset the WeightedPQueue to its state at construction"""
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self.array_ptr = 0
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self.array_ = <WeightedPQueueRecord*> calloc(self.capacity,
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sizeof(WeightedPQueueRecord))
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cdef bint is_empty(self) nogil:
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return self.array_ptr <= 0
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cdef SIZE_t size(self) nogil:
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return self.array_ptr
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cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil:
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"""Push record on the array.
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Returns 0 if successful; -1 on out of memory error.
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"""
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cdef SIZE_t array_ptr = self.array_ptr
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cdef WeightedPQueueRecord* array = NULL
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cdef SIZE_t i
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# Resize if capacity not sufficient
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if array_ptr >= self.capacity:
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self.capacity *= 2
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array = <WeightedPQueueRecord*> realloc(self.array_,
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self.capacity *
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sizeof(WeightedPQueueRecord))
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if array == NULL:
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# no free; __dealloc__ handles that
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return -1
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self.array_ = array
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# Put element as last element of array
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array = self.array_
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array[array_ptr].data = data
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array[array_ptr].weight = weight
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# bubble last element up according until it is sorted
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# in ascending order
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i = array_ptr
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while(i != 0 and array[i].data < array[i-1].data):
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array[i], array[i-1] = array[i-1], array[i]
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i -= 1
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# Increase element count
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self.array_ptr = array_ptr + 1
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return 0
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cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil:
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"""Remove a specific value/weight record from the array.
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Returns 0 if successful, -1 if record not found."""
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cdef SIZE_t array_ptr = self.array_ptr
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cdef WeightedPQueueRecord* array = self.array_
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cdef SIZE_t idx_to_remove = -1
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cdef SIZE_t i
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if array_ptr <= 0:
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return -1
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# find element to remove
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for i in range(array_ptr):
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if array[i].data == data and array[i].weight == weight:
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idx_to_remove = i
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break
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if idx_to_remove == -1:
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return -1
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# shift the elements after the removed element
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# to the left.
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for i in range(idx_to_remove, array_ptr-1):
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array[i] = array[i+1]
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self.array_ptr = array_ptr - 1
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return 0
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cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil:
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"""Remove the top (minimum) element from array.
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Returns 0 if successful, -1 if nothing to remove."""
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cdef SIZE_t array_ptr = self.array_ptr
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cdef WeightedPQueueRecord* array = self.array_
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cdef SIZE_t i
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if array_ptr <= 0:
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return -1
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data[0] = array[0].data
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weight[0] = array[0].weight
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# shift the elements after the removed element
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# to the left.
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for i in range(0, array_ptr-1):
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array[i] = array[i+1]
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self.array_ptr = array_ptr - 1
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return 0
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cdef int peek(self, DOUBLE_t* data, DOUBLE_t* weight) nogil:
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"""Write the top element from array to a pointer.
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Returns 0 if successful, -1 if nothing to write."""
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cdef WeightedPQueueRecord* array = self.array_
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if self.array_ptr <= 0:
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return -1
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# Take first value
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data[0] = array[0].data
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weight[0] = array[0].weight
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return 0
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cdef DOUBLE_t get_weight_from_index(self, SIZE_t index) nogil:
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"""Given an index between [0,self.current_capacity], access
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the appropriate heap and return the requested weight"""
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cdef WeightedPQueueRecord* array = self.array_
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# get weight at index
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return array[index].weight
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cdef DOUBLE_t get_value_from_index(self, SIZE_t index) nogil:
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"""Given an index between [0,self.current_capacity], access
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the appropriate heap and return the requested value"""
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cdef WeightedPQueueRecord* array = self.array_
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# get value at index
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return array[index].data
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# =============================================================================
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# WeightedMedianCalculator data structure
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# =============================================================================
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cdef class WeightedMedianCalculator:
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"""A class to handle calculation of the weighted median from streams of
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data. To do so, it maintains a parameter ``k`` such that the sum of the
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weights in the range [0,k) is greater than or equal to half of the total
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weight. By minimizing the value of ``k`` that fulfills this constraint,
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calculating the median is done by either taking the value of the sample
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at index ``k-1`` of ``samples`` (samples[k-1].data) or the average of
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the samples at index ``k-1`` and ``k`` of ``samples``
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((samples[k-1] + samples[k]) / 2).
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Attributes
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----------
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initial_capacity : SIZE_t
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The initial capacity of the WeightedMedianCalculator.
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samples : WeightedPQueue
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Holds the samples (consisting of values and their weights) used in the
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weighted median calculation.
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total_weight : DOUBLE_t
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The sum of the weights of items in ``samples``. Represents the total
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weight of all samples used in the median calculation.
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k : SIZE_t
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Index used to calculate the median.
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sum_w_0_k : DOUBLE_t
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The sum of the weights from samples[0:k]. Used in the weighted
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median calculation; minimizing the value of ``k`` such that
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``sum_w_0_k`` >= ``total_weight / 2`` provides a mechanism for
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calculating the median in constant time.
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"""
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def __cinit__(self, SIZE_t initial_capacity):
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self.initial_capacity = initial_capacity
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self.samples = WeightedPQueue(initial_capacity)
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self.total_weight = 0
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self.k = 0
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self.sum_w_0_k = 0
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cdef SIZE_t size(self) nogil:
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"""Return the number of samples in the
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WeightedMedianCalculator"""
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return self.samples.size()
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cdef void reset(self) nogil:
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"""Reset the WeightedMedianCalculator to its state at construction"""
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self.samples.reset()
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self.total_weight = 0
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self.k = 0
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self.sum_w_0_k = 0
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cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil:
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"""Push a value and its associated weight
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to the WeightedMedianCalculator to be considered
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in the median calculation.
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"""
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cdef int return_value
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cdef DOUBLE_t original_median
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if self.size() != 0:
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original_median = self.get_median()
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return_value = self.samples.push(data, weight)
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self.update_median_parameters_post_push(data, weight,
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original_median)
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return return_value
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|
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cdef int update_median_parameters_post_push(self, DOUBLE_t data,
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DOUBLE_t weight,
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DOUBLE_t original_median) nogil:
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"""Update the parameters used in the median calculation,
|
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namely `k` and `sum_w_0_k` after an insertion"""
|
|
|
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# trivial case of one element.
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if self.size() == 1:
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self.k = 1
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self.total_weight = weight
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self.sum_w_0_k = self.total_weight
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return 0
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|
|
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# get the original weighted median
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self.total_weight += weight
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|
|
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if data < original_median:
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# inserting below the median, so increment k and
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# then update self.sum_w_0_k accordingly by adding
|
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# the weight that was added.
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self.k += 1
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# update sum_w_0_k by adding the weight added
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self.sum_w_0_k += weight
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|
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# minimize k such that sum(W[0:k]) >= total_weight / 2
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# minimum value of k is 1
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while(self.k > 1 and ((self.sum_w_0_k -
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self.samples.get_weight_from_index(self.k-1))
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|
>= self.total_weight / 2.0)):
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self.k -= 1
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self.sum_w_0_k -= self.samples.get_weight_from_index(self.k)
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return 0
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|
|
|
if data >= original_median:
|
|
# inserting above or at the median
|
|
# minimize k such that sum(W[0:k]) >= total_weight / 2
|
|
while(self.k < self.samples.size() and
|
|
(self.sum_w_0_k < self.total_weight / 2.0)):
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self.k += 1
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self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1)
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return 0
|
|
|
|
cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil:
|
|
"""Remove a value from the MedianHeap, removing it
|
|
from consideration in the median calculation
|
|
"""
|
|
cdef int return_value
|
|
cdef DOUBLE_t original_median
|
|
|
|
if self.size() != 0:
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original_median = self.get_median()
|
|
|
|
return_value = self.samples.remove(data, weight)
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self.update_median_parameters_post_remove(data, weight,
|
|
original_median)
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return return_value
|
|
|
|
cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil:
|
|
"""Pop a value from the MedianHeap, starting from the
|
|
left and moving to the right.
|
|
"""
|
|
cdef int return_value
|
|
cdef double original_median
|
|
|
|
if self.size() != 0:
|
|
original_median = self.get_median()
|
|
|
|
# no elements to pop
|
|
if self.samples.size() == 0:
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|
return -1
|
|
|
|
return_value = self.samples.pop(data, weight)
|
|
self.update_median_parameters_post_remove(data[0],
|
|
weight[0],
|
|
original_median)
|
|
return return_value
|
|
|
|
cdef int update_median_parameters_post_remove(self, DOUBLE_t data,
|
|
DOUBLE_t weight,
|
|
double original_median) nogil:
|
|
"""Update the parameters used in the median calculation,
|
|
namely `k` and `sum_w_0_k` after a removal"""
|
|
# reset parameters because it there are no elements
|
|
if self.samples.size() == 0:
|
|
self.k = 0
|
|
self.total_weight = 0
|
|
self.sum_w_0_k = 0
|
|
return 0
|
|
|
|
# trivial case of one element.
|
|
if self.samples.size() == 1:
|
|
self.k = 1
|
|
self.total_weight -= weight
|
|
self.sum_w_0_k = self.total_weight
|
|
return 0
|
|
|
|
# get the current weighted median
|
|
self.total_weight -= weight
|
|
|
|
if data < original_median:
|
|
# removing below the median, so decrement k and
|
|
# then update self.sum_w_0_k accordingly by subtracting
|
|
# the removed weight
|
|
|
|
self.k -= 1
|
|
# update sum_w_0_k by removing the weight at index k
|
|
self.sum_w_0_k -= weight
|
|
|
|
# minimize k such that sum(W[0:k]) >= total_weight / 2
|
|
# by incrementing k and updating sum_w_0_k accordingly
|
|
# until the condition is met.
|
|
while(self.k < self.samples.size() and
|
|
(self.sum_w_0_k < self.total_weight / 2.0)):
|
|
self.k += 1
|
|
self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1)
|
|
return 0
|
|
|
|
if data >= original_median:
|
|
# removing above the median
|
|
# minimize k such that sum(W[0:k]) >= total_weight / 2
|
|
while(self.k > 1 and ((self.sum_w_0_k -
|
|
self.samples.get_weight_from_index(self.k-1))
|
|
>= self.total_weight / 2.0)):
|
|
self.k -= 1
|
|
self.sum_w_0_k -= self.samples.get_weight_from_index(self.k)
|
|
return 0
|
|
|
|
cdef DOUBLE_t get_median(self) nogil:
|
|
"""Write the median to a pointer, taking into account
|
|
sample weights."""
|
|
if self.sum_w_0_k == (self.total_weight / 2.0):
|
|
# split median
|
|
return (self.samples.get_value_from_index(self.k) +
|
|
self.samples.get_value_from_index(self.k-1)) / 2.0
|
|
if self.sum_w_0_k > (self.total_weight / 2.0):
|
|
# whole median
|
|
return self.samples.get_value_from_index(self.k-1)
|