rolling_volume in cython etc

rolling_volume.pyx

%%cython
import numpy as np
import pandas as pd
import sys
cimport cython
cimport numpy as np

ctypedef np.double_t DTYPE_t
cdef extern from "math.h":
    bint isnan(double x)

cdef inline double double_max(double a, double b): return a if a >= b else b
cdef inline double double_min(double a, double b): return a if a <= b else b

cdef inline double abz(double a) : return a if a >= 0. else -1 * a
cdef inline long labz(long a) : return a if a >= 0 else -1 * a

def wavgDeltas(np.ndarray[long,ndim=1] prices,np.ndarray[long,ndim=1] sizes, long deltas):
    cdef:
        long plen = prices.shape[0],count,i,j,sz
        np.ndarray[double, ndim=1] res = np.zeros(plen, dtype=np.double)
        double avg_price
    
    for i from 0<=i<plen:
        count = 0
        avg_price =0
        for j from i>=j>=0:
            sz = labz(sizes[j])
            if sz>0: #trade!
                count+=sz
                avg_price+=prices[j]*sz
                if count > deltas:
                    avg_price -= (prices[j] * (count-deltas))
                    count = deltas
                    j=-1
        if count>0:
            avg_price/=count
            res[i] = avg_price
        
    return res

def rolling_volume(np.ndarray[long,ndim=1] times, np.ndarray[long,ndim=1] sizes, long time_in_ns):
    cdef:
        long t_len = times.shape[0]
        long s_len = sizes.shape[0]
        
        long i =0, window_start, j, tots_volume
        
        np.ndarray[long, ndim=1] res = np.zeros(t_len, dtype=long)

    assert(t_len==s_len)

    for i in range(1,t_len):
        window_start = times[i] - time_in_ns
        j = i
        tots_volume=0
        #climb back to find the start of the window
        while times[j]>= window_start and j>=0:
            j-=1
        j+=1
        #now step FORWARD through to calculate the streaks
        while j<=i:
            tots_volume+=sizes[j]
            j+=1
        res[i] = tots_volume
        
    return res