def stoc_osc(high, low, close, k_periods, k_slow_periods, d_periods, d_method):
N = close.__len__();
per_k = per_d = zeros(N);
numerator = zeros(N);
denominator = zeros(N);
for index in arange(0,k_periods-1):
max_high = max(high[0:index+1]);
min_low = min(low[0:index+1]);
numerator[index] = abs(close[index] - min_low);
denominator[index] = abs(max_high - min_low); # abs to handle negative values
for index in arange(k_periods-1,N):
max_high = max(high[index-k_periods+1:index+1]);
min_low = min(low[index-k_periods+1:index+1]);
numerator[index] = close[index] - min_low;
denominator[index] = max_high - min_low;
# %K Slowing periods, sum over last slowing periods (moving average work since we are doing a division)
num = moving_average.sma(numerator, k_slow_periods);
den = moving_average.sma(denominator, k_slow_periods);
for index in arange(0, N):
if(den[index] == 0):
per_k[index] = 100;
else:
per_k[index] = num[index] / den[index] * 100;
per_d = moving_average.ma(per_k, d_periods, d_method);
return [per_k, per_d];
def stoc_osc(high, low, close, k_periods, k_slow_periods, d_periods, d_method):
N = close.__len__()
per_k = per_d = zeros(N)
numerator = zeros(N)
denominator = zeros(N)
for index in arange(0, k_periods - 1):
max_high = max(high[0:index + 1])
min_low = min(low[0:index + 1])
numerator[index] = abs(close[index] - min_low)
denominator[index] = abs(max_high - min_low)
# abs to handle negative values
for index in arange(k_periods - 1, N):
max_high = max(high[index - k_periods + 1:index + 1])
min_low = min(low[index - k_periods + 1:index + 1])
numerator[index] = close[index] - min_low
denominator[index] = max_high - min_low
# %K Slowing periods, sum over last slowing periods (moving average work since we are doing a division)
num = moving_average.sma(numerator, k_slow_periods)
den = moving_average.sma(denominator, k_slow_periods)
for index in arange(0, N):
if (den[index] == 0):
per_k[index] = 100
else:
per_k[index] = num[index] / den[index] * 100
per_d = moving_average.ma(per_k, d_periods, d_method)
return [per_k, per_d]
def maCross(data, length):
ma = moving_average.ma(data.vClose, length)
N = size(data.vClose);
# days going back
M = 25;
for index in arange(N-M, N):
# find the last index associated with a value below the moving average
if(ma[index-1] > data.vClose[index]):
minIndex = index;
for index in arange(minIndex, N):
if(ma[minIndex] < data.vClose[index]):
maxIndex = index;
break
print maxIndex;
print data.vClose[maxIndex]
def maCross(data, length):
ma = moving_average.ma(data.vClose, length)
N = size(data.vClose)
# days going back
M = 25
for index in arange(N - M, N):
# find the last index associated with a value below the moving average
if (ma[index - 1] > data.vClose[index]):
minIndex = index
for index in arange(minIndex, N):
if (ma[minIndex] < data.vClose[index]):
maxIndex = index
break
print maxIndex
print data.vClose[maxIndex]
