def port_ppsr(asset_indicator, high_arr, low_arr, close_arr):
"""Calculate port Pivot Points, Supports and Resistances for given data
:param asset_indicator: the indicator of beginning of the stock
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:return: PP R1 S1 R2 S2 R3 S3
"""
high_gpu = high_arr.data.to_gpu_array()
low_gpu = low_arr.data.to_gpu_array()
close_gpu = close_arr.data.to_gpu_array()
PP = average_price(high_gpu, low_gpu, close_gpu)
R1 = substract(scale(PP, 2.0), low_gpu)
S1 = substract(scale(PP, 2.0), high_gpu)
R2 = substract(summation(PP, high_gpu), low_gpu)
S2 = summation(substract(PP, high_gpu), low_gpu)
R3 = summation(high_gpu, scale(substract(PP, low_gpu), 2.0))
S3 = substract(low_gpu, scale(substract(high_gpu, PP), 2.0))
out = collections.namedtuple('PPSR', 'PP R1 S1 R2 S2 R3 S3')
return out(PP=cudf.Series(PP),
R1=cudf.Series(R1),
S1=cudf.Series(S1),
R2=cudf.Series(R2),
S2=cudf.Series(S2),
R3=cudf.Series(R3),
S3=cudf.Series(S3))
def ppsr(high_arr, low_arr, close_arr):
"""Calculate Pivot Points, Supports and Resistances for given data
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:return: PP R1 S1 R2 S2 R3 S3
"""
high_gpu = high_arr.to_gpu_array()
low_gpu = low_arr.to_gpu_array()
close_gpu = close_arr.to_gpu_array()
PP = average_price(high_gpu, low_gpu, close_gpu)
R1 = substract(scale(PP, 2.0), low_gpu)
S1 = substract(scale(PP, 2.0), high_gpu)
R2 = substract(summation(PP, high_gpu), low_gpu)
S2 = summation(substract(PP, high_gpu), low_gpu)
R3 = summation(high_gpu, scale(substract(PP, low_gpu), 2.0))
S3 = substract(low_gpu, scale(substract(high_gpu, PP), 2.0))
out = collections.namedtuple('PPSR', 'PP R1 S1 R2 S2 R3 S3')
return out(PP=cudf.Series(PP, nan_as_null=False),
R1=cudf.Series(R1, nan_as_null=False),
S1=cudf.Series(S1, nan_as_null=False),
R2=cudf.Series(R2, nan_as_null=False),
S2=cudf.Series(S2, nan_as_null=False),
R3=cudf.Series(R3, nan_as_null=False),
S3=cudf.Series(S3, nan_as_null=False))
def commodity_channel_index(high_arr, low_arr, close_arr, n):
"""Calculate Commodity Channel Index for given data.
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps
:return: Commodity Channel Index in cudf.Series
"""
PP = average_price(high_arr.to_gpu_array(), low_arr.to_gpu_array(),
close_arr.to_gpu_array())
M = Rolling(n, PP).mean()
N = Rolling(n, PP).std()
CCI = division(substract(PP, M), N)
return cudf.Series(CCI, nan_as_null=False)
def money_flow_index(high_arr, low_arr, close_arr, volume_arr, n):
"""Calculate Money Flow Index and Ratio for given data.
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:param volume_arr: volume the bar, expect series from cudf
:param n: time steps
:return: Money Flow Index in cudf.Series
"""
PP = average_price(high_arr.to_gpu_array(), low_arr.to_gpu_array(),
close_arr.to_gpu_array())
PosMF = money_flow(PP, volume_arr.to_gpu_array())
MFR = division(PosMF, (multiply(PP, volume_arr.to_gpu_array()))) # TotMF
MFI = Rolling(n, MFR).mean()
return cudf.Series(MFI, nan_as_null=False)
def port_commodity_channel_index(asset_indicator, high_arr, low_arr, close_arr,
n):
"""Calculate port Commodity Channel Index for given data.
:param asset_indicator: the indicator of beginning of the stock
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps
:return: Commodity Channel Index in cudf.Series
"""
PP = average_price(high_arr.to_gpu_array(), low_arr.to_gpu_array(),
close_arr.to_gpu_array())
M = Rolling(n, PP).mean()
port_mask_nan(asset_indicator.to_gpu_array(), M, 0, n - 1)
N = Rolling(n, PP).std()
port_mask_nan(asset_indicator.to_gpu_array(), N, 0, n - 1)
CCI = division(substract(PP, M), N)
return cudf.Series(CCI, nan_as_null=False)
def port_money_flow_index(asset_indicator, high_arr, low_arr, close_arr,
volume_arr, n):
"""Calculate port Money Flow Index and Ratio for given data.
:param asset_indicator: the indicator of beginning of the stock
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:param volume_arr: volume the bar, expect series from cudf
:param n: time steps
:return: Money Flow Index in cudf.Series
"""
PP = average_price(high_arr.to_gpu_array(), low_arr.to_gpu_array(),
close_arr.to_gpu_array())
PosMF = port_money_flow(asset_indicator.to_gpu_array(), PP,
volume_arr.to_gpu_array())
MFR = division(PosMF, (multiply(PP, volume_arr.to_gpu_array()))) # TotMF
MFI = Rolling(n, MFR).mean()
port_mask_nan(asset_indicator.to_gpu_array(), MFI, 0, n - 1)
return cudf.Series(MFI, nan_as_null=False)