mintalib

mintalib.functions module

Calculation functions for technical analysis indicators.

The function names are all lower case and may conflict with standard functions, so the best way to use this module is to alias it to a short name like ta and access all functions as attributes.

The first parameter series or prices indicates whether the function accepts a single series or a prices dataframe.

Functions that accept a series usually have an optional parameter item to specify which column to use if the input is a dataframe.

All functions wrap their output to match the type of their input.

In particular the result of a function applied to a pandas series or dataframes will have the same index as the input.

price function

price(prices, item: str = None)

Generic Price

Args:

• item (str) : one of ‘open’, ‘high’, ‘low’, ‘close’, ‘avg’, ‘mid’, ‘typ’, ‘wcl’ defaults to ‘close’

avgprice function

avgprice(prices)

Average Price

Value of (open + high + low + close) / 4

typprice function

typprice(prices)

Typical Price

Value of (high + low + close ) / 3

wclprice function

wclprice(prices)

Weighted Close Price

Value of (high + low + 2 * close) / 4

midprice function

midprice(prices)

Mid Price

Value of (high + low) / 2

crossover function

crossover(series, level: float = 0.0, *, item: str = None)

Cross Over

Yields a value of 1 at the point where series crosses over level

Args:

• level (float) : level to cross, default 0.0

crossunder function

crossunder(series, level: float = 0.0, *, item: str = None)

Cross Under

Yields a value of 1 at the point where series crosses under level

Args:

• level (float) : level to cross, default 0.0

flag function

flag(series, *, item: str = None)

Flag Value

Flag value of 1 for positive, 0 for zero or negative, and NaN otherwize

updown function

updown(series, up_level: float = 0.0, down_level: float = 0.0, *, item: str = None)

Flag for value crossing up & down levels

Args:

• up_level (float) : flag set at 1 above that level
• down_level (float) : flag set at 0 below that level

sign function

sign(series, na_value: float = nan, *, item: str = None)

Sign

step function

step(series, threshold: float = 1.0, *, item: str = None)

Step Function

Limit value changes to threshold (in absolute value)

Args:

• threshold (float) : threshold value, default 1.0

clag function

clag(series, period: int = 1, *, item: str = None)

Confirmation Lag

Changes value only after a confirmation period

Args:

• period (int) : time period, default 1

abs function

abs(series, *, item: str = None)

Absolute Value

log function

log(series, *, item: str = None)

Logarithm

exp function

exp(series, *, item: str = None)

Exponential

shift function

shift(series, period: int, *, item: str = None)

Shift Function

Args:

• period (int) : time period, required

diff function

diff(series, period: int = 1, *, item: str = None)

Difference

Difference between current value and the one offset by period

Args:

• period (int) : time period, default 1

lag function

lag(series, period: int, *, item: str = None)

Lag Function

Args:

• period (int) : time period, required

min function

min(series, period: int, *, item: str = None)

Rolling Minimum

Args:

• period (int) : time period, required

max function

max(series, period: int, *, item: str = None)

Rolling Maximum

sum function

sum(series, period: int, *, item: str = None)

Rolling sum

Args:

• period (int) : time period, required

roc function

roc(series, period: int = 1, *, item: str = None)

Rate of Change

Args:

• period (int) : time period, default 1 when negative the calculation is shifted back

lroc function

lroc(series, period: int = 1, *, item: str = None)

Logarithmic Rate of Change

Equivalent to the difference of log values

Args:

• period (int) : time period, default 1 when negative the calculation is shifted back

mad function

mad(series, period: int = 14, *, item: str = None)

Rolling Mean Absolute Deviation

stdev function

stdev(series, period: int = 20, *, item: str = None)

Standard Deviation

Args:

• period (int) : time period, default 20

mav function

mav(series, period: int = 20, *, ma_type: str = 'SMA', item: str = None)

Generic Moving Average

Moving average computed according to ma_type

Args:

• ma_type (str) : one of ‘SMA’, ‘EMA’, ‘WMA’, ‘HMA’, ‘DEMA’, ‘TEMA’ defaults to ‘SMA’

sma function

sma(series, period: int, *, item: str = None)

Simple Moving Average

Args:

• period (int) : time period, required

ema function

ema(series, period: int, *, adjust: bool = False, item: str = None)

Exponential Moving Average

Args:

• period (int) : time period, required
• adjust (bool) : whether to adjust weights, default False when true update ratio increases gradually (see formula)

Formula:

• EMA is calculated as a recursive formula The standard formula is ema += alpha * (value - ema) with alpha = 2.0 / (period + 1.0) The adjusted formula is ema = num/div where num = value + rho * num, div = 1.0 + rho * div with rho = 1.0 - alpha

rma function

rma(series, period: int, *, item: str = None)

Rolling Moving Average (RSI style)

Exponential moving average with alpha = 2 / period, that starts as a simple moving average until number of bars is equal to period.

wma function

wma(series, period: int, *, item: str = None)

Weighted Moving Average

Args:

• period (int) : time period, required

hma function

hma(series, period: int, *, item: str = None)

Hull Moving Average

Args:

• period (int) : time period, required

dema function

dema(series, period: int, *, item: str = None)

Double Exponential Moving Average

Args:

• period (int) : time period, required

tema function

tema(series, period: int = 20, *, item: str = None)

Triple Exponential Moving Average

Args:

• period (int) : time period, default 20

alma function

alma(series, period: int = 9, offset: float = 0.85, sigma: float = 6.0, *, item: str = None)

Arnaud Legoux Moving Average

rsi function

rsi(series, period: int = 14, *, item: str = None)

Relative Strength Index

Args:

• period (int) : time period, default 14

dmi function

dmi(prices, period: int = 14)

Directional Movement Indicator

Args:

• period (int) : time period, default 14

adx function

adx(prices, period: int = 14)

Average Directional Index

Args:

• period (int) : time period, default 14

pdi function

pdi(prices, period: int = 14)

Plus Directional Index

Args:

• period (int) : time period, default 14

mdi function

mdi(prices, period: int = 14)

Minus Directional Index

Args:

• period (int) : time period, default 14

trange function

trange(prices, *, log_prices: bool = False, percent: bool = False)

True Range

Args:

• log_percent (bool) : whether to apply log to prices before calculatio
• percent (bool) : result as percentage of price

atr function

atr(prices, period: int = 14)

Average True Range

Args:

• period (int) : time period, default 14

natr function

natr(prices, period: int = 14)

Average True Range (normalized)

Args:

• period (int) : time period, default 14

sar function

sar(prices, afs: float = 0.02, maxaf: float = 0.2)

Parabolic Stop and Reverse

Args:

• afs (float) : starting acceleration factor, default 0.02
• maxaf (float) : maximum acceleration factor, default 0.2

cci function

cci(prices, period: int = 20)

Commodity Channel Index

Args:

• period (int) : time period, default 20

cmf function

cmf(prices, period: int = 20)

Chaikin Money Flow

Args:

• period (int) : time period, default 20

mfi function

mfi(prices, period: int = 14)

Money Flow Index

Args:

• period (int) : time period, default 14

bop function

bop(prices, period: int = 20)

Balance of Power

Args:

• period (int) : time period, default 20

bbands function

bbands(prices, period: int = 20, nbdev: float = 2.0)

Bollinger Bands

Args:

• period (int) : time period, default 20
• nbdev (float) : bands width in number of standard deviations

keltner function

keltner(prices, period: int = 20, nbatr: float = 2.0)

Keltner Channel

Args:

• period (int) : time period, default 20
• nbatr (float) : channel width in number of atrs, default 2.0

ker function

ker(series, period: int = 10, *, item: str = None)

Kaufman Efficiency Ratio

Args:

• period (int) : time period, default 10

kama function

kama(series, period: int = 10, fastn: int = 2, slown: int = 30, *, item: str = None)

Kaufman Adaptive Moving Average

Args:

• period (int) : time period for efficiency ratio, default 10
• fastn (int) : time period for fast moving average, default, 2
• slown (int) : time period for slow moving average, default 30

macd function

macd(series, n1: int = 12, n2: int = 26, n3: int = 9, *, item: str = None)

Moving Average Convergenge Divergence

Args:

• n1 (int) : show time period, default 12
• n2 (int) : long time periodm, default 26
• n3 (int) : signal time period, default 9

Outputs:

• macd, macdsignal, macdhist

ppo function

ppo(series, n1: int = 12, n2: int = 26, n3: int = 9, *, item: str = None)

Price Percentage Oscillator

Args:

• n1 (int) : short time period, default 12
• n2 (int) : long time period, default 26
• n3 (int) : signal time period, default 9

Outputs:

• ppo, pposignal, ppohist

slope function

slope(series, period: int = 20, *, item: str = None)

Slope (linear regression)

Args:

• period (int) : time period, default 20

rvalue function

rvalue(series, period: int = 20, *, item: str = None)

R-Value (linear regression)

Args:

• period (int) : time period, default 20

tsf function

tsf(series, period: int = 20, offset: int = 0, *, item: str = None)

Time Series Forecast (linear regression)

Args:

• period (int) : time period, default 20

curve function

curve(series, period: int = 20, *, item: str = None)

Curve (quadratic regression)

qsf function

qsf(series, period: int = 20, offset: int = 0, *, item: str = None)

Quadratic Series Forecast (quadratic regression)

Args:

• period (int) : time period, default 20

stoch function

stoch(prices, period: int = 14, fastn: int = 3, slown: int = 3)

Stochastic Oscillator

Args:

• period (int) : time period of window, default, 14
• fastn (int) : time period of fast average, default 3
• slown (int) : time period of slow average, default 3

streak function

streak(series, *, item: str = None)

Consecutive streak of ups or downs

Length of streak of values all up or down, times +1 or -1 whether ups or downs.

eval function

eval(prices, expr: str, *, as_flag: bool = False)

Expression Eval (pandas only)

Args:

• expr (str) : expression to eval

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