How do I account for the fill price must be greater than 0 error?

[EuclideanWild]

I get the following error:
ValueError: Fill price must be > 0: 0.0

Whenever I run the following code:

import pandas as pd
import numpy as np
from pybroker import Strategy, StrategyConfig, YFinance
import pandas as pd
import pybroker
from sklearn.linear_model import LinearRegression
from sklearn.metrics import r2_score

# Load your dataset
data = pd.read_csv('CB_SOMUSDT, 1D.csv')

# Register custom columns
pybroker.register_columns('dem', 'pred', 'mob')

def train_slr(symbol, train_data, test_data):
    # Train
    # Train the LinearRegession model to predict the next day's return
    # given the 20-day CMMA.
    X_train = train_data[['dem', 'mob']]
    y_train = train_data[['pred']]
    model = LinearRegression()
    model.fit(X_train, y_train)

    # Test
    X_test = test_data[['dem', 'mob']]
    y_test = test_data[['pred']]
    # Make predictions from test data.
    y_pred = model.predict(X_test)
    # Print goodness of fit.
    r2 = r2_score(y_test, np.squeeze(y_pred))
    print(symbol, f'R^2={r2}')

    # Return the trained model and columns to use as input data.
    return model, ['dem', 'mob']

model_slr = pybroker.model('slr', train_slr)

config = StrategyConfig(bootstrap_sample_size=100)
strategy = Strategy(data, '12/20/2023', '5/13/2024', config)
strategy.add_execution(None, ['SOM'], models=model_slr)

strategy.backtest(train_size=0.5)

def exec_fn(ctx):
    preds = ctx.preds('slr')
    # Open a long position given my_model's latest prediction.
    if not ctx.long_pos() and preds[-1] > 0:
        ctx.buy_shares = 100
    # Close the long position given my_model's latest prediction.
    elif ctx.long_pos() and preds[-1] < 0:
        ctx.sell_all_shares()

strategy.clear_executions()
strategy.add_execution(exec_fn, ['SOM'], models=model_slr)

result = strategy.walkforward(
    warmup=20,
    windows=3,
    train_size=0.5,
    lookahead=1,
    calc_bootstrap=True
)

Keep in mind that my close prices in my dataframe are relatively small. For example one rows close price is 0.005580.

Whenever I use a data set with larger close prices like aapl I don't have this problem.

[SW4T400]

I think pyb rounds to nearest cent. To disable this set the round_fill_price = False and try again.
For me it was rounding very small crypto prices to 0 and hence the error.

config = StrategyConfig(bootstrap_sample_size=10,
                        bars_per_year=bars_per_year(freq),
                        return_signals=True,
                        enable_fractional_shares=True,
                        round_test_result=False,
                        round_fill_price=False
                        ) ```