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file_format: mystnb
kernelspec:
  name: python3
---

(continuous_ordinal_patterns)=
# Continuous Ordinal Patterns

The Continuous Ordinal Patterns (COP) connectivity metric analyzes the patterns in time series data to detect relationships.

```python
import delaynet as dn

# Calculate COP connectivity
result = dn.connectivity(
    ts1, ts2, metric="random_patterns", p_size=5, num_rnd_patterns=50, lag_steps=5
)
```

Parameters:
- `p_size`: Size of the ordinal pattern.
- `num_rnd_patterns`: Number of random patterns to consider.
- `lag_steps`: Time lags to consider. An integer will consider lags [1, ..., lag_steps]. Passing a list will consider the specified values as lags.
- `linear`: Whether to start with the identity pattern. Default is True.

```{eval-rst}
.. automethod:: delaynet.connectivities.continuous_ordinal_patterns.random_patterns
    :noindex:
```