# analysis { #tvbo.analysis }

`analysis`

Analysis subpackage.

Houses analysis result container classes (e.g., BifurcationResult) and related APIs that are logically distinct from plotting utilities or simulation drivers.

## Functions

| Name | Description |
| --- | --- |
| [compare_timeseries](#tvbo.analysis.compare_timeseries) | Compare state variables between two time series using multiple measures. |
| [per_window_fc](#tvbo.analysis.per_window_fc) | Calculate per-window functional connectivity. |
| [ttest_correlation_strength](#tvbo.analysis.ttest_correlation_strength) | Perform a t-test on the strength of the correlation. |

### compare_timeseries { #tvbo.analysis.compare_timeseries }

```python
analysis.compare_timeseries(exp, ts1, ts2, atol=1e-10)
```

Compare state variables between two time series using multiple measures.

#### Parameters {.doc-section .doc-section-parameters}

| Name   | Type                 | Description                                                  | Default    |
|--------|----------------------|--------------------------------------------------------------|------------|
| exp    | SimulationExperiment | Experiment object containing metadata about state variables. | _required_ |
| ts1    | Any                  | First time series.                                           | _required_ |
| ts2    | Any                  | Second time series.                                          | _required_ |
| atol   | float                | Absolute tolerance for broader identity check.               | `1e-10`    |

### per_window_fc { #tvbo.analysis.per_window_fc }

```python
analysis.per_window_fc(tv, xv, window=1000.0)
```

Calculate per-window functional connectivity.



#### Parameters {.doc-section .doc-section-parameters}

tv : ndarray
    Time vector.
xv : ndarray
    Data vector.
window : float, optional
    Time window for calculation. Default is 1e3.



#### Returns: {.doc-section .doc-section-returns}

ndarray
    Correlation coefficients for each window.

### ttest_correlation_strength { #tvbo.analysis.ttest_correlation_strength }

```python
analysis.ttest_correlation_strength(cs)
```

Perform a t-test on the strength of the correlation.



#### Parameters {.doc-section .doc-section-parameters}

cs : ndarray
    Correlation coefficients.



#### Returns: {.doc-section .doc-section-returns}

ndarray
    P-values of the t-test for each correlation coefficient.