`results_network.py`¶

Network / Chord Diagram Node – circular element correlation network.

Elements are arranged around a circle. Edges represent significant pairwise Pearson correlations. Red = positive, Blue = negative. Edge width ∝ |r|.

Rendered with Matplotlib (MplDraggableCanvas) for full drag/export support.

Constants¶

Name	Value
`NET_DATA_TYPES`	`['Counts', 'Element Mass (fg)', 'Particle Mass ...`
`NET_DATA_KEY_MAP`	`{'Counts': 'elements', 'Element Mass (fg)': 'el...`
`DEFAULT_CONFIG`	`{'data_type_display': 'Counts', 'r_threshold': ...`

Method	Signature	Description
`__init__`	`(self, color = '#FFFFFF', parent = None)`	Args:
`_apply`	`(self)`
`color`	`(self)`	Returns:
`mousePressEvent`	`(self, event)`	Args:

Method	Signature	Description
`__init__`	`(self, cfg, input_data, parent = None)`	Args:
`_build_ui`	`(self)`
`collect`	`(self)`	Returns:

Method	Signature	Description
`__init__`	`(self, node, parent_window = None)`	Args:
`_build_ui`	`(self)`
`_ctx_menu`	`(self, pos)`	Args:
`_toggle`	`(self, key)`	Args:
`_set`	`(self, key, value)`	Args:
`_reset_layout`	`(self)`
`_export_figure`	`(self)`
`_open_settings`	`(self)`
`_refresh`	`(self)`
`_draw_network`	`(self, ax, net_data, cfg)`	Draw one circular correlation network onto ax.

Method	Signature	Description
`__init__`	`(self, parent_window = None)`	Args:
`set_position`	`(self, pos)`	Args:
`configure`	`(self, parent_window)`	Args:
`process_data`	`(self, input_data)`	Args:
`_get_elements`	`(self)`	Returns:
`extract_network_data`	`(self)`	Returns:
`_extract_single`	`(self, data_key, elements, r_threshold, min_n)`	Args:
`_extract_multi`	`(self, data_key, elements, r_threshold, min_n)`	Args:

def _is_multi(input_data)

Args:

Returns:

def _compute_edges(particles, elements, data_key, r_threshold, min_n)

Return list of (i, j, r) where |r| >= threshold.

Args:

Returns: