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remove linemath and tablemath

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This commit is contained in:
matei jordache
2026-03-25 22:39:21 -07:00
parent 7f3dfa8fdf
commit 6de239caa1
11 changed files with 251 additions and 195 deletions
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22
backend/execution.py
View File

@@ -219,10 +219,10 @@ class ExecutionEngine:
) -> None:
"""Wire up broadcast callbacks on display node classes."""
from backend.nodes.display import PreviewImage, PrintTable, View3D, ValueDisplay, Markup
from backend.nodes.analysis import CrossSection, LineCursors, TableMath, Stats, HeightHistogram
from backend.nodes.analysis import CrossSection, LineCursors, TableMath, Stats, Histogram
from backend.nodes.modify import CropResizeField, RotateField
from backend.nodes.mask import ThresholdMask, MaskMorphology, MaskInvert, MaskCombine, DrawMask
from backend.nodes.io import SaveImage, LoadFile, LoadDemo
from backend.nodes.io import SaveImage, Image, ImageDemo
PreviewImage._broadcast_fn = on_preview
ThresholdMask._broadcast_fn = on_preview
@@ -235,26 +235,26 @@ class ExecutionEngine:
ValueDisplay._broadcast_value_fn = on_value
TableMath._broadcast_value_fn = on_value
Stats._broadcast_value_fn = on_value
HeightHistogram._broadcast_overlay_fn = on_overlay
Histogram._broadcast_overlay_fn = on_overlay
CrossSection._broadcast_overlay_fn = on_overlay
LineCursors._broadcast_overlay_fn = on_overlay
CropResizeField._broadcast_overlay_fn = on_overlay
RotateField._broadcast_warning_fn = on_warning
Markup._broadcast_overlay_fn = on_overlay
LoadFile._broadcast_warning_fn = on_warning
LoadDemo._broadcast_warning_fn = on_warning
Image._broadcast_warning_fn = on_warning
ImageDemo._broadcast_warning_fn = on_warning
SaveImage._broadcast_warning_fn = on_warning
def _set_node_id_on_display(self, cls: type, node_id: str) -> None:
"""Inform display nodes of their current node_id for WS tagging."""
from backend.nodes.display import PreviewImage, PrintTable, View3D, ValueDisplay, Markup
from backend.nodes.analysis import CrossSection, LineCursors, TableMath, Stats, HeightHistogram
from backend.nodes.analysis import CrossSection, LineCursors, TableMath, Stats, Histogram
from backend.nodes.modify import CropResizeField, RotateField
from backend.nodes.mask import ThresholdMask, MaskMorphology, MaskInvert, MaskCombine, DrawMask
from backend.nodes.io import LoadFile, LoadDemo, SaveImage
if cls in (PreviewImage, PrintTable, View3D, ValueDisplay, TableMath, Stats, HeightHistogram, CrossSection, LineCursors, CropResizeField, RotateField, Markup,
from backend.nodes.io import Image, ImageDemo, SaveImage
if cls in (PreviewImage, PrintTable, View3D, ValueDisplay, TableMath, Stats, Histogram, CrossSection, LineCursors, CropResizeField, RotateField, Markup,
ThresholdMask, MaskMorphology, MaskInvert, MaskCombine, DrawMask,
LoadFile, LoadDemo, SaveImage):
Image, ImageDemo, SaveImage):
cls._current_node_id = node_id
def _auto_preview(
@@ -275,12 +275,12 @@ class ExecutionEngine:
from backend.data_types import (
DataField, image_to_uint8, encode_preview, render_datafield_preview,
)
from backend.nodes.io import LoadFile, LoadDemo
from backend.nodes.io import Image, ImageDemo
if getattr(cls, "_CUSTOM_PREVIEW", False):
return
if cls in (LoadFile, LoadDemo) and on_preview:
if cls in (Image, ImageDemo) and on_preview:
preview = self._render_load_node_preview(result, inputs or {})
if preview:
on_preview(node_id, preview)

98
backend/node_menu.py Normal file
View File

@@ -0,0 +1,98 @@
"""
Central Add Node menu manifest.
Edit MENU_LAYOUT to rearrange which nodes appear under each menu leaf and
their order within that leaf. Node classes not listed here fall back to their
class CATEGORY.
"""
from __future__ import annotations
from typing import Any
MENU_LAYOUT: dict[str, list[str]] = {
"Add": [
"Image",
"ImageDemo",
"Folder",
"ColorMap",
"Number",
"RangeSlider",
"Coordinate",
"Font",
],
"Output": [
"PreviewImage",
"SaveImage",
"View3D",
"PrintTable",
"ValueDisplay",
],
"Overlay": [
"Markup",
"Annotations",
],
"Modify": [
"ColormapAdjust",
"CropResizeField",
"RotateField",
],
"Filter": [
"GaussianFilter",
"MedianFilter",
"EdgeDetect",
"FFTFilter1D",
"FFTFilter2D",
],
"Frequency": [
"FFT2D",
"InverseFFT2D",
],
"Flatten": [
"PlaneLevelField",
"PolyLevelField",
"FixZero",
],
"Measure": [
"Statistics",
"Histogram",
"LineCursors",
"CrossSection",
"Stats",
],
"Mask": [
"DrawMask",
"ThresholdMask",
"MaskMorphology",
"MaskInvert",
"MaskCombine",
],
"Particles": [
"ParticleAnalysis",
],
}
_CATEGORY_ORDER = {category: index for index, category in enumerate(MENU_LAYOUT)}
_NODE_METADATA: dict[str, dict[str, Any]] = {}
for category, class_names in MENU_LAYOUT.items():
for node_order, class_name in enumerate(class_names):
_NODE_METADATA[class_name] = {
"category": category,
"category_order": _CATEGORY_ORDER[category],
"menu_order": node_order,
}
def get_menu_metadata(class_name: str, fallback_category: str = "uncategorized") -> dict[str, Any]:
metadata = _NODE_METADATA.get(class_name)
if metadata is not None:
return dict(metadata)
fallback_order = _CATEGORY_ORDER.get(fallback_category, len(_CATEGORY_ORDER))
return {
"category": fallback_category,
"category_order": fallback_order,
"menu_order": 10_000,
}

7
backend/node_registry.py
View File

@@ -9,6 +9,8 @@ the execution engine and the /nodes REST endpoint.
from __future__ import annotations
from typing import Any
from backend.node_menu import get_menu_metadata
NODE_CLASS_MAPPINGS: dict[str, type] = {}
NODE_DISPLAY_NAME_MAPPINGS: dict[str, str] = {}
@@ -37,11 +39,14 @@ def get_node_info(class_name: str) -> dict[str, Any]:
"""
cls = NODE_CLASS_MAPPINGS[class_name]
input_types: dict = cls.INPUT_TYPES()
menu_metadata = get_menu_metadata(class_name, getattr(cls, "CATEGORY", "uncategorized"))
return {
"name": class_name,
"display_name": NODE_DISPLAY_NAME_MAPPINGS.get(class_name, class_name),
"category": getattr(cls, "CATEGORY", "uncategorized"),
"category": menu_metadata["category"],
"category_order": menu_metadata["category_order"],
"menu_order": menu_metadata["menu_order"],
"input": input_types,
"input_order": {k: list(v.keys()) for k, v in input_types.items()},
"output": list(cls.RETURN_TYPES),

98
backend/nodes/analysis.py
View File

@@ -2,8 +2,8 @@
Analysis nodes — statistics, histograms, FFT, cross sections.
Gwyddion equivalents:
StatisticsNode → gwy_data_field_get_min/max/avg/rms (libprocess/stats.h)
HeightHistogram → DH (height distribution), gwy_data_field_dh
Statistics → gwy_data_field_get_min/max/avg/rms (libprocess/stats.h)
Histogram → DH (height distribution), gwy_data_field_dh
FFT2D → gwy_data_field_2dfft + gwy_data_field_2dpsdf
CrossSection → gwy_data_field_get_profile (libprocess/datafield.c)
"""
@@ -16,11 +16,11 @@ from backend.data_types import DataField, MeasureTable, RecordTable, datafield_t
# ---------------------------------------------------------------------------
# StatisticsNode
# Statistics
# ---------------------------------------------------------------------------
@register_node(display_name="Statistics")
class StatisticsNode:
class Statistics:
@classmethod
def INPUT_TYPES(cls):
return {
@@ -59,11 +59,11 @@ class StatisticsNode:
# ---------------------------------------------------------------------------
# HeightHistogram
# Histogram
# ---------------------------------------------------------------------------
@register_node(display_name="Height Histogram")
class HeightHistogram:
class Histogram:
@classmethod
def INPUT_TYPES(cls):
return {
@@ -130,9 +130,9 @@ class HeightHistogram:
yb = float(counts[idx_b]) if len(counts) else 0.0
count_unit = "count" if y_scale == "linear" else "log10(1+count)"
if HeightHistogram._broadcast_overlay_fn is not None:
HeightHistogram._broadcast_overlay_fn(
HeightHistogram._current_node_id,
if Histogram._broadcast_overlay_fn is not None:
Histogram._broadcast_overlay_fn(
Histogram._current_node_id,
{
"kind": "line_plot",
"section_title": "Histogram",
@@ -754,36 +754,6 @@ def _op_da(z):
return float(np.mean(np.abs(np.diff(z))))
@register_node(display_name="Line Math")
class LineMath:
"""Compute a single scalar value from a LINE profile."""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"line": ("LINE",),
"operation": (list(LINE_OPS.keys()),),
}
}
RETURN_TYPES = ("MEASURE_TABLE",)
RETURN_NAMES = ("result",)
FUNCTION = "process"
CATEGORY = "analysis"
DESCRIPTION = (
"Compute a single scalar measurement from a LINE profile. "
"Includes basic stats and Gwyddion-convention roughness parameters."
)
def process(self, line, operation: str) -> tuple:
z = np.asarray(line, dtype=np.float64).ravel()
fn, unit = LINE_OPS[operation]
value = fn(z)
table = MeasureTable([{"quantity": operation, "value": value, "unit": unit}])
return (table,)
# ---------------------------------------------------------------------------
# TableMath — scalar measurement from a numeric record-table column
# ---------------------------------------------------------------------------
@@ -869,56 +839,6 @@ def _scalar_payload(value: float, unit: str = "") -> dict:
return payload
@register_node(display_name="Table Math")
class TableMath:
"""Compute a scalar reduction over one numeric column in a record table."""
_broadcast_value_fn = None
_current_node_id: str = ""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"table": ("RECORD_TABLE",),
"column": ("STRING", {
"default": "value",
"choices_from_table_input": "table",
}),
"operation": (list(TABLE_OPS.keys()),),
}
}
RETURN_TYPES = ("FLOAT",)
RETURN_NAMES = ("value",)
FUNCTION = "process"
CATEGORY = "analysis"
DESCRIPTION = (
"Compute a scalar reduction over one numeric record-table column. "
"Useful for max, min, avg, median, sum, range, std, variance, and count."
)
def process(self, table: list, column: str, operation: str) -> tuple:
if isinstance(table, MeasureTable):
raise ValueError("Table Math only accepts record tables, not measurement tables.")
if not isinstance(table, list) or not table:
raise ValueError("Table Math requires a non-empty record table input.")
column_name = resolve_table_column_name(table, column)
values = extract_numeric_table_values(table, column_name)
if not values:
raise ValueError(f"Column '{column_name}' has no numeric values.")
op = TABLE_OPS.get(operation)
if op is None:
raise ValueError(f"Unsupported table operation: {operation}")
result = op(np.asarray(values, dtype=np.float64))
if TableMath._broadcast_value_fn is not None:
TableMath._broadcast_value_fn(TableMath._current_node_id, result)
return (result,)
def extract_numeric_table_values(table: list, column: str) -> list[float]:
values = []
for row in table:

18
backend/nodes/io.py
View File

@@ -125,11 +125,11 @@ def list_folder_paths(folderpath: str) -> list[dict]:
# ---------------------------------------------------------------------------
# LoadFile (unified loader — replaces LoadImage + LoadSPM)
# Image (unified loader — replaces LoadImage + LoadSPM)
# ---------------------------------------------------------------------------
@register_node(display_name="Load File")
class LoadFile:
@register_node(display_name="Image")
class Image:
@classmethod
def INPUT_TYPES(cls):
return {
@@ -185,8 +185,8 @@ class LoadFile:
return (field,)
def _send_warning(self, message: str):
fn = LoadFile._broadcast_warning_fn
nid = LoadFile._current_node_id
fn = Image._broadcast_warning_fn
nid = Image._current_node_id
if fn and nid:
fn(nid, message)
@@ -353,7 +353,7 @@ class LoadFile:
# ---------------------------------------------------------------------------
# LoadDemo
# ImageDemo
# ---------------------------------------------------------------------------
def _list_demo_files() -> list[str]:
@@ -366,8 +366,8 @@ def _list_demo_files() -> list[str]:
)
@register_node(display_name="Load Demo File")
class LoadDemo:
@register_node(display_name="Image (Demo)")
class ImageDemo:
@classmethod
def INPUT_TYPES(cls):
choices = _list_demo_files() or ["(no demo files found)"]
@@ -388,7 +388,7 @@ class LoadDemo:
DESCRIPTION = "Load a bundled demo file so you can try the app without providing your own data."
def load(self, name: str = "", colormap: str = "viridis", colormap_map=None):
loader = LoadFile()
loader = Image()
demo_path = DEMO_DIR / name
if not demo_path.exists():
raise FileNotFoundError(f"Demo file not found: {name}")

65
frontend/src/App.jsx
View File

@@ -80,6 +80,23 @@ function sameStringArray(a = [], b = []) {
return a.every((item, index) => item === b[index]);
}
function compareMenuNodes(a, b) {
const orderA = Number.isFinite(a?.def?.menu_order) ? a.def.menu_order : Number.MAX_SAFE_INTEGER;
const orderB = Number.isFinite(b?.def?.menu_order) ? b.def.menu_order : Number.MAX_SAFE_INTEGER;
if (orderA !== orderB) return orderA - orderB;
const nameA = (a?.def?.display_name || a?.className || '').toLowerCase();
const nameB = (b?.def?.display_name || b?.className || '').toLowerCase();
return nameA.localeCompare(nameB);
}
function compareMenuCategories(a, b) {
const orderA = Number.isFinite(a?.order) ? a.order : Number.MAX_SAFE_INTEGER;
const orderB = Number.isFinite(b?.order) ? b.order : Number.MAX_SAFE_INTEGER;
if (orderA !== orderB) return orderA - orderB;
return String(a?.name || '').localeCompare(String(b?.name || ''));
}
function socketTypesCompatible(sourceType, targetType) {
if (sourceType === targetType) return true;
const accepted = SOCKET_COMPATIBILITY[targetType];
@@ -272,10 +289,25 @@ function ContextMenu({ x, y, nodeDefs, onAdd, onClose, filterType, filterDirecti
}
}
const cat = def.category || 'uncategorized';
if (!cats[cat]) cats[cat] = [];
cats[cat].push({ className, def });
if (!cats[cat]) {
cats[cat] = {
name: cat,
order: Number.isFinite(def.category_order) ? def.category_order : Number.MAX_SAFE_INTEGER,
items: [],
};
}
cats[cat].order = Math.min(
cats[cat].order,
Number.isFinite(def.category_order) ? def.category_order : Number.MAX_SAFE_INTEGER,
);
cats[cat].items.push({ className, def });
}
return cats;
return Object.values(cats)
.map((category) => ({
...category,
items: [...category.items].sort(compareMenuNodes),
}))
.sort(compareMenuCategories);
}, [nodeDefs, filterType, filterDirection]);
// Flat filtered list for search
@@ -283,8 +315,8 @@ function ContextMenu({ x, y, nodeDefs, onAdd, onClose, filterType, filterDirecti
if (!search.trim()) return null;
const q = search.toLowerCase();
const results = [];
for (const items of Object.values(categories)) {
for (const { className, def } of items) {
for (const category of categories) {
for (const { className, def } of category.items) {
const name = (def.display_name || className).toLowerCase();
if (name.includes(q)) results.push({ className, def });
}
@@ -341,7 +373,7 @@ function ContextMenu({ x, y, nodeDefs, onAdd, onClose, filterType, filterDirecti
setOpenCat(cat);
}, []);
if (Object.keys(categories).length === 0) {
if (categories.length === 0) {
return (
<div className="context-menu" ref={menuRef} style={{ left: menuPos.x, top: menuPos.y }} onClick={(e) => e.stopPropagation()}>
<div className="context-item" style={{ color: '#64748b' }}>No compatible nodes</div>
@@ -349,7 +381,8 @@ function ContextMenu({ x, y, nodeDefs, onAdd, onClose, filterType, filterDirecti
);
}
const catNames = Object.keys(categories).sort();
const catNames = categories.map((category) => category.name);
const categoryMap = Object.fromEntries(categories.map((category) => [category.name, category.items]));
return (
<>
@@ -411,7 +444,7 @@ function ContextMenu({ x, y, nodeDefs, onAdd, onClose, filterType, filterDirecti
</div>
{/* Submenu rendered as a sibling, positioned at computed screen coords */}
{openCat && categories[openCat] && (
{openCat && categoryMap[openCat] && (
<div
className="context-menu ctx-submenu"
ref={subMenuRef}
@@ -423,7 +456,7 @@ function ContextMenu({ x, y, nodeDefs, onAdd, onClose, filterType, filterDirecti
setOpenCat(null);
}}
>
{categories[openCat].map(({ className, def }) => (
{categoryMap[openCat].map(({ className, def }) => (
<div
key={className}
className="context-item"
@@ -512,9 +545,9 @@ function Flow() {
resolvedPath = getResolvedPathInput(nodeId);
}
if (!resolvedPath) {
if (node.data.className === 'LoadFile') {
if (node.data.className === 'Image') {
resolvedPath = node.data.widgetValues?.filename || '';
} else if (node.data.className === 'LoadDemo') {
} else if (node.data.className === 'ImageDemo') {
resolvedPath = node.data.widgetValues?.name || '';
}
}
@@ -707,7 +740,7 @@ function Flow() {
refreshFolderNodeOutputs(nodeId, value);
}
if (node && (node.data.className === 'LoadFile' || node.data.className === 'LoadDemo') && (name === 'filename' || name === 'name')) {
if (node && (node.data.className === 'Image' || node.data.className === 'ImageDemo') && (name === 'filename' || name === 'name')) {
refreshLoadNodeOutputs(nodeId, value);
}
@@ -803,11 +836,11 @@ function Flow() {
refreshFolderNodeOutputs(newNodeId, widgetValues.folder);
}
// For LoadFile/LoadDemo, auto-fetch channels for the default value
if (className === 'LoadDemo' && widgetValues.name) {
// For Image/ImageDemo, auto-fetch channels for the default value
if (className === 'ImageDemo' && widgetValues.name) {
refreshLoadNodeOutputs(newNodeId, widgetValues.name);
}
if (className === 'LoadFile' && widgetValues.filename) {
if (className === 'Image' && widgetValues.filename) {
refreshLoadNodeOutputs(newNodeId, widgetValues.filename);
}
@@ -924,7 +957,7 @@ function Flow() {
}
});
hydrated.nodes.forEach((node) => {
if (node.data.className === 'LoadFile' || node.data.className === 'LoadDemo') {
if (node.data.className === 'Image' || node.data.className === 'ImageDemo') {
refreshLoadNodeOutputs(node.id);
}
});

4
frontend/src/CustomNode.jsx
View File

@@ -868,10 +868,10 @@ function CustomNode({ id, data }) {
if (data.className === 'Folder') {
return getBasename(data.widgetValues?.folder);
}
if (data.className === 'LoadFile') {
if (data.className === 'Image') {
return getBasename(connectedPathInfo?.path || data.widgetValues?.filename);
}
if (data.className === 'LoadDemo') {
if (data.className === 'ImageDemo') {
return getBasename(data.widgetValues?.name);
}
return '';

6
frontend/src/executionGraph.js
View File

@@ -21,14 +21,14 @@ export function getConnectedNodeIds(edges) {
}
function isPreviewLoadNode(node) {
return ['LoadFile', 'LoadDemo'].includes(node?.data?.className);
return ['Image', 'ImageDemo'].includes(node?.data?.className);
}
function hasPreviewLoadSelection(node) {
if (node?.data?.className === 'LoadFile') {
if (node?.data?.className === 'Image') {
return !!String(node.data?.widgetValues?.filename || '').trim();
}
if (node?.data?.className === 'LoadDemo') {
if (node?.data?.className === 'ImageDemo') {
return !!String(node.data?.widgetValues?.name || '').trim();
}
return false;

42
frontend/tests/executionGraph.test.mjs
View File

@@ -12,7 +12,7 @@ test('serializeExecutionGraph excludes isolated nodes from the backend prompt',
{
id: '1',
data: {
className: 'LoadFile',
className: 'Image',
definition: {
input: { required: { filename: ['FILE_PICKER', {}] }, optional: {} },
manual_trigger: false,
@@ -34,7 +34,7 @@ test('serializeExecutionGraph excludes isolated nodes from the backend prompt',
{
id: '3',
data: {
className: 'LoadFile',
className: 'Image',
definition: {
input: { required: { filename: ['FILE_PICKER', {}] }, optional: {} },
manual_trigger: false,
@@ -56,7 +56,7 @@ test('serializeExecutionGraph excludes isolated nodes from the backend prompt',
assert.deepEqual(prompt, {
'1': {
class_type: 'LoadFile',
class_type: 'Image',
inputs: { filename: 'scan.gwy' },
},
'2': {
@@ -72,7 +72,7 @@ test('serializeExecutionGraph includes isolated preview-load nodes alongside con
{
id: '1',
data: {
className: 'LoadFile',
className: 'Image',
definition: {
input: { required: { filename: ['FILE_PICKER', {}] }, optional: {} },
manual_trigger: false,
@@ -94,7 +94,7 @@ test('serializeExecutionGraph includes isolated preview-load nodes alongside con
{
id: '3',
data: {
className: 'LoadDemo',
className: 'ImageDemo',
definition: {
input: { required: { name: [['demo.npy'], {}] }, optional: {} },
manual_trigger: false,
@@ -105,7 +105,7 @@ test('serializeExecutionGraph includes isolated preview-load nodes alongside con
{
id: '4',
data: {
className: 'LoadFile',
className: 'Image',
definition: {
input: { required: { filename: ['FILE_PICKER', {}] }, optional: {} },
manual_trigger: false,
@@ -127,7 +127,7 @@ test('serializeExecutionGraph includes isolated preview-load nodes alongside con
assert.deepEqual(prompt, {
'1': {
class_type: 'LoadFile',
class_type: 'Image',
inputs: { filename: 'first.gwy' },
},
'2': {
@@ -135,19 +135,19 @@ test('serializeExecutionGraph includes isolated preview-load nodes alongside con
inputs: { field: ['1', 0] },
},
'3': {
class_type: 'LoadDemo',
class_type: 'ImageDemo',
inputs: { name: 'demo.npy' },
},
});
assert.equal('4' in prompt, false);
});
test('serializeExecutionGraph allows a singleton LoadFile graph so previews can run', () => {
test('serializeExecutionGraph allows a singleton Image graph so previews can run', () => {
const nodes = [
{
id: '1',
data: {
className: 'LoadFile',
className: 'Image',
definition: {
input: { required: { filename: ['FILE_PICKER', {}] }, optional: {} },
manual_trigger: false,
@@ -161,18 +161,18 @@ test('serializeExecutionGraph allows a singleton LoadFile graph so previews can
assert.deepEqual(prompt, {
'1': {
class_type: 'LoadFile',
class_type: 'Image',
inputs: { filename: 'scan.gwy' },
},
});
});
test('serializeExecutionGraph allows a singleton LoadDemo graph so previews can run', () => {
test('serializeExecutionGraph allows a singleton ImageDemo graph so previews can run', () => {
const nodes = [
{
id: '1',
data: {
className: 'LoadDemo',
className: 'ImageDemo',
definition: {
input: { required: { name: [['demo.npy'], {}] }, optional: {} },
manual_trigger: false,
@@ -186,7 +186,7 @@ test('serializeExecutionGraph allows a singleton LoadDemo graph so previews can
assert.deepEqual(prompt, {
'1': {
class_type: 'LoadDemo',
class_type: 'ImageDemo',
inputs: { name: 'demo.npy' },
},
});
@@ -214,10 +214,10 @@ test('getAutoRunnableNodes ignores disconnected nodes when deciding what can aut
test('getAutoRunnableNodes includes isolated preview-load nodes with selections', () => {
const nodes = [
{ id: '1', data: { className: 'LoadFile', definition: {}, widgetValues: { filename: 'first.gwy' } } },
{ id: '1', data: { className: 'Image', definition: {}, widgetValues: { filename: 'first.gwy' } } },
{ id: '2', data: { className: 'PreviewImage', definition: {}, widgetValues: {} } },
{ id: '3', data: { className: 'LoadDemo', definition: {}, widgetValues: { name: 'demo.npy' } } },
{ id: '4', data: { className: 'LoadFile', definition: {}, widgetValues: { filename: '' } } },
{ id: '3', data: { className: 'ImageDemo', definition: {}, widgetValues: { name: 'demo.npy' } } },
{ id: '4', data: { className: 'Image', definition: {}, widgetValues: { filename: '' } } },
];
const edges = [
{
@@ -233,12 +233,12 @@ test('getAutoRunnableNodes includes isolated preview-load nodes with selections'
assert.deepEqual(runnable.map((node) => node.id), ['1', '2', '3']);
});
test('getAutoRunnableNodes allows a singleton LoadFile graph', () => {
test('getAutoRunnableNodes allows a singleton Image graph', () => {
const nodes = [
{
id: '1',
data: {
className: 'LoadFile',
className: 'Image',
definition: {},
widgetValues: { filename: 'scan.gwy' },
},
@@ -250,12 +250,12 @@ test('getAutoRunnableNodes allows a singleton LoadFile graph', () => {
assert.deepEqual(runnable.map((node) => node.id), ['1']);
});
test('getAutoRunnableNodes allows a singleton LoadDemo graph', () => {
test('getAutoRunnableNodes allows a singleton ImageDemo graph', () => {
const nodes = [
{
id: '1',
data: {
className: 'LoadDemo',
className: 'ImageDemo',
definition: {},
widgetValues: { name: 'demo.npy' },
},

14
frontend/tests/workflowSerialization.test.mjs
View File

@@ -103,7 +103,7 @@ test('hydrateWorkflowState clears shared path widgets while restoring saved dyna
id: '12',
position: { x: 40, y: 80 },
data: {
className: 'LoadFile',
className: 'Image',
widgetValues: { filename: 'scan.ibw', colormap: 'viridis' },
output: ['DATA_FIELD', 'DATA_FIELD'],
output_name: ['Height', 'Phase'],
@@ -123,7 +123,7 @@ test('hydrateWorkflowState clears shared path widgets while restoring saved dyna
};
const defs = {
LoadFile: {
Image: {
category: 'io',
input: { required: { filename: ['FILE_PICKER', {}], colormap: [['viridis', 'gray'], {}] } },
output: ['DATA_FIELD'],
@@ -138,13 +138,13 @@ test('hydrateWorkflowState clears shared path widgets while restoring saved dyna
assert.deepEqual(hydrated.edges, saved.edges);
assert.equal(hydrated.nodes[0].type, 'custom');
assert.equal(hydrated.nodes[0].dragHandle, '.drag-handle');
assert.equal(hydrated.nodes[0].data.label, 'LoadFile');
assert.equal(hydrated.nodes[0].data.label, 'Image');
assert.equal(hydrated.nodes[0].data.previewImage, null);
assert.equal(hydrated.nodes[0].data.widgetValues.filename, '');
assert.equal(hydrated.nodes[0].data.widgetValues.colormap, 'viridis');
assert.deepEqual(hydrated.nodes[0].data.definition.output, ['DATA_FIELD', 'DATA_FIELD']);
assert.deepEqual(hydrated.nodes[0].data.definition.output_name, ['Height', 'Phase']);
assert.deepEqual(hydrated.nodes[0].data.definition.input, defs.LoadFile.input);
assert.deepEqual(hydrated.nodes[0].data.definition.input, defs.Image.input);
});
test('serializeWorkflowState and hydrateWorkflowState clear path-like widgets but preserve other metadata', () => {
@@ -153,8 +153,8 @@ test('serializeWorkflowState and hydrateWorkflowState clear path-like widgets bu
id: '7',
position: { x: 10, y: 20 },
data: {
label: 'Load File',
className: 'LoadFile',
label: 'Image',
className: 'Image',
widgetValues: { filename: 'scan.gwy', colormap: 'gray' },
definition: {
category: 'io',
@@ -176,7 +176,7 @@ test('serializeWorkflowState and hydrateWorkflowState clear path-like widgets bu
},
];
const defs = {
LoadFile: {
Image: {
category: 'io',
input: { required: { filename: ['FILE_PICKER', {}], colormap: [['gray', 'viridis'], {}] } },
output: ['DATA_FIELD'],

72
tests/test_nodes.py
View File

@@ -476,9 +476,9 @@ def test_fix_zero():
# =========================================================================
def test_statistics():
print("=== Test: StatisticsNode ===")
from backend.nodes.analysis import StatisticsNode
node = StatisticsNode()
print("=== Test: Statistics ===")
from backend.nodes.analysis import Statistics
node = Statistics()
data = np.array([[1, 2], [3, 4]], dtype=np.float64)
field = make_field(data=data)
@@ -506,17 +506,17 @@ def test_statistics():
def test_height_histogram():
print("=== Test: HeightHistogram ===")
from backend.nodes.analysis import HeightHistogram
node = HeightHistogram()
print("=== Test: Histogram ===")
from backend.nodes.analysis import Histogram
node = Histogram()
# Uniform data should give a roughly flat histogram
data = np.linspace(0, 1, 1000).reshape(25, 40)
field = make_field(data=data)
overlays = []
HeightHistogram._broadcast_overlay_fn = lambda nid, data: overlays.append(data)
HeightHistogram._current_node_id = "test"
Histogram._broadcast_overlay_fn = lambda nid, data: overlays.append(data)
Histogram._current_node_id = "test"
table, = node.process(
field,
@@ -549,7 +549,7 @@ def test_height_histogram():
measurements["B count"]["value"] - measurements["A count"]["value"],
)
HeightHistogram._broadcast_overlay_fn = None
Histogram._broadcast_overlay_fn = None
print(" PASS\n")
@@ -829,10 +829,10 @@ def test_particle_analysis():
# =========================================================================
def test_load_file():
print("=== Test: LoadFile ===")
from backend.nodes.io import LoadFile
print("=== Test: Image ===")
from backend.nodes.io import Image
from PIL import Image
node = LoadFile()
node = Image()
with tempfile.TemporaryDirectory() as tmpdir:
# Test loading a grayscale PNG → single DataField output
@@ -1247,10 +1247,10 @@ def test_value_display():
# =========================================================================
def test_load_file_ibw():
print("=== Test: LoadFile IBW multi-channel ===")
from backend.nodes.io import LoadFile
print("=== Test: Image IBW multi-channel ===")
from backend.nodes.io import Image
node = LoadFile()
node = Image()
ibw_path = os.path.join(os.path.dirname(__file__), "..", "demo", "BR_New20012.ibw")
ibw_path = os.path.abspath(ibw_path)
if not os.path.exists(ibw_path):
@@ -1283,10 +1283,10 @@ def test_load_file_ibw():
def test_load_file_npz():
print("=== Test: LoadFile .npz ===")
from backend.nodes.io import LoadFile
print("=== Test: Image .npz ===")
from backend.nodes.io import Image
node = LoadFile()
node = Image()
with tempfile.TemporaryDirectory() as tmpdir:
data = np.random.default_rng(99).standard_normal((30, 40))
path = os.path.join(tmpdir, "test.npz")
@@ -1300,10 +1300,10 @@ def test_load_file_npz():
def test_load_file_not_found():
print("=== Test: LoadFile not found ===")
from backend.nodes.io import LoadFile
print("=== Test: Image not found ===")
from backend.nodes.io import Image
node = LoadFile()
node = Image()
try:
node.load(filename="/nonexistent/path/file.png")
assert False, "Should have raised FileNotFoundError"
@@ -1314,10 +1314,10 @@ def test_load_file_not_found():
def test_load_file_unsupported():
print("=== Test: LoadFile unsupported format ===")
from backend.nodes.io import LoadFile
print("=== Test: Image unsupported format ===")
from backend.nodes.io import Image
node = LoadFile()
node = Image()
with tempfile.TemporaryDirectory() as tmpdir:
path = os.path.join(tmpdir, "test.xyz")
with open(path, "w") as f:
@@ -1332,14 +1332,14 @@ def test_load_file_unsupported():
def test_load_file_warning():
print("=== Test: LoadFile warning for uncalibrated data ===")
from backend.nodes.io import LoadFile
print("=== Test: Image warning for uncalibrated data ===")
from backend.nodes.io import Image
from PIL import Image
node = LoadFile()
node = Image()
warnings = []
LoadFile._broadcast_warning_fn = lambda nid, msg: warnings.append(msg)
LoadFile._current_node_id = "test"
Image._broadcast_warning_fn = lambda nid, msg: warnings.append(msg)
Image._current_node_id = "test"
with tempfile.TemporaryDirectory() as tmpdir:
arr = np.random.default_rng(10).integers(0, 256, (16, 16), dtype=np.uint8)
@@ -1352,7 +1352,7 @@ def test_load_file_warning():
assert len(warnings) == 1
assert "Uncalibrated" in warnings[0]
LoadFile._broadcast_warning_fn = None
Image._broadcast_warning_fn = None
print(" PASS\n")
@@ -1428,14 +1428,14 @@ def test_list_channels():
# =========================================================================
# I/O — LoadDemo
# I/O — ImageDemo
# =========================================================================
def test_load_demo():
print("=== Test: LoadDemo ===")
from backend.nodes.io import LoadDemo
print("=== Test: ImageDemo ===")
from backend.nodes.io import ImageDemo
node = LoadDemo()
node = ImageDemo()
# Should be able to load a demo file by name
result = node.load(name="nanoparticles.npy")
@@ -1460,14 +1460,14 @@ def test_load_demo():
def test_load_demo_multi_layer_preview_payload():
print("=== Test: LoadDemo multi-layer preview payload ===")
print("=== Test: ImageDemo multi-layer preview payload ===")
from backend.execution import ExecutionEngine
import backend.nodes # noqa: F401
previews = []
prompt = {
"1": {
"class_type": "LoadDemo",
"class_type": "ImageDemo",
"inputs": {
"name": "whiskers.ibw",
"colormap": "viridis",