diff --git a/src/mol-io/reader/cif/data-model.ts b/src/mol-io/reader/cif/data-model.ts
index 28299b6599dae18ecf170e296b41aec2bddae78e..74a15117a134757bb6e747a278445463b01c8e04 100644
--- a/src/mol-io/reader/cif/data-model.ts
+++ b/src/mol-io/reader/cif/data-model.ts
@@ -106,6 +106,6 @@ export function getTensor(category: Category, field: string, space: Tensor.Space
}
}
}
- } else throw new Error('Tensors with rank > 3 currently not supported.');
+ } else throw new Error('Tensors with rank > 3 or rank 0 are currently not supported.');
return ret;
}
\ No newline at end of file
diff --git a/src/mol-io/reader/cif/schema.ts b/src/mol-io/reader/cif/schema.ts
index e3bb62f3e66ae462480cb2d27d505ccd7872fdc0..707710930e283a417ac2da38e1b49f02d2c98701 100644
--- a/src/mol-io/reader/cif/schema.ts
+++ b/src/mol-io/reader/cif/schema.ts
@@ -25,7 +25,7 @@ function getColumnCtor(t: Column.Schema): ColumnCtor {
case 'int': return (f, c, k) => createColumn(t, f, f.int, f.toIntArray);
case 'float': return (f, c, k) => createColumn(t, f, f.float, f.toFloatArray);
case 'list': return (f, c, k) => createColumn(t, f, f.list, f.toListArray);
- case 'tensor': throw new Error(`Use createTensorColumn instead.`);
+ case 'tensor': throw new Error('Use createTensorColumn instead.');
}
}
@@ -44,7 +44,14 @@ function createColumn<T>(schema: Column.Schema, field: Data.Field, value: (row:
function createTensorColumn(schema: Column.Schema.Tensor, category: Data.Category, key: string): Column<Tensor> {
const space = schema.space;
- const first = category.getField(`${key}[1]`) || Column.Undefined(category.rowCount, schema);
+ let firstFieldName: string;
+ switch (space.rank) {
+ case 1: firstFieldName = `${key}[1]`; break;
+ case 2: firstFieldName = `${key}[1][1]`; break;
+ case 3: firstFieldName = `${key}[1][1][1]`; break;
+ default: throw new Error('Tensors with rank > 3 or rank 0 are currently not supported.');
+ }
+ const first = category.getField(firstFieldName) || Column.Undefined(category.rowCount, schema);
const value = (row: number) => Data.getTensor(category, key, space, row);
const toArray: Column<Tensor>['toArray'] = params => ColumnHelpers.createAndFillArray(category.rowCount, value, params)
diff --git a/src/mol-io/writer/cif/encoder.ts b/src/mol-io/writer/cif/encoder.ts
index 21fad348a834a7c2d6781974853105ac99757be2..1f08e032009d55bf6590c778617169d2caa4d6b9 100644
--- a/src/mol-io/writer/cif/encoder.ts
+++ b/src/mol-io/writer/cif/encoder.ts
@@ -1,11 +1,13 @@
/**
- * Copyright (c) 2017 mol* contributors, licensed under MIT, See LICENSE file for more info.
+ * Copyright (c) 2017-2018 mol* contributors, licensed under MIT, See LICENSE file for more info.
*
* @author David Sehnal <david.sehnal@gmail.com>
+ * @author Alexander Rose <alexander.rose@weirdbyte.de>
*/
import Iterator from 'mol-data/iterator'
-import { Column } from 'mol-data/db'
+import { Column, Table } from 'mol-data/db'
+import { Tensor } from 'mol-math/linear-algebra'
import Encoder from '../encoder'
// TODO: support for "coordinate fields", make "coordinate precision" a parameter of the encoder
@@ -13,7 +15,6 @@ import Encoder from '../encoder'
// TODO: automatically detect "best encoding" for integer arrays. This could be used for "fixed-point" as well.
// TODO: add "repeat encoding"? [[1, 2], [1, 2], [1, 2]] --- Repeat ---> [[1, 2], 3]
// TODO: Add "higher level fields"? (i.e. generalization of repeat)
-// TODO: Add tensor field definition
// TODO: align "data blocks" to 8 byte offsets for fast typed array windows? (prolly needs some testing if this is actually the case too)
// TODO: "parametric encoders"? Specify encoding as [{ param: 'value1', encoding1 }, { param: 'value2', encoding2 }]
// then the encoder can specify { param: 'value1' } and the correct encoding will be used.
@@ -35,7 +36,6 @@ export type FieldDefinition<Key = any, Data = any> =
| FieldDefinitionBase<Key, Data> & { type: FieldType.Str, value(key: Key, data: Data): string }
| FieldDefinitionBase<Key, Data> & { type: FieldType.Int, value(key: Key, data: Data): number }
| FieldDefinitionBase<Key, Data> & { type: FieldType.Float, value(key: Key, data: Data): number }
- // TODO: add tensor
export interface FieldFormat {
// TODO: do we actually need this?
@@ -74,4 +74,79 @@ export interface CIFEncoder<T = string | Uint8Array, Context = any> extends Enco
startDataBlock(header: string): void,
writeCategory(category: CategoryProvider, contexts?: Context[]): void,
getData(): T
-}
\ No newline at end of file
+}
+
+function columnValue(k: string) {
+ return (i: number, d: any) => d[k].value(i);
+}
+
+function columnTensorValue(k: string, ...coords: number[]) {
+ return (i: number, d: any) => d[k].schema.space.get(d[k].value(i), ...coords);
+}
+
+function columnValueKind(k: string) {
+ return (i: number, d: any) => d[k].valueKind(i);
+}
+
+function getTensorDefinitions(field: string, space: Tensor.Space) {
+ const fieldDefinitions: FieldDefinition[] = []
+ const type = FieldType.Float
+ const valueKind = columnValueKind(field)
+ if (space.rank === 1) {
+ const rows = space.dimensions[0]
+ for (let i = 0; i < rows; i++) {
+ const name = `${field}[${i + 1}]`
+ fieldDefinitions.push({ name, type, value: columnTensorValue(field, i), valueKind })
+ }
+ } else if (space.rank === 2) {
+ const rows = space.dimensions[0], cols = space.dimensions[1]
+ for (let i = 0; i < rows; i++) {
+ for (let j = 0; j < cols; j++) {
+ const name = `${field}[${i + 1}][${j + 1}]`
+ fieldDefinitions.push({ name, type, value: columnTensorValue(field, i, j), valueKind })
+ }
+ }
+ } else if (space.rank === 3) {
+ const d0 = space.dimensions[0], d1 = space.dimensions[1], d2 = space.dimensions[2]
+ for (let i = 0; i < d0; i++) {
+ for (let j = 0; j < d1; j++) {
+ for (let k = 0; k < d2; k++) {
+ const name = `${field}[${i + 1}][${j + 1}][${k + 1}]`
+ fieldDefinitions.push({ name, type, value: columnTensorValue(field, i, j, k), valueKind })
+ }
+ }
+ }
+ } else {
+ throw new Error('Tensors with rank > 3 or rank 0 are currently not supported.')
+ }
+ return fieldDefinitions
+}
+
+export namespace FieldDefinitions {
+ export function ofSchema(schema: Table.Schema) {
+ const fields: FieldDefinition[] = [];
+ for (const k of Object.keys(schema)) {
+ const t = schema[k];
+ if (t.valueType === 'int') {
+ fields.push({ name: k, type: FieldType.Int, value: columnValue(k), valueKind: columnValueKind(k) });
+ } else if (t.valueType === 'float') {
+ fields.push({ name: k, type: FieldType.Float, value: columnValue(k), valueKind: columnValueKind(k) });
+ } else if (t.valueType === 'str') {
+ fields.push({ name: k, type: FieldType.Str, value: columnValue(k), valueKind: columnValueKind(k) });
+ } else if (t.valueType === 'list') {
+ throw new Error('list not implemented');
+ } else if (t.valueType === 'tensor') {
+ fields.push(...getTensorDefinitions(k, t.space))
+ } else {
+ throw new Error(`Unknown valueType ${t.valueType}`);
+ }
+ }
+ return fields;
+ }
+}
+
+export namespace CategoryDefinition {
+ export function ofTable<S extends Table.Schema>(name: string, table: Table<S>): CategoryDefinition<number> {
+ return { name, fields: FieldDefinitions.ofSchema(table._schema) }
+ }
+}
diff --git a/src/mol-model/structure/export/mmcif.ts b/src/mol-model/structure/export/mmcif.ts
index 6af666d843779c1b55ca99f83e903775e228a5a7..91771616fc93427657c374b92bf151bc95abdbb0 100644
--- a/src/mol-model/structure/export/mmcif.ts
+++ b/src/mol-model/structure/export/mmcif.ts
@@ -1,13 +1,14 @@
/**
- * Copyright (c) 2017 mol* contributors, licensed under MIT, See LICENSE file for more info.
+ * Copyright (c) 2017-2018 mol* contributors, licensed under MIT, See LICENSE file for more info.
*
* @author David Sehnal <david.sehnal@gmail.com>
+ * @author Alexander Rose <alexander.rose@weirdbyte.de>
*/
-import { Column, Table } from 'mol-data/db'
+import { Column } from 'mol-data/db'
import Iterator from 'mol-data/iterator'
import * as Encoder from 'mol-io/writer/cif'
-//import { mmCIF_Schema } from 'mol-io/reader/cif/schema/mmcif'
+// import { mmCIF_Schema } from 'mol-io/reader/cif/schema/mmcif'
import { Structure, Atom, AtomSet } from '../structure'
import { Model } from '../model'
import P from '../query/properties'
@@ -36,29 +37,6 @@ function float<K, D = any>(name: string, value: (k: K, d: D) => number, valueKin
// return { name, type, value, valueKind }
// }
-function columnValue(k: string) {
- return (i: number, d: any) => d[k].value(i);
-}
-
-function columnValueKind(k: string) {
- return (i: number, d: any) => d[k].valueKind(i);
-}
-
-function ofSchema(schema: Table.Schema) {
- const fields: Encoder.FieldDefinition[] = [];
- for (const k of Object.keys(schema)) {
- const t = schema[k];
- // TODO: matrix/vector/support
- const type: any = t.valueType === 'str' ? Encoder.FieldType.Str : t.valueType === 'int' ? Encoder.FieldType.Int : Encoder.FieldType.Float;
- fields.push({ name: k, type, value: columnValue(k), valueKind: columnValueKind(k) })
- }
- return fields;
-}
-
-function ofTable<S extends Table.Schema>(name: string, table: Table<S>): Encoder.CategoryDefinition<number> {
- return { name, fields: ofSchema(table._schema) }
-}
-
// type Entity = Table.Columns<typeof mmCIF_Schema.entity>
// const entity: Encoder.CategoryDefinition<number, Entity> = {
@@ -66,7 +44,6 @@ function ofTable<S extends Table.Schema>(name: string, table: Table<S>): Encoder
// fields: ofSchema(mmCIF_Schema.entity)
// }
-
// [
// str('id', (i, e) => e.id.value(i)),
// str('type', (i, e) => e.type.value(i)),
@@ -126,7 +103,7 @@ const atom_site: Encoder.CategoryDefinition<Atom.Location> = {
function entityProvider({ model }: Context): Encoder.CategoryInstance {
return {
data: model.hierarchy.entities,
- definition: ofTable('entity', model.hierarchy.entities), //entity,
+ definition: Encoder.CategoryDefinition.ofTable('entity', model.hierarchy.entities),
keys: () => Iterator.Range(0, model.hierarchy.entities._rowCount - 1),
rowCount: model.hierarchy.entities._rowCount
}