diff --git a/src/mol-data/db/column.ts b/src/mol-data/db/column.ts
index be5a2b17113b76fd1bfe3d53e8160a3edacfbdaf..76a893cb9b149267420b39a287ea91a02a2c818e 100644
--- a/src/mol-data/db/column.ts
+++ b/src/mol-data/db/column.ts
@@ -25,8 +25,6 @@ namespace Column {
export type Schema<T = any> = Schema.Str | Schema.Int | Schema.Float | Schema.Coordinate | Schema.Aliased<T> | Schema.Tensor
export namespace Schema {
- export type Scalar<T = any> = Schema.Str | Schema.Int | Schema.Float | Schema.Coordinate | Schema.Aliased<T>
-
export type Str = { '@type': 'str', T: string, valueKind: 'str' }
export type Int = { '@type': 'int', T: number, valueKind: 'int' }
export type Float = { '@type': 'float', T: number, valueKind: 'float' }
@@ -44,7 +42,7 @@ namespace Column {
export function vector(dim: number): Tensor { return tensor(Tensors.Vector(dim)); }
export function matrix(rows: number, cols: number): Tensor { return tensor(Tensors.ColumnMajorMatrix(rows, cols)); }
- export function aliased<T>(t: Schema): Aliased<T> { return t as any as Aliased<T>; }
+ export function aliased<T>(t: Str | Int): Aliased<T> { return t as any as Aliased<T>; }
}
export interface ToArrayParams<T> {
diff --git a/src/mol-io/reader/cif/binary/field.ts b/src/mol-io/reader/cif/binary/field.ts
index 89e2c47af7f28c42cd7490d3a4a56bea03a5e855..c3b2ad33faaffda2590d25d08f34b1c4d215218f 100644
--- a/src/mol-io/reader/cif/binary/field.ts
+++ b/src/mol-io/reader/cif/binary/field.ts
@@ -9,10 +9,6 @@ import * as Data from '../data-model'
import { EncodedColumn, decode } from '../../../common/binary-cif'
import { parseInt as fastParseInt, parseFloat as fastParseFloat } from '../../common/text/number-parser'
-function wrap(o: Data.Field) {
- return { ...o };
-}
-
export default function Field(column: EncodedColumn): Data.Field {
const mask = column.mask ? decode(column.mask) as number[] : void 0;
const data = decode(column.data);
@@ -40,7 +36,7 @@ export default function Field(column: EncodedColumn): Data.Field {
const rowCount = data.length;
- return wrap({
+ return {
'@array': data,
isDefined: true,
rowCount,
@@ -56,5 +52,5 @@ export default function Field(column: EncodedColumn): Data.Field {
toFloatArray: isNumeric
? params => ColumnHelpers.typedArrayWindow(data, params)
: params => ColumnHelpers.createAndFillArray(rowCount, float, params)
- });
+ };
}
\ 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 deb96faffdb3be8a3c3a38e4bbe0beccf5a9141b..8a538d9a363ad431c0f0158f8da0391fd3e61671 100644
--- a/src/mol-io/reader/cif/schema.ts
+++ b/src/mol-io/reader/cif/schema.ts
@@ -4,8 +4,9 @@
* @author David Sehnal <david.sehnal@gmail.com>
*/
-import * as Data from './data-model'
import { Database, Table, Column, ColumnHelpers } from 'mol-data/db'
+import { Tensor } from 'mol-math/linear-algebra'
+import * as Data from './data-model'
export function toDatabase<Schema extends Database.Schema, Frame extends Database<Schema> = Database<Schema>>(schema: Schema, frame: Data.Frame): Frame {
return createDatabase(schema, frame) as Frame;
@@ -22,18 +23,13 @@ function getColumnCtor(t: Column.Schema): ColumnCtor {
case 'str': return (f, c, k) => createColumn(t, f, f.str, f.toStringArray);
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 'tensor': return (f, c, k) => {
- const space = t.space;
- const value = (row: number) => Data.getTensor(c, k, space, row);
- return createColumn(t, f, value, params => ColumnHelpers.createAndFillArray(f.rowCount, value, params));
- }
+ case 'tensor': throw new Error(`Use createTensorColumn instead.`);
}
}
-
function createColumn<T>(schema: Column.Schema, field: Data.Field, value: (row: number) => T, toArray: Column<T>['toArray']): Column<T> {
return {
- schema: schema,
+ schema,
'@array': field['@array'],
isDefined: field.isDefined,
rowCount: field.rowCount,
@@ -44,6 +40,24 @@ 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);
+ const value = (row: number) => Data.getTensor(category, key, space, row);
+ const toArray: Column<Tensor>['toArray'] = params => ColumnHelpers.createAndFillArray(category.rowCount, value, params)
+
+ return {
+ schema,
+ '@array': void 0,
+ isDefined: first.isDefined,
+ rowCount: category.rowCount,
+ value,
+ valueKind: first.valueKind,
+ areValuesEqual: (rowA, rowB) => Tensor.areEqualExact(value(rowA), value(rowB)),
+ toArray
+ };
+}
+
class CategoryTable implements Table<any> { // tslint:disable-line:class-name
_rowCount: number;
_columns: ReadonlyArray<string>;
@@ -57,13 +71,17 @@ class CategoryTable implements Table<any> { // tslint:disable-line:class-name
this._schema = schema;
const cache = Object.create(null);
for (const k of fieldKeys) {
- const cType = schema[k];
- const ctor = getColumnCtor(cType);
Object.defineProperty(this, k, {
get: function() {
if (cache[k]) return cache[k];
- const field = category.getField(k);
- cache[k] = !!field ? ctor(field, category, k) : Column.Undefined(category.rowCount, cType);
+ const cType = schema[k];
+ if (cType.valueKind === 'tensor') {
+ cache[k] = createTensorColumn(cType, category, k);
+ } else {
+ const ctor = getColumnCtor(cType);
+ const field = category.getField(k);
+ cache[k] = !!field ? ctor(field, category, k) : Column.Undefined(category.rowCount, cType);
+ }
return cache[k];
},
enumerable: true,
diff --git a/src/mol-math/linear-algebra/tensor.ts b/src/mol-math/linear-algebra/tensor.ts
index e5a872b9ed58f71a8b4acb992bfbd822cb58275b..3efd39d60ebb057788b8e4bda0e12ff292ea971c 100644
--- a/src/mol-math/linear-algebra/tensor.ts
+++ b/src/mol-math/linear-algebra/tensor.ts
@@ -75,6 +75,13 @@ export namespace Tensor {
return vec;
}
+ export function areEqualExact(a: Tensor, b: Tensor) {
+ const len = a.length;
+ if (len !== b.length) return false;
+ for (let i = 0; i < len; i++) if (a[i] !== b[i]) return false;
+ return true;
+ }
+
function accessors(layout: Layout): { get: Space['get'], set: Space['set'] } {
const { dimensions, axisOrderFastToSlow: ao } = layout;
switch (dimensions.length) {
diff --git a/src/perf-tests/structure.ts b/src/perf-tests/structure.ts
index 62c780e59418929245801c1a19cda96e74ed4713..3ae723fc755aa4eae7250d397a0bed8c21113a44 100644
--- a/src/perf-tests/structure.ts
+++ b/src/perf-tests/structure.ts
@@ -243,8 +243,11 @@ export namespace PropertyAccess {
export async function run() {
//const { structures, models } = await readCIF('./examples/1cbs_full.bcif');
- const { structures, models } = await readCIF('e:/test/quick/3j3q_full.bcif');
- //const { structures, models } = await readCIF('e:/test/quick/1cbs_updated.cif');
+ const { structures, models, mmcif } = await readCIF('e:/test/quick/3j3q_full.bcif');
+ //const { structures, models, mmcif } = await readCIF('e:/test/quick/1cbs_updated.cif');
+
+ console.log(mmcif.pdbx_struct_oper_list.matrix.toArray());
+ console.log(mmcif.pdbx_struct_oper_list.vector.toArray());
//const { structures, models } = await readCIF('e:/test/molstar/3j3q.bcif');
@@ -255,8 +258,6 @@ export namespace PropertyAccess {
// return;
- console.log('parsed');
-
console.log(baseline(models[0]));
console.log(sumProperty(structures[0], l => l.unit.model.conformation.atomId.value(l.atom)));
console.log(sumPropertySegmented(structures[0], l => l.unit.model.conformation.atomId.value(l.atom)));