diff --git a/dist/index.js b/dist/index.js
index 902c17b..e75cb6a 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -1,18 +1,18 @@
-"use strict";var g=function(e,a){return function(){return a||e((a={exports:{}}).exports,a),a.exports}};var E=g(function(De,O){
+"use strict";var g=function(e,a){return function(){return a||e((a={exports:{}}).exports,a),a.exports}};var T=g(function(Ie,O){
 var R=require('@stdlib/constants-float64-pinf/dist'),U=require('@stdlib/math-base-assert-is-integer/dist');function G(e){return typeof e=="object"&&e!==null&&typeof e.length=="number"&&U(e.length)&&e.length>=0&&e.length<R}O.exports=G
-});var x=g(function(Se,T){
-var m=require('@stdlib/ndarray-defaults/dist');function _(){return{casting:m.get("casting"),copy:!1,dtype:m.get("dtypes.default"),flatten:!0,mode:m.get("index_mode"),ndmin:0,order:m.get("order"),readonly:!1}}T.exports=_
-});var k=g(function(Ae,j){
-var H=require('@stdlib/ndarray-base-buffer-ctors/dist'),J=require('@stdlib/buffer-alloc-unsafe/dist');function K(e,a,r){var o,i,t;if(o=H(r),r==="generic")for(i=[],t=0;t<a;t++)i.push(e[t]);else if(r==="binary")for(i=J(a),t=0;t<a;t++)i[t]=e[t];else for(i=new o(a),t=0;t<a;t++)i[t]=e[t];return i}j.exports=K
-});var D=g(function(Ne,B){
-var Q=require('@stdlib/ndarray-base-buffer-ctors/dist'),W=require('@stdlib/buffer-alloc-unsafe/dist');function X(e){var a,r,o;for(a=e.length,r=[],o=0;o<a;o++)r.push(e.get(o));return r}function Y(e){var a,r,o;for(a=e.length,r=W(a),o=0;o<a;o++)r[o]=e.get(o);return r}function Z(e,a){var r,o,i,t;for(r=Q(a),o=e.length,i=new r(o),t=0;t<o;t++)i[t]=e.get(t);return i}function $(e,a){return a==="generic"?X(e):a==="binary"?Y(e):Z(e,a)}B.exports=$
-});var A=g(function(Ce,S){
-function ee(e,a,r){var o,i;for(o=[],i=0;i<r-e;i++)o.push(1);for(i=0;i<e;i++)o.push(a[i]);return o}S.exports=ee
-});var C=g(function(Ve,N){
-var re=require('@stdlib/math-base-special-abs/dist');function ie(e,a,r,o){var i,t,u,n,f;if(t=r.length,f=e-t,i=[],o==="row-major"){for(u=re(r[0])*a[f],n=0;n<f;n++)i.push(u);for(n=0;n<t;n++)i.push(r[n])}else{for(n=0;n<f;n++)i.push(1);for(n=0;n<t;n++)i.push(r[n])}return i}N.exports=ie
-});var M=g(function(Le,I){
-var d=require('@stdlib/assert-has-own-property/dist'),V=require('@stdlib/assert-is-plain-object/dist'),L=require('@stdlib/assert-is-boolean/dist').isPrimitive,te=require('@stdlib/assert-is-array/dist'),ae=require('@stdlib/assert-is-nonnegative-integer/dist').isPrimitive,ne=require('@stdlib/assert-is-ndarray-like/dist'),oe=require('@stdlib/ndarray-base-shape2strides/dist'),se=require('@stdlib/ndarray-base-strides2offset/dist'),ue=require('@stdlib/ndarray-base-strides2order/dist'),h=require('@stdlib/ndarray-base-numel/dist'),fe=require('@stdlib/ndarray-ctor/dist'),pe=require('@stdlib/ndarray-base-assert-is-data-type/dist'),de=require('@stdlib/ndarray-base-assert-is-order/dist'),le=require('@stdlib/ndarray-base-assert-is-casting-mode/dist'),ve=require('@stdlib/ndarray-base-assert-is-allowed-data-type-cast/dist'),ce=require('@stdlib/ndarray-base-buffer/dist'),ge=require('@stdlib/ndarray-base-buffer-dtype/dist'),ye=require('@stdlib/ndarray-dtype/dist'),me=require('@stdlib/ndarray-shape/dist'),P=require('@stdlib/ndarray-strides/dist'),he=require('@stdlib/ndarray-offset/dist'),z=require('@stdlib/ndarray-order/dist'),qe=require('@stdlib/ndarray-data-buffer/dist'),F=require('@stdlib/array-shape/dist'),we=require('@stdlib/array-base-flatten/dist'),p=require('@stdlib/error-tools-fmtprodmsg/dist'),q=E(),be=x(),Oe=k(),Ee=D(),Te=A(),xe=C(),l=be();function je(){var e,a,r,o,i,t,u,n,f,v,s,w,c,b,y;if(arguments.length===1)if(q(arguments[0]))r=arguments[0],e={};else{if(e=arguments[0],!V(e))throw new TypeError(p('0hT56',e));if(d(e,"buffer")&&(r=e.buffer,!q(r)))throw new TypeError(p('0hT57',"buffer",r))}else{if(r=arguments[0],!q(r))throw new TypeError(p('0hT58',r));if(e=arguments[1],!V(e))throw new TypeError(p('0hT2V',e))}if(r&&(ne(r)?(u=ye(r),y=!0):(u=ge(r),y=!1)),v={},s={},d(e,"casting")){if(s.casting=e.casting,!le(s.casting))throw new TypeError(p('0hT59',"casting",s.casting))}else s.casting=l.casting;if(d(e,"flatten")){if(s.flatten=e.flatten,!L(s.flatten))throw new TypeError(p('0hT2o',"flatten",s.flatten))}else s.flatten=l.flatten;if(d(e,"ndmin")){if(s.ndmin=e.ndmin,!ae(s.ndmin))throw new TypeError(p('0hT2t',"ndmin",s.ndmin))}else s.ndmin=l.ndmin;if(d(e,"dtype")){if(t=e.dtype,!pe(t))throw new TypeError(p('0hTBf',"dtype",t));if(u&&!ve(u,t,s.casting))throw new Error(p('0hT5B',s.casting,u,t))}else u?!y&&u==="generic"?t=l.dtype:t=u:t=l.dtype;if(d(e,"order")){if(i=e.order,i==="any"||i==="same")y?i==="any"?(b=ue(P(r)),b===3?i=l.order:i=z(r)):i==="same"&&(i=z(r)):i=l.order;else if(!de(i))throw new TypeError(p('0hT5C',"order",i))}else i=l.order;if(d(e,"mode")?v.mode=e.mode:v.mode=l.mode,d(e,"submode")?v.submode=e.submode:v.submode=[v.mode],d(e,"readonly")?v.readonly=e.readonly:v.readonly=l.readonly,d(e,"copy")){if(s.copy=e.copy,!L(s.copy))throw new TypeError(p('0hT2o',"copy",s.copy))}else s.copy=l.copy;if(d(e,"shape")){if(n=e.shape,!q(n))throw new TypeError(p('0hT5D',"shape",n));f=n.length,c=h(n)}else if(r)y?(n=me(r),f=n.length,c=h(n)):s.flatten&&te(r)?(n=F(r),w=n,f=n.length,c=h(n)):(f=1,c=r.length,n=[c]);else throw new Error(p('0hT0X'));if(f<s.ndmin&&(n=Te(f,n,s.ndmin),f=s.ndmin),y){if(h(r.shape)!==c)throw new RangeError(p('0hT0Y'));u!==t||s.copy?r=Ee(r,t):(a=P(r),o=he(r),r=qe(r),a.length<f&&(a=xe(f,n,a,i)))}else if(r){if(u==="generic"&&s.flatten&&(r=we(r,w||F(r),!1)),r.length!==c)throw new RangeError(p('0hT0Y'));(u!==t||s.copy)&&(r=Oe(r,c,t))}else r=ce(t,c);return a===void 0&&(a=oe(n,i),o=se(n,a)),new fe(t,r,n,a,o,i,v)}I.exports=je
-});var ke=M();module.exports=ke;
+});var E=g(function(Me,x){
+var m=require('@stdlib/ndarray-defaults/dist');function _(){return{casting:m.get("casting"),copy:!1,dtype:m.get("dtypes.default"),flatten:!0,mode:m.get("index_mode"),ndmin:0,order:m.get("order"),readonly:!1}}x.exports=_
+});var k=g(function(Re,j){
+var H=require('@stdlib/ndarray-base-buffer-ctors/dist'),J=require('@stdlib/buffer-alloc-unsafe/dist');function K(e,a,r){var o,i,n;if(o=H(r),r==="generic")for(i=[],n=0;n<a;n++)i.push(e[n]);else if(r==="binary")for(i=J(a),n=0;n<a;n++)i[n]=e[n];else for(i=new o(a),n=0;n<a;n++)i[n]=e[n];return i}j.exports=K
+});var S=g(function(Ue,D){
+var Q=require('@stdlib/array-base-arraylike2object/dist'),W=require('@stdlib/complex-base-cast-return/dist'),X=require('@stdlib/complex-ctors/dist'),Y=require('@stdlib/ndarray-base-buffer-ctors/dist'),Z=require('@stdlib/buffer-alloc-unsafe/dist'),$=require('@stdlib/ndarray-base-ctor/dist'),ee=require('@stdlib/ndarray-dtype/dist'),re=require('@stdlib/ndarray-shape/dist'),ie=require('@stdlib/ndarray-strides/dist'),te=require('@stdlib/ndarray-offset/dist'),ae=require('@stdlib/ndarray-order/dist'),ne=require('@stdlib/ndarray-data-buffer/dist');function oe(e){var a,r,o;for(a=e.length,r=[],o=0;o<a;o++)r.push(e.iget(o));return r}function se(e){var a,r,o;for(a=e.length,r=Z(a),o=0;o<a;o++)r[o]=e.iget(o);return r}function ue(e,a){var r,o,i,n,f,t,u;if(r=Y(a),o=e.length,i=new r(o),t=Q(i),t.accessorProtocol)for(n=t.accessors[1],f=W(v,1,X(a)),u=0;u<o;u++)n(i,u,f(u));else for(u=0;u<o;u++)i[u]=e.iget(u);return i;function v(s){return e.iget(s)}}function fe(e,a){var r;return r=new $(ee(e),ne(e),re(e),ie(e),te(e),ae(e)),a==="generic"?oe(r):a==="binary"?se(r):ue(r,a)}D.exports=fe
+});var A=g(function(Ge,B){
+function pe(e,a,r){var o,i;for(o=[],i=0;i<r-e;i++)o.push(1);for(i=0;i<e;i++)o.push(a[i]);return o}B.exports=pe
+});var N=g(function(_e,C){
+var ve=require('@stdlib/math-base-special-abs/dist');function le(e,a,r,o){var i,n,f,t,u;if(n=r.length,u=e-n,i=[],o==="row-major"){for(f=ve(r[0])*a[u],t=0;t<u;t++)i.push(f);for(t=0;t<n;t++)i.push(r[t])}else{for(t=0;t<u;t++)i.push(1);for(t=0;t<n;t++)i.push(r[t])}return i}C.exports=le
+});var M=g(function(He,I){
+var l=require('@stdlib/assert-has-own-property/dist'),P=require('@stdlib/assert-is-plain-object/dist'),V=require('@stdlib/assert-is-boolean/dist').isPrimitive,de=require('@stdlib/assert-is-array/dist'),ce=require('@stdlib/assert-is-nonnegative-integer/dist').isPrimitive,ge=require('@stdlib/assert-is-ndarray-like/dist'),ye=require('@stdlib/ndarray-base-shape2strides/dist'),me=require('@stdlib/ndarray-base-strides2offset/dist'),he=require('@stdlib/ndarray-base-strides2order/dist'),h=require('@stdlib/ndarray-base-numel/dist'),qe=require('@stdlib/ndarray-ctor/dist'),we=require('@stdlib/ndarray-base-assert-is-data-type/dist'),be=require('@stdlib/ndarray-base-assert-is-order/dist'),Oe=require('@stdlib/ndarray-base-assert-is-casting-mode/dist'),Te=require('@stdlib/ndarray-base-assert-is-allowed-data-type-cast/dist'),xe=require('@stdlib/ndarray-base-buffer/dist'),Ee=require('@stdlib/ndarray-base-buffer-dtype/dist'),je=require('@stdlib/ndarray-dtype/dist'),ke=require('@stdlib/ndarray-shape/dist'),L=require('@stdlib/ndarray-strides/dist'),De=require('@stdlib/ndarray-offset/dist'),z=require('@stdlib/ndarray-order/dist'),Se=require('@stdlib/ndarray-data-buffer/dist'),F=require('@stdlib/array-shape/dist'),Be=require('@stdlib/array-base-flatten/dist'),p=require('@stdlib/error-tools-fmtprodmsg/dist'),q=T(),Ae=E(),Ce=k(),Ne=S(),Pe=A(),Ve=N(),d=Ae();function Le(){var e,a,r,o,i,n,f,t,u,v,s,w,c,b,y;if(arguments.length===1)if(q(arguments[0]))r=arguments[0],e={};else{if(e=arguments[0],!P(e))throw new TypeError(p('0hT56',e));if(l(e,"buffer")&&(r=e.buffer,!q(r)))throw new TypeError(p('0hT57',"buffer",r))}else{if(r=arguments[0],!q(r))throw new TypeError(p('0hT58',r));if(e=arguments[1],!P(e))throw new TypeError(p('0hT2V',e))}if(r&&(ge(r)?(f=je(r),y=!0):(f=Ee(r),y=!1)),v={},s={},l(e,"casting")){if(s.casting=e.casting,!Oe(s.casting))throw new TypeError(p('0hT59',"casting",s.casting))}else s.casting=d.casting;if(l(e,"flatten")){if(s.flatten=e.flatten,!V(s.flatten))throw new TypeError(p('0hT2o',"flatten",s.flatten))}else s.flatten=d.flatten;if(l(e,"ndmin")){if(s.ndmin=e.ndmin,!ce(s.ndmin))throw new TypeError(p('0hT2t',"ndmin",s.ndmin))}else s.ndmin=d.ndmin;if(l(e,"dtype")){if(n=e.dtype,!we(n))throw new TypeError(p('0hTBf',"dtype",n));if(f&&!Te(f,n,s.casting))throw new Error(p('0hT5B',s.casting,f,n))}else f?!y&&f==="generic"?n=d.dtype:n=f:n=d.dtype;if(l(e,"order")){if(i=e.order,i==="any"||i==="same")y?i==="any"?(b=he(L(r)),b===3?i=d.order:i=z(r)):i==="same"&&(i=z(r)):i=d.order;else if(!be(i))throw new TypeError(p('0hT5C',"order",i))}else i=d.order;if(l(e,"mode")?v.mode=e.mode:v.mode=d.mode,l(e,"submode")?v.submode=e.submode:v.submode=[v.mode],l(e,"readonly")?v.readonly=e.readonly:v.readonly=d.readonly,l(e,"copy")){if(s.copy=e.copy,!V(s.copy))throw new TypeError(p('0hT2o',"copy",s.copy))}else s.copy=d.copy;if(l(e,"shape")){if(t=e.shape,!q(t))throw new TypeError(p('0hT5D',"shape",t));u=t.length,c=h(t)}else if(r)y?(t=ke(r),u=t.length,c=h(t)):s.flatten&&de(r)?(t=F(r),w=t,u=t.length,c=h(t)):(u=1,c=r.length,t=[c]);else throw new Error(p('0hT0X'));if(u<s.ndmin&&(t=Pe(u,t,s.ndmin),u=s.ndmin),y){if(h(r.shape)!==c)throw new RangeError(p('0hT0Y'));f!==n||s.copy?r=Ne(r,n):(a=L(r),o=De(r),r=Se(r),a.length<u&&(a=Ve(u,t,a,i)))}else if(r){if(f==="generic"&&s.flatten&&(r=Be(r,w||F(r),!1)),r.length!==c)throw new RangeError(p('0hT0Y'));(f!==n||s.copy)&&(r=Ce(r,c,n))}else r=xe(n,c);return a===void 0&&(a=ye(t,i),o=me(t,a)),new qe(n,r,t,a,o,i,v)}I.exports=Le
+});var ze=M();module.exports=ze;
 /** @license Apache-2.0 */
 /** @license Apache-2.0 */
 //# sourceMappingURL=index.js.map
diff --git a/dist/index.js.map b/dist/index.js.map
index fb8a95b..39a7f74 100644
--- a/dist/index.js.map
+++ b/dist/index.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../lib/is_array_like_object.js", "../lib/defaults.js", "../lib/cast_buffer.js", "../lib/copy_view.js", "../lib/expand_shape.js", "../lib/expand_strides.js", "../lib/main.js", "../lib/index.js"],
-  "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar PINF = require( '@stdlib/constants-float64-pinf' );\nvar isInteger = require( '@stdlib/math-base-assert-is-integer' );\n\n\n// MAIN //\n\n/**\n* Tests (loosely) if an input value is an array-like object.\n*\n* @private\n* @param {*} value - value to test\n* @returns {boolean} boolean indicating if an input value is an array-like object\n*\n* @example\n* var bool = isArrayLikeObject( [] );\n* // returns true\n*\n* @example\n* var bool = isArrayLikeObject( '' );\n* // returns false\n*/\nfunction isArrayLikeObject( value ) {\n\treturn (\n\t\ttypeof value === 'object' &&\n\t\tvalue !== null &&\n\t\ttypeof value.length === 'number' &&\n\t\tisInteger( value.length ) &&\n\t\tvalue.length >= 0 &&\n\t\tvalue.length < PINF\n\t);\n}\n\n\n// EXPORTS //\n\nmodule.exports = isArrayLikeObject;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2023 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar settings = require( '@stdlib/ndarray-defaults' );\n\n\n// MAIN //\n\n/**\n* Returns default options.\n*\n* @private\n* @returns {Object} default options\n*\n* @example\n* var o = defaults();\n* // returns {...}\n*/\nfunction defaults() {\n\treturn {\n\t\t'casting': settings.get( 'casting' ),\n\t\t'copy': false,\n\t\t'dtype': settings.get( 'dtypes.default' ),\n\t\t'flatten': true,\n\t\t'mode': settings.get( 'index_mode' ),\n\t\t'ndmin': 0,\n\t\t'order': settings.get( 'order' ),\n\t\t'readonly': false\n\t};\n}\n\n\n// EXPORTS //\n\nmodule.exports = defaults;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar bufferCtors = require( '@stdlib/ndarray-base-buffer-ctors' );\nvar allocUnsafe = require( '@stdlib/buffer-alloc-unsafe' );\n\n\n// MAIN //\n\n/**\n* Casts buffer elements by copying those elements to a buffer of another data type.\n*\n* @private\n* @param {(Array|TypedArray|Buffer)} buffer - input buffer\n* @param {NonNegativeInteger} len - number of elements to cast\n* @param {string} dtype - data type\n* @returns {(Array|TypedArray|Buffer)} output buffer\n*\n* @example\n* var b = castBuffer( [ 1.0, 2.0, 3.0 ], 3, 'float64' );\n* // returns <Float64Array>[ 1.0, 2.0, 3.0 ]\n*/\nfunction castBuffer( buffer, len, dtype ) {\n\tvar ctor;\n\tvar out;\n\tvar i;\n\n\tctor = bufferCtors( dtype );\n\tif ( dtype === 'generic') {\n\t\tout = [];\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout.push( buffer[ i ] );\n\t\t}\n\t} else if ( dtype === 'binary' ) {\n\t\tout = allocUnsafe( len );\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout[ i ] = buffer[ i ];\n\t\t}\n\t} else {\n\t\tout = new ctor( len );\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout[ i ] = buffer[ i ]; // TODO: wrap and use accessors here and above\n\t\t}\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = castBuffer;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar bufferCtors = require( '@stdlib/ndarray-base-buffer-ctors' );\nvar allocUnsafe = require( '@stdlib/buffer-alloc-unsafe' );\n\n\n// FUNCTIONS //\n\n/**\n* Copies a \"generic\" ndarray view.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @returns {Array} output data buffer\n*/\nfunction generic( arr ) {\n\tvar len;\n\tvar out;\n\tvar i;\n\n\tlen = arr.length;\n\tout = [];\n\tfor ( i = 0; i < len; i++ ) {\n\t\tout.push( arr.get( i ) ); // FIXME: what if `arr` has more than one dimensions?\n\t}\n\treturn out;\n}\n\n/**\n* Copies a \"binary\" ndarray view.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @returns {Array} output data buffer\n*/\nfunction binary( arr ) {\n\tvar len;\n\tvar out;\n\tvar i;\n\n\tlen = arr.length;\n\tout = allocUnsafe( len );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tout[ i ] = arr.get( i ); // FIXME: what if `arr` has more than one dimensions?\n\t}\n\treturn out;\n}\n\n/**\n* Copies a \"typed\" ndarray view.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @param {string} dtype - data type\n* @returns {Array} output data buffer\n*/\nfunction typed( arr, dtype ) {\n\tvar ctor;\n\tvar len;\n\tvar out;\n\tvar i;\n\n\tctor = bufferCtors( dtype );\n\tlen = arr.length;\n\tout = new ctor( len ); // FIXME: need to account for complex number arrays; in which case, we may want to do something similar to `array/convert`\n\tfor ( i = 0; i < len; i++ ) {\n\t\tout[ i ] = arr.get( i ); // FIXME: what if `arr` has more than one dimensions?\n\t}\n\treturn out;\n}\n\n\n// MAIN //\n\n/**\n* Copies an ndarray view to a data buffer.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @param {string} dtype - data type\n* @returns {(Array|TypedArray|Buffer)} output data buffer\n*\n* @example\n* var ndarray = require( '@stdlib/ndarray-ctor' );\n*\n* var buffer = [ 1.0, 2.0, 3.0 ];\n* var shape = [ 3 ];\n* var strides = [ -1 ];\n* var vec = ndarray( 'generic', buffer, shape, strides, 2, 'row-major' );\n*\n* var b = copyView( vec, 'float64' );\n* // returns <Float64Array>[ 3.0, 2.0, 1.0 ]\n*/\nfunction copyView( arr, dtype ) {\n\t// TODO: handle complex number dtypes!!\n\tif ( dtype === 'generic') {\n\t\treturn generic( arr );\n\t}\n\tif ( dtype === 'binary' ) {\n\t\treturn binary( arr );\n\t}\n\treturn typed( arr, dtype );\n}\n\n\n// EXPORTS //\n\nmodule.exports = copyView;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Prepends singleton dimensions in order to satisfy a minimum number of dimensions.\n*\n* @private\n* @param {NonNegativeInteger} ndims - number of dimensions\n* @param {Array} shape - array dimensions\n* @param {NonNegativeInteger} ndmin - minimum number of dimensions\n* @returns {Array} output shape array\n*/\nfunction expandShape( ndims, shape, ndmin ) {\n\tvar out;\n\tvar i;\n\n\tout = [];\n\tfor ( i = 0; i < ndmin-ndims; i++ ) {\n\t\tout.push( 1 );\n\t}\n\tfor ( i = 0; i < ndims; i++ ) {\n\t\tout.push( shape[ i ] );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = expandShape;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar abs = require( '@stdlib/math-base-special-abs' );\n\n\n// MAIN //\n\n/**\n* Expands a strides array to accommodate an expanded array shape (i.e., an array shape with prepended singleton dimensions).\n*\n* @private\n* @param {NonNegativeInteger} ndims - number of dimensions\n* @param {Array} shape - expanded array shape\n* @param {Array} strides - strides array\n* @param {string} order - memory layout order\n* @returns {Array} output strides array\n*\n* @example\n* var out = expandStrides( 4, [ 1, 1, 2, 2 ], [ 1, 2 ], 'column-major' );\n* // returns [ 1, 1, 1, 2 ]\n*\n* @example\n* var out = expandStrides( 4, [ 1, 1, 2, 2 ], [ 2, 1 ], 'row-major' );\n* // returns [ 4, 4, 2, 1 ]\n*/\nfunction expandStrides( ndims, shape, strides, order ) {\n\tvar out;\n\tvar N;\n\tvar s;\n\tvar i;\n\tvar j;\n\n\tN = strides.length;\n\tj = ndims - N;\n\tout = [];\n\tif ( order === 'row-major' ) {\n\t\ts = abs( strides[ 0 ] ) * shape[ j ]; // at `j` is the size of the first non-prepended dimension\n\t\tfor ( i = 0; i < j; i++ ) {\n\t\t\tout.push( s );\n\t\t}\n\t\tfor ( i = 0; i < N; i++ ) {\n\t\t\tout.push( strides[ i ] );\n\t\t}\n\t} else { // column-major\n\t\tfor ( i = 0; i < j; i++ ) {\n\t\t\tout.push( 1 );\n\t\t}\n\t\tfor ( i = 0; i < N; i++ ) {\n\t\t\tout.push( strides[ i ] );\n\t\t}\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = expandStrides;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar hasOwnProp = require( '@stdlib/assert-has-own-property' );\nvar isObject = require( '@stdlib/assert-is-plain-object' );\nvar isBoolean = require( '@stdlib/assert-is-boolean' ).isPrimitive;\nvar isArray = require( '@stdlib/assert-is-array' );\nvar isNonNegativeInteger = require( '@stdlib/assert-is-nonnegative-integer' ).isPrimitive;\nvar isndarrayLike = require( '@stdlib/assert-is-ndarray-like' );\nvar shape2strides = require( '@stdlib/ndarray-base-shape2strides' );\nvar strides2offset = require( '@stdlib/ndarray-base-strides2offset' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar ndarray = require( '@stdlib/ndarray-ctor' );\nvar isDataType = require( '@stdlib/ndarray-base-assert-is-data-type' );\nvar isOrder = require( '@stdlib/ndarray-base-assert-is-order' );\nvar isCastingMode = require( '@stdlib/ndarray-base-assert-is-casting-mode' );\nvar isAllowedCast = require( '@stdlib/ndarray-base-assert-is-allowed-data-type-cast' );\nvar createBuffer = require( '@stdlib/ndarray-base-buffer' );\nvar getBufferDType = require( '@stdlib/ndarray-base-buffer-dtype' );\nvar getDType = require( '@stdlib/ndarray-dtype' );\nvar getShape = require( '@stdlib/ndarray-shape' );\nvar getStrides = require( '@stdlib/ndarray-strides' );\nvar getOffset = require( '@stdlib/ndarray-offset' );\nvar getOrder = require( '@stdlib/ndarray-order' );\nvar getData = require( '@stdlib/ndarray-data-buffer' );\nvar arrayShape = require( '@stdlib/array-shape' );\nvar flatten = require( '@stdlib/array-base-flatten' );\nvar format = require( '@stdlib/string-format' );\nvar isArrayLikeObject = require( './is_array_like_object.js' );\nvar getDefaults = require( './defaults.js' );\nvar castBuffer = require( './cast_buffer.js' );\nvar copyView = require( './copy_view.js' );\nvar expandShape = require( './expand_shape.js' );\nvar expandStrides = require( './expand_strides.js' );\n\n\n// VARIABLES //\n\nvar defaults = getDefaults();\n\n\n// MAIN //\n\n/**\n* Returns a multidimensional array.\n*\n* @param {(ArrayLikeObject|TypedArrayLike|Buffer|ndarrayLike)} [buffer] - data source\n* @param {Options} [options] - function options\n* @param {(ArrayLikeObject|TypedArrayLike|Buffer|ndarrayLike)} [options.buffer] - data source\n* @param {string} [options.dtype=\"float64\"] - underlying storage data type (if the input data is not of the same type, this option specifies the data type to which to cast the input data)\n* @param {string} [options.order=\"row-major\"] - specifies the memory layout of the array as either row-major (C-style) or column-major (Fortran-style)\n* @param {NonNegativeIntegerArray} [options.shape] - array shape\n* @param {string} [options.mode=\"throw\"] - specifies how to handle indices which exceed array dimensions\n* @param {StringArray} [options.submode=[\"throw\"]] - specifies how to handle subscripts which exceed array dimensions on a per dimension basis\n* @param {boolean} [options.copy=false] - boolean indicating whether to copy source data to a new data buffer\n* @param {boolean} [options.flatten=true] - boolean indicating whether to automatically flatten generic array data sources\n* @param {NonNegativeInteger} [options.ndmin=0] - minimum number of dimensions\n* @param {string} [options.casting=\"safe\"] - casting rule used to determine what constitutes an acceptable cast\n* @param {boolean} [options.readonly=false] - boolean indicating if an array should be read-only\n* @throws {TypeError} options argument must be an object\n* @throws {TypeError} must provide valid options\n* @throws {Error} must provide either an array shape, data source, or both\n* @throws {Error} invalid cast\n* @throws {RangeError} data source must be compatible with specified meta data\n* @returns {ndarray} ndarray instance\n*\n* @example\n* var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n* // returns <ndarray>\n*\n* var v = arr.get( 0, 0 );\n* // returns 1\n*\n* @example\n* var opts = {\n*     'dtype': 'generic',\n*     'flatten': false\n* };\n*\n* var arr = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );\n* // returns <ndarray>\n*\n* var v = arr.get( 0 );\n* // returns [ 1, 2 ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n*\n* var opts = {\n*     'shape': [ 2, 2 ]\n* };\n*\n* var arr = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ), opts );\n* // returns <ndarray>\n*\n* var v = arr.get( 0, 0 );\n* // returns 1.0\n*/\nfunction array() {\n\tvar options;\n\tvar strides;\n\tvar buffer;\n\tvar offset;\n\tvar order;\n\tvar dtype;\n\tvar btype;\n\tvar shape;\n\tvar ndims;\n\tvar nopts;\n\tvar opts;\n\tvar osh;\n\tvar len;\n\tvar ord;\n\tvar FLG;\n\n\tif ( arguments.length === 1 ) {\n\t\tif ( isArrayLikeObject( arguments[ 0 ] ) ) {\n\t\t\tbuffer = arguments[ 0 ];\n\t\t\toptions = {};\n\t\t} else {\n\t\t\toptions = arguments[ 0 ];\n\t\t\tif ( !isObject( options ) ) {\n\t\t\t\tthrow new TypeError( format( 'invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.', options ) );\n\t\t\t}\n\t\t\tif ( hasOwnProp( options, 'buffer' ) ) {\n\t\t\t\tbuffer = options.buffer;\n\t\t\t\tif ( !isArrayLikeObject( buffer ) ) { // weak test\n\t\t\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.', 'buffer', buffer ) );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t} else {\n\t\tbuffer = arguments[ 0 ];\n\t\tif ( !isArrayLikeObject( buffer ) ) { // weak test\n\t\t\tthrow new TypeError( format( 'invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.', buffer ) );\n\t\t}\n\t\toptions = arguments[ 1 ];\n\t\tif ( !isObject( options ) ) {\n\t\t\tthrow new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );\n\t\t}\n\t\t// Note: we ignore whether `options` has a `buffer` property\n\t}\n\tif ( buffer ) {\n\t\tif ( isndarrayLike( buffer ) ) {\n\t\t\tbtype = getDType( buffer );\n\t\t\tFLG = true;\n\t\t} else {\n\t\t\tbtype = getBufferDType( buffer );\n\t\t\tFLG = false;\n\t\t}\n\t}\n\tnopts = {};\n\topts = {};\n\n\t// Validate some options before others...\n\tif ( hasOwnProp( options, 'casting' ) ) {\n\t\topts.casting = options.casting;\n\t\tif ( !isCastingMode( opts.casting ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a recognized casting mode. Option: `%s`.', 'casting', opts.casting ) );\n\t\t}\n\t} else {\n\t\topts.casting = defaults.casting;\n\t}\n\tif ( hasOwnProp( options, 'flatten' ) ) {\n\t\topts.flatten = options.flatten;\n\t\tif ( !isBoolean( opts.flatten ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a boolean. Option: `%s`.', 'flatten', opts.flatten ) );\n\t\t}\n\t} else {\n\t\topts.flatten = defaults.flatten;\n\t}\n\tif ( hasOwnProp( options, 'ndmin' ) ) {\n\t\topts.ndmin = options.ndmin;\n\t\tif ( !isNonNegativeInteger( opts.ndmin ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a nonnegative integer. Option: `%s`.', 'ndmin', opts.ndmin ) );\n\t\t}\n\t\t// TODO: validate that minimum number of dimensions does not exceed the maximum number of possible dimensions (in theory, infinite; in practice, determined by max array length; see https://github.com/stdlib-js/stdlib/blob/ac350059877c036640775d6b30d0e98e840d07cf/lib/node_modules/%40stdlib/ndarray/ctor/lib/main.js#L57)\n\t} else {\n\t\topts.ndmin = defaults.ndmin;\n\t}\n\n\t// Validate the remaining options...\n\tif ( hasOwnProp( options, 'dtype' ) ) {\n\t\tdtype = options.dtype;\n\t\tif ( !isDataType( dtype ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a recognized data type. Option: `%s`.', 'dtype', dtype ) );\n\t\t}\n\t\tif ( btype && !isAllowedCast( btype, dtype, opts.casting ) ) {\n\t\t\tthrow new Error( format( 'invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.', opts.casting, btype, dtype ) );\n\t\t}\n\t} else if ( btype ) {\n\t\t// TODO: reconcile difference in behavior when provided a generic array and no `dtype` option. Currently, we cast here, but do not allow casting a generic array (by default) when explicitly providing a `dtype` option.\n\n\t\t// Only cast generic array data sources when not provided an ndarray...\n\t\tif ( !FLG && btype === 'generic' ) {\n\t\t\tdtype = defaults.dtype;\n\t\t} else {\n\t\t\tdtype = btype;\n\t\t}\n\t} else {\n\t\tdtype = defaults.dtype;\n\t}\n\tif ( hasOwnProp( options, 'order' ) ) {\n\t\torder = options.order;\n\t\tif ( order === 'any' || order === 'same' ) {\n\t\t\tif ( FLG ) {\n\t\t\t\t// If the user indicated that \"any\" order suffices (meaning the user does not care about ndarray order), then we use the default order, unless the input ndarray is either unequivocally \"row-major\" or \"column-major\" or configured as such....\n\t\t\t\tif ( order === 'any' ) {\n\t\t\t\t\t// Compute the layout order in order to ascertain whether an ndarray can be considered both \"row-major\" and \"column-major\":\n\t\t\t\t\tord = strides2order( getStrides( buffer ) );\n\n\t\t\t\t\t// If the ndarray can be considered both \"row-major\" and \"column-major\", then use the default order; otherwise, use the ndarray's stated layout order...\n\t\t\t\t\tif ( ord === 3 ) {\n\t\t\t\t\t\torder = defaults.order;\n\t\t\t\t\t} else {\n\t\t\t\t\t\torder = getOrder( buffer );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t// Otherwise, use the same order as the provided ndarray...\n\t\t\t\telse if ( order === 'same' ) {\n\t\t\t\t\torder = getOrder( buffer );\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\torder = defaults.order;\n\t\t\t}\n\t\t} else if ( !isOrder( order ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a recognized order. Option: `%s`.', 'order', order ) );\n\t\t}\n\t} else {\n\t\torder = defaults.order;\n\t}\n\tif ( hasOwnProp( options, 'mode' ) ) {\n\t\tnopts.mode = options.mode;\n\t} else {\n\t\tnopts.mode = defaults.mode;\n\t}\n\tif ( hasOwnProp( options, 'submode' ) ) {\n\t\tnopts.submode = options.submode;\n\t} else {\n\t\tnopts.submode = [ nopts.mode ];\n\t}\n\tif ( hasOwnProp( options, 'readonly' ) ) {\n\t\tnopts.readonly = options.readonly;\n\t} else {\n\t\tnopts.readonly = defaults.readonly;\n\t}\n\tif ( hasOwnProp( options, 'copy' ) ) {\n\t\topts.copy = options.copy;\n\t\tif ( !isBoolean( opts.copy ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a boolean. Option: `%s`.', 'copy', opts.copy ) );\n\t\t}\n\t} else {\n\t\topts.copy = defaults.copy;\n\t}\n\t// If not provided a shape, infer from a provided data source...\n\tif ( hasOwnProp( options, 'shape' ) ) {\n\t\tshape = options.shape;\n\t\tif ( !isArrayLikeObject( shape ) ) { // weak test\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.', 'shape', shape ) );\n\t\t}\n\t\tndims = shape.length;\n\t\tlen = numel( shape );\n\t} else if ( buffer ) {\n\t\tif ( FLG ) {\n\t\t\tshape = getShape( buffer );\n\t\t\tndims = shape.length;\n\t\t\tlen = numel( shape );\n\t\t} else if ( opts.flatten && isArray( buffer ) ) {\n\t\t\tshape = arrayShape( buffer );\n\t\t\tosh = shape; // cache a reference to the inferred shape\n\t\t\tndims = shape.length;\n\t\t\tlen = numel( shape );\n\t\t} else {\n\t\t\tndims = 1;\n\t\t\tlen = buffer.length;\n\t\t\tshape = [ len ]; // assume a 1-dimensional array (vector)\n\t\t}\n\t} else {\n\t\tthrow new Error( 'invalid arguments. Must provide either a data source, array shape, or both.' );\n\t}\n\t// Adjust the array shape to satisfy the minimum number of dimensions...\n\tif ( ndims < opts.ndmin ) {\n\t\tshape = expandShape( ndims, shape, opts.ndmin );\n\t\tndims = opts.ndmin;\n\t}\n\t// If not provided a data buffer, create it; otherwise, see if we need to cast a provided data buffer to another data type or perform a copy...\n\tif ( FLG ) {\n\t\tif ( numel( buffer.shape ) !== len ) {\n\t\t\tthrow new RangeError( 'invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.' );\n\t\t}\n\t\tif ( btype !== dtype || opts.copy ) {\n\t\t\tbuffer = copyView( buffer, dtype );\n\t\t} else {\n\t\t\tstrides = getStrides( buffer );\n\t\t\toffset = getOffset( buffer );\n\t\t\tbuffer = getData( buffer );\n\t\t\tif ( strides.length < ndims ) {\n\t\t\t\t// Account for augmented dimensions (note: expanding the strides array to account for prepended singleton dimensions does **not** affect the index offset):\n\t\t\t\tstrides = expandStrides( ndims, shape, strides, order );\n\t\t\t}\n\t\t}\n\t} else if ( buffer ) {\n\t\tif ( btype === 'generic' && opts.flatten ) {\n\t\t\tbuffer = flatten( buffer, osh || arrayShape( buffer ), false );\n\t\t}\n\t\tif ( buffer.length !== len ) {\n\t\t\tthrow new RangeError( 'invalid arguments. Array shape is incompatible with provided data source. 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+  "sourcesContent": ["/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar PINF = require( '@stdlib/constants-float64-pinf' );\nvar isInteger = require( '@stdlib/math-base-assert-is-integer' );\n\n\n// MAIN //\n\n/**\n* Tests (loosely) if an input value is an array-like object.\n*\n* @private\n* @param {*} value - value to test\n* @returns {boolean} boolean indicating if an input value is an array-like object\n*\n* @example\n* var bool = isArrayLikeObject( [] );\n* // returns true\n*\n* @example\n* var bool = isArrayLikeObject( '' );\n* // returns false\n*/\nfunction isArrayLikeObject( value ) {\n\treturn (\n\t\ttypeof value === 'object' &&\n\t\tvalue !== null &&\n\t\ttypeof value.length === 'number' &&\n\t\tisInteger( value.length ) &&\n\t\tvalue.length >= 0 &&\n\t\tvalue.length < PINF\n\t);\n}\n\n\n// EXPORTS //\n\nmodule.exports = isArrayLikeObject;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2023 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar settings = require( '@stdlib/ndarray-defaults' );\n\n\n// MAIN //\n\n/**\n* Returns default options.\n*\n* @private\n* @returns {Object} default options\n*\n* @example\n* var o = defaults();\n* // returns {...}\n*/\nfunction defaults() {\n\treturn {\n\t\t'casting': settings.get( 'casting' ),\n\t\t'copy': false,\n\t\t'dtype': settings.get( 'dtypes.default' ),\n\t\t'flatten': true,\n\t\t'mode': settings.get( 'index_mode' ),\n\t\t'ndmin': 0,\n\t\t'order': settings.get( 'order' ),\n\t\t'readonly': false\n\t};\n}\n\n\n// EXPORTS //\n\nmodule.exports = defaults;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar bufferCtors = require( '@stdlib/ndarray-base-buffer-ctors' );\nvar allocUnsafe = require( '@stdlib/buffer-alloc-unsafe' );\n\n\n// MAIN //\n\n/**\n* Casts buffer elements by copying those elements to a buffer of another data type.\n*\n* @private\n* @param {(Array|TypedArray|Buffer)} buffer - input buffer\n* @param {NonNegativeInteger} len - number of elements to cast\n* @param {string} dtype - data type\n* @returns {(Array|TypedArray|Buffer)} output buffer\n*\n* @example\n* var b = castBuffer( [ 1.0, 2.0, 3.0 ], 3, 'float64' );\n* // returns <Float64Array>[ 1.0, 2.0, 3.0 ]\n*/\nfunction castBuffer( buffer, len, dtype ) {\n\tvar ctor;\n\tvar out;\n\tvar i;\n\n\tctor = bufferCtors( dtype );\n\tif ( dtype === 'generic') {\n\t\tout = [];\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout.push( buffer[ i ] );\n\t\t}\n\t} else if ( dtype === 'binary' ) {\n\t\tout = allocUnsafe( len );\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout[ i ] = buffer[ i ];\n\t\t}\n\t} else {\n\t\tout = new ctor( len );\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout[ i ] = buffer[ i ]; // TODO: wrap and use accessors here and above\n\t\t}\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = castBuffer;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar arraylike2object = require( '@stdlib/array-base-arraylike2object' );\nvar castReturn = require( '@stdlib/complex-base-cast-return' );\nvar complexCtors = require( '@stdlib/complex-ctors' );\nvar bufferCtors = require( '@stdlib/ndarray-base-buffer-ctors' );\nvar allocUnsafe = require( '@stdlib/buffer-alloc-unsafe' );\nvar ndarray = require( '@stdlib/ndarray-base-ctor' );\nvar getDType = require( '@stdlib/ndarray-dtype' );\nvar getShape = require( '@stdlib/ndarray-shape' );\nvar getStrides = require( '@stdlib/ndarray-strides' );\nvar getOffset = require( '@stdlib/ndarray-offset' );\nvar getOrder = require( '@stdlib/ndarray-order' );\nvar getData = require( '@stdlib/ndarray-data-buffer' );\n\n\n// FUNCTIONS //\n\n/**\n* Copies a \"generic\" ndarray view.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @returns {Array} output data buffer\n*/\nfunction generic( arr ) {\n\tvar len;\n\tvar out;\n\tvar i;\n\n\tlen = arr.length;\n\tout = [];\n\tfor ( i = 0; i < len; i++ ) {\n\t\tout.push( arr.iget( i ) ); // as output buffer is generic, should work with both real- and complex-valued ndarrays\n\t}\n\treturn out;\n}\n\n/**\n* Copies a \"binary\" ndarray view.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @returns {Array} output data buffer\n*/\nfunction binary( arr ) {\n\tvar len;\n\tvar out;\n\tvar i;\n\n\tlen = arr.length;\n\tout = allocUnsafe( len );\n\tfor ( i = 0; i < len; i++ ) {\n\t\tout[ i ] = arr.iget( i ); // we're assuming that we're doing something sensible here (e.g., not trying to cast a complex-valued ndarray to a \"binary\" ndarray or a double-precision floating-point ndarray to binary, etc)\n\t}\n\treturn out;\n}\n\n/**\n* Copies a \"typed\" ndarray view.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @param {string} dtype - data type\n* @returns {Array} output data buffer\n*/\nfunction typed( arr, dtype ) {\n\tvar ctor;\n\tvar len;\n\tvar out;\n\tvar set;\n\tvar fcn;\n\tvar o;\n\tvar i;\n\n\tctor = bufferCtors( dtype );\n\tlen = arr.length;\n\tout = new ctor( len );\n\n\t// If the output data buffer is a complex number array, we need to use accessors...\n\to = arraylike2object( out );\n\tif ( o.accessorProtocol ) {\n\t\tset = o.accessors[ 1 ];\n\t\tfcn = castReturn( wrapper, 1, complexCtors( dtype ) );\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tset( out, i, fcn( i ) ); // we're assuming that we're doing something sensible here (e.g., not trying to cast arbitrary objects to complex numbers, etc)\n\t\t}\n\t} else {\n\t\tfor ( i = 0; i < len; i++ ) {\n\t\t\tout[ i ] = arr.iget( i ); // we're assuming that we're doing something sensible here (e.g., not trying to cast an ndarray containing generic objects to a double-precision floating-point array or a complex-valued ndarray to a real-valued ndarray, etc)\n\t\t}\n\t}\n\treturn out;\n\n\t/**\n\t* Returns the ndarray element specified by a provided linear index.\n\t*\n\t* @private\n\t* @param {NonNegativeInteger} i - linear index\n\t* @returns {*} value\n\t*/\n\tfunction wrapper( i ) {\n\t\treturn arr.iget( i );\n\t}\n}\n\n\n// MAIN //\n\n/**\n* Copies an ndarray view to a data buffer.\n*\n* @private\n* @param {ndarray} arr - input ndarray\n* @param {string} dtype - data type\n* @returns {(Array|TypedArray|Buffer)} output data buffer\n*\n* @example\n* var ndarray = require( '@stdlib/ndarray-ctor' );\n*\n* var buffer = [ 1.0, 2.0, 3.0 ];\n* var shape = [ 3 ];\n* var strides = [ -1 ];\n* var vec = ndarray( 'generic', buffer, shape, strides, 2, 'row-major' );\n*\n* var b = copyView( vec, 'float64' );\n* // returns <Float64Array>[ 3.0, 2.0, 1.0 ]\n*/\nfunction copyView( arr, dtype ) {\n\tvar x;\n\n\t// Create a new \"base\" view, thus ensuring we have an `.iget` method and associated meta data...\n\tx = new ndarray( getDType( arr ), getData( arr ), getShape( arr ), getStrides( arr ), getOffset( arr ), getOrder( arr ) ); // eslint-disable-line max-len\n\n\tif ( dtype === 'generic') {\n\t\treturn generic( x );\n\t}\n\tif ( dtype === 'binary' ) {\n\t\treturn binary( x );\n\t}\n\treturn typed( x, dtype );\n}\n\n\n// EXPORTS //\n\nmodule.exports = copyView;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MAIN //\n\n/**\n* Prepends singleton dimensions in order to satisfy a minimum number of dimensions.\n*\n* @private\n* @param {NonNegativeInteger} ndims - number of dimensions\n* @param {Array} shape - array dimensions\n* @param {NonNegativeInteger} ndmin - minimum number of dimensions\n* @returns {Array} output shape array\n*/\nfunction expandShape( ndims, shape, ndmin ) {\n\tvar out;\n\tvar i;\n\n\tout = [];\n\tfor ( i = 0; i < ndmin-ndims; i++ ) {\n\t\tout.push( 1 );\n\t}\n\tfor ( i = 0; i < ndims; i++ ) {\n\t\tout.push( shape[ i ] );\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = expandShape;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar abs = require( '@stdlib/math-base-special-abs' );\n\n\n// MAIN //\n\n/**\n* Expands a strides array to accommodate an expanded array shape (i.e., an array shape with prepended singleton dimensions).\n*\n* @private\n* @param {NonNegativeInteger} ndims - number of dimensions\n* @param {Array} shape - expanded array shape\n* @param {Array} strides - strides array\n* @param {string} order - memory layout order\n* @returns {Array} output strides array\n*\n* @example\n* var out = expandStrides( 4, [ 1, 1, 2, 2 ], [ 1, 2 ], 'column-major' );\n* // returns [ 1, 1, 1, 2 ]\n*\n* @example\n* var out = expandStrides( 4, [ 1, 1, 2, 2 ], [ 2, 1 ], 'row-major' );\n* // returns [ 4, 4, 2, 1 ]\n*/\nfunction expandStrides( ndims, shape, strides, order ) {\n\tvar out;\n\tvar N;\n\tvar s;\n\tvar i;\n\tvar j;\n\n\tN = strides.length;\n\tj = ndims - N;\n\tout = [];\n\tif ( order === 'row-major' ) {\n\t\ts = abs( strides[ 0 ] ) * shape[ j ]; // at `j` is the size of the first non-prepended dimension\n\t\tfor ( i = 0; i < j; i++ ) {\n\t\t\tout.push( s );\n\t\t}\n\t\tfor ( i = 0; i < N; i++ ) {\n\t\t\tout.push( strides[ i ] );\n\t\t}\n\t} else { // column-major\n\t\tfor ( i = 0; i < j; i++ ) {\n\t\t\tout.push( 1 );\n\t\t}\n\t\tfor ( i = 0; i < N; i++ ) {\n\t\t\tout.push( strides[ i ] );\n\t\t}\n\t}\n\treturn out;\n}\n\n\n// EXPORTS //\n\nmodule.exports = expandStrides;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n// MODULES //\n\nvar hasOwnProp = require( '@stdlib/assert-has-own-property' );\nvar isObject = require( '@stdlib/assert-is-plain-object' );\nvar isBoolean = require( '@stdlib/assert-is-boolean' ).isPrimitive;\nvar isArray = require( '@stdlib/assert-is-array' );\nvar isNonNegativeInteger = require( '@stdlib/assert-is-nonnegative-integer' ).isPrimitive;\nvar isndarrayLike = require( '@stdlib/assert-is-ndarray-like' );\nvar shape2strides = require( '@stdlib/ndarray-base-shape2strides' );\nvar strides2offset = require( '@stdlib/ndarray-base-strides2offset' );\nvar strides2order = require( '@stdlib/ndarray-base-strides2order' );\nvar numel = require( '@stdlib/ndarray-base-numel' );\nvar ndarray = require( '@stdlib/ndarray-ctor' );\nvar isDataType = require( '@stdlib/ndarray-base-assert-is-data-type' );\nvar isOrder = require( '@stdlib/ndarray-base-assert-is-order' );\nvar isCastingMode = require( '@stdlib/ndarray-base-assert-is-casting-mode' );\nvar isAllowedCast = require( '@stdlib/ndarray-base-assert-is-allowed-data-type-cast' );\nvar createBuffer = require( '@stdlib/ndarray-base-buffer' );\nvar getBufferDType = require( '@stdlib/ndarray-base-buffer-dtype' );\nvar getDType = require( '@stdlib/ndarray-dtype' );\nvar getShape = require( '@stdlib/ndarray-shape' );\nvar getStrides = require( '@stdlib/ndarray-strides' );\nvar getOffset = require( '@stdlib/ndarray-offset' );\nvar getOrder = require( '@stdlib/ndarray-order' );\nvar getData = require( '@stdlib/ndarray-data-buffer' );\nvar arrayShape = require( '@stdlib/array-shape' );\nvar flatten = require( '@stdlib/array-base-flatten' );\nvar format = require( '@stdlib/string-format' );\nvar isArrayLikeObject = require( './is_array_like_object.js' );\nvar getDefaults = require( './defaults.js' );\nvar castBuffer = require( './cast_buffer.js' );\nvar copyView = require( './copy_view.js' );\nvar expandShape = require( './expand_shape.js' );\nvar expandStrides = require( './expand_strides.js' );\n\n\n// VARIABLES //\n\nvar defaults = getDefaults();\n\n\n// MAIN //\n\n/**\n* Returns a multidimensional array.\n*\n* @param {(ArrayLikeObject|TypedArrayLike|Buffer|ndarrayLike)} [buffer] - data source\n* @param {Options} [options] - function options\n* @param {(ArrayLikeObject|TypedArrayLike|Buffer|ndarrayLike)} [options.buffer] - data source\n* @param {string} [options.dtype=\"float64\"] - underlying storage data type (if the input data is not of the same type, this option specifies the data type to which to cast the input data)\n* @param {string} [options.order=\"row-major\"] - specifies the memory layout of the array as either row-major (C-style) or column-major (Fortran-style)\n* @param {NonNegativeIntegerArray} [options.shape] - array shape\n* @param {string} [options.mode=\"throw\"] - specifies how to handle indices which exceed array dimensions\n* @param {StringArray} [options.submode=[\"throw\"]] - specifies how to handle subscripts which exceed array dimensions on a per dimension basis\n* @param {boolean} [options.copy=false] - boolean indicating whether to copy source data to a new data buffer\n* @param {boolean} [options.flatten=true] - boolean indicating whether to automatically flatten generic array data sources\n* @param {NonNegativeInteger} [options.ndmin=0] - minimum number of dimensions\n* @param {string} [options.casting=\"safe\"] - casting rule used to determine what constitutes an acceptable cast\n* @param {boolean} [options.readonly=false] - boolean indicating if an array should be read-only\n* @throws {TypeError} options argument must be an object\n* @throws {TypeError} must provide valid options\n* @throws {Error} must provide either an array shape, data source, or both\n* @throws {Error} invalid cast\n* @throws {RangeError} data source must be compatible with specified meta data\n* @returns {ndarray} ndarray instance\n*\n* @example\n* var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n* // returns <ndarray>\n*\n* var v = arr.get( 0, 0 );\n* // returns 1\n*\n* @example\n* var opts = {\n*     'dtype': 'generic',\n*     'flatten': false\n* };\n*\n* var arr = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );\n* // returns <ndarray>\n*\n* var v = arr.get( 0 );\n* // returns [ 1, 2 ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n*\n* var opts = {\n*     'shape': [ 2, 2 ]\n* };\n*\n* var arr = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ), opts );\n* // returns <ndarray>\n*\n* var v = arr.get( 0, 0 );\n* // returns 1.0\n*/\nfunction array() {\n\tvar options;\n\tvar strides;\n\tvar buffer;\n\tvar offset;\n\tvar order;\n\tvar dtype;\n\tvar btype;\n\tvar shape;\n\tvar ndims;\n\tvar nopts;\n\tvar opts;\n\tvar osh;\n\tvar len;\n\tvar ord;\n\tvar FLG;\n\n\tif ( arguments.length === 1 ) {\n\t\tif ( isArrayLikeObject( arguments[ 0 ] ) ) {\n\t\t\tbuffer = arguments[ 0 ];\n\t\t\toptions = {};\n\t\t} else {\n\t\t\toptions = arguments[ 0 ];\n\t\t\tif ( !isObject( options ) ) {\n\t\t\t\tthrow new TypeError( format( 'invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.', options ) );\n\t\t\t}\n\t\t\tif ( hasOwnProp( options, 'buffer' ) ) {\n\t\t\t\tbuffer = options.buffer;\n\t\t\t\tif ( !isArrayLikeObject( buffer ) ) { // weak test\n\t\t\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.', 'buffer', buffer ) );\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t} else {\n\t\tbuffer = arguments[ 0 ];\n\t\tif ( !isArrayLikeObject( buffer ) ) { // weak test\n\t\t\tthrow new TypeError( format( 'invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.', buffer ) );\n\t\t}\n\t\toptions = arguments[ 1 ];\n\t\tif ( !isObject( options ) ) {\n\t\t\tthrow new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );\n\t\t}\n\t\t// Note: we ignore whether `options` has a `buffer` property\n\t}\n\tif ( buffer ) {\n\t\tif ( isndarrayLike( buffer ) ) {\n\t\t\tbtype = getDType( buffer );\n\t\t\tFLG = true;\n\t\t} else {\n\t\t\tbtype = getBufferDType( buffer );\n\t\t\tFLG = false;\n\t\t}\n\t}\n\tnopts = {};\n\topts = {};\n\n\t// Validate some options before others...\n\tif ( hasOwnProp( options, 'casting' ) ) {\n\t\topts.casting = options.casting;\n\t\tif ( !isCastingMode( opts.casting ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a recognized casting mode. Option: `%s`.', 'casting', opts.casting ) );\n\t\t}\n\t} else {\n\t\topts.casting = defaults.casting;\n\t}\n\tif ( hasOwnProp( options, 'flatten' ) ) {\n\t\topts.flatten = options.flatten;\n\t\tif ( !isBoolean( opts.flatten ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a boolean. Option: `%s`.', 'flatten', opts.flatten ) );\n\t\t}\n\t} else {\n\t\topts.flatten = defaults.flatten;\n\t}\n\tif ( hasOwnProp( options, 'ndmin' ) ) {\n\t\topts.ndmin = options.ndmin;\n\t\tif ( !isNonNegativeInteger( opts.ndmin ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a nonnegative integer. Option: `%s`.', 'ndmin', opts.ndmin ) );\n\t\t}\n\t\t// TODO: validate that minimum number of dimensions does not exceed the maximum number of possible dimensions (in theory, infinite; in practice, determined by max array length; see https://github.com/stdlib-js/stdlib/blob/ac350059877c036640775d6b30d0e98e840d07cf/lib/node_modules/%40stdlib/ndarray/ctor/lib/main.js#L57)\n\t} else {\n\t\topts.ndmin = defaults.ndmin;\n\t}\n\n\t// Validate the remaining options...\n\tif ( hasOwnProp( options, 'dtype' ) ) {\n\t\tdtype = options.dtype;\n\t\tif ( !isDataType( dtype ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a recognized data type. Option: `%s`.', 'dtype', dtype ) );\n\t\t}\n\t\tif ( btype && !isAllowedCast( btype, dtype, opts.casting ) ) {\n\t\t\tthrow new Error( format( 'invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.', opts.casting, btype, dtype ) );\n\t\t}\n\t} else if ( btype ) {\n\t\t// TODO: reconcile difference in behavior when provided a generic array and no `dtype` option. Currently, we cast here, but do not allow casting a generic array (by default) when explicitly providing a `dtype` option.\n\n\t\t// Only cast generic array data sources when not provided an ndarray...\n\t\tif ( !FLG && btype === 'generic' ) {\n\t\t\tdtype = defaults.dtype;\n\t\t} else {\n\t\t\tdtype = btype;\n\t\t}\n\t} else {\n\t\tdtype = defaults.dtype;\n\t}\n\tif ( hasOwnProp( options, 'order' ) ) {\n\t\torder = options.order;\n\t\tif ( order === 'any' || order === 'same' ) {\n\t\t\tif ( FLG ) {\n\t\t\t\t// If the user indicated that \"any\" order suffices (meaning the user does not care about ndarray order), then we use the default order, unless the input ndarray is either unequivocally \"row-major\" or \"column-major\" or configured as such....\n\t\t\t\tif ( order === 'any' ) {\n\t\t\t\t\t// Compute the layout order in order to ascertain whether an ndarray can be considered both \"row-major\" and \"column-major\":\n\t\t\t\t\tord = strides2order( getStrides( buffer ) );\n\n\t\t\t\t\t// If the ndarray can be considered both \"row-major\" and \"column-major\", then use the default order; otherwise, use the ndarray's stated layout order...\n\t\t\t\t\tif ( ord === 3 ) {\n\t\t\t\t\t\torder = defaults.order;\n\t\t\t\t\t} else {\n\t\t\t\t\t\torder = getOrder( buffer );\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t\t// Otherwise, use the same order as the provided ndarray...\n\t\t\t\telse if ( order === 'same' ) {\n\t\t\t\t\torder = getOrder( buffer );\n\t\t\t\t}\n\t\t\t} else {\n\t\t\t\torder = defaults.order;\n\t\t\t}\n\t\t} else if ( !isOrder( order ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a recognized order. Option: `%s`.', 'order', order ) );\n\t\t}\n\t} else {\n\t\torder = defaults.order;\n\t}\n\tif ( hasOwnProp( options, 'mode' ) ) {\n\t\tnopts.mode = options.mode;\n\t} else {\n\t\tnopts.mode = defaults.mode;\n\t}\n\tif ( hasOwnProp( options, 'submode' ) ) {\n\t\tnopts.submode = options.submode;\n\t} else {\n\t\tnopts.submode = [ nopts.mode ];\n\t}\n\tif ( hasOwnProp( options, 'readonly' ) ) {\n\t\tnopts.readonly = options.readonly;\n\t} else {\n\t\tnopts.readonly = defaults.readonly;\n\t}\n\tif ( hasOwnProp( options, 'copy' ) ) {\n\t\topts.copy = options.copy;\n\t\tif ( !isBoolean( opts.copy ) ) {\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be a boolean. Option: `%s`.', 'copy', opts.copy ) );\n\t\t}\n\t} else {\n\t\topts.copy = defaults.copy;\n\t}\n\t// If not provided a shape, infer from a provided data source...\n\tif ( hasOwnProp( options, 'shape' ) ) {\n\t\tshape = options.shape;\n\t\tif ( !isArrayLikeObject( shape ) ) { // weak test\n\t\t\tthrow new TypeError( format( 'invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.', 'shape', shape ) );\n\t\t}\n\t\tndims = shape.length;\n\t\tlen = numel( shape );\n\t} else if ( buffer ) {\n\t\tif ( FLG ) {\n\t\t\tshape = getShape( buffer );\n\t\t\tndims = shape.length;\n\t\t\tlen = numel( shape );\n\t\t} else if ( opts.flatten && isArray( buffer ) ) {\n\t\t\tshape = arrayShape( buffer );\n\t\t\tosh = shape; // cache a reference to the inferred shape\n\t\t\tndims = shape.length;\n\t\t\tlen = numel( shape );\n\t\t} else {\n\t\t\tndims = 1;\n\t\t\tlen = buffer.length;\n\t\t\tshape = [ len ]; // assume a 1-dimensional array (vector)\n\t\t}\n\t} else {\n\t\tthrow new Error( 'invalid arguments. Must provide either a data source, array shape, or both.' );\n\t}\n\t// Adjust the array shape to satisfy the minimum number of dimensions...\n\tif ( ndims < opts.ndmin ) {\n\t\tshape = expandShape( ndims, shape, opts.ndmin );\n\t\tndims = opts.ndmin;\n\t}\n\t// If not provided a data buffer, create it; otherwise, see if we need to cast a provided data buffer to another data type or perform a copy...\n\tif ( FLG ) {\n\t\tif ( numel( buffer.shape ) !== len ) {\n\t\t\tthrow new RangeError( 'invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.' );\n\t\t}\n\t\tif ( btype !== dtype || opts.copy ) {\n\t\t\tbuffer = copyView( buffer, dtype );\n\t\t} else {\n\t\t\tstrides = getStrides( buffer );\n\t\t\toffset = getOffset( buffer );\n\t\t\tbuffer = getData( buffer );\n\t\t\tif ( strides.length < ndims ) {\n\t\t\t\t// Account for augmented dimensions (note: expanding the strides array to account for prepended singleton dimensions does **not** affect the index offset):\n\t\t\t\tstrides = expandStrides( ndims, shape, strides, order );\n\t\t\t}\n\t\t}\n\t} else if ( buffer ) {\n\t\tif ( btype === 'generic' && opts.flatten ) {\n\t\t\tbuffer = flatten( buffer, osh || arrayShape( buffer ), false );\n\t\t}\n\t\tif ( buffer.length !== len ) {\n\t\t\tthrow new RangeError( 'invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.' );\n\t\t}\n\t\tif ( btype !== dtype || opts.copy ) {\n\t\t\tbuffer = castBuffer( buffer, len, dtype );\n\t\t}\n\t} else {\n\t\tbuffer = createBuffer( dtype, len );\n\t}\n\t// If we have yet to determine array strides, we assume that we can compute the strides, along with the index offset, for a **contiguous** data source based solely on the array shape and specified memory layout order...\n\tif ( strides === void 0 ) {\n\t\tstrides = shape2strides( shape, order );\n\t\toffset = strides2offset( shape, strides );\n\t}\n\treturn new ndarray( dtype, buffer, shape, strides, offset, order, nopts );\n}\n\n\n// EXPORTS //\n\nmodule.exports = array;\n", "/**\n* @license Apache-2.0\n*\n* Copyright (c) 2018 The Stdlib Authors.\n*\n* Licensed under the Apache License, Version 2.0 (the \"License\");\n* you may not use this file except in compliance with the License.\n* You may obtain a copy of the License at\n*\n*    http://www.apache.org/licenses/LICENSE-2.0\n*\n* Unless required by applicable law or agreed to in writing, software\n* distributed under the License is distributed on an \"AS IS\" BASIS,\n* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n* See the License for the specific language governing permissions and\n* limitations under the License.\n*/\n\n'use strict';\n\n/**\n* Multidimensional array.\n*\n* @module @stdlib/ndarray-array\n*\n* @example\n* var array = require( '@stdlib/ndarray-array' );\n*\n* var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n* // returns <ndarray>\n*\n* var v = arr.get( 0, 0 );\n* // returns 1\n*\n* @example\n* var array = require( '@stdlib/ndarray-array' );\n*\n* var opts = {\n*     'dtype': 'generic',\n*     'flatten': false\n* };\n*\n* var arr = array( [ [ 1, 2 ], [ 3, 4 ] ], opts );\n* // returns <ndarray>\n*\n* var v = arr.get( 0 );\n* // returns [ 1, 2 ]\n*\n* @example\n* var Float64Array = require( '@stdlib/array-float64' );\n* var array = require( '@stdlib/ndarray-array' );\n*\n* var opts = {\n*     'shape': [ 2, 2 ]\n* };\n*\n* var arr = array( new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ), opts );\n* // returns <ndarray>\n*\n* var v = arr.get( 0, 0 );\n* // returns 1.0\n*/\n\n// MODULES //\n\nvar main = require( './main.js' );\n\n\n// EXPORTS //\n\nmodule.exports = main;\n"],
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+  "names": ["require_is_array_like_object", "__commonJSMin", "exports", "module", "PINF", "isInteger", "isArrayLikeObject", "value", "require_defaults", "__commonJSMin", "exports", "module", "settings", "defaults", "require_cast_buffer", "__commonJSMin", "exports", "module", "bufferCtors", "allocUnsafe", "castBuffer", "buffer", "len", "dtype", "ctor", "out", "i", "require_copy_view", "__commonJSMin", "exports", "module", "arraylike2object", "castReturn", "complexCtors", "bufferCtors", "allocUnsafe", "ndarray", "getDType", "getShape", "getStrides", "getOffset", "getOrder", "getData", "generic", "arr", "len", "out", "i", "binary", "typed", "dtype", "ctor", "set", "fcn", "o", "wrapper", "copyView", "x", "require_expand_shape", "__commonJSMin", "exports", "module", "expandShape", "ndims", "shape", "ndmin", "out", "require_expand_strides", "__commonJSMin", "exports", "module", "abs", "expandStrides", "ndims", "shape", "strides", "order", "out", "N", "s", "i", "j", "require_main", "__commonJSMin", "exports", "module", "hasOwnProp", "isObject", "isBoolean", "isArray", "isNonNegativeInteger", "isndarrayLike", "shape2strides", "strides2offset", "strides2order", "numel", "ndarray", "isDataType", "isOrder", "isCastingMode", "isAllowedCast", "createBuffer", "getBufferDType", "getDType", "getShape", "getStrides", "getOffset", "getOrder", "getData", "arrayShape", "flatten", "format", "isArrayLikeObject", "getDefaults", "castBuffer", "copyView", "expandShape", "expandStrides", "defaults", "array", "options", "strides", "buffer", "offset", "order", "dtype", "btype", "shape", "ndims", "nopts", "opts", "osh", "len", "ord", "FLG", "main"]
 }
diff --git a/lib/copy_view.js b/lib/copy_view.js
index b5dd747..4c40a44 100644
--- a/lib/copy_view.js
+++ b/lib/copy_view.js
@@ -20,8 +20,18 @@
 
 // MODULES //
 
+var arraylike2object = require( '@stdlib/array-base-arraylike2object' );
+var castReturn = require( '@stdlib/complex-base-cast-return' );
+var complexCtors = require( '@stdlib/complex-ctors' );
 var bufferCtors = require( '@stdlib/ndarray-base-buffer-ctors' );
 var allocUnsafe = require( '@stdlib/buffer-alloc-unsafe' );
+var ndarray = require( '@stdlib/ndarray-base-ctor' );
+var getDType = require( '@stdlib/ndarray-dtype' );
+var getShape = require( '@stdlib/ndarray-shape' );
+var getStrides = require( '@stdlib/ndarray-strides' );
+var getOffset = require( '@stdlib/ndarray-offset' );
+var getOrder = require( '@stdlib/ndarray-order' );
+var getData = require( '@stdlib/ndarray-data-buffer' );
 
 
 // FUNCTIONS //
@@ -41,7 +51,7 @@ function generic( arr ) {
 	len = arr.length;
 	out = [];
 	for ( i = 0; i < len; i++ ) {
-		out.push( arr.get( i ) ); // FIXME: what if `arr` has more than one dimensions?
+		out.push( arr.iget( i ) ); // as output buffer is generic, should work with both real- and complex-valued ndarrays
 	}
 	return out;
 }
@@ -61,7 +71,7 @@ function binary( arr ) {
 	len = arr.length;
 	out = allocUnsafe( len );
 	for ( i = 0; i < len; i++ ) {
-		out[ i ] = arr.get( i ); // FIXME: what if `arr` has more than one dimensions?
+		out[ i ] = arr.iget( i ); // we're assuming that we're doing something sensible here (e.g., not trying to cast a complex-valued ndarray to a "binary" ndarray or a double-precision floating-point ndarray to binary, etc)
 	}
 	return out;
 }
@@ -78,15 +88,40 @@ function typed( arr, dtype ) {
 	var ctor;
 	var len;
 	var out;
+	var set;
+	var fcn;
+	var o;
 	var i;
 
 	ctor = bufferCtors( dtype );
 	len = arr.length;
-	out = new ctor( len ); // FIXME: need to account for complex number arrays; in which case, we may want to do something similar to `array/convert`
-	for ( i = 0; i < len; i++ ) {
-		out[ i ] = arr.get( i ); // FIXME: what if `arr` has more than one dimensions?
+	out = new ctor( len );
+
+	// If the output data buffer is a complex number array, we need to use accessors...
+	o = arraylike2object( out );
+	if ( o.accessorProtocol ) {
+		set = o.accessors[ 1 ];
+		fcn = castReturn( wrapper, 1, complexCtors( dtype ) );
+		for ( i = 0; i < len; i++ ) {
+			set( out, i, fcn( i ) ); // we're assuming that we're doing something sensible here (e.g., not trying to cast arbitrary objects to complex numbers, etc)
+		}
+	} else {
+		for ( i = 0; i < len; i++ ) {
+			out[ i ] = arr.iget( i ); // we're assuming that we're doing something sensible here (e.g., not trying to cast an ndarray containing generic objects to a double-precision floating-point array or a complex-valued ndarray to a real-valued ndarray, etc)
+		}
 	}
 	return out;
+
+	/**
+	* Returns the ndarray element specified by a provided linear index.
+	*
+	* @private
+	* @param {NonNegativeInteger} i - linear index
+	* @returns {*} value
+	*/
+	function wrapper( i ) {
+		return arr.iget( i );
+	}
 }
 
 
@@ -112,14 +147,18 @@ function typed( arr, dtype ) {
 * // returns <Float64Array>[ 3.0, 2.0, 1.0 ]
 */
 function copyView( arr, dtype ) {
-	// TODO: handle complex number dtypes!!
+	var x;
+
+	// Create a new "base" view, thus ensuring we have an `.iget` method and associated meta data...
+	x = new ndarray( getDType( arr ), getData( arr ), getShape( arr ), getStrides( arr ), getOffset( arr ), getOrder( arr ) ); // eslint-disable-line max-len
+
 	if ( dtype === 'generic') {
-		return generic( arr );
+		return generic( x );
 	}
 	if ( dtype === 'binary' ) {
-		return binary( arr );
+		return binary( x );
 	}
-	return typed( arr, dtype );
+	return typed( x, dtype );
 }
 
 
diff --git a/package.json b/package.json
index 625db17..cb41c67 100644
--- a/package.json
+++ b/package.json
@@ -37,6 +37,7 @@
     "url": "https://github.com/stdlib-js/stdlib/issues"
   },
   "dependencies": {
+    "@stdlib/array-base-arraylike2object": "^0.1.0",
     "@stdlib/array-base-flatten": "^0.1.0",
     "@stdlib/array-shape": "^0.1.0",
     "@stdlib/assert-has-own-property": "^0.1.1",
@@ -46,6 +47,8 @@
     "@stdlib/assert-is-nonnegative-integer": "^0.1.0",
     "@stdlib/assert-is-plain-object": "^0.1.1",
     "@stdlib/buffer-alloc-unsafe": "^0.1.0",
+    "@stdlib/complex-base-cast-return": "^0.1.0",
+    "@stdlib/complex-ctors": "^0.1.1",
     "@stdlib/constants-float64-pinf": "^0.1.1",
     "@stdlib/math-base-assert-is-integer": "^0.1.1",
     "@stdlib/math-base-special-abs": "^0.1.1",
@@ -56,6 +59,7 @@
     "@stdlib/ndarray-base-buffer": "^0.1.1",
     "@stdlib/ndarray-base-buffer-ctors": "^0.1.0",
     "@stdlib/ndarray-base-buffer-dtype": "^0.1.0",
+    "@stdlib/ndarray-base-ctor": "^0.1.0",
     "@stdlib/ndarray-base-numel": "^0.1.1",
     "@stdlib/ndarray-base-shape2strides": "^0.1.1",
     "@stdlib/ndarray-base-strides2offset": "^0.1.1",