除非我错误地诊断出我的问题，否则在我看来，Cocoapods要求您将源文件指定为s.source_files =的全局或s.ios.source_files =的平台特定（或任何平台） ）。
是否无法将所有源文件一起指定（全局和特定于平台），而只是让他们在Xcode中的目标/平台设置决定了应该为给定平台构建什么？
我不想将我的源文件分成common/，iOS/和macOS/ 以及等目录。目标会员资格。
答案 0 :(得分：0)
你有没有尝试过：
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<title>Weighted Citation Graph</title>
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<script>
function load_graph(text) {
var color = d3.scale.category20();
//try{
// var data = JSON.parse(text);
//} catch (e) {
// window.alert("sometext: "+e);
//}
var data = { "nodes": [{ "id": 127230, "name": "Optimization of query evaluation algorithms", "citation": 26, "group": 10 }, { "id": 127254, "name": "Flow algorithms for parallel query optimization", "citation": 22, "group": 10 }, { "id": 127380, "name": "Randomized approximation algorithms for query optimization problems on two processors", "citation": 14, "group": 10 }, { "id": 127438, "name": "Optimization algorithms for simultaneous multidimensional queries in OLAP environments", "citation": 12, "group": 10 }, { "id": 127063, "name": "Query optimization in database systems", "citation": 230, "group": 10 }, { "id": 127158, "name": "Query optimization in a memory-resident domain relational calculus database system", "citation": 41, "group": 10 }, { "id": 129760, "name": "An Overview of TQuel", "citation": 22, "group": 10 }, { "id": 129867, "name": "ADVISORS", "citation": 10, "group": 10 }, { "id": 129872, "name": "Tellabs and THRIP through the Telkom Centre of Excellence at Rhodes University.", "citation": 10, "group": 10 }, { "id": 127412, "name": "Optimal service ordering in decentralized queries over web services", "citation": 13, "group": 10 }, { "id": 130856, "name": "Queries over Web Services", "citation": 10, "group": 10 }, { "id": 130959, "name": "Exploiting Parallelism to Accelerate Keyword Search On Deep-web Sources", "citation": 10, "group": 10 }, { "id": 131199, "name": "Contents lists available at ScienceDirect Future Generation Computer Systems", "citation": 10, "group": 10 }, { "id": 131211, "name": "Flow Algorithms for Parallel Query Optimization", "citation": 10, "group": 10 }, { "id": 127373, "name": "Multi-query Optimization for On-Line Analytical Processing", "citation": 14, "group": 10 }, { "id": 133379, "name": "Concise descriptions of subsets of structured sets", "citation": 21, "group": 10 }], "links": [{ "source": 127230, "target": 127063, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127230, "target": 127158, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127230, "target": 129760, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127230, "target": 129867, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127230, "target": 129872, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127230, "target": 127063, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127230, "target": 127158, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127230, "target": 129760, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127230, "target": 129867, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127230, "target": 129872, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127254, "target": 127412, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127254, "target": 130856, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127254, "target": 130959, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127254, "target": 131199, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127254, "target": 131211, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127254, "target": 127412, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127254, "target": 130856, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127254, "target": 130959, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127254, "target": 131199, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127254, "target": 131211, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127438, "target": 127373, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127438, "target": 133379, "name": "c1", "value": 10, "grouo": 1 }, { "source": 127438, "target": 127373, "name": "c1", "value": 10, "grouo": 9 }, { "source": 127438, "target": 133379, "name": "c1", "value": 10, "grouo": 9 }] };
// used to store the number of links between two nodes.
// mLinkNum[data.links[i].source + "," + data.links[i].target] = data.links[i].linkindex;
var mLinkNum = {};
// sort links first
// sortLinks();
data.links.sort(function (a, b) {
if (a.source > b.source) { return 1; }
else if (a.source < b.source) { return -1; }
else {
if (a.target > b.target) { return 1; }
if (a.target < b.target) { return -1; }
else { return 0; }
}
})
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var color = d3.scale.category10()
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data.links.forEach(function (e) {
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target: targetNode,
name: e.name,
value: e.value,
linkindex: e.linkindex,
grouo: e.grouo
});
});
console.log(edges)
force
.nodes(data.nodes)
.links(edges)
.start();
var path = svg.append("svg:g")
.selectAll("line")
.data(edges)
.enter().append("svg:path")
.attr("class", "link")
.style("stroke-width", function (d, i) {
console.log(d.value)
return Math.sqrt(d.value);
}).style('stroke', function (d) {
return color(d.grouo);
});
var circle = svg.append("svg:g")
.selectAll("circle")
.data(force.nodes())
.enter().append("svg:circle")
.attr("r", function (d) {
return (Math.sqrt(d.citation));
})
.style("fill", function (d) {
return color(d.group);
})
.call(force.drag);
var text = svg.append("svg:g")
.selectAll("g")
.data(force.nodes())
.enter().append("svg:g");
console.log('test');
// A copy of the text with a thick white stroke for legibility.
//text.append("svg:text")
//.attr("x", 8)
//.attr("y", ".31em")
//.attr("class", "shadow")
//.text(function (d) {
//return d.name;
//});
text.append("svg:text")
.attr("x", 8)
.attr("y", ".31em")
.text(function (d) {
// return d.name;
});
// Use elliptical arc path segments to doubly-encode directionality.
function tick() {
path.attr("d", function (d, i) {
var dx = d.target.x - d.source.x,
dy = d.target.y - d.source.y,
dr = 30 * d.linkindex; //linknum is defined above
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path.append("svg:title")
.text(function (d, i) {
return d.name;
});
circle.attr("transform", function (d) {
return "translate(" + d.x + "," + d.y + ")";
});
text.attr("transform", function (d) {
return "translate(" + d.x + "," + d.y + ")";
});
}
// sort the links by source, then target
function sortLinks1() {
data.links.sort(function (a, b) {
if (a.source > b.source) {
return 1;
} else if (a.source < b.source) {
return -1;
} else {
if (a.target > b.target) {
return 1;
}
if (a.target < b.target) {
return -1;
} else {
return 0;
}
}
});
}
//any links with duplicate source and target get an incremented 'linknum'
function setLinkIndexAndNum1() {
for (var i = 0; i < data.links.length; i++) {
if (i != 0 &&
data.links[i].source == data.links[i - 1].source &&
data.links[i].target == data.links[i - 1].target) {
data.links[i].linkindex = data.links[i - 1].linkindex + 1;
console.log(data.links[i].linkindex)
} else {
data.links[i].linkindex = 1;
console.log(data.links[i].linkindex)
}
// save the total number of links between two nodes
if (mLinkNum[data.links[i].target + "," + data.links[i].source] !== undefined) {
mLinkNum[data.links[i].target + "," + data.links[i].source] = data.links[i].linkindex;
} else {
mLinkNum[data.links[i].source + "," + data.links[i].target] = data.links[i].linkindex;
}
}
}
function setLinkIndexAndNum() {
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if (i != 0 &&
data.links[i].source == data.links[i - 1].source &&
data.links[i].target == data.links[i - 1].target) {
data.links[i].linkindex = data.links[i - 1].linkindex + 1;
}
else {
data.links[i].linkindex = 1;
};
};
}
}
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