def __init__(self, db, outtf=True):
self.size = None
self.pFile = None
self.tFile = None
self.temp = mtemp.Mtemp()
self.db = db # 入力データベース
self.file = self.temp.file()
self.outtf = outtf
self.weightFile = {}
self.posWeight = {}
self.sigma = {}
self.msgoff = True
items = self.db.items
for cName, posSize in db.clsNameRecSize.items():
self.weightFile[cName] = self.temp.file()
self.posWeight[cName] = self.calOmega(posSize)
f = nm.mcut(nfno=True, f=self.db.clsFN, i=self.db.cFile)
f <<= nm.mchgstr(nfn=True,
f=0,
O=-1,
o=self.weightFile[cName],
c="%s:%s" % (cName, self.posWeight[cName]))
f.run()
# アイテムをシンボルから番号に変換する。
f = nm.mjoin(k=self.db.itemFN,
K=items.itemFN,
i=self.db.file,
m=items.file,
f=items.idFN)
f <<= nm.mcut(f=self.db.idFN + "," + items.idFN)
f <<= nm.mtra(k=self.db.idFN, f=items.idFN)
f <<= nm.mcut(f=items.idFN, nfno=True, o=self.file)
f.run()
def __init__(self,db): self.db=db self.eArgs=None self.type =None self.minCnt=None self.minSup=None self.maxCnt=None self.maxSup=None self.minLen=None self.maxLen=None self.top =None self.skipTP=False #self.size =None self.pFile =None self.tFile =None self.msgoff = True self.temp=mtemp.Mtemp() self.db = db # 入力データベース self.file=self.temp.file() items=self.db.items # アイテムをシンボルから番号に変換する。 f = nm.mjoin(k=self.db.itemFN,K=items.itemFN,m=items.file,f=items.idFN,i=self.db.file) f <<= nm.mcut(f=self.db.idFN+","+items.idFN) f <<= nm.mtra(k=self.db.idFN,f=items.idFN) f <<= nm.mcut(f=items.idFN,nfno=True,o=self.file) f.run()
def __init__(self,
edgeFile=None,
edgeList=None,
title1=None,
title2=None,
nodeFile=None,
nodeList=None,
title=None):
#メンバ変数定義
self.eFileT = None # Take内部で使用するエッジファイル(アイテム間をスペース区切りにしたファイル)
self.eFile = None # エッジファイル
self.eFileN = None # エッジファイル名
self.edgeFN1 = None # エッジファイル項目名1(String)
self.edgeFN2 = None # エッジファイル項目名2(String)
self.nFile = None # ノードファイル
self.nFileN = None # ノードファイル名
self.nodeFN = None # ノードファイル項目名(String)
self.mFile = None # ノードIDマッピングファイル
self.__wfE = None # エッジ用ワークファイル
self.__wfN = None # ノード用ワークファイル
self.__tempW = mtemp.Mtemp()
self.__temp = mtemp.Mtemp()
#引数指定があればデータ読み込み(ファイルとリストが同時に指定された場合はファイル優先)
#エッジ読み込み
if edgeFile is not None:
self.__readEdgeCSV(edgeFile=edgeFile, title1=title1, title2=title2)
else:
if edgeList is not None:
self.__readEdgeList(edgeList=edgeList,
title1=title1,
title2=title2)
#ノード読み込み
if nodeFile is not None:
self.__readNodeCSV(nodeFile=nodeFile, title=title)
else:
if nodeList is not None:
self.__readNodeList(nodeList=nodeList, title=title)
#符号化
if self.__wfE is not None:
self.__convertToNumeric()
def isSame(self, targetGraph):
if os.path.getsize(self.eFile) != os.path.getsize(targetGraph.eFile):
return False
else:
xxt = mtemp.Mtemp()
xx = xxt.file()
os.system("diff -q %s %s > %s" %
(self.eFile, targetGraph.eFile, xx))
if (os.path.getsize(xx) != 0):
xxt.rm()
return False
else:
xxt.rm()
return True
def mnest2tree(ei, ef, k, ni=None, nf=None, ev=None, no=None, eo=None):
# paracheck追加
efs = ef.split(",")
ef1 = efs[0]
ef2 = efs[1]
f = nm.mcut(f="%s:#orgKey,%s:#orgEf1,%s:#orgEf2" % (k, ef1, ef2), i=ei)
temp = mtemp.Mtemp()
of = temp.file()
with _nu.mcsvout(o=of, f="#orgKey,#orgEf1,#orgEf2,#ef1,#ef2") as oCSV:
for flds in f:
orgKey = flds[0]
orgEf1 = flds[1]
orgEf2 = flds[2]
oCSV.write([orgKey, orgEf1, orgEf2, orgKey, orgEf1])
oCSV.write([orgKey, orgEf1, orgEf2, orgKey, orgEf2])
f = None
f <<= nm.mjoin(k="#orgKey,#orgEf1,#orgEf2", K=[k, ef1, ef2], m=ei,
i=of) # 全項目join
if ev:
f <<= nm.mavg(k="#ef1,#ef2", f=ev)
else:
f <<= nm.muniq(k="#ef1,#ef2")
f <<= nm.mcut(r=True, f="#orgKey,#orgEf1,#orgEf2")
f <<= nm.mfldname(f="#ef1:%s,#ef2:%s" % (ef1, ef2), o=eo)
f.run()
if ni:
head = nu.mheader(i=ni)
fldnames = [s for s in head if s != nf]
commas = ',' * (len(fldnames) - 1)
f0 = None
f0 <<= nm.mcut(f="%s:%s" % (ef1, nf), i=eo)
f0 <<= nm.muniq(k=nf)
f0 <<= nm.mcommon(k=nf, m=ni, r=True)
f0 <<= nm.msetstr(v=commas, a=fldnames)
f = nm.mcut(f=k, r=True, i=[ni, f0])
f <<= nm.msetstr(v="", a=k, o=no)
f.run()
def __init__(self,
gi=None,
go=None,
sim="R",
th=None,
indirect=False,
sup=0,
iter=30,
O=None,
log=None):
self.gi = None # (graph object) input graph set
self.go = None # (graph object) output graph set
self.__eo = None # (string) output edge file name
self.__no = None # (string) output node file name
self.__nf = None # (string) output node file column title
self.th = float(th) # (float) threshhold of degree of similarity
self.indirect = indirect # (boolean) exclude direct relationship from adjacent node set in similarity calculation
self.measure = sim # (string) similarity measure
self.minSupp = int(sup) # (float) minimum support
self.iterMax = int(iter) # (int) upper bound of iterations
self.logFile = log # (string) log file name
self.outDir = O # (string) directory name for outputs in the process
self.msgoff = True
self.__tempW = mtemp.Mtemp(
) # temp files created by this instance will be deleted, after self.run() executed.
if (gi):
self.gi = gi # input graph object
else:
raise Exception("gi is mandatory.")
if (go):
self.go = go
self.__eo = self.__tempW.file()
self.__no = self.__tempW.file()
self.__nf = "n"
if self.iterMax < 1:
raise Exception("iter must be 1 or more.")
if self.outDir and not os.path.isdir(self.outDir):
os.makedirs(self.outDir)
def __init__(self, db, outtf=True):
self.size = None
self.temp = mtemp.Mtemp()
self.db = db # 入力データベース
self.file = self.temp.file()
items = self.db.items
self.outtf = outtf
self.top = None
self.msgoff = True
# アイテムをシンボルから番号に変換する。
f = nm.mjoin(k=self.db.itemFN,
K=items.itemFN,
m=items.file,
f=items.idFN,
i=self.db.file)
f <<= nm.mcut(f=self.db.idFN + "," + self.db.timeFN + "," + items.idFN)
f <<= nm.mtra(k=self.db.idFN, s=self.db.timeFN + "%n", f=items.idFN)
f <<= nm.mcut(f=items.idFN, nfno=True, o=self.file)
f.run()
def __init__(self,iFile,itemFN,taxoFN): # アイテムの項目名(=>String) self.itemFN = None # 分類の項目名(=>String) self.taxoFN = None # アイテムの種類数(=>Fixnum) self.itemSize = None # 分類の種類数(=>Fixnum) self.taxoSize = None # taxonomyデータファイル名(=>String) self.file = None self.temp = mtemp.Mtemp() self.iFile = iFile self.iPath = os.path.abspath(self.iFile) self.itemFN = itemFN self.taxoFN = taxoFN # item順に並べ替えてpathに書き出す self.file = self.temp.file() para_it = self.itemFN +"," + self.taxoFN nm.mcut(f=para_it,i=self.iFile).muniq(k=para_it,o=self.file).run(msg="on") f = nm.mcut(f=self.itemFN,i=self.iFile) f <<= nm.mtrafld(f=self.itemFN,a="__fld",valOnly=True) f <<= nm.mtra(f="__fld",r=True) f <<= nm.muniq(k="__fld") f <<= nm.mcount(a="size") f <<= nm.mcut(f="size") xx1 = f.run() self.itemSize = int(xx1[0][0]) xx2 = nm.mcut(f=self.taxoFN+":item",i=self.file).muniq(k="item").mcount(a="size").mcut(f="size").run() self.taxoSize = int(xx2[0][0])
def repTaxo(self, taxonomy):
#@taxonomy=taxonomy
self.items.repTaxo(taxonomy) # アイテムクラスをtaxonomyで置換する
tFile = taxonomy.file
itemFN = taxonomy.itemFN
taxoFN = taxonomy.taxoFN
tf = mtemp.Mtemp()
xx1 = tf.file()
f = None
f <<= nm.mjoin(k=self.itemFN, K=itemFN, f=taxoFN, m=tFile, i=self.file)
f <<= nm.mcut(f=self.idFN + "," + self.timeFN + "," + taxoFN + ":" +
self.itemFN)
f <<= nm.msortf(f=self.idFN + "," + self.timeFN + "," + self.itemFN,
o=xx1)
f.run()
self.file = self.temp.file()
shutil.move(xx1, self.file)
def msankey(i, o, v, f, title="", h=500, w=960, nl=False, T=None):
# f= 2 fld
if type(f) is str:
ff = f.split(',')
elif type(f) is list:
ff = f
else:
raise TypeError("f= unsupport " + str(type(k)))
if len(ff) < 2:
raise TypeError("f= takes just two field names")
if T != None:
import re
os.environ["KG_TmpPath"] = re.sub(r'/$', "", T)
if h == None:
h = 500
if w == None:
w = 960
if title == None:
title = ""
tempW = mtemp.Mtemp()
nodef = tempW.file()
edgef = tempW.file()
ef1 = ff[0]
ef2 = ff[1]
ev = v
iFile = i
oFile = o
f0 = nm.mcut(i=iFile, f="%s:nodes" % (ef1))
f1 = nm.mcut(i=iFile, f="%s:nodes" % (ef2))
f2 = None
f2 <<= nm.muniq(i=[f0, f1], k="nodes")
f2 <<= nm.mnumber(s="nodes", a="num", o=nodef)
f2.run()
f3 = None
f3 <<= nm.mcut(f="%s:nodes1,%s:nodes2,%s" % (ef1, ef2, ev), i=iFile)
f3 <<= nm.mjoin(k="nodes1", K="nodes", m=nodef, f="num:num1")
f3 <<= nm.mjoin(k="nodes2", K="nodes", m=nodef, f="num:num2")
f3 <<= nm.mcut(f="num1,num2,%s" % (ev))
f3 <<= nm.msortf(f="num1%n,num2%n", o=edgef)
f3.run()
wk = []
nodeL = []
for flds in nm.readcsv(nodef).getline(otype='dict'):
nodeL.append({"name": flds['nodes']})
nodes = json.JSONEncoder().encode(nodeL)
linkL = []
for flds in nm.readcsv(edgef).getline(otype='dict',
dtype={
"num1": "int",
"num2": "int",
ev: "int"
}):
linkL.append({
"source": flds["num1"],
"target": flds["num2"],
"value": flds[ev]
})
links = json.JSONEncoder().encode(linkL)
nolabel = ""
if nl:
nolabel = "font-size: 0px;"
html = sys.stdout
if not oFile == None:
html = open(oFile, "w")
outTemplate = '''
<!DOCTYPE html>
<html class="ocks-org do-not-copy">
<meta charset="utf-8">
<title>{title}</title>
<style>
body {{
font: 10px sans-serif;
}}
svg {{
padding: 10px 0 0 10px;
}}
.arc {{
stroke: #fff;
}}
#tooltip {{
position: absolute;
width: 150px;
height: auto;
padding: 10px;
background-color: white;
-webkit-border-radius: 10px;
-moz-border-radius: 10px;
border-radius: 10px;
-webkit-box-shadow: 4px 4px 10px rgba(0,0,0,0.4);
-moz-box-shadow: 4px 4px 10px rgba(0,0,0,0.4);
box-shadow: 4px 4px 10px rgba(0,0,0,0.4);
pointer-events: none;
}}
#tooltip.hidden {{
display: none;
}}
#tooltip p {{
margin: 0;
font-family: sans-serif;
font-size: 10px;
line-height: 14px;
}}
#chart {{
height: 500px;
}}
.node rect {{
cursor: move;
fill-opacity: .9;
shape-rendering: crispEdges;
}}
.node text {{
pointer-events: none;
text-shadow: 0 1px 0 #fff;
{nolabel}
}}
.link {{
fill: none;
stroke: #000;
stroke-opacity: .2;
}}
.link:hover {{
stroke-opacity: .5;
}}
</style>
<body>
<h1>{title}</h1>
<p id="chart">
<script>
{d3js_str}
d3.sankey = function() {{
var sankey = {{}},
nodeWidth = 24,
nodePadding = 8,
size = [1, 1],
nodes = [],
links = [];
sankey.nodeWidth = function(_) {{
if (!arguments.length) return nodeWidth;
nodeWidth = +_;
return sankey;
}};
sankey.nodePadding = function(_) {{
if (!arguments.length) return nodePadding;
nodePadding = +_;
return sankey;
}};
sankey.nodes = function(_) {{
if (!arguments.length) return nodes;
nodes = _;
return sankey;
}};
sankey.links = function(_) {{
if (!arguments.length) return links;
links = _;
return sankey;
}};
sankey.size = function(_) {{
if (!arguments.length) return size;
size = _;
return sankey;
}};
sankey.layout = function(iterations){{
computeNodeLinks();
computeNodeValues();
computeNodeBreadths();
computeNodeDepths(iterations);
computeLinkDepths();
return sankey;
}};
sankey.relayout = function() {{
computeLinkDepths();
return sankey;
}};
sankey.link = function() {{
var curvature = .5;
function link(d) {{
var x0 = d.source.x + d.source.dx,
x1 = d.target.x,
xi = d3.interpolateNumber(x0, x1),
x2 = xi(curvature),
x3 = xi(1 - curvature),
y0 = d.source.y + d.sy + d.dy / 2,
y1 = d.target.y + d.ty + d.dy / 2;
return "M" + x0 + "," + y0
+ "C" + x2 + "," + y0
+ " " + x3 + "," + y1
+ " " + x1 + "," + y1;
}}
link.curvature = function(_) {{
if (!arguments.length) return curvature;
curvature = +_;
return link;
}};
return link;
}};
// Populate the sourceLinks and targetLinks for each node.
// Also, if the source and target are not objects, assume they are indices.
function computeNodeLinks() {{
nodes.forEach(function(node) {{
node.sourceLinks = [];
node.targetLinks = [];
}});
links.forEach(function(link) {{
var source = link.source,
target = link.target;
if (typeof source === "number") source = link.source = nodes[link.source];
if (typeof target === "number") target = link.target = nodes[link.target];
source.sourceLinks.push(link);
target.targetLinks.push(link);
}});
}}
// Compute the value (size) of each node by summing the associated links.
function computeNodeValues() {{
nodes.forEach( function(node) {{
node.value = Math.max(d3.sum(node.sourceLinks, value),d3.sum(node.targetLinks, value));
}} );
}}
// Iteratively assign the breadth (x-position) for each node.
// Nodes are assigned the maximum breadth of incoming neighbors plus one;
// nodes with no incoming links are assigned breadth zero, while
// nodes with no outgoing links are assigned the maximum breadth.
function computeNodeBreadths() {{
var remainingNodes = nodes,
nextNodes,
x = 0;
while (remainingNodes.length) {{
nextNodes = [];
remainingNodes.forEach(function(node) {{
node.x = x;
node.dx = nodeWidth;
node.sourceLinks.forEach(function(link) {{
nextNodes.push(link.target);
}});
}});
remainingNodes = nextNodes;
++x;
}}
//
moveSinksRight(x);
scaleNodeBreadths((width - nodeWidth) / (x - 1));
}}
function moveSourcesRight() {{
nodes.forEach(function(node) {{
if (!node.targetLinks.length) {{
node.x = d3.min(node.sourceLinks, function(d) {{ return d.target.x; }} ) - 1;
}}
}});
}}
function moveSinksRight(x) {{
nodes.forEach(function(node) {{
if (!node.sourceLinks.length) {{
node.x = x - 1;
}}
}});
}}
function scaleNodeBreadths(kx) {{
nodes.forEach(function(node) {{
node.x *= kx;
}});
}}
function computeNodeDepths(iterations) {{
var nodesByBreadth = d3.nest()
.key(function(d) {{ return d.x; }})
.sortKeys(d3.ascending)
.entries(nodes)
.map(function(d) {{ return d.values; }});
//
initializeNodeDepth();
resolveCollisions();
for (var alpha = 1; iterations > 0; --iterations){{
relaxRightToLeft(alpha *= .99);
resolveCollisions();
relaxLeftToRight(alpha);
resolveCollisions();
}}
function initializeNodeDepth() {{
var ky = d3.min(nodesByBreadth, function(nodes) {{
return (size[1] - (nodes.length - 1) * nodePadding) / d3.sum(nodes, value);
}});
nodesByBreadth.forEach(function(nodes) {{
nodes.forEach(function(node, i) {{
node.y = i;
node.dy = node.value * ky;
}});
}});
links.forEach(function(link) {{
link.dy = link.value * ky;
}});
}}
function relaxLeftToRight(alpha) {{
nodesByBreadth.forEach(function(nodes, breadth) {{
nodes.forEach(function(node) {{
if (node.targetLinks.length) {{
var y = d3.sum(node.targetLinks, weightedSource) / d3.sum(node.targetLinks, value);
node.y += (y - center(node)) * alpha;
}}
}});
}});
function weightedSource(link) {{
return center(link.source) * link.value;
}}
}}
function relaxRightToLeft(alpha) {{
nodesByBreadth.slice().reverse().forEach(function(nodes){{
nodes.forEach(function(node) {{
if (node.sourceLinks.length) {{
var y = d3.sum(node.sourceLinks, weightedTarget) / d3.sum(node.sourceLinks, value);
node.y += (y - center(node)) * alpha;
}}
}});
}});
function weightedTarget(link) {{
return center(link.target) * link.value;
}}
}}
function resolveCollisions() {{
nodesByBreadth.forEach(function(nodes) {{
var node, dy, y0 = 0,
n = nodes.length, i;
// Push any overlapping nodes down.
nodes.sort(ascendingDepth);
for (i = 0; i < n; ++i) {{
node = nodes[i];
dy = y0 - node.y;
if (dy > 0) node.y += dy;
y0 = node.y + node.dy + nodePadding;
}}
// If the bottommost node goes outside the bounds, push it back up.
dy = y0 - nodePadding - size[1];
if (dy > 0) {{
y0 = node.y -= dy;
// Push any overlapping nodes back up.
for (i = n - 2; i >= 0; --i) {{
node = nodes[i];
dy = node.y + node.dy + nodePadding - y0;
if (dy > 0) node.y -= dy;
y0 = node.y;
}}
}}
}});
}}
function ascendingDepth(a, b) {{ return a.y - b.y; }}
}}
function computeLinkDepths() {{
nodes.forEach(function(node) {{
node.sourceLinks.sort(ascendingTargetDepth);
node.targetLinks.sort(ascendingSourceDepth);
}});
nodes.forEach(function(node) {{
var sy = 0, ty = 0;
node.sourceLinks.forEach(function(link) {{
link.sy = sy;
sy += link.dy;
}});
node.targetLinks.forEach(function(link) {{
link.ty = ty;
ty += link.dy;
}});
}});
function ascendingSourceDepth(a, b) {{
return a.source.y - b.source.y;
}}
function ascendingTargetDepth(a, b) {{
return a.target.y - b.target.y;
}}
}}
function center(node){{
return node.y + node.dy / 2;
}}
function value(link) {{
return link.value;
}}
return sankey;
}};
</script>
<script>
var margin = {{top: 1, right: 1, bottom: 6, left: 1}},
width = {width} - margin.left - margin.right,
height = {height} - margin.top - margin.bottom;
var formatNumber = d3.format(",.0f"),
format = function(d) {{ return formatNumber(d) + " TWh"; }},
color = d3.scale.category20();
var svg = d3.select("#chart").append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
var sankey = d3.sankey()
.nodeWidth(15)
.nodePadding(10)
.size([width, height]);
var path = sankey.link();
var nodes={nodes}
var links={links}
sankey
.nodes(nodes)
.links(links)
.layout(32);
var link = svg.append("g").selectAll(".link")
.data(links)
.enter().append("path")
.attr("class", "link")
.attr("d", path)
.style("stroke-width", function(d) {{ return Math.max(1, d.dy); }})
.sort(function(a, b) {{ return b.dy - a.dy; }});
link.append("title")
.text(function(d) {{ return d.source.name + " → " + d.target.name + "" + format(d.value); }});
var node = svg.append("g").selectAll(".node")
.data(nodes)
.enter().append("g")
.attr("class", "node")
.attr("transform", function(d) {{ return "translate(" + d.x + "," + d.y + ")"; }})
.call(
d3.behavior.drag()
.origin(function(d) {{ return d; }})
.on("dragstart", function() {{ this.parentNode.appendChild(this); }})
.on("drag", dragmove)
);
node.append("rect")
.attr("height", function(d) {{ return d.dy; }})
.attr("width", sankey.nodeWidth() )
.style("fill", function(d) {{ return d.color = color(d.name.replace(/ .*/, "")); }})
.style("stroke", function(d) {{ return d3.rgb(d.color).darker(2); }})
.append("title")
.text(function(d) {{ return d.name + "" + format(d.value); }});
node.append("text")
.attr("x", -6)
.attr("y", function(d) {{ return d.dy / 2; }})
.attr("dy", ".35em")
.attr("text-anchor", "end")
.attr("transform", null)
.text(function(d) {{ return d.name; }})
.filter(function(d) {{ return d.x < width / 2; }})
.attr("x", 6 + sankey.nodeWidth())
.attr("text-anchor", "start");
function dragmove(d){{
d3.select(this)
.attr("transform", "translate(" + d.x + "," + (d.y = Math.max(0, Math.min(height - d.dy, d3.event.y))) + ")");
sankey.relayout();
link.attr("d", path);
}}
</script>
'''.format(title=title,
nolabel=nolabel,
d3js_str=vjs.ViewJs.d3jsMin(),
nodes=nodes,
links=links,
width=w,
height=h)
html.write(outTemplate)
if not oFile == None:
html.close()
T3,F,8
T4,B,7
T4,D,1
T4,F,2
T5,A,44
T5,B,5
T5,D,7
T5,E,8
T6,A,3
T6,B,2
T6,D,1
T6,E,9
T6,F,1\
"""
temo = mtemp.Mtemp()
inpname = temo.file()
scp = """\
readcsv {inpdata}
head -n 10
mcut f=tid,item,val
msum k=tid f=val
writecsv runcheck.csv\
""".format(inpdata=inpname)
if len(sys.argv) != 2:
print("run sample")
scpname = temo.file()
with open(scpname, "w") as wfp:
def run(self):
tempW = mtemp.Mtemp()
xxtra = tempW.file()
xxmap1 = tempW.file()
xxmap2 = tempW.file()
lcmout = tempW.file()
xxt0 = tempW.file()
xxp0 = tempW.file()
xx3t = tempW.file()
xx4t = tempW.file()
self.pair2tra(self.ei, self.ef1, self.ef2, xxtra, xxmap1, xxmap2)
runPara = {}
runPara["type"] = "CIf"
runPara["sup"] = 1
runPara["o"] = lcmout
runPara["i"] = xxtra
if self.minSize2:
runPara["l"] = self.minSize2
if self.maxSize2:
runPara["u"] = self.maxSize2
extTake.lcm(runPara)
extTake.lcmtrans(lcmout, "p", xxt0)
f = None
f <<= nm.mdelnull(f="pattern", i=xxt0)
f <<= nm.mvreplace(vf="pattern", m=xxmap2, K="num2", f="node2")
f <<= nm.mcut(f="pid,pattern,size:size2")
f <<= nm.mvsort(vf="pattern")
f <<= nm.msortf(f="pid")
if self.byedge:
f_e0 = nm.mtra(f="pattern", i=f, r=True)
extTake.lcmtrans(lcmout, "t", xx3t)
f_e1 = None
f_e1 <<= nm.mjoin(k="__tid", m=xxmap1, f="node1", K="num1", i=xx3t)
f_e1 <<= nm.msortf(f="pid")
## xx2
f_e2 = None
f_e2 <<= nm.mcount(k="pid", a="size1", i=f_e1)
f_e2 <<= nm.mselnum(f="size1",
c="[{},{}]".format(self.minSize1,
self.maxSize1))
f_e3 = None
f_e3 <<= nm.mjoin(k="pid", m=f_e2, f="size1", i=f_e1)
f_e3 <<= nm.mnjoin(k="pid", m=f_e0, f="pattern,size2")
f_e3 <<= nm.mcut(f="pid:id,node1:{},pattern:{},size1,size2".format(
self.ef1, self.ef2),
o=self.oFile)
f_e3.run()
else:
extTake.lcmtrans(lcmout, "t", xx4t)
f_e4 = None
f_e4 <<= nm.mjoin(k="__tid", m=xxmap1, i=xx4t, f="node1", K="num1")
f_e4 <<= nm.mtra(k="pid", f="node1")
f_e4 <<= nm.mvcount(vf="node1:size1")
f_e4 <<= nm.mjoin(k="pid", m=f, f="pattern,size2")
f_e4 <<= nm.mselnum(f="size1",
c="[{},{}]".format(self.minSize1,
self.maxSize1))
f_e4 <<= nm.mvsort(vf="node1,pattern")
f_e4 <<= nm.msortf(f="node1,pattern")
f_e4 <<= nm.mcut(f="node1:{},pattern:{},size1,size2".format(
self.ef1, self.ef2),
o=self.oFile)
f_e4.run()
def run(self):
wf = mtemp.Mtemp()
xxpal = wf.file()
xxa = wf.file()
xxb = wf.file()
xxc = wf.file()
xxd = wf.file()
xxout = wf.file()
# ============
# n1,n2,sim
# a,b,0.40
# a,c,0.31
# a,d,0.22
# b,c,0.20
# b,d,0.24
# b,e,0.14
# c,d,0.30
# d,e,0.09
xpal = None
if self.directed:
# 任意の枝a->bのaについて上位rankを選択
xpal <<= nm.mnumber(k=self.ef1,
s=self.sim + "%nr",
e="skip",
S=1,
a="##rank",
i=self.ei)
xpal <<= nm.mselnum(f="##rank", c="[," + str(self.rank) + "]")
else:
xxa = nm.mfsort(f=[self.ef1, self.ef2], i=self.ei)
xxb = nm.mfsort(f=[self.ef2, self.ef1], i=self.ei)
xpal <<= nm.muniq(k=[self.ef1, self.ef2], i=[xxa, xxb])
xpal <<= nm.mnumber(k=self.ef1,
s=self.sim + "%nr",
e="skip",
S=1,
a="##rank")
xpal <<= nm.mselnum(f="##rank", c="[," + str(self.rank) + "]")
# 両方向+片方向
xpal1 = None
if self.dir == "x":
xpal1 <<= nm.mcut(f=[self.ef1, self.ef2, self.sim], i=xpal)
# 両方向
elif self.dir == "b":
selpara = "$s{%s}==$s{##ef2}" % (self.ef1)
# 得られた上位rankグラフからa->b->cを作成し、a==cであれば相思相愛ということ
xpal1 <<= nm.mnjoin(k=self.ef2,
K=self.ef1,
m=xpal,
f=self.ef2 + ":##ef2," + self.sim + ":sim2",
i=xpal)
xpal1 <<= nm.msel(c=selpara)
xpal1 <<= nm.mcut(f=[self.ef1, self.ef2, self.sim])
else:
selpara = "$s{%s}==$s{##ef2}" % (self.ef1)
xxc = None
xxc <<= nm.mnjoin(k=self.ef2,
K=self.ef1,
m=xpal,
f=self.ef2 + ":##ef2," + self.sim + ":sim2",
i=xpal)
xxc <<= nm.msel(c=selpara)
xxc <<= nm.mcut(f=[self.ef1, self.ef2])
xpal1 <<= nm.mcut(f=[self.ef1, self.ef2, self.sim], i=xpal)
xpal1 <<= nm.mcommon(k=self.ef1 + "," + self.ef2, m=xxc, r=True)
runpal = None
kpara = "%s,%s" % (self.ef1, self.ef2)
if self.udout:
runpal <<= nm.mfsort(f=kpara, i=xpal1)
runpal <<= nm.mavg(k=kpara, f=self.sim)
runpal <<= nm.msortf(f=kpara, o=self.eo)
else:
runpal <<= nm.msortf(f=kpara, i=xpal1, o=self.eo)
runpal.run()
if self.ni and self.no:
shutil.copyfile(self.ni, self.no)
def enumerate(self, eArgs):
tf = mtemp.Mtemp()
# 最小サポートと最小サポート件数
if "minCnt" in eArgs and eArgs["minCnt"] != None:
self.minCnt = int(eArgs["minCnt"])
self.minSup = float(self.minCnt) / float(self.db.size)
else:
self.minSup = float(eArgs["minSup"])
self.minCnt = int(self.minSup * float(self.db.size) + 0.99)
# 最大サポートと最大サポート件数
self.maxCnt = None
if ("maxCnt" in eArgs
and eArgs["maxCnt"] != None) or ("maxSup" in eArgs
and eArgs["maxSup"] != None):
if "maxCnt" in eArgs and eArgs["maxCnt"] != None:
self.maxCnt = int(eArgs["maxCnt"])
self.maxSup = float(self.maxCnt) / float(self.db.size)
else:
self.maxSup = float(eArgs["maxSup"])
self.maxCnt = int(self.maxSup * float(self.db.size) + 0.99)
# 列挙パターン数上限が指定されれば、一度lcmを実行して最小サポートを得る
if "top" in eArgs and eArgs["top"] != None:
self.top = eArgs["top"]
# 列挙パターン数上限が指定されれば、一度lcmを実行して最小サポートを得る
if self.top and self.top > 0:
xxtop = tf.file()
extTake.lcmseq(type="Cf",
K=str(self.top),
i=self.file,
sup="1",
so=xxtop)
with open(xxtop, "r") as rfile:
self.minCnt = int(rfile.read().strip())
# lcm_seq出力ファイル
lcmout = tf.file()
# 頻出パターンがなかった場合、lcm出力ファイルが生成されないので
# そのときのために空ファイルを生成しておいく。
with open(lcmout, "w") as efile:
pass
# lcm_seqのパラメータ設定と実行
params = {}
if self.msgoff:
params["type"] = "CIf_"
else:
params["type"] = "CIf"
if self.maxCnt:
params["U"] = str(self.maxCnt)
if "minLen" in eArgs:
params["l"] = str(eArgs["minLen"])
if 'maxLen' in eArgs:
params["u"] = str(eArgs["maxLen"])
if 'gap' in eArgs:
params["g"] = str(eArgs["gap"])
if 'win' in eArgs:
params["G"] = str(eArgs["win"])
params["i"] = self.file
params["sup"] = str(self.minCnt)
params["o"] = lcmout
# lcm_seq実行
#MCMD::msgLog("#{run}")
if 'padding' in eArgs and eArgs[
"padding"]: # padding指定時は、0アイテムを出力しないlcm_seqを実行
extTake.lcmseq_zero(params)
else:
extTake.lcmseq(params)
# パターンのサポートを計算しCSV出力する
self.pFile = self.temp.file()
items = self.db.items
transl = self.temp.file()
extTake.lcmtrans(lcmout, "p", transl)
f = nm.mdelnull(f="pattern", i=transl)
f <<= nm.mvreplace(vf="pattern",
m=items.file,
K=items.idFN,
f=items.itemFN)
f <<= nm.msetstr(v=self.db.size, a="total")
f <<= nm.mcal(c='${count}/${total}', a="support") # サポートの計算
f <<= nm.mcut(f="pid,pattern,size,count,total,support")
f <<= nm.msortf(f="support%nr", o=self.pFile)
f.run()
if self.outtf:
# トランザクション毎に出現するシーケンスを書き出す
#MCMD::msgLog("output tid-patterns ...")
self.tFile = self.temp.file()
xxw = tf.file() #Mtemp.new.name
f = None
f <<= nm.mcut(f=self.db.idFN, i=self.db.file)
f <<= nm.muniq(k=self.db.idFN)
f <<= nm.mnumber(S=0, a="__tid", q=True)
f <<= nm.msortf(f="__tid", o=xxw)
f.run()
translt = self.temp.file()
extTake.lcmtrans(lcmout, "t", translt)
f = None
f <<= nm.msortf(f="__tid", i=translt)
f <<= nm.mjoin(k="__tid", m=xxw, f=self.db.idFN)
f <<= nm.mcut(f=self.db.idFN + ",pid")
f <<= nm.msortf(f=self.db.idFN + ",pid", o=self.tFile)
f.run()
def enumerate(self, eArgs):
pFiles = []
tFiles = []
tf = mtemp.Mtemp()
for cName, posSize in self.db.clsNameRecSize.items():
negSize = self.db.traSize - posSize
if "minGR" in eArgs:
self.minGR = eArgs["minGR"]
else:
minProb = eArgs["minProb"] if ("minProb" in eArgs) else 0.5
if "uniform" in eArgs and eArgs["uniform"] == True:
self.minGR = (minProb / (1 - minProb)) * (
self.db.clsSize - 1) # マニュアルの式(4)
else:
self.minGR = (minProb / (1 - minProb)) * (
float(negSize) / float(posSize)) # マニュアルの式(4)
# 最小サポートと最小サポート件数
# s=0.05
# s=c1:0.05,c2:0.06
# S=10
# S=c1:10,c2:15
if "minCnt" in eArgs:
if isinstance(eArgs["minCnt"], dict):
self.minPos = eArgs["minCnt"][cName]
else:
self.minPos = eArgs["minCnt"]
else:
if isinstance(eArgs["minSup"], dict):
self.minPos = int(eArgs["minSup"][cName] * float(posSize) +
0.99)
else:
self.minPos = int(eArgs["minSup"] * flost(posSize) + 0.99)
# 最大サポートと最大サポート件数
if "maxCnt" in eArgs:
if isinstance(eArgs["maxCnt"], dict):
self.maxPos = eArgs["maxCnt"][cName]
else:
self.maxPos = eArgs["maxCnt"]
elif "maxSup" in eArgs:
if isinstance(eArgs["maxSup"], dict):
self.maxPos = int(eArgs["maxSup"][cName] * float(posSize) +
0.99)
else:
self.maxPos = int(eArgs["maxSup"] * float(posSize) + 0.99)
else:
self.maxPos = None
self.sigma[cName] = self.calSigma(self.minPos, self.minGR, posSize,
negSize)
# lcmのパラメータ設定と実行
# 頻出パターンがなかった場合、lcm出力ファイルが生成されないので
# そのときのために空ファイルを生成しておいく。
lcmout = tf.file() # lcm出力ファイル
with open(lcmout, "w") as efile:
pass
runPara = {}
if self.msgoff:
runPara["type"] = eArgs["type"] + "IA_"
else:
runPara["type"] = eArgs["type"] + "IA"
#if self.maxPos: #rubyだとif @maxCntなってる（どこにも設定されてないので）動いてないはず
if self.maxPos:
runPara["U"] = self.maxPos
if "minLen" in eArgs:
runPara["l"] = str(eArgs["minLen"])
if "maxLen" in eArgs:
runPara["u"] = str(eArgs["maxLen"])
runPara["w"] = self.weightFile[cName]
runPara["i"] = self.file
runPara["sup"] = str(self.sigma[cName])
runPara["o"] = lcmout
# lcm実行
#MCMD::msgLog("#{run}")
#TAKE::run_lcm(run)
#print(self.sigma)
#print(runPara)
#MCMD::msgLog("output patterns to CSV file ...")
extTake.lcm(runPara)
pFiles.append(self.temp.file())
transle = tf.file()
extTake.lcmtrans(lcmout, "e", transle)
f = nm.mdelnull(f="pattern", i=transle)
f <<= nm.mcal(c='round(${countN},1)', a="neg")
f <<= nm.mcal(c='round(${countP}/%s,1)' % (self.posWeight[cName]),
a="pos")
f <<= nm.mdelnull(f="pattern") #いる？
f <<= nm.msetstr(v=cName, a="class")
f <<= nm.msetstr(v=posSize, a="posTotal")
f <<= nm.msetstr(v=self.minGR, a="minGR")
f <<= nm.mcut(f="class,pid,pattern,size,pos,neg,posTotal,minGR",
o=pFiles[-1])
f.run()
#s = nutil.mrecount(i=self.file)
#MCMD::msgLog("the number of contrast patterns on class `#{cName}' enumerated is #{s}")
if self.outtf:
# トランザクション毎に出現するパターンを書き出す
#MCMD::msgLog("output tid-patterns ...")
tFiles.append(self.temp.file())
xxw = tf.file()
xxw = nm.mcut(f=self.db.idFN, i=self.db.file)
xxw <<= nm.muniq(k=self.db.idFN)
xxw <<= nm.mnumber(S=0, a="__tid", q=True)
translt = self.temp.file()
extTake.lcmtrans(lcmout, "t", translt)
f = nm.mjoin(k="__tid", m=xxw, f=self.db.idFN, i=translt)
f <<= nm.msetstr(v=cName, a="class")
f <<= nm.mcut(f=self.db.idFN + ",class,pid", o=tFiles[-1])
f.run()
# クラス別のパターンとtid-pidファイルを統合して最終出力
self.pFile = self.temp.file()
self.tFile = self.temp.file()
# パターンファイル併合
xxpCat = tf.file()
f = nm.mcat(i=",".join(pFiles))
f <<= nm.msortf(f="class,pid")
f <<= nm.mnumber(s="class,pid", S=0, a="ppid", o=xxpCat)
f.run()
# パターンファイル計算
items = self.db.items
f = nm.mcut(f="class,ppid:pid,pattern,size,pos,neg,posTotal,minGR",
i=xxpCat)
f <<= nm.msetstr(v=self.db.traSize, a="total")
f <<= nm.mcal(c='${total}-${posTotal}', a="negTotal") # negのトータル件数
f <<= nm.mcal(c='${pos}/${posTotal}', a="support") # サポートの計算
f <<= nm.mcal(
c=
'if(${neg}==0,1.797693135e+308,(${pos}/${posTotal})/(${neg}/${negTotal}))',
a="growthRate")
if "uniform" in eArgs and eArgs["uniform"] == True:
f <<= nm.mcal(
c='(${pos}/${posTotal})/(${pos}/${posTotal}+(%s-1)*${neg}/${negTotal})'
% (self.db.clsSize),
a="postProb")
else:
f <<= nm.mcal(c='${pos}/(${pos}+${neg})', a="postProb")
f <<= nm.msel(c='${pos}>=%s&&${growthRate}>=${minGR}' %
(self.minPos)) # minSupとminGRによる選択
f <<= nm.mvreplace(vf="pattern",
m=items.file,
K=items.idFN,
f=items.itemFN)
f <<= nm.mcut(
f="class,pid,pattern,size,pos,neg,posTotal,negTotal,total,support,growthRate,postProb"
)
f <<= nm.mvsort(vf="pattern")
f <<= nm.msortf(f="class%nr,postProb%nr,pos%nr", o=self.pFile)
f.run()
# アイテムを包含している冗長なタクソノミを削除
if items.taxonomy:
#MCMD::msgLog("reducing redundant rules in terms of taxonomy ...")
##ここは後で
zdd = VSOP.constant(0)
dt = nm.mcut(i=self.pFile, f="pattern")
for fldVal in dt:
zdd = zdd + VSOP.itemset(fldVal[0])
zdd = self.reduceTaxo(zdd, self.db.items)
xxp1 = tf.file()
xxp2 = tf.file()
xxp3 = tf.file()
zdd.csvout(xxp1)
nm.mcut(nfni=True, f="1:pattern",
i=xxp1).mvsort(vf="pattern").msortf(f="pattern",
o=xxp2).run()
nm.msortf(f="pattern", i=self.pFile).mcommon(
k="pattern", m=xxp2).msortf(f="class%nr,postProb%nr,pos%nr",
o=xxp3).run()
shutil.move(xxp3, self.pFile)
if self.outtf:
# 列挙されたパターンを含むtraのみ選択するためのマスタ
xxp4 = nm.mcut(f="class,pid", i=self.pFile)
f = nm.mcat(i=",".join(tFiles))
f <<= nm.mjoin(k="class,pid", m=xxpCat,
f="ppid") # 全クラス統一pid(ppid)結合
f <<= nm.mcommon(k="class,ppid", K="class,pid",
m=xxp4) # 列挙されたパターンの選択
f <<= nm.mcut(f=self.db.idFN + ",class,ppid:pid")
f <<= nm.msortf(f=self.db.idFN + ",class,pid", o=self.tFile)
f.run()
def enumerate(self,eArgs):
"""
eArgsで与えられた条件で、頻出アイテム集合の列挙を実行する。
:type eArgs: dict
:type eArgs['type']: str
:type eArgs['minCnt']: int
:type eArgs['minSup']: float
:type eArgs['maxCnt']: int
:type eArgs['maxSup']: float
:type eArgs['minLen']: int
:type eArgs['maxLen']: int
:type eArgs['top']: int
:type eArgs['skipTP']: bool【default:False】
:param eArgs: 各種列挙パラメータ
:param eArgs['type']: 抽出するアイテム集合の型【'F':頻出集合, 'C':飽和集合, 'M':極大集合】
:param eArgs['minCnt']: 最小サポート(件数)
:param eArgs['minSup']: 最小サポート(確率)
:param eArgs['maxCnt']: 最大サポート(件数)
:param eArgs['maxSup']: 最大サポート(確率)
:param eArgs['minLen']: アイテム集合の最小アイテム数(件数)
:param eArgs['maxLen']: アイテム集合の最大アイテム数(件数)
:param eArgs['top']: 列挙するサポート上位件数(件数)
:param eArgs['skipTP']: トランザクションにマッチするパターン(アイテム集合)の出力を行わない。
"""
tf=mtemp.Mtemp()
self.eArgs=eArgs
self.type = eArgs["type"]
if "minCnt" in eArgs and eArgs["minCnt"] != None:
self.minCnt = int(eArgs["minCnt"])
self.minSup = float(self.minCnt) / float(self.db.traSize)
else:
self.minSup = float(eArgs["minSup"])
self.minCnt = int(self.minSup * float(self.db.traSize) + 0.99)
# 最大サポートと最大サポート件数
self.maxCnt=None
if ("maxCnt" in eArgs and eArgs["maxCnt"]!= None) or ( "maxSup" in eArgs and eArgs["maxSup"]!= None):
if "maxCnt" in eArgs and eArgs["maxCnt"]!= None:
self.maxCnt = int(eArgs["maxCnt"])
self.maxSup = float(self.maxCnt) / float(self.db.traSize)
else:
self.maxSup = float(eArgs["maxSup"])
self.maxCnt = int(self.maxSup * float(self.db.traSize) + 0.99)
params = {}
if self.msgoff:
params["type"] ="%sIf_"%(self.type)
else:
params["type"] ="%sIf"%(self.type)
if self.maxCnt :
params["U"] = str(self.maxCnt)
if "minLen" in eArgs and eArgs["minLen"] != None :
params["l"] = str(eArgs['minLen'])
if "maxLen" in eArgs and eArgs["maxLen"] != None :
params["u"] = str(eArgs['maxLen'])
# 列挙パターン数上限が指定されれば、一度lcmを実行して最小サポートを得る
if "top" in eArgs and eArgs["top"] != None :
self.top = eArgs["top"]
if self.top and self.top>0 :
xxtop = tf.file()
import copy
top_params = copy.deepcopy(params)
top_params["i"] = self.file
top_params["sup"] = "1"
top_params["K"] = str(self.top)
top_params["so"] = xxtop
import re
top_params["type"] = re.sub('_$', '', top_params["type"] )
extTake.lcm(top_params)
with open(xxtop, "r") as rfile:
self.minCnt = int(rfile.read().strip())
if self.minCnt<0 :
self.minCnt=1
self.skipTP=False
if "skipTP" in eArgs:
self.skipTP=eArgs["skipTP"]
# lcm_seq出力ファイル
lcmout = tf.file()
# 頻出パターンがなかった場合、lcm出力ファイルが生成されないので
# そのときのために空ファイルを生成しておいく。
with open(lcmout, "w") as efile:
pass
# lcm実行
params["i"] = self.file
params["sup"] = str(self.minCnt)
params["o"] = lcmout
extTake.lcm(params)
# caliculate one itemset for lift value
xxone= tf.file()
tpstr = "FIf_" if self.msgoff else "FIf"
extTake.lcm(type=tpstr,i=self.file,sup=1,o=xxone,l=1,u=1)
# パターンのサポートを計算しCSV出力する
#MCMD::msgLog("output patterns to CSV file ...")
xxp0 = tf.file()
self.pFile = self.temp.file()
items=self.db.items
trans0 = self.temp.file()
extTake.lcmtrans(lcmout,"p",trans0)
f = nm.mdelnull(i=trans0,f="pattern")
f <<= nm.mvreplace(vf="pattern",m=items.file,K=items.idFN,f=items.itemFN)
f <<= nm.msetstr(v=self.db.traSize,a="total")
f <<= nm.mcal(c='${count}/${total}',a="support")
f <<= nm.mcut(f="pid,pattern,size,count,total,support")
f <<= nm.mvsort(vf="pattern")
f <<= nm.msortf(f="pid",o=xxp0)
f.run()
# xxp0
# pid,count,total,support,pattern
# 0,13,13,1,A
# 4,6,13,0.4615384615,A B
xxp1=tf.file()
# taxonomy指定がない場合(2010/11/20追加)
if items.taxonomy==None:
shutil.move(xxp0,xxp1)
# taxonomy指定がある場合
else:
#MCMD::msgLog("reducing redundant rules in terms of taxonomy ...")
zdd=VSOP.constant(0)
fobj = nm.mcut(i=xxp0,f='pattern')
for fldVal in fobj:
zdd=zdd+VSOP.itemset(fldVal[0])
zdd=self.reduceTaxo(zdd,self.db.items)
xxz1=tf.file()
xxz2=tf.file()
zdd.csvout(xxz1)
f0=None
f0 <<= nm.mcut(nfni=True,f="1:pattern",i=xxz1)
f0 <<= nm.mvsort(vf="pattern")
f0 <<= nm.msortf(f="pattern")
f=None
f <<= nm.msortf(f="pattern",i=xxp0)
f <<= nm.mcommon(k="pattern",m=f0)
f <<= nm.msortf(f="pid",o=xxp1)
f.run()
# lift値の計算
transl = tf.file()
extTake.lcmtrans(xxone,"p",transl)
xxp2 = nm.mdelnull(i=transl,f="pattern")
xxp2 <<= nm.mvreplace(vf="pattern",m=items.file,K=items.idFN,f=items.itemFN)
xxp2 <<= nm.msortf(f="pattern")
xxp3 = nm.mcut(f="pid,pattern",i=xxp1)
xxp3 <<= nm.mtra(f="pattern",r=True)
xxp3 <<= nm.mjoin(k="pattern",m=xxp2,f="count:c1")
xxp3 <<= nm.mcal(c='ln(${c1})',a="c1ln")
xxp3 <<= nm.msum(k="pid",f="c1ln")
# p3
# pid,pattern,c1,c1ln
# 0,A,13,2.564949357
# 1,E,7,1.945910149
#おかしくなる?=>OK
f3 = nm.mjoin(k="pid",f="c1ln",i=xxp1,m=xxp3)
f3 <<= nm.mcal(c='round(exp(ln(${count})-${c1ln}+(${size}-1)*ln(${total})),0.0001)',a="lift")
f3 <<= nm.mcut(f="pid,size,count,total,support,lift,pattern")
f3 <<= nm.msortf(f="support%nr",o=self.pFile)
f3.run()
#self.size = mrecount.mrecount(i=self.file)
#MCMD::msgLog("the number of patterns enumerated is #{@size}")
if not self.skipTP:
# トランザクション毎に出現するシーケンスを書き出す
#MCMD::msgLog("output tid-patterns ...")
self.tFile = self.temp.file()
xxw3i = tf.file()
extTake.lcmtrans(lcmout,"t",xxw3i)
xxw1 = nm.mcut(f=self.db.idFN,i=self.db.file).muniq(k=self.db.idFN).mnumber(S=0,a="__tid",q=True).msortf(f="__tid")
xxw2 = nm.mcut(f="pid",i=self.pFile)
xxw3 = nm.mcommon(k="pid",i=xxw3i,m=xxw2).mjoin(k="__tid",m=xxw1,f=self.db.idFN).mcut(f=self.db.idFN+",pid",o=self.tFile)
xxw3.run()
def __mkTree(iFile, oFile):
temp = mtemp.Mtemp()
xxbase0 = temp.file()
xxbase1 = temp.file()
xxiFile2 = temp.file()
xxcheck = temp.file()
"""
# #{iFile}
# key,nam%0,keyNum,num,nv,nc
# #2_1,#1_1,4,1,6,1
# #2_1,#1_2,4,2,0.9999999996,1
"""
# keyNumとnum項目のuniqリストを作り、お互いの包含関係でrootノードとleafノードを識別する。
f0 = nm.mcut(f="keyNum,num", i=iFile) #{xxiFile1}
fk = f0.mcut(f="keyNum").muniq(k="keyNum") #{xxkey}
fn = f0.mcut(f="num").muniq(k="num") #{xxnum}
# root nodesの選択
fr = nm.mcommon(k="keyNum", K="num", m=fn, i=fk,
r=True).mcut(f="keyNum:node0", o=xxbase0) #{xxbase[0]}
# leaf nodesの選択
fl = nm.mcommon(k="num", K="keyNum", m=fk, i=fn,
r=True).mcut(f="num") #{xxleaf}
# leaf nodeの構造を知る必要はないので入力ファイルのnodeからleafを除外
f = nm.mcommon(k="num", m=fl, r=True, i=f0, o=xxiFile2)
nm.runs([f, fr])
def _xnjoin(inf, outf, mfile, check, no):
f = nm.mnjoin(k="node%d" % (no),
K="keyNum",
m=mfile,
n=True,
f="num:node%d" % (no + 1),
i=inf,
o=outf)
fc = nm.mdelnull(i=f, f="node%d" % (no + 1), o=check)
return fc
i = 0
depth = None
inf = xxbase0
outf = xxbase1
'''
# root nodesファイルから親子関係noodeを次々にjoinしていく
# xxbase0 : root nodes
# node0%0
# 3
# 4
# xxbase1
# node0%0,node1
# 3,
# 4,1
# 4,2
# xxbase2
# node0,node1%0,node2
# 3,,
# 4,1,
# 4,2,
# join項目(node2)の非null項目が0件で終了
'''
while True:
_xnjoin(inf, outf, xxiFile2, xxcheck, i).run()
size = mrecount(i=xxcheck)
if size == 0:
nm.msortf(f="*", i=outf, o=oFile).run()
depth = i + 1
break
# swap f_name
xxtmp = outf
outf = inf
inf = xxtmp
i += 1
return depth
def mgv(ei,
ef,
ev=None,
ec=None,
el=None,
ed=None,
ni=None,
nf=None,
nv=None,
nc=None,
nl=None,
nw=1,
tp="flat",
k=None,
o=None,
d=False,
clusterLabel=False,
noiso=False,
normalize=False,
normalizeEdge=False,
normalizeNode=False):
# arg check
# ei : str (filename)
# ef : str | list (fldname size=2)
# ev : str | None (fldname)
# ec : str | None (fldname)
# el : str | list | None (fldname no limit )
# ed : str | None (fldname)
# ni : str | None (filename)
# nf : str | None (fldname)
# nv : str | None (fldname)
# nc : str | None (fldname)
# nl : str | list | None (fldname no limit )
# tp : str (flat|nest default:flat )
# k : str | None (fldname)
# o : str (filename)
# d : bool | None
# clusterLabel : bool | None
# noiso : bool | None
# ei
if not (isinstance(ei, str)):
raise TypeError("ei= unsupport " + str(type(ei)))
# ef
if isinstance(ef, str):
ef = ef.split(',')
elif not isinstance(ef, list):
raise TypeError("ef= unsupport " + str(type(ef)))
if len(ef) < 2:
raise TypeError("ef size == 2 ")
elif len(ef) > 2:
sys.stderr.write('warning : ef size == 2 ')
# k
if not (isinstance(k, str) or k == None):
raise TypeError("k= unsupport " + str(type(k)))
# ev
if not (isinstance(ev, str) or ev == None):
raise TypeError("ev= unsupport " + str(type(ev)))
# ec
if not (isinstance(ec, str) or ec == None):
raise TypeError("ec= unsupport " + str(type(ec)))
# el
if isinstance(el, str):
el = el.split(',')
if len(el) == 1 and el[0] == '':
el = None
elif not (isinstance(el, list) or el == None):
raise TypeError("el= unsupport " + str(type(el)))
# ed
if not (isinstance(ed, str) or ed == None):
raise TypeError("ed= unsupport " + str(type(ed)))
# ni
if not (isinstance(ni, str) or ni == None):
raise TypeError("ni= unsupport " + str(type(ni)))
# nf
if not (isinstance(nf, str) or nf == None):
raise TypeError("nf= unsupport " + str(type(nf)))
# nv
if not (isinstance(nv, str) or nv == None):
raise TypeError("nv= unsupport " + str(type(nv)))
# nc
if not (isinstance(nc, str) or nc == None):
raise TypeError("nc= unsupport " + str(type(nc)))
# nl
if isinstance(nl, str):
nl = nl.split(',')
if len(nl) == 1 and nl[0] == '':
nl = None
elif not (isinstance(nl, list) or nl == None):
raise TypeError("nl= unsupport " + str(type(nl)))
# tp
if tp == None:
tp = "flat"
elif not isinstance(tp, str):
raise TypeError("tp= unsupport " + str(type(tp)))
# o
if isinstance(o, str):
oFile = o
else:
raise TypeError("o= unsupport " + str(type(o)))
# d
if d == None:
d = False
if not isinstance(d, bool):
raise TypeError("d= unsupport " + str(type(d)))
# clusterLabel
if clusterLabel == None:
clusterLabel = False
if not isinstance(clusterLabel, bool):
raise TypeError("clusterLabel= unsupport " + str(type(clusterLabel)))
# noiso
if noiso == None:
noiso = False
if not isinstance(noiso, bool):
raise TypeError("noiso= unsupport " + str(type(noiso)))
# noiso
if normalize == None:
normalize = False
if not isinstance(normalize, bool):
raise TypeError("noiso= unsupport " + str(type(normalize)))
if normalizeEdge == None:
normalizeEdge = False
if not isinstance(normalizeEdge, bool):
raise TypeError("noiso= unsupport " + str(type(normalizeEdge)))
if normalizeNode == None:
normalizeNode = False
if not isinstance(normalizeNode, bool):
raise TypeError("noiso= unsupport " + str(type(normalizeNode)))
if normalize:
normalizeEdge = True
normalizeNode = True
temp = mtemp.Mtemp()
xxni = temp.file()
xxei = temp.file()
xxmap = temp.file()
xxnode = temp.file()
xxedge = temp.file()
xxdotNode = temp.file()
xxdotEdge = temp.file()
xxtree = temp.file()
mkDir(xxdotNode)
mkDir(xxdotEdge)
if d:
directedStr = "edge []"
else:
directedStr = "edge [dir=none]"
# key追加 (cluster用)
if not k:
if ni:
nm.msetstr(v="", a="#key", i=ni, o=xxni).run()
ni = xxni
nm.msetstr(v="", a="#key", i=ei, o=xxei).run()
ei = xxei
k = "#key"
#efs = ef.split(",")
ef1 = ef[0]
ef2 = ef[1]
__mkMap(k, nf, ni, ef1, ef2, ei, xxmap)
__mkNode(k, nf, nl, nv, nc, ni, ef1, ef2, ei, noiso, normalizeNode, xxmap,
xxnode)
__mkEdge(k, ef1, ef2, el, ec, ed, ev, ei, normalizeEdge, xxmap, xxedge)
# dot用のnodeとedgeデータをcluster別ファイルとして生成
__dotNode(xxnode, nw, tp, clusterLabel, xxdotNode)
__dotEdge(xxedge, xxdotEdge)
depth = None
if tp == "flat":
depth = __mkFlat(xxnode, xxtree) # mgvとおなじ
elif tp == "nest":
# tree構造の処理
# クラスタのみtree構造に格納する
depth = __mkTree(xxnode, xxtree) # mgvとおなじ
else:
raise TypeError("unsupport type " + tp)
xxdotTree = temp.file()
header = '''digraph G {{
{directedStr}
'''.format(directedStr=directedStr)
footer = "}\n"
__dotTree(xxtree, depth, header, footer, xxdotTree) # mgvとおなじ
__replace(xxdotTree, xxdotNode, xxdotEdge, clusterLabel, o)
def __init__(self, iFile, idFN, timeFN, itemFN, padding, clsFN=None):
self.file = None # トランザクションファイル名
self.idFN = None # トランザクションID項目名(String)
self.timeFN = None # 時間項目名(String)
self.itemFN = None # アイテム集合項目名(String)
self.clsFN = None # クラス項目名(String)
self.size = None # トランザクションサイズ(Num)
self.items = None # Itemsクラス
self.taxonomy = None # 階層分類クラス
self.clsNameRecSize = None # クラス別件数
self.clsSize = None # クラス数
self.cFile = None # クラスファイル
self.temp = mtemp.Mtemp()
self.iFile = iFile # 入力ファイル
self.iPath = os.path.abspath(self.iFile) # フルパス
self.idFN = idFN # トランザクションID項目名
self.timeFN = timeFN # 時間項目名
self.itemFN = itemFN # アイテム項目名
self.file = self.temp.file() # 出力ファイル名
self.padding = padding # 時系列パディング
# padding指定の場合は、asciiコードの先頭文字列を挿入
f = None
if self.padding:
f <<= nm.mcut(f=self.idFN + "," + self.timeFN + "," + self.itemFN,
i=self.iFile)
f <<= nm.msortf(f=self.idFN + "," + self.timeFN + "%n," +
self.itemFN)
f <<= nm.muniq(k=self.idFN + "," + self.timeFN + "," + self.itemFN)
f <<= nm.mpadding(k=self.idFN,
f=self.timeFN + "%n",
v="!",
o=self.file)
else:
f <<= nm.mcut(f=self.idFN + "," + self.timeFN + "," + self.itemFN,
i=self.iFile)
f <<= nm.msortf(f=self.idFN + "," + self.timeFN + "%n," +
self.itemFN)
f <<= nm.muniq(k=self.idFN + "," + self.timeFN + "," + self.itemFN,
o=self.file)
f.run()
# レコード数の計算
#@recCnt = MCMD::mrecount("i=#{@file}")
# トランザクション数の計算
xx1 = nm.mcut(f=self.idFN, i=self.file).muniq(k=self.idFN).mcount(
a="__cnt").mcut(f='__cnt').run()
self.size = int(xx1[0][0])
# トランザクションデータからアイテムオブジェクトを生成
if self.padding: #同じ？
# paddingの場合は、特殊アイテム(!)を0番とし、出力を制御する。
self.items = items.Items(self.file, self.itemFN)
else:
self.items = items.Items(self.file, self.itemFN)
if clsFN:
self.clsFN = clsFN
self.cFile = self.temp.file()
fpara_c = "%s,%s" % (self.idFN, self.clsFN)
nm.mcut(f=fpara_c, i=self.iFile).muniq(k=fpara_c,
o=self.cFile).run()
# 文字列としてのクラス別件数配列を数値配列に変換する
self.clsSize = 0
self.clsNames = []
self.clsNameRecSize = {}
for vv in nm.mcut(f=self.clsFN, i=self.cFile).mcount(k=self.clsFN,
a='count'):
self.clsNames.append(vv[0])
self.clsNameRecSize[vv[0]] = int(vv[1])
self.clsSize += 1
def mnetpie(ei,
ni,
ef,
nf,
o,
nodeSizeFld=None,
nodeTipsFld=None,
nodeColorFld=None,
edgeWidthFld=None,
edgeColorFld=None,
pieDataFld=None,
pieTipsFld=None,
picFld=None,
undirect=False,
offline=False):
#ei:edge file
#ef:egfile
if type(ef) is str:
ef = ef.split(',')
if len(ef) != 2:
raise Exception("ef= takes just two field names")
if not ((pieDataFld == None and pieTipsFld == None) or
(pieDataFld != None and pieTipsFld != None)):
raise Exception(
"pieDataFld= pieTipsFld= are necessary at the same time")
if picFld != None and pieDataFld != None:
raise Exception(
"picFld= cannot be specified with pieDataFld= pieTipsFld=")
if nodeColorFld != None:
if picFld != None or pieDataFld != None or pieTipsFld != None:
raise Exception(
"nodeColorFld= cannot be specified with pieDataFld= pieTipsFld= picFld="
)
if pieDataFld != None and pieTipsFld != None:
caseNo = 1
elif picFld != None:
caseNo = 2
else:
caseNo = 0
tempW = mtemp.Mtemp()
xxnode = tempW.file()
nodefld = []
nodedmy1 = []
nodedmy2 = []
nodefld.append("%s:node" % (nf))
if nodeSizeFld != None:
nodefld.append("%s:nodesize" % (nodeSizeFld))
else:
nodedmy1.append("nodesize")
nodedmy2.append("50")
if nodeTipsFld != None:
nodefld.append("%s:nodeT" % (nodeTipFld))
else:
nodedmy1.append("nodeT")
nodedmy2.append("")
if nodeColorFld != None:
nodefld.append("%s:nodeClr" % (nodeColorFld))
else:
nodedmy1.append("nodeClr")
nodedmy2.append("skyblue")
if caseNo == 1:
nodefld.append("%s:pieD" % (pieDataFld))
nodefld.append("%s:pieT" % (pieTipsFld))
elif caseNo == 2:
nodefld.append("%s:pic" % (picFld))
else:
nodedmy1.append("pic")
nodedmy2.append("")
f1 = None
f1 <<= nm.mcut(i=ni, f=nodefld)
if len(nodedmy1) != 0:
f1 <<= nm.msetstr(a=nodedmy1, v=nodedmy2)
if caseNo == 1:
f1 <<= nm.mshare(k="node", f="pieD:pieDS")
f1 <<= nm.mnumber(k="node", a="nodeid", B=True)
f2 = nm.muniq(k="pieT", i=f1)
f2 <<= nm.mnumber(q=True, a="pieTno")
f2 <<= nm.mjoin(k="pieT", f="pieTno", i=f1).iredirect("m")
f2 <<= nm.msortf(f="nodeid%n,pieTno%n", o=xxnode)
else:
f2 = nm.mnumber(a="nodeid%n", q=True, i=f1, o=xxnode)
f2.run()
xxedge = tempW.file()
# MAKE EDGE DATA
edgefld = []
edgedmy1 = []
edgedmy2 = []
edgefld.append("%s:edgeS" % (ef[0]))
edgefld.append("%s:edgeE" % (ef[1]))
if edgeWidthFld != None:
edgefld.append("%s:edgesize" % (edgeWidthFld))
else:
edgedmy1.append("edgesize")
edgedmy2.append("1")
if edgeColorFld != None:
edgefld.append("%s:edgecolor" % (edgeColorFld))
else:
edgedmy1.append("edgecolor")
edgedmy2.append("black")
f3 = None
f3 <<= nm.mcut(i=ei, f=edgefld)
if len(edgedmy1) != 0:
f3 <<= nm.msetstr(a=edgedmy1, v=edgedmy2)
f3 <<= nm.mnumber(a="preNo", q=True)
f3 <<= nm.mbest(k="edgeS,edgeE", s="preNo%nr")
f3 <<= nm.mnumber(s="preNo%n", a="edgeID")
f3 <<= nm.mjoin(k="edgeS", K="node", f="nodeid:edgeSid", m=xxnode)
f3 <<= nm.mjoin(k="edgeE", K="node", f="nodeid:edgeEid", m=xxnode)
#双方向チェック一応
f4 = None
f4 <<= nm.mfsort(i=f3, f="edgeS,edgeE")
f4 <<= nm.mcount(k="edgeS,edgeE", a="edgecnt")
f4 <<= nm.mselnum(c="[2,]", f="edgecnt")
f4 <<= nm.msetstr(a="biflg", v=1)
f4 <<= nm.mjoin(k="edgeID", f="biflg", n=True, i=f3).iredirect("m")
f4 <<= nm.msortf(f="edgeID%n", o=xxedge)
f4.run()
gdata = "{\"nodes\":["
if caseNo == 1:
nodedatastk = []
nodedatas = ""
for val, top, bot in nm.readcsv(xxnode).getline(k="nodeid",
otype='dict',
q=True):
name = val["node"]
r = val["nodesize"]
title = val["nodeT"]
if top:
nodedatas = "{\"name\":\"%s\",\"title\":\"%s\",\"r\":%s,\"node\":[" % (
name, title, r)
pieTno = val["pieTno"]
pieT = val["pieT"]
pieDS = val["pieDS"]
nodedatas += "{\"group\":%s,\"color\":%s,\"value\":%s,\"title\":\"%s\"}" % (
pieTno, pieDS, pieDS, pieT)
if bot:
nodedatas += "]}"
nodedatastk.append(nodedatas)
nodedatas = ""
else:
nodedatas += ","
gdata += ",".join(nodedatastk)
else:
nodedatastk = []
for val in nm.readcsv(xxnode).getline(otype='dict'):
name = val["node"]
r = val["nodesize"]
title = val["nodeT"]
pic = val["pic"]
nclr = val["nodeClr"]
nodedatas = "{\"name\":\"%s\",\"title\":\"%s\",\"pic\":\"%s\",\"color\":\"%s\",\"r\":%s}" % (
name, title, pic, nclr, r)
nodedatastk.append(nodedatas)
gdata += ",".join(nodedatastk)
gdata += "],\"links\": ["
edgedatastk = []
for val in nm.readcsv(xxedge).getline(otype='dict'):
es = val["edgeSid"]
et = val["edgeEid"]
esize = val["edgesize"]
ecolor = val["edgecolor"]
edgedatas = "{\"source\":%s,\"target\":%s,\"length\":500,\"ewidth\":%s,\"color\":\"%s\"}" % (
es, et, esize, ecolor)
edgedatastk.append(edgedatas)
gdata += ','.join(edgedatastk)
gdata += "]}"
direct = ".attr('marker-end','url(#arrowhead)')"
if undirect:
direct = ""
nodeTemplate = '''
node
.append("circle")
.attr("r",function(d){return d.r/4;})
.attr("fill", function(d){return d.color;})
.append("title")
.text(function(d){return d.title;})
'''
nodemakeTemplate = '''
for(var i=0 ; i< graph.nodes.length;i++){
graph.nodes[i].id = i
}
'''
if pieDataFld != None:
nodeTemplate = '''
node.selectAll("path")
.data( function(d, i){
return pie(d.node);
})
.enter()
.append("svg:path")
.attr("d", arc)
.attr("fill", function(d, i) {
return color(d.data.group);
})
.append("title")
.text(function(d){{return d.data.title;}})
node.append("circle")
.attr("r",function(d){{return d.r/4;}})
.attr({
'fill': 'white'
})
.append("title")
.text(function(d){{return d.title;}});
'''
nodemakeTemplate = '''
for(var i=0 ; i< graph.nodes.length;i++){
var r = graph.nodes[i].r
for(var j=0 ; j< graph.nodes[i].node.length;j++){
graph.nodes[i].node[j]['r'] = r
}
graph.nodes[i].id = i
}
'''
elif picFld != None:
nodeTemplate = '''
node
.append("image")
.attr("height",function(d){return d.r;})
.attr("width",function(d){return d.r;})
.attr("x",function(d){return -1 * d.r/2; })
.attr("y",function(d){return -1 * d.r/2; })
.attr("xlink:href",function(d){return d.pic; })
.append("title")
.text(function(d){return d.title;})
'''
d3js_str = "<script type='text/javascript' src='http://d3js.org/d3.v3.min.js'></script>"
if offline:
d3js_str = "<script>%s<script>" % (vjs.ViewJs.d3jsMin())
outTemplate = '''
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
{d3js_str}
<style></style>
</head>
<body>
<script type="text/javascript">
var graph = {gdata} ;
var width = 4000,
height = 3000;
var color = d3.scale.category10();
{nodemakeTemplate};
for(var i=0 ; i< graph.links.length;i++){{
graph.links[i].id = i
}}
var pie = d3.layout.pie()
.sort(null)
.value(function(d) {{ return d.value; }});
var arc = d3.svg.arc()
.outerRadius( function(d){{ return d.data.r ; }})
.innerRadius( function(d){{ return d.data.r/2 ; }} );
var svg = d3.select("body").append("svg")
.attr("width", width)
.attr("height", height);
d3.select("svg").append('defs').append('marker')
.attr({{'id':'arrowhead',
'viewBox':'-0 -5 10 10',
'refX':30,
'refY':0,
'orient':'auto-start-reverse',
'markerWidth':5,
'markerHeight':5,
'xoverflow':'visible'}})
.append('path')
.attr('d', 'M 0,-5 L 10 ,0 L 0,5')
.attr('fill', '#999')
.style('stroke','none');
var g = svg.append("g");
var node = g.selectAll(".node");
var link = g.selectAll(".link");
nodes = graph.nodes
links = graph.links
var force =
d3.layout.force()
.linkDistance(200)
.linkStrength(3.5)
.charge(-3500)
.gravity(0.1)
.friction(0.95)
.size([width, height])
.on("tick", function() {{
link
.attr("x1", function(d) {{ return d.source.x; }})
.attr("y1", function(d) {{ return d.source.y; }})
.attr("x2", function(d) {{ return d.target.x; }})
.attr("y2", function(d) {{ return d.target.y; }});
node
.attr("x", function(d) {{ return d.x; }})
.attr("y", function(d) {{ return d.y; }})
.attr("transform", function(d) {{ return "translate(" + d.x + "," + d.y + ")"}});
}});
node = node.data(nodes, function( d ) {{ return d.id; }} );
link = link.data(links, function( d ) {{ return d.id; }} );
link
.enter()
.append("line")
.attr("class", "link")
.style("stroke", function( d ) {{ return d.color; }} )
.style("stroke-width", function( d ) {{ return d.ewidth; }})
{direct}
node
.enter()
.append("g")
.attr("class", "node")
.style({{}})
.call(force.drag)
.on("contextmenu", function(nd) {{
d3.event.preventDefault();
force.stop()
nodes.splice( nd.index, 1 );
links = links.filter(function(nl) {{
return nl.source.index != nd.index && nl.target.index != nd.index;
}});
node = node.data(nodes, function( d ) {{ return d.id; }} );
node.exit().remove();
link = link.data( links, function( d ) {{ return d.id; }} );
link.exit().remove();
force.nodes(nodes)
.links(links)
.start();
}});
{nodeTemplate}
node
.append("text")
.attr("text-anchor", "middle")
.style("stroke", "black")
.text(function(d) {{ return d.name; }});
force.nodes(nodes)
.links(links)
.start();
</script>
</body>
</html>
'''.format(d3js_str=d3js_str,
gdata=gdata,
nodemakeTemplate=nodemakeTemplate,
direct=direct,
nodeTemplate=nodeTemplate)
html = sys.stdout
if not o == None:
html = open(o, "w")
html.write(outTemplate)
if not o == None:
html.close()
def run(self):
temp = mtemp.Mtemp()
### mtra2gc
xxsimgN = temp.file()
xxsimgE = temp.file()
xxsimgE0 = temp.file()
param = {}
param["i"] = self.iFile
if self.idFN:
param["tid"] = self.idFN
if self.itemFN:
param["item"] = self.itemFN
if self.sp1:
param["s"] = self.sp1
if self.sp2:
param["S"] = self.sp2
#####################
# 異なる向きのconfidenceを列挙するためにsim=C th=0として双方向列挙しておく
# 出力データは倍になるが、mfriendsで-directedとすることで元が取れている
param["sim"] = "C"
param["th"] = "0"
param["node_support"] = True
if self.numtp:
param["num"] = True
param["no"] = xxsimgN
param["eo"] = xxsimgE0
nt.mtra2gc(**param).run()
f = nm.readcsv(xxsimgE0)
for i in range(self.filterSize):
f <<= nm.mselnum(f=self.filter[i],
c="[%s,%s]" % (self.lb[i], self.ub[i]))
f <<= nm.writecsv(xxsimgE)
f.run()
### mfrirends
xxfriends = temp.file()
xxfriendE = temp.file()
xxw = temp.file()
xxf = temp.file()
xxff = temp.file()
xxor = temp.file()
if not os.path.isdir(xxfriends):
os.makedirs(xxfriends)
col = [["FF000080", "FF888880"], ["0000FF80", "8888FF80"],
["00FF0080", "88FF8880"]]
for i in range(len(self.sim)):
paramf = {}
paramf["ei"] = xxsimgE
paramf["ni"] = xxsimgN
paramf["ef"] = "node1,node2"
paramf["nf"] = "node"
paramf["eo"] = xxfriendE
paramf["no"] = xxfriends + "/n_" + str(i)
paramf["sim"] = self.sim[i]
paramf["dir"] = self.dir[i]
paramf["rank"] = self.rank[i]
paramf["directed"] = True
nt.mfriends(**paramf).run()
frec2 = nm.mfsort(f="node1,node2", i=xxfriendE)
frec2 <<= nm.msummary(k="node1,node2",
f=self.sim[i],
c="count,mean")
frec2 <<= nm.mselstr(f="count", v=2)
# node1%0,node2%1,fld,count,mean
# a,b,support,2,0.1818181818
# a,d,support,2,0.1818181818
f = nm.mjoin(k="node1,node2",
K="node1,node2",
m=frec2,
f="mean:s1",
n=True,
i=xxfriendE)
f <<= nm.mjoin(k="node2,node1",
K="node1,node2",
m=frec2,
f="mean:s2",
n=True)
# 1) xxrecs2でsimをjoinできない(s1,s2共にnull)ということは、それは片方向枝なので"F"をつける
# 2) 双方向枝a->b,b->aのうちa->bのみ(s1がnullでない)に"W"の印をつける。
# 3) それ以外の枝は"D"として削除
f <<= nm.mcal(
c='if(isnull($s{s1}),if(isnull($s{s2}),\"F\",\"D\"),\"W\")',
a="dir")
f <<= nm.mselstr(f="dir", v="D", r=True)
f <<= nm.mcal(c='if($s{dir}==\"W\",$s{s1},$s{%s})' % (self.sim[i]),
a="sim")
f <<= nm.mchgstr(f="dir:color",
c='W:%s,F:%s' % (col[i][0], col[i][1]),
A=True)
f <<= nm.msetstr(v=[self.sim[i], str(i)], a="simType,simPriority")
f <<= nm.mcut(f="simType,simPriority,node1,node2,sim,dir,color",
o=xxfriends + "/e_" + str(i))
f.run()
# node1%1,node2%0,simType,sim,dir,color
# b,a,jaccard,0.3333333333,F,8888FF
# j,c,jaccard,0.3333333333,F,8888FF
# b,d,jaccard,0.3333333333,F,8888FF
# a,e,jaccard,0.5,W,0000FF
# d,e,jaccard,0.5,W,0000FF
# rule fileの出力
if self.orFile:
mmm = nm.mcat(i=xxfriends + "/e_*").muniq(k="node1,node2")
nm.mcommon(k="node1,node2", i=xxsimgE, m=mmm, o=self.orFile).run()
# マルチ枝の単一化(W優先,パラメータ位置優先)
if self.prune:
"""
# 双方向と片方向に分割
nm.mcat(i=xxfriends+"/e_*").mselstr(f="dir",v="W",o=xxw,u=xxf).run()
# 片方向のみの枝を選択
f = nm.mcommon(k="node1,node2",K="node1,node2",r=True,m=xxw,i=xxf)
f <<= nm.mcommon(k="node1,node2",K="node2,node1",r=True,m=xxw,o=xxff)
f.run()
f = nm.mcat(i=xxw+","+xxff).mbest(k="node1,node2",s="dir%r,simPriority%n",o=self.oeFile).run()
"""
#これだめ
fo = nm.mcat(i=xxfriends + "/e_*").mselstr(f="dir", v="W")
fu = fo.direction("u") # これは再考
fu <<= nm.mcommon(k="node1,node2", K="node1,node2", r=True, m=fo)
fu <<= nm.mcommon(k="node1,node2", K="node2,node1", r=True, m=fo)
#f = nm.m2cat()
f = nm.mbest(i=[fo, fu],
k="node1,node2",
s="dir%r,simPriority%n",
o=self.oeFile)
f.run()
else:
nm.mcat(i=xxfriends + "/e_*", o=self.oeFile).run()
nm.mcat(i=xxfriends + "/n_0", o=self.onFile).run()