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humanities
gargantext
Commits
3090732a
Commit
3090732a
authored
Nov 10, 2014
by
Administrator
Browse files
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Plain Diff
[FEATURE] CHART CORPUS OK, need to adapt first and last date of graphs.
parent
c819f020
Changes
3
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Showing
3 changed files
with
395 additions
and
84 deletions
+395
-84
urls.py
gargantext_web/urls.py
+1
-1
views.py
gargantext_web/views.py
+33
-80
corpus.html
templates/corpus.html
+361
-3
No files found.
gargantext_web/urls.py
View file @
3090732a
...
...
@@ -33,7 +33,7 @@ urlpatterns = patterns('',
url
(
r'^exploration$'
,
exploration
),
url
(
r'^data.csv$'
,
send_csv
),
url
(
r'^
chart/corpus/(\d+)/
data.csv$'
,
send_csv
),
url
(
r'^graph.json$'
,
send_graph
),
)
...
...
gargantext_web/views.py
View file @
3090732a
...
...
@@ -268,90 +268,44 @@ def corpus(request, project_id, corpus_id):
project
=
Node
.
objects
.
get
(
id
=
project_id
)
corpus
=
Node
.
objects
.
get
(
id
=
corpus_id
)
#print(Document.objects.filter(corpus=c_id, user=request.user.pk).query)
documents
=
corpus
.
children
.
all
()
number
=
corpus
.
children
.
count
()
#documents = corpus.children.all()
#number = corpus.children.count()
# try:
# sources = defaultdict(int)
# for document in documents.all():
# sources[document.metadata['journal']] += 1
#
# sources_donut = []
#
# for source in sources.keys():
# source_count = dict()
# source_count['count'] = source['count']
# try:
# source_count['part'] = round(source_count['count'] * 100 / number)
# except:
# source_count['part'] = None
# source_count['source'] = source['source']
# sources_donut.append(source_count)
# except:
# sources_donut = []
try
:
sources
=
defaultdict
(
int
)
for
document
in
documents
.
all
():
sources
[
document
.
metadata
[
'journal'
]]
+=
1
sources_donut
=
[]
for
source
in
sources
.
keys
():
source_count
=
dict
()
source_count
[
'count'
]
=
source
[
'count'
]
try
:
source_count
[
'part'
]
=
round
(
source_count
[
'count'
]
*
100
/
number
)
except
:
source_count
[
'part'
]
=
None
source_count
[
'source'
]
=
source
[
'source'
]
sources_donut
.
append
(
source_count
)
except
:
sources_donut
=
[]
try
:
histo
=
[
{
'to_char'
:
2000
,
'count'
:
13
},
{
'to_char'
:
2001
,
'count'
:
20
},
{
'to_char'
:
2002
,
'count'
:
5
},
{
'to_char'
:
2003
,
'count'
:
130
},
{
'to_char'
:
2004
,
'count'
:
300
},
]
first
=
parse
(
documents
.
first
()
.
metadata
[
'publication_date'
])
last
=
parse
(
documents
.
last
()
.
metadata
[
'publication_date'
])
duree
=
first
-
last
if
duree
.
days
>
365
:
date_format
=
'YYYY'
date_form
=
'years'
for
document
in
documents
:
pass
elif
duree
.
days
>
60
:
date_format
=
'YYYY-MM'
date_form
=
'months'
else
:
date_format
=
'YYYY-MM-DD'
date_form
=
'days'
try
:
dates
=
dict
()
except
:
pass
# for e in date_range('1990-01', '1992-02', format=date_form):
# print(e)
# if date_format = 'YYYY':
# while True:
# if d -histo.append(d)
# for d in dates:
# histo.append(d)
except
:
histo
=
[
{
'to_char'
:
2000
,
'count'
:
13
},
{
'to_char'
:
2001
,
'count'
:
20
},
{
'to_char'
:
2002
,
'count'
:
5
},
{
'to_char'
:
2003
,
'count'
:
130
},
{
'to_char'
:
2004
,
'count'
:
300
},
]
#histo = None
chart
=
dict
()
chart
[
'first'
]
=
parse
(
corpus
.
children
.
first
()
.
metadata
[
'publication_date'
])
.
strftime
(
"
%
Y,
%
m,
%
d"
)
chart
[
'last'
]
=
parse
(
corpus
.
children
.
last
()
.
metadata
[
'publication_date'
])
.
strftime
(
"
%
Y,
%
m,
%
d"
)
print
(
chart
)
except
Exception
as
error
:
print
(
error
)
html
=
t
.
render
(
Context
({
\
'user'
:
user
,
\
'date'
:
date
,
\
'project'
:
project
,
\
'corpus'
:
corpus
,
\
'documents'
:
documents
,
\
'number'
:
number
,
\
'dates'
:
histo
,
\
#
'documents': documents,\
#
'number' : number,\
'dates'
:
chart
,
\
}))
return
HttpResponse
(
html
)
...
...
@@ -416,7 +370,7 @@ def explorer_chart(request):
import
csv
from
django.db
import
connection
def
send_csv
(
request
):
def
send_csv
(
request
,
corpus_id
):
'''
Create the HttpResponse object with the appropriate CSV header.
'''
...
...
@@ -424,8 +378,6 @@ def send_csv(request):
response
[
'Content-Disposition'
]
=
'attachment; filename="data.csv"'
writer
=
csv
.
writer
(
response
)
#writer = csv.writer(response, delimiter=',', quotechar=' ', quoting=csv.QUOTE_NONE)
cursor
=
connection
.
cursor
()
cursor
.
execute
(
"""
...
...
@@ -442,7 +394,7 @@ def send_csv(request):
day, month, year
ORDER BY
year, month, day ASC
"""
,
[
45044
])
"""
,
[
corpus_id
])
writer
.
writerow
([
'date'
,
'volume'
])
...
...
@@ -451,6 +403,7 @@ def send_csv(request):
if
row
is
None
:
break
writer
.
writerow
([
row
[
0
]
+
'/'
+
row
[
1
]
+
'/'
+
row
[
2
]
,
str
(
row
[
3
])
])
#dates['last']['day'] = documents.last().metadata['publication_day'])
cursor
.
close
()
...
...
templates/corpus.html
View file @
3090732a
...
...
@@ -52,7 +52,7 @@
<div
class=
"row"
>
<div
id=
"monthly-move-chart"
>
<strong>
Title
</strong>
(Blue Line:
Avg Index, Green Line: Index Fluctuation
)
<strong>
Title
</strong>
(Blue Line:
Publications by months, Green Line: Zoomable publications
)
<a
class=
"reset"
href=
"javascript:volumeChart.filterAll();dc.redrawAll();"
style=
"display: none;"
>
reset
</a>
<div
class=
"clearfix"
></div>
...
...
@@ -65,7 +65,7 @@
</div>
</div>
<a
class=
"btn btn-primary btn-lg"
role=
"button"
href=
"/data.csv"
>
Save
</a></p>
<a
class=
"btn btn-primary btn-lg"
role=
"button"
href=
"/
chart/corpus/{{ corpus.id }}/
data.csv"
>
Save
</a></p>
<div
class=
"container"
>
...
...
@@ -117,8 +117,366 @@
<script
src=
"{% static "
js
/
charts
/
jquery-latest
.
js
"
%}"
></script>
<script
src=
"{% static "
js
/
charts
/
bootstrap
.
min
.
js
"
%}"
></script>
<script
src=
"{% static "
js
/
d3
/
DC
.
js
"%}"
></script>
<script>
// var gainOrLossChart = dc.pieChart("#gain-loss-chart");
// var fluctuationChart = dc.barChart("#fluctuation-chart");
// var quarterChart = dc.pieChart("#quarter-chart");
// var dayOfWeekChart = dc.rowChart("#day-of-week-chart");
var
moveChart
=
dc
.
compositeChart
(
"#monthly-move-chart"
);
var
volumeChart
=
dc
.
barChart
(
"#monthly-volume-chart"
);
// var yearlyBubbleChart = dc.bubbleChart("#yearly-bubble-chart");
// set dc.js version in title
d3
.
selectAll
(
"#version"
).
text
(
dc
.
version
);
// load data from a csv file
//
//
//
//
d3
.
csv
(
"/chart/corpus/{{ corpus.id }}/data.csv"
,
function
(
data
)
{
// since its a csv file we need to format the data a bit
var
dateFormat
=
d3
.
time
.
format
(
"%Y/%m/%d"
);
var
numberFormat
=
d3
.
format
(
".2f"
);
data
.
forEach
(
function
(
e
)
{
e
.
dd
=
dateFormat
.
parse
(
e
.
date
);
e
.
month
=
d3
.
time
.
month
(
e
.
dd
);
// pre-calculate month for better performance
});
// feed it through crossfilter
var
ndx
=
crossfilter
(
data
);
var
all
=
ndx
.
groupAll
();
/*
var yearlyDimension = ndx.dimension(function (d) {
return d3.time.year(d.dd);
});
var yearlyPerformanceGroup = yearlyDimension.group().reduce(
//add
function (p, v) {
++p.count;
p.absGain += +v.close - +v.open;
p.fluctuation += Math.abs(+v.close - +v.open);
p.sumIndex += (+v.open + +v.close) / 2;
p.avgIndex = p.sumIndex / p.count;
p.percentageGain = (p.absGain / p.avgIndex) * 100;
p.fluctuationPercentage = (p.fluctuation / p.avgIndex) * 100;
return p;
},
//remove
function (p, v) {
--p.count;
p.absGain -= +v.close - +v.open;
p.fluctuation -= Math.abs(+v.close - +v.open);
p.sumIndex -= (+v.open + +v.close) / 2;
p.avgIndex = p.sumIndex / p.count;
p.percentageGain = (p.absGain / p.avgIndex) * 100;
p.fluctuationPercentage = (p.fluctuation / p.avgIndex) * 100;
return p;
},
//init
function () {
return {count: 0, absGain: 0, fluctuation: 0, fluctuationPercentage: 0, sumIndex: 0, avgIndex: 0, percentageGain: 0};
}
);
var dateDimension = ndx.dimension(function (d) {
return d.dd;
});
*/
//volumeChart:(1)
//moveChart:(1)
// monthly index avg fluctuation in percentage
var
moveMonths
=
ndx
.
dimension
(
function
(
d
)
{
return
d
.
month
;
});
//moveChart:(3)
var
monthlyMoveGroup
=
moveMonths
.
group
().
reduceSum
(
function
(
d
)
{
return
d
.
volume
;
//return Math.abs(+d.close - +d.open);
});
//volumeChart:(2)
var
volumeByMonthGroup
=
moveMonths
.
group
().
reduceSum
(
function
(
d
)
{
return
d
.
volume
/
500000
;
});
//moveChart:(2)
var
indexAvgByMonthGroup
=
moveMonths
.
group
().
reduce
(
function
(
p
,
v
)
{
++
p
.
days
;
p
.
total
+=
(
+
v
.
open
+
+
v
.
close
)
/
2
;
p
.
avg
=
Math
.
round
(
p
.
total
/
p
.
days
);
return
p
;
},
function
(
p
,
v
)
{
--
p
.
days
;
p
.
total
-=
(
+
v
.
open
+
+
v
.
close
)
/
2
;
p
.
avg
=
p
.
days
==
0
?
0
:
Math
.
round
(
p
.
total
/
p
.
days
);
return
p
;
},
function
()
{
return
{
days
:
0
,
total
:
0
,
avg
:
0
};
}
);
/*
var gainOrLoss = ndx.dimension(function (d) {
return +d.open > +d.close ? "Loss" : "Gain";
});
var gainOrLossGroup = gainOrLoss.group();
var fluctuation = ndx.dimension(function (d) {
return Math.round((d.close - d.open) / d.open * 100);
});
var fluctuationGroup = fluctuation.group();
var quarter = ndx.dimension(function (d) {
var month = d.dd.getMonth();
if (month <= 3)
return "Q1";
else if (month > 3 && month <= 5)
return "Q2";
else if (month > 5 && month <= 7)
return "Q3";
else
return "Q4";
});
var quarterGroup = quarter.group().reduceSum(function (d) {
return d.volume;
});
var dayOfWeek = ndx.dimension(function (d) {
var day = d.dd.getDay();
switch (day) {
case 0:
return "0.Sun";
case 1:
return "1.Mon";
case 2:
return "2.Tue";
case 3:
return "3.Wed";
case 4:
return "4.Thu";
case 5:
return "5.Fri";
case 6:
return "6.Sat";
}
});
var dayOfWeekGroup = dayOfWeek.group();
*/
/*
yearlyBubbleChart.width(990)
.height(250)
.margins({top: 10, right: 50, bottom: 30, left: 40})
.dimension(yearlyDimension)
.group(yearlyPerformanceGroup)
.transitionDuration(1500)
.colors(["#a60000", "#ff0000", "#ff4040", "#ff7373", "#67e667", "#39e639", "#00cc00"])
.colorDomain([-12000, 12000])
.colorAccessor(function (d) {
return d.value.absGain;
})
.keyAccessor(function (p) {
return p.value.absGain;
})
.valueAccessor(function (p) {
return p.value.percentageGain;
})
.radiusValueAccessor(function (p) {
return p.value.fluctuationPercentage;
})
.maxBubbleRelativeSize(0.3)
.x(d3.scale.linear().domain([-2500, 2500]))
.y(d3.scale.linear().domain([-100, 100]))
.r(d3.scale.linear().domain([0, 4000]))
.elasticY(true)
.yAxisPadding(100)
.elasticX(true)
.xAxisPadding(500)
.renderHorizontalGridLines(true)
.renderVerticalGridLines(true)
.renderLabel(true)
.renderTitle(true)
.label(function (p) {
return p.key.getFullYear();
})
.title(function (p) {
return p.key.getFullYear()
+ "\n"
+ "Index Gain: " + numberFormat(p.value.absGain) + "\n"
+ "Index Gain in Percentage: " + numberFormat(p.value.percentageGain) + "%\n"
+ "Fluctuation / Index Ratio: " + numberFormat(p.value.fluctuationPercentage) + "%";
})
.yAxis().tickFormat(function (v) {
return v + "%";
});
*/
/*
gainOrLossChart.width(180)
.height(180)
.radius(80)
.dimension(gainOrLoss)
.group(gainOrLossGroup)
.label(function (d) {
return d.data.key + "(" + Math.floor(d.data.value / all.value() * 100) + "%)";
});
*/
/*
quarterChart.width(180)
.height(180)
.radius(80)
.innerRadius(30)
.dimension(quarter)
.group(quarterGroup);
*/
/*
dayOfWeekChart.width(180)
.height(180)
.margins({top: 20, left: 10, right: 10, bottom: 20})
.group(dayOfWeekGroup)
.dimension(dayOfWeek)
.colors(['#3182bd', '#6baed6', '#9ecae1', '#c6dbef', '#dadaeb'])
.label(function (d){
return d.key.split(".")[1];
})
.xAxis().ticks(4);
*/
/*
fluctuationChart.width(420)
.height(180)
.margins({top: 10, right: 50, bottom: 30, left: 40})
.dimension(fluctuation)
.group(fluctuationGroup)
.elasticY(true)
.centerBar(true)
.gap(1)
.round(dc.round.floor)
.x(d3.scale.linear().domain([-25, 25]))
.renderHorizontalGridLines(true)
.xAxis()
.tickFormat(function (v) {
return v + "%";
});
*/
moveChart
.
width
(
800
)
.
height
(
150
)
.
transitionDuration
(
1000
)
.
margins
({
top
:
10
,
right
:
50
,
bottom
:
25
,
left
:
40
})
.
dimension
(
moveMonths
)
.
group
(
indexAvgByMonthGroup
)
.
valueAccessor
(
function
(
d
)
{
return
d
.
value
.
avg
;
})
.
x
(
d3
.
time
.
scale
().
domain
([
new
Date
(
1950
,
01
,
01
),
new
Date
(
2014
,
12
,
31
)]))
.
round
(
d3
.
time
.
month
.
round
)
.
xUnits
(
d3
.
time
.
months
)
.
elasticY
(
true
)
.
renderHorizontalGridLines
(
true
)
.
brushOn
(
false
)
.
compose
([
dc
.
lineChart
(
moveChart
).
group
(
indexAvgByMonthGroup
)
.
valueAccessor
(
function
(
d
)
{
return
d
.
value
.
avg
;
})
.
renderArea
(
true
)
.
stack
(
monthlyMoveGroup
,
function
(
d
)
{
return
d
.
value
;
})
.
title
(
function
(
d
)
{
var
value
=
d
.
value
.
avg
?
d
.
value
.
avg
:
d
.
value
;
if
(
isNaN
(
value
))
value
=
0
;
return
dateFormat
(
d
.
key
)
+
"
\n
"
+
numberFormat
(
value
);
})
])
.
xAxis
();
volumeChart
.
width
(
800
)
.
height
(
100
)
.
margins
({
top
:
0
,
right
:
50
,
bottom
:
20
,
left
:
40
})
.
dimension
(
moveMonths
)
.
group
(
volumeByMonthGroup
)
.
centerBar
(
true
)
.
gap
(
0
)
.
x
(
d3
.
time
.
scale
().
domain
([
new
Date
(
1950
,
01
,
01
),
new
Date
(
2015
,
01
,
01
)]))
.
round
(
d3
.
time
.
month
.
round
)
.
xUnits
(
d3
.
time
.
months
)
.
renderlet
(
function
(
chart
)
{
chart
.
select
(
"g.y"
).
style
(
"display"
,
"none"
);
moveChart
.
filter
(
chart
.
filter
());
})
.
on
(
"filtered"
,
function
(
chart
)
{
dc
.
events
.
trigger
(
function
()
{
moveChart
.
focus
(
chart
.
filter
());
});
});
/*
dc.dataCount(".dc-data-count")
.dimension(ndx)
.group(all);
*/
/*
dc.dataTable(".dc-data-table")
.dimension(dateDimension)
.group(function (d) {
var format = d3.format("02d");
return d.dd.getFullYear() + "/" + format((d.dd.getMonth() + 1));
})
.size(10)
.columns([
function (d) {
return d.date;
},
function (d) {
return d.open;
},
function (d) {
return d.close;
},
function (d) {
return numberFormat(d.close - d.open);
},
function (d) {
return d.volume;
}
])
.sortBy(function (d) {
return d.dd;
})
.order(d3.ascending)
.renderlet(function (table) {
table.selectAll(".dc-table-group").classed("info", true);
});
*/
dc
.
renderAll
();
}
);
</script>
{% endblock %}
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