I'm interested in creating an edge (u,v) between two nodes of the same class in a graph if they share the same day of year and v.year = u.year+1.
Say I have vertices.csv:
id,date
A,2014-01-02
B,2015-01-02
C,2016-01-02
D,2013-06-01
E,2014-06-01
F,2016-06-01
The edge structure I'd like to see would be this:
A --> B --> C
D --> E
F
Let's set the vertex class to be "myVertex" and edge class to be "myEdge"? Is it possible to generate these edges using the SQL interface?
Based on this question, I started trying something like this:
BEGIN
LET source = SELECT FROM myVertex
LET target = SELECT from myVertex
LET edge = CREATE EDGE myEdge
FROM $source
TO (SELECT FROM $target WHERE $source.date.format('MM-dd') = $target.date.format('MM-dd')
AND $source.date.format('yyyy').asInteger() = $target.date.format('yyyy').asInteger()-1)
COMMIT
Unfortunately, this isn't correct. So I got less ambitious and wanted to see if I can create edges just based on matching day-of-year:
BEGIN
LET source = SELECT FROM myVertex
LET target = SELECT from myVertex
LET edge = CREATE EDGE myEdge FROM $source TO (SELECT FROM $target WHERE $source.date.format('MM-dd') = $target.date.format('MM-dd'))
COMMIT
Which still has errors... I'm sure it's something pretty simple to an experienced OrientDB user.
I thought about putting together a JavaScript function like Michela suggested on this question, but I'd prefer to stick to using the SQL commands as much as possible for now.
Help is greatly appreciated.
Other Stack Overflow References
How to print or log on function javascript OrientDB
I tried with OSQL batch but I think that you can't get what you want.
With whis OSQL batch
begin
let a = select #rid, $a1 as toAdd from test let $a1 = (select from test where date.format("MM") == $parent.$current.date.format("MM") and date.format("dd") == $parent.$current.date.format("dd") and #rid<>$parent.$current.#rid and date.format("yyyy") == sum($parent.$current.date.format("yyyy").asInteger(),1))
commit
return $a
I got this
but the problem is that when you create the edge you can not cycle on the table obtained in the previous step.
I think the best solution is to use an JS server-side function.
Hope it helps.
Related
Using Spark/Scala to attempt a "simple" query. I have a file which, after line 1 below runs, looks like this
EmpReg,EmpOT,RegPay,OTPay
Alice,Alice,400,20
Bob,Bob,300,0
Carol,Carol,450,120
Dan,Dan,400,200
Ellen,Ellen,360,40
The first and third columns (EmpReg, RegPay) come from one source and the second and third columns (EmpOT, OTPay) come from a second source. My objective is output that looks like this.
Emp,Pay
Alice,420
Bob,300
Carol,570
Dan,600
Ellen,400
Here is the code that I have been trying, at least what I have saved.
var q2 = q.join(q1, q("EmpReg") === q1("EmpOT"), "fullouter")
//q2 = q2.select("EmpReg", ($"RegPay" + $"OTPay"))
//q2 = q2.groupBy($"EmpReg".sum($"RegPay" + $"OTPay"))
var add = q2.select(($"RegPay" + $"OTPay"))
//q2 = q2.sum("RegPay", "OTPay")
//q2 = q2.groupBy("EmpReg", "EmpOT")
//var q2 = q.join(q1).where("EmpReg") === "EmpOT"))
//q2 = q2.select("EmpReg").sum("RegPay", "OTPay")
//q2.show
add.show
[q] is the first file which represents regular pay. [q1] is the second file which represents overtime pay. [q2] is the combination shown in the first example above. Primary keys are [EmpReg] and [EmpOT]. don't really need to combine [EmpReg] and [EmpOT] since they are the same, and it doesn't make any difference which I use.
I really need to add [RegPay] and [OTPay] to get [Pay], but for the life of me I can't get it to work. The lines commented out return various errors. I can add the two pay columns, and select an appropriate employee column, but can't seem to do it in one query. I am constrained to use Scala on Databricks. Othewise, I might do something like this.
select q.EmpReg as Emp, (q.RegPay + q1.OTPay) as Pay
from q join q1 on q.EmpReg = q1.EmpOT
(Why can't things ever be simple?)
You can use a similar approach as in your SQL query:
val q2 = q.join(q1, q("EmpReg") === q1("EmpOT"), "fullouter")
val add = q2.select(q("EmpReg").as("Emp"), (q("RegPay") + q1("OTPay")).as("Pay"))
Your code has this line
q2.select("EmpReg", ($"RegPay" + $"OTPay"))
which should work if you add $ before "EmpReg". You can't have both strings and columns in the select statement. This works in Python but not Scala.
So I have a list of stars and their respective distances. My assignment is to find which stars are in a certain distance (+- 10parsec). I want to exclude some of them from further calculations in the program. The thing is I don't want to remove them completely so remove, pop etc isn't helping me. I still want those stars on the list to be present in my output csv. I just want a line saying something like those stars which don't support the if statement, don't use them in this calculation. So i guess the output would be blank for those.
I suppose it is an if or for statement, to mark those bad stars as False and then down the line use calculation that excludes those faulty stars.
I'm a physics student and this is my first python program ever! Please be cool about my ignorance...
Edit: forgive me if i include useless stuff i don't really know what's important. I also use uncertainties library if its of any use
column_names = ['id','pi','s_pi','v_r' ,'s_v', 'dis', 'X',
'ra_h', 'ra_m', 'ra_s','dec_d', 'dec_m',
'dec_s', 'ma', 's_ma', 'md', 's_md']
data = pd.read_csv("hyades_data.dat", skiprows=2, sep='\s+',
names=column_names)
calculations with all
v_r = unumpy.uarray(data['v_r'], data['s_v'])
ma = unumpy.uarray(data['ma'], data['s_ma'])
md = unumpy.uarray(data['md'], data['s_md'])
mi = unumpy.sqrt(ma**2+md**2)
r_m = v_r*unumpy.tan(th)/(4.74*mi/1000)
diff = np.abs(r_pc - r_m)
'''
if np.abs(dist-46.43) <=10:
r_m=True
else r_m=False
at this point i want to make the distiction
'''
mean_diff = diff.mean()
print("Mean : ")
print(mean_diff)
print(a_ref,d_ref)
df_va=pd.DataFrame(v_r)
df_mi = pd.DataFrame(mi)
df_rm = pd.DataFrame(r_m)
df_rpc = pd.DataFrame(r_pc)
df_diff = pd.DataFrame(diff)
#df_mean_diff = pd.DataFrame(mean_diff)
ve = v_r*np.tan(th)
output = pd.concat([data['id'], ra, dec, th_d, df_mi, df_rm, df_rpc,
df_diff,df_va], axis=1)
output.columns = ['id','ra', 'dec', 'th_d','mi', 'r_m', 'r_pc',
'dist_diff','va']
output.to_csv('results.csv', index=False)
Using networkx 2.0 I try to dynamically add an additional edge attribute by looping through all the edges. The graph is a MultiDiGraph.
According to the tutorial it seems to be possible to add edge attributes the way I do in the code below:
g = nx.read_gpickle("../pickles/" + gname)
yearmonth = gname[:7]
g.name = yearmonth # works
for source, target in g.edges():
g[source][target]['yearmonth'] = yearmonth
This code throws the following error:
TypeError: 'AtlasView' object does not support item assignment
What am I doing wrong?
That should happen if your graph is a nx.MultiGraph. From which case you need an extra index going from 0 to n where n is the number of edges between the two nodes.
Try:
for source, target in g.edges():
g[source][target][0]['yearmonth'] = yearmonth
The tutorial example is intended for a nx.Graph.
Can any one tell how to add roll up functionality in sugarCRM(Ce).
Our requirement is to "sum of project amounts to roll up to opportunity amount field in sugar crm"
You can achieve it by writing after_save logic hook as described below:
I have achived similar functionality where sum of pending amount of each cases will be store in accounts module.
$customer_id = $_REQUEST['mc_companyusers_cases_1mc_companyusers_ida'];
if($customer_id){
$rs = $bean->db->query("SELECT cc.pending_payment_c FROM mc_companyusers_cases_1_c m inner join cases c on m.`mc_companyusers_cases_1cases_idb` = c.`id` inner join cases_cstm cc on cc.`id_c` = c.`id` where m.`mc_companyusers_cases_1mc_companyusers_ida` = '".$customer_id."'");
$total_pending_amount = 0;
while($row = $bean->db->fetchByAssoc($rs)){
$total_pending_amount += $row['pending_payment_c'];
}
$bean->db->query("Update mc_companyusers_cstm set total_pending_payment_c='".$total_pending_amount."' where id_c='".$customer_id."'");
}
So you can map project module with cases and opportunity module with account in above query.
Thank you.
You could add a field with a function that dynamically calculates the sum.
Or use a logic hook that adds to a real db field whenever a submodule item gets added.
I'm using NDepend to write a query to extract a subset of my assemblies and their dependent assemblies into a Dependency Matrix.
I would like to further reduce the size of the matrix to show only dependent assemblies that have a small or medium coupling (the ones that would be relatively easy to decouple) Therefore I only want to show the assemblies that have < 20 method usages.
how do I update this query to show this?
let agentAssemblies =Assemblies.WithNameLike("Agent")
let assembliesUsedByAgents = Assemblies.ExceptThirdParty().UsedByAny(agentAssemblies)
from a in agentAssemblies.Union(assembliesUsedByAgents )
select a
You can refine the query this way:
let agentAssemblies = Assemblies.WithNameLike("Agent")
let assembliesUsedByAgents = Assemblies.ExceptThirdParty().UsedByAny(agentAssemblies)
from a in assembliesUsedByAgents
let methodsUsedFromAgentAssemblies = a.ChildMethods.UsedByAny(agentAssemblies)
where methodsUsedFromAgentAssemblies.Count() < 20
let agentAssembliesMethodsUsingMe = agentAssemblies.ChildMethods().UsingAny(methodsUsedFromAgentAssemblies)
select new {
a,
methodsUsedFromAgentAssemblies ,
agentAssembliesMethodsUsingMe
}
From the code query result you can visualise both methodsUsedFromAgentAssemblies and agentAssembliesMethodsUsingMe...
.. and by right clicking methods sets, you can export both sets to the Dependency Matrix to have a clear understanding of which method is calling which method.