I am using nivo line component to draw a stacked line graph. I am getting this error:
Warning: Encountered two children with the same key, `L1.87.83999837239584`. Keys should be unique so that components maintain their identity across updates. Non-unique keys may cause children to be duplicated and/or omitted — the behavior is unsupported and could change in a future version
What keys and children is it talking about? Is it remotely possible that each data point on the graph is a distinct React element which is part of some collection and must be uniquely identified in "react sense"?
so apparently Nivo takes your x,y data pairs and combines each pair values into react key used for identity within a collection. Which means if you have a duplicate x,y pair, you end up with a duplicate key which causes the error I had reported.
It also blows up on having 2 same x values and different y values -- doesnt know how to handle that.
Related
For some context: I am currently using azure cosmos db with gremlin api, because of the storage-scaling architecture, it's much less expensive to perform a '.out()' operation than a '.in()' operation, hence I always create double directed edges, so I choose which one to use with '.out()' operation depending on which direction I want to query.
We use the graph to associate events with users. Whenever a user 'U' raises an event 'E', we create two edges:
g.V('U').addE('raisedEvent').to(g.V('E'))
g.V('E').addE('raisedByUser').to(g.V('U'))
Very rarely, one of these queries fails for one reason or another and we end up with only a single edge between the two vertices. I've been trying to find a way to query for all vertices that have only a uni-directional relationship given a set of 'paired' edge-labels, in order to find these errors and re-create the missing edge.
Basically I need a query where...
given a pair of edge labels E1 (for outgoing, V1-->V2), E2 (for incoming V1<--V2)
finds finds all vertices V1 where for every outgoing edge E1 to another vertex V2, V2 doesn't have an edge E2 going back to V1; and vice-versa
Example:
// given a graph
g.addV('user').property('id','user_1')
g.addV('user').property('id','user_2')
g.addV('user').property('id','user_3')
g.addV('user').property('id','user_4')
g.addV('event').property('id','event_1')
g.addV('event').property('id','event_2')
g.addV('event').property('id','event_3')
g.addV('event').property('id','event_4')
g.V('user_1').addE('raisedEvent').to(g.V('event_1')).V('event_1').addE('raisedByUser').to(g.V('user1'))
g.V('user_2').addE('raisedEvent').to(g.V('event_2')).V('event_1').addE('raisedByUser').to(g.V('user1'))
g.V('user_2').addE('raisedEvent').to(g.V('event_3'))
g.V('event_4').addE('raisedByUser').to(g.V('user_3'))
// i.e.
// (user_1) <--> (event_1)
// (event_2) <--> (user_2) ---> (event_3)
// (event_4) ---> (user_3)
// (user_4)
// Then, the query should match with user_2 and user_3...
// ...as they contain uni-directional links to events
Edit: Note - The cosmosdb implementation of the 'is()' operation doesn't support giving traversal results as an input I.e. queries such as
where(_.outE('raisedEvent').count().is(__.out('raisedEvent').outE('raisedByUser').count()))
Are currently unsupported in cosmosdb.
If possible, it would also be great to get a list of which pairs of vertices have a bad link (e.g. in this case [(user_2, event_3), (user_3, event_4)]), but just knowing which vertices have a bad link will be very useful already.
Thanks to Kelvin Lawrence, I ended up using this pattern to get a list of vertex id pairs that are only uni-directionally connected from a to b:
g.V().haslabel("user").as('a').out('raisedEvent').where(__.not(out('raisedByUser').as('a'))).as('b').select('a','b').by('id')
I'm building a workout app that has an entity called Workout and another one called Exercise.
A workout can contain multiple exercises (thus a one-to-many relationship). I want to show the users of my app the exercises contained in a workout but in an ordered way (it's not the same to start with strength exercises as with the cardio ones).
Apparently, when establishing this kind of relationship in Core Data, I need to use an NSSet, because if I try to use for example an Array where its elements are ordered, I get the following error:
*** Terminating app due to uncaught exception 'NSInvalidArgumentException', reason: 'Unacceptable type of value for to-many relationship: property = "consistsOf"; desired type = NSSet; given type = __NSArray0; value = (
).'
I have tried to check the "ordered" checkmark in my model, but then I get an error saying "Workout.consistsOf must not be ordered".
I have also tried to use an NSDictionary whose keys would be the position and the values would be the exercises themselves, but I'm getting the same error as above.
How can I show the users the exercises that a workout consists of in an ordered way?
Thanks a lot in advance!
P.S.: Here's a screenshot of the properties of my model.
Ordered relationships use NSOrderedSet, but CloudKit doesn't support ordered sets, so you can't use an ordered relationship and CloudKit in the same data model.
To keep an order, you need to have some property on Exercise that would indicate the order. This could be as simple as an integer property called something like index. You'd sort the result based on the index value. If there's something else that also indicates order-- like a date, maybe?-- use that instead of adding a new property.
I want to map a timestamp t and an identifier id to a certain state of an object. I can do so by mapping a tuple (t,id) -> state_of_id_in_t. I can use this mapping to access one specific (t,id) combination.
However, sometimes I want to know all states (with matching timestamps t) of a specific id (i.e. id -> a set of (t, state_of_id_in_t)) and sometimes all states (with matching identifiers id) of a specific timestamp t (i.e. t -> a set of (id, state_of_id_in_t)). The problem is that I can't just put all of these in a single large matrix and do linear search based on what I want. The amount of (t,id) tuples for which I have states is very large (1m +) and very sparse (some timestamps have many states, others none etc.). How can I make such a dict, which can deal with accessing its contents by partial keys?
I created two distinct dicts dict_by_time an dict_by_id, which are dicts of dicts. dict_by_time maps a timestamp t to a dict of ids, which each point to a state. Similiarly, dict_by_id maps an id to a dict of timestamps, which each point to a state. This way I can access a state or a set of states however I like. Notice that the 'leafs' of both dicts (dict_by_time an dict_by_id) point to the same objects, so its just the way I access the states that's different, the states themselves however are the same python objects.
dict_by_time = {'t_1': {'id_1': 'some_state_object_1',
'id_2': 'some_state_object_2'},
't_2': {'id_1': 'some_state_object_3',
'id_2': 'some_state_object_4'}
dict_by_id = {'id_1': {'t_1': 'some_state_object_1',
't_2': 'some_state_object_3'},
'id_2': {'t_1': 'some_state_object_2',
't_2': 'some_state_object_4'}
Again, notice the leafs are shared across both dicts.
I don't think it is good to do it using two dicts, simply because maintaining both of them when adding new timestamps or identifiers result in double work and could easily lead to inconsistencies when I do something wrong. Is there a better way to solve this? Complexity is very important, which is why I can't just do manual searching and need to use some sort of HashMap magic.
You can always trade add complexity with lookup complexity. Instead of using a single dict, you can create a Class with an add method and a lookup method. Internally, you can keep track of the data using 3 different dictionaries. One uses the (t,id) tuple as key, one uses t as the key and one uses id as the key. Depending on the arguments given to lookup, you can return the result from one of the dictionaries.
I've seen examples using the NewDimension method to dimension between two points and two lines, I assume in the family editor, but I want to add a dimension to two family instances in the model, such as a pipe tap's centerline and a pipe end. Then the dimension would 'drive' the distance if the user edits it, moving the outlet along the pipe, just like it does if a user created the dimension using the Revit UI.
I just don't know what way Revit wants me to try to do this:
Finding the family instance ID, going into each family ID, and finding a line/plane/point in the family to use as a dimension point when you use NewDimension. Hopefully this would work outside the family editor trying to make a dimension between two different family instances (pipe end and pipe tap).
Finding the x,y,z location of the points you want to snap to, and creating a dimension (using NewDimension method for example) between those two x,y,z locations, and if the x,y,z locations fall on appropriate points like a pipe end and center-line of a pipe tap then perhaps Revit automatically makes it a 'smart' dimension that 'drives' the location of the pipe tap.
Here's some promising methods I found in the API, not sure which of them I should be using though.
NewDimension
AlignedDimension
AddListeningDimensionBendToBend
AddListeningDimensionSegmentToBend
AddListeningDimensionSegmentToSegment
SetElementsToDimension
Look at the two Building Coder samples showing how to Dimension Walls by Iterating Faces and Dimension Walls using FindReferencesByDirection.
The approach used for walls works with standard family instances as well.
Note that the FindReferencesByDirection method has now been replaced by the `ReferenceIntersector class.
I have the following information in a Titan Graph database.I am trying to make sense of the information by sending queries across gremlin shell.The Graph database that I am trying to investigate models a Network.There are two types of vertices
- `Switch`
- `Port`
I am trying to figure out the relationship between these two types of vertices.
g = TitanFactory.open("/tmp/cassandra.titan")
To see the list of vertices of each type
$ g.V('type', 'switch')
==>v[228]
==>v[108]
==>v[124]
==>v[92]
==>v[156]
==>v[140]
$ g.V('type', 'port')
==>v[160]
==>v[120152]
==>v[164]
==>v[120156]
==>v[560104]
==>v[680020]
==>v[680040]
==>v[112]
==>v[120164]
==>v[560112]
==>v[680012]
==>v[680004]
==>v[144]
==>v[680032]
==>v[236]
==>v[100]
==>v[560128]
==>v[128]
==>v[680028]
==>v[232]
==>v[96]
To find the relation between the switch and port.
g.v(108).out
==>v[560104]
==>v[680004]
==>v[112]
What is this "out"? As I understand there is a outward arrow pointing from Switch represented by vertex 108 to the Ports represented by vertices 560104 680004 and 112
What is this in and out? Is it something very specific to Graph Databases? Also what is a label in a graph databse? Are in and out labels?
The use of in and out is descriptive of the direction of the edge going from one vertex to another. In your case, you have this:
switch --> port
When you write:
g.v(108).out
you are telling Gremlin to find the vertex at 108, then walk along edges that point out or away from it. You might also think of out as starting from the tail of the arrow and walking to the head. Given your schema, those lead to "ports".
Similarly, in simply means to have Gremlin walk along edges that point in to the vertex. You might also think of in as starting from the head of the arrow and walking to the tail. Given your schema, switches will have no in edges and hence will always return no results. However if you were to start from a "port" vertex and traverse in:
g.v(560104).in
you would at least get back vertex 108 as vertex "560104" has at least one edge with an arrow pointing to it (given what I know of your sample data).
By now you've gathered that in and out are "directions" and not "labels". A label has a different purpose; it categorizes an edge. For example, you might have the following schema:
switch --connectsTo--> port
company --manufactures--> switch
switch --locatedIn--> rack
In other words you might have three edge labels representing different ways that a "switch" relates to other parts of your schema. In this way your queries can be more descriptive about what you want. Given your previous example and this revised schema you would have to write the following to get the same result you originally showed:
g.v(108).out("connectsTo")
==>v[560104]
==>v[680004]
==>v[112]
Graph databases will typically take advantage of these labels to help improve performance of queries.