I have two geometries in different tables which look like the same, but one is valid and the other is invalid. I checked it out:
select ST_IsValid(_s.geom) as _gvalid,
ST_IsValid(s.geom) as gvalid,
_s.geom = s.geom as geom_bin_equal,
ST_SRID(_s.geom)=ST_SRID(s.geom) as srid_equal,
ST_EQUALS(_s.geom, s.geom),
ST_AsText(_s.geom) = ST_AsText(s.geom) as text_equal
from _spatial_object _s, spatial_object s
where _s.id_spatial_object = 314 and s.id_spatial_object = 314
Output here:
How on the earth it could be?
Actually, the both geometries should be invalid (Interior is disconnected at or near point 58.182000000000002 51.457000000000001)
Geometry:
POLYGON((58.169 51.456,58.176 51.458,58.18 51.458,58.182 51.457,58.183 51.456,58.182 51.453,58.184 51.451,58.182 51.449,58.183 51.448,58.181 51.445,58.179 51.443,58.177 51.444,58.179 51.445,58.178 51.446,58.178 51.448,58.178 51.448,58.177 51.448,58.173 51.447,58.17 51.449,58.173 51.45,58.174 51.451,58.178 51.451,58.178 51.452,58.178 51.452,58.176 51.452,58.173 51.451,58.169 51.456),(58.169 51.456,58.1732222222222 51.4569444444444,58.182 51.457,58.169 51.456))
select ST_ISValid(geom), ST_IsValid(ST_GeomFromText(ST_AsText(geom))) from _spatial_object
outputs
true false
Prior to version 2.4, the equality using = was relying on a bounding box comparison only, so two very different geometries could still be considered as being equal.
When using ST_Equals, the two geometries must "look" the same (but the vertices order does not matter). However, the doc notes that
[Important]
This function will return false if either geometry is invalid except
in the case where they are binary equal.
but also mentions that
Changed: 2.2.0 Returns true even for invalid geometries if they are
binary equal
So because you are using an older version, the result is unreliable / false.
Related
I am trying to use k-medoids to cluster some trajectory data I am working with (multiple points along the trajectory of an aircraft). I want to cluster these into a set number of clusters (as I know how many types of paths there should be).
I have found that k-medoids is implemented inside the pyclustering package, and am trying to use that. I am technically able to get it to cluster, but I do not know how to control the number of clusters. I originally thought it was directly tied to the number of elements inside what I called initial_medoids, but experimentation shows that it is more complicated than this. My relevant code snippet is below.
Note that D holds a list of lists. Each list corresponds to a single trajectory.
def hausdorff( u, v):
d = max(directed_hausdorff(u, v)[0], directed_hausdorff(v, u)[0])
return d
traj_count = len(traj_lst)
D = np.zeros((traj_count, traj_count))
for i in range(traj_count):
for j in range(i + 1, traj_count):
distance = hausdorff(traj_lst[i], traj_lst[j])
D[i, j] = distance
D[j, i] = distance
from pyclustering.cluster.kmedoids import kmedoids
initial_medoids = [104, 345, 123, 1]
kmedoids_instance = kmedoids(traj_lst, initial_medoids)
kmedoids_instance.process()
cluster_lst = kmedoids_instance.get_clusters()[0]
num_clusters = len(np.unique(cluster_lst))
print('There were %i clusters found' %num_clusters)
I have a total of 1900 trajectories, and the above-code finds 1424 clusters. I had expected that I could control the number of clusters through the length of initial_medoids, as I did not see any option to input the number of clusters into the program, but this seems unrelated. Could anyone guide me as to the mistake I am making? How do I choose the number of clusters?
In case of requirement to obtain clusters you need to call get_clusters():
cluster_lst = kmedoids_instance.get_clusters()
Not get_clusters()[0] (in this case it is a list of object indexes in the first cluster):
cluster_lst = kmedoids_instance.get_clusters()[0]
And that is correct, you can control amount of clusters by initial_medoids.
It is true you can control the number of cluster, which correspond to the length of initial_medoids.
The documentation is not clear about this. The get__clusters function "Returns list of medoids of allocated clusters represented by indexes from the input data". so, this function does not return the cluster labels. It returns the index of rows in your original (input) data.
Please check the shape of cluster_lst in your example, using .get_clusters() and not .get_clusters()[0] as annoviko suggested. In your case, this shape should be (4,). So, you have a list of four elements (clusters), each containing the index or rows in your original data.
To get, for example, data from the first cluster, use:
kmedoids_instance = kmedoids(traj_lst, initial_medoids)
kmedoids_instance.process()
cluster_lst = kmedoids_instance.get_clusters()
traj_lst_first_cluster = traj_lst[cluster_lst[0]]
Consider the following example code:
spacing_Pin = transpose(-27:0.001:2);
Phi_intrp3 = interp1(P_in3,Phi_out_deg3,spacing_Pin,'spline');
size(P_in3) = size(Phi_out_deg3) = 40 1
P_in1st = P_in3 -0.76;
thetah_1st = Phi_intrp3(ismember(spacing_Pin,P_in1st));
I think thetah_1stshould now have 40 elements. It turns out, however, it only has 20. This must be, because P_in1stcan only be found 20 times in spacing_Pin. I know, you're not given P_in3, but it only has up to 2 digits after the dot. So should P_in1st. min(P_in3) = -25.9800and max(P_in3) = -0.0200. These values should be included in spacing_Pin. Why does thetah_1st have only 20 entries.
It's impossible to say without more information and your actual variable values, but I suspect that the issue is with using ismember the way that you have.
Since you are looking for floating point numbers within an array rather than integers, you should use ismembertol (ismember with a tolerance) to handle any potential floating point errors.
thetah_1st = Phi_intrp3(ismembertol(spacing_Pin, P_in1st));
I'm looking for a way to handle ranges in Scala.
What I need to do is:
given a set of ranges and a range(A) return the range(B) where range(A) intersect range (B) is not empty
given a set of ranges and a range(A) remove/add range(A) from/to the set of ranges.
given range(A) and range(B) create a range(C) = [min(A,B), max(A,B)]
I saw something similar in java - http://docs.guava-libraries.googlecode.com/git/javadoc/com/google/common/collect/RangeSet.html
Though subRangeSet returns only the intersect values and not the range in the set (or list of ranges) that it intersects with.
RangeSet rangeSet = TreeRangeSet.create();
rangeSet.add(Range.closed(0, 10));
rangeSet.add(Range.closed(30, 40));
Range range = Range.closed(12, 32);
System.out.println(rangeSet.subRangeSet(range)); //[30,32] (I need [30,40])
System.out.println(range.span(Range.closed(30, 40))); //[12,40]
There is an Interval[A] type in the spire math library. This allows working with ranges of arbitrary types that define an Order. Boundaries can be inclusive, exclusive or omitted. So e.g. (-∞, 0.0] or [0.0, 1.0) would be possible intervals of doubles.
Here is a library intervalset for working with sets of non-overlapping intervals (IntervalSeq or IntervalTrie) as well as maps of intervals to arbitrary values (IntervalMap).
Here is a related question that describes how to use IntervalSeq with DateTime.
Note that if the type you want to use is 64bit or less (basically any primitive), IntervalTrie is extremely fast. See the Benchmarks.
As Tzach Zohar has mentioned in the comment, if all you need is range of Int - go for scala.collection.immutable.Range:
val rangeSet = Set(0 to 10, 30 to 40)
val r = 12 to 32
rangeSet.filter(range => range.contains(r.start) || range.contains(r.end))
If you need it for another underlying type - implement it by yourself, it's easy for your usecase.
what is the easy way to convert points to polygon?
i've tried this query
SELECT ST_GeomFromText('POLYGON((157 -536.0,157 -537.0,157 -538.0,157 -539.0,157 -540.0,157 -541.0,157 -542.0,157 -543.0,157 -544.0,157 -545.0,158 -545.0,159 -545.0,160 -545.0,161 -545.0,162 -545.0,163 -545.0,164 -545.0,165 -545.0,165 -544.0,165 -543.0,165 -542.0,165 -541.0,165 -540.0,165 -539.0,165 -538.0,165 -537.0,165 -536.0,164 -536.0,163 -536.0,162 -536.0,161 -536.0,160 -536.0,159 -536.0,158 -536.0,157.0 -536.0))');
but its results are not as expected as shown below
which is supposed to be like this
Obviously your points are not in the correct order to define a polygon., and as the commenter pointed out, you have more than one polygons.
You could divide them into sets that make each polygon (manually?), and construct a multipolygon as follows:
SELECT ST_AsText(ST_Collect(ARRAY[ST_GeomFromText('POLYGON(..first polygon...)'),ST_GeomFromText('POLYGON(..2nd polygon...)',...,ST_GeomFromText('POLYGON(..last polygon...)')]));
I'm looking for a function or solution to the following:
For the chart in SQL Reporting i need to multiply values from a Column A. For summation i would use =SUM(COLUMN_A) for the chart. But what can i use for multiplication - i was not able to find a solution so far?
Currently i am calculating the value of the stacked column as following:
=ROUND(SUM(Fields!Value_Is.Value)/SUM(Fields!StartValue.Value),3)
Instead of SUM i need something to multiply the values.
Something like that:
=ROUND(MULTIPLY(Fields!Value_Is.Value)/MULTIPLY(Fields!StartValue.Value),3)
EDIT #1
Okay tried to get this thing running.
The expression for the chart looks like this:
=Exp(Sum(Log(IIf(Fields!Menge_Ist.Value = 0, 10^-306, Fields!Menge_Ist.Value)))) / Exp(Sum(Log(IIf(Fields!Startmenge.Value = 0, 10^-306, Fields!Startmenge.Value))))
If i calculate my 'needs' manually i have to get the following result:
In my SQL Report i get the following result:
To make it easier, these are the raw values:
and you have the possibility to group the chart by CW, CQ or CY
(The values from the first pictures are aggregated Sum values from the raw values by FertStufe)
EDIT #2
Tried your expression, which results in this:
Just to make it clear:
The values in the column
=Value_IS / Start_Value
in the first picture are multiplied against each other
0,9947 x 1,0000 x 0,59401 = 0,58573
Diffusion Calenderweek 44 Sums
Startvalue: 1900,00 Value Is: 1890,00 == yield:0,99474
Waffer unbestrahlt Calenderweek 44 Sums
Startvalue: 620,00 Value Is: 620,00 == yield 1,0000
Pellet Calenderweek 44 Sums
Startvalue: 271,00 Value Is: 160,00 == yield 0,59041
yield Diffusion x yield Wafer x yield Pellet = needed Value in chart = 0,58730
EDIT #3
The raw values look like this:
The chart ist grouped - like in the image - on these fields
CY (Calendar year), CM (Calendar month), CW (Calendar week)
You can download the data as xls here:
https://www.dropbox.com/s/g0yrzo3330adgem/2013-01-17_data.xls
The expression i use (copy / past from the edit window)
=Exp(Sum(Log(Fields!Menge_Ist.Value / Fields!Startmenge.Value)))
I've exported the whole report result to excel, you can get it here:
https://www.dropbox.com/s/uogdh9ac2onuqh6/2013-01-17_report.xls
it's actually a workaround. But I am pretty sure is the only solution for this infamous problem :D
This is how I did:
Exp(∑(Log(X))), so what you should do is:
Exp(Sum(Log(Fields!YourField.Value)))
Who said math was worth nothing? =D
EDIT:
Corrected the formula.
By the way, it's tested.
Addressing Ian's concern:
Exp(Sum(Log(IIf(Fields!YourField.Value = 0, 10^-306, Fields!YourField.Value))))
The idea is change 0 with a very small number. Just an idea.
EDIT:
Based on your updated question this is what you should do:
Exp(Sum(Log(Fields!Value_IS.Value / Fields!Start_Value.Value)))
I just tested the above code and got the result you hoped for.