I am new to Qgis. I am trying to export a shapefile of polygons so that I can read its vertices can be read (e.g. by python packages like fiona or shapely) as lat and lon coordinates in degrees. What I am getting now are coordinates in meters.
I am using a EPSG:4326 projected coordinate reference system, though I could change that.
Any tips are welcome.
You may open your layer in tabular form (press F6) and copy-paste (Ctrl+A, Ctrl+C, Ctrl+V) all features into excel. There (usually, in the first column) you might notice your geometries in WKT (well-known text) format - every vertex is shown in form of decimal degree coordinates.
Alternatively, you may use field calculator (button ) and create new text field of 0 length (no length limitations) with geom_to_wkt($geometry) in 'Expression'. So that, explicit wkt representation of your geometries will be present in each feature attributes. From there you may export your layer to csv-file, for instance.
Related
I'm currently developing a Qt desktop application using the Q3DScatter class. I'm inspecting Qt's 3D Scatter example project and I tried to modify the data item set to plot my own data. The data is plotted except that one axis is not well scaled and my 3D plot looks really messy. I'm looking for a way to adjust this axis. I've tried to change the range and the segment count of the axis, I even tried to set the "AutoAdjustRange" of the axis to true, but nothing seemed to solve the problem.
Would really appreciate some help.
PS: Here's a screen capture of what my 3D scatter graph looks like (the "messy" axis is shown with the red arrow)
I figured this out by creating a CustomFormatter class by subclassing QValue3DAxisFormatter and reimplementing some of its functions (I followed this tutorial). Then I set up my axis formatter to my custom formatter (m_graph->axisZ()->setFormatter(cf);).
Subclassing QValue3DAxisFormatter will not work: it determines where ticks and labels are placed, but not how large the axex actually are.
To do that, you can set the (horizontal) aspect ratio, that is a property of Q3DScatter. The following settings will make the data into a cube volume:
plot->setAspectRatio(1.0);
plot->setHorizontalAspectRatio(1.0);
So, what I am trying to do is to calculate the density profile (HU) along a trajectory (represented by target x,y,z and tangent to it) in a CT. At the moment, I am able to get the profile along a line passing through the target and at a certain distance from the target (entrance). What I would like to do is to get the density profile for a volume (cylinder in this case) of width 1mm or so.
I guess I have to do interpolation of some sort along voxels since depending on the spacing between successive coordinates, several coordinates can point to the same index. For example, this is what I am talking about.
Additionally, I would like to get the density profile for different shapes of the tip of the trajectory, for example:
My idea is that I make a 3 by 3 matrix, representing the shapes of the tip, and convolve this with the voxel values to get HU values corresponding to the tip. How can I do this using ITK/VTK?
Kindly let me know if you need some more information. (I hope the images are clear enough).
If you want to calculate the density drill tip will encounter, it is probably easiest to create a mask of the tip's cutting surface in a resolution higher than your image. Define a transform matrix M which puts your drill into the wanted position in the CT image.
Then iterate through all the non-zero voxels in the mask, transform indices to physical points, apply transform M to them, sample (evaluate) the value in the CT image at that point using an interpolator, multiply it by the mask's opacity (in case of non-binary mask) and add the value to the running sum.
At the end your running sum will represent the total encountered density. This density sum will be dependent on the resolution of your mask of the tip's cutting surface. I don't know how you will relate it to some physical quantity (like resisting force in Newtons).
To get a profile along some path, you would use resample filter. Set up a transform matrix which transforms your starting point to 0,0,0 and your end point to x,0,0. Set the size of the target image to x,1,1 and spacing the same as in source image.
I don't understand your second question. To get HU value at the tip, you would sample that point using a high quality interpolator (example using linear interpolator). I don't get why would the shape of the tip matter.
I'm working on getting all events within 10 miles of the user's location. My models look something like this:
class User(models.Model):
location = models.PointField()
...
class Event(models.Model):
location = models.PointField()
...
In my tests, when I check the distance between the user and an event, I get the value 11.5122663513:
from geopy.distance import vincenty
print vincenty(request.user.location, event.location).miles # 11.5122663513
Yet, when I query for all events within 10 miles of the user's location, that event is returned:
Event.objects.filter(location__distance_lte=(request.user.location, D(mi=10))).count() # 1
Only when I drop the radius to less than 4 miles does the filter take effect:
Event.objects.filter(location__distance_lte=(request.user.location, D(mi=3))).count() # 0
I'm following the docs' example almost exactly, so I don't think my query is the problem.
What could be causing this discrepancy?
This very much depends on what type of database you are using.
Because cartesian math is much faster than geospatial math, the query likely treats coordinates as if they are on a plane rather than on a sphere.
The docs explain it this way:
Most people are familiar with using latitude and longitude to
reference a location on the earth’s surface. However, latitude and
longitude are angles, not distances. In other words, while the
shortest path between two points on a flat surface is a straight line,
the shortest path between two points on a curved surface (such as the
earth) is an arc of a great circle. Thus, additional computation
is required to obtain distances in planar units (e.g., kilometers and
miles). Using a geographic coordinate system may introduce
complications for the developer later on. For example, Spatialite does
not have the capability to perform distance calculations between
geometries using geographic coordinate systems, e.g. constructing a
query to find all points within 5 miles of a county boundary stored as
WGS84.
Portions of the earth’s surface may projected onto a two-dimensional,
or Cartesian, plane. Projected coordinate systems are especially
convenient for region-specific applications, e.g., if you know that
your database will only cover geometries in North Kansas, then you may
consider using projection system specific to that region. Moreover,
projected coordinate systems are defined in Cartesian units (such as
meters or feet), easing distance calculations.
Furthermore, this may be influenced by your database choice. If you are using Postgres/PostGIS, it has the following note in the docs:
In PostGIS, ST_Distance_Sphere does not limit the geometry types
geographic distance queries are performed with. However, these
queries may take a long time, as great-circle distances must be
calculated on the fly for every row in the query. This is because the
spatial index on traditional geometry fields cannot be used.
For much better performance on WGS84 distance queries, consider using
geography columns in your database instead because they are able to
use their spatial index in distance queries. You can tell GeoDjango to
use a geography column by setting geography=True in your field
definition.
You can check this yourself by printing out the raw SQL:
qs = Event.objects.filter(location__distance_lte=(request.user.location, D(mi=10))
print qs.query
Depending on your database type, and the amount of data you plan to store, you have a couple options:
Filter the points a second time in python
Try setting geography=True
Set an explicit SRID
Take a point, buffer it out into a circle with the given radius and then find points within that circle using contains
Use a different database type
If you share the raw query it'll be easier to figure out what is happening.
Looking to store a circle in a geodjango field so I can use the geodjango query __contains to find out if a point is in the circle (similar to what can be done with a PolygonField).
Currently have it stored as a Decimal radius and GeoDjango Point Field, but need a way to query a list of locations in the DB such that these varying circles (point field and radii) contain my search point (long/lat).
Hope it makes sense.
Technically speaking, PostGIS supports CurvePolygon and CircularString geometry types, which can be used to store curved geometries. For example, a 2-unit radius around x=10, y=10 that has been approximated by a 64-point buffered polygon is:
SELECT ST_AsText(ST_LineToCurve(ST_Buffer(ST_MakePoint(10, 10), 2, 16)));
st_astext
------------------------------------------------
CURVEPOLYGON(CIRCULARSTRING(12 10,8 10,12 10))
(1 row)
However, this approach is not typically done, as there is very limited support for this geometry type (i.e., ST_AsSVG, and others won't work). These geometry types will likely cause plenty of grief, and I'd recommend not doing this.
Typically, all geometries are stored as a well supported type: POINT, LINESTRING or POLYGON (with optional MULTI- prefix). With these types, use the ST_DWithin function (e.g., GeoDjango calls this __dwithin, see also this question) to query if another geometry is within a specified distance. For example, if you have a point location, you can see if other geometries are within a certain distance (i.e., radius) from the point.
I'm creating a simulator coded in python and based on ODE (Open Dynamics Engine). For visualization I chose VTK.
For every object in the simulation, I create a corresponding source (e.g. vtkCubeSource), mapper and actor. I am able to show objects correctly and update them as the simulation runs.
I want to add axes to have a point of reference and to show the direction of each axis. Doing that I realized that, by default, X and Z are in the plane of the screen and Y points outwards. In my program I have a different convention.
I've been able to display axes in 2 ways:
1) Image
axes = vtk.vtkAxes()
axesMapper = vtk.vtkPolyDataMapper()
axesMapper.SetInputConnection(axes.GetOutputPort())
axesActor = vtk.vtkActor()
axesActor.SetMapper(axesMapper)
axesActor.GetProperty().SetLineWidth(4)
2) Image (colors do not match with the first case)
axesActor = vtk.vtkAxesActor()
axesActor.AxisLabelsOn()
axesActor.SetShaftTypeToCylinder()
axesActor.SetCylinderRadius(0.05)
In the second one, the user is allowed to set many parameters related to how the axis are displayed. In the first one, I only managed to set the line width but nothing else.
So, my questions are:
Which is the correct way to define and display axes in a 3D scene? I just want them in a fixed position and orientation.
How can I set a different convention for the axes orientation, both for their display and the general visualization?
Well, if you do not mess with objects' transformation matrix for display
purposes, it could probably be sufficient to just put your camera into a
different position while using axes approach 2. The easy methods to adjust
your camera position are: Pitch(), Azimuth() and Roll().
If you mess with object transforms, then apply the same transform to the
axes.
Dženan Zukić kindly answered this question in vtkusers#vtk.org mail list.
http://www.vtk.org/pipermail/vtkusers/2011-November/119990.html