I use following code to draw a point cloud in vispy
# init
view = vispy.sence.widgets.ViewBox()
vis = visuals.Markers()
view.add(vis)
# updata data
vis.set_data(data,
face_color = color,
edge_color=color,
size = 1
)
vispy.app.run
As you can see, I could set the fixed point size for whole data.
How can I set multi size in one data?
You should be able to set the size with a numpy array (one element for every marker point):
https://github.com/vispy/vispy/blob/932d6e499791a423822513549ebd825601345c85/vispy/visuals/markers.py#L517-L518
size : float or array
The symbol size in px.
Related
I have an elevation raster layer in my GeoServer with a single channel ("gray").
The "gray" values is elevations values (signed int16).
I have 2 clients:
The first one is using that elevation values as is.
The second one expect to get [Mapbox Terrain-RGB format][1]
I do not want to convert the "gray scale" format to Mapbox Terrain-RGB format and hold duplicate data in the GeoServer.
I was thinking to use the SLD style and elements to map the elevation value to the appropriate RGB value (with gradient interpolation between discrete values).
For example:
<ColorMap>
<ColorMapEntry color="#000000" quantity="-10000" />
<ColorMapEntry color="#FFFFFF" quantity="1667721.5" />
</ColorMap>
It turns out that the above example does not span the full range of colors but rather creates gray values only.
That is, it seems that it interpolate each color (red, green, blue) independent of each other.
Any idea how to make it interpolate values like that: #000000, #000001, #000002, ... , #0000FF, #000100, ..., #0001FF, ..., #FFFFFF?
Tx.
[1]: https://docs.mapbox.com/data/tilesets/reference/mapbox-terrain-rgb-v1/
I'm trying to do the same with no luck, and i think it can't be done... Check this example. It's a "gradient" [-10000, -5000, -1000, -500 ... 100000000000000000, 5000000000000000000, 1000000000000000000] with the Mapbox color codification. The color progression/interpolation is anything but linear, so i think it can't be emulated in an SLD.
If you have the elevation data in the format you desire then that is the easiest option: it just works. However, if you want a more customized solution, here's what I've done for a project using the Mapbox Terrain-RGB format:
I have a scale of colors from dark blue to light blue to white.
I want to be able to specify how many steps are used from light blue to white (default is 10).
This code uses GDAL Python bindings. The following code snippet was used for testing.
It just outputs the color mapping to a GeoTIFF file.
To get values between 0 and 1, simply use value *= 1/num_steps.
You can use that value in the lookup table to get an RGB value.
If you're only interested in outputting the colors, you can ignore everything involving gdal_translate. The colors will automatically be stored in a single-band GeoTIFF. If you do want to re-use those colors, note that this version ignores alpha values (if present). You can use gdal_translate to add those. That code snippet is also available at my gist here.
import numpy as np
import gdal
from osgeo import gdal, osr
def get_color_map(num_steps):
colors = np.zeros((num_steps, 3), dtype=np.uint8)
colors[:, 0] = np.linspace(0, 255, num_steps, dtype=np.uint8)
colors[:, 1] = colors[::-1, 0]
return colors
ds = gdal.Open('/Users/myusername/Desktop/raster.tif')
band = ds.GetRasterBand(1) # Assuming single band raster
arr = band.ReadAsArray()
arr = arr.astype(np.float32)
arr *= 1/num_steps # Ensure values are between 0 and 1 (or use arr -= arr.min() / (arr.max() - arr.min()) to normalize to 0 to 1)
colors = get_color_map(num_steps) # Create color lookup table
colors[0] = [0, 0, 0] # Set black for no data so it doesn't show up as gray in the final product.
# Create new GeoTIFF with colors included (transparent alpha channel if possible). If you don't care about including the colors in the GeoTIFF, skip this.
cols = ds.RasterXSize
rows = ds.RasterYSize
out_ds = gdal.GetDriverByName('GTiff').Create('/Users/myusername/Desktop/raster_color.tif', cols, rows, 4)
out_ds.SetGeoTransform(ds.GetGeoTransform())
out_ds.SetProjection(ds.GetProjection())
band = out_ds.GetRasterBand(1)
band.WriteArray(colors[arr]) # This can be removed if you don't care about including the colors in the GeoTIFF
band = out_ds.GetRasterBand(2)
band.WriteArray(colors[arr]) # This can be removed if you don't care about including the colors in the GeoTIFF
band = out_ds.GetRasterBand(3)
band.WriteArray(colors[arr]) # This can be removed if you don't care about including the colors in the GeoTIFF
band = out_ds.GetRasterBand(4)
alpha = np.zeros((rows, cols), dtype=np.uint8) # Create alpha channel to simulate transparency of no data pixels (assuming 0 is "no data" and non-zero is data). You can remove this if your elevation values are not 0.
alpha[arr == 0] = 255
band.WriteArray(alpha) # This can be removed if you don't care about including the colors in the GeoTIFF
out_ds.FlushCache()
This issue is also present in Rasterio when using a palette with multiple values. Here is an example.
However, if your raster has n-dimensions or is a masked array, the flip operation can be tricky. Here's a solution based on one of the answers in this stackoverflow question: How to vertically flip a 2D NumPy array?.
Following the example from the documentation page of the centerCropWindow2d function, I am trying to dynamically crop an image based on a 'scale' value that is set by the user. In the end, this code would be used in a loop that would scale an image at different increments, and compare the landmarks between them using feature detection and extraction methods.
I wrote some test code to try and isolate 1 instance of this user-specified image cropping,
file = 'frameCropped000001.png';
image = imread(file);
scale = 1.5;
scaled_width = scale * 900;
scaled_height = scale * 635;
target_size = [scaled_width scaled_height];
scale_window = centerCropWindow2d(size(image), target_size);
image2 = imcrop(image, scale_window);
figure;
imshow(image);
figure;
imshow(image2);
but I am met with this error:
Error using centerCropWindow2d (line 30)
Expected input to be integer-valued.
Error in testRIA (line 20)
scale_window = centerCropWindow2d(size(image), target_size);
Is there no way to do use this function the way I explained above? If not, what's the easiest way to "scale" an image without just resizing it [that is, if I scale it by 0.5, the image stays the same size but is zoomed in by 2x].
Thank you in advance.
I didn't take into account that the height and width for some scales would NOT be whole integers. Since Matlab cannot crop images that are inbetween whole pixel numbers, the "Expected input to be integer-valued." popped up.
I solved my issue by using Math.floor() on the 'scaled_width' and 'scaled_height' variables.
I have a Matlab script that creates a Model Block for each element i found in a text file.
The problem is that all Models are created on each other in the window. So i'm trying to make a loop like:
for each element in text file
I add a Model block
I place right to the previous one
end
So it can look like this:
As you can see on the left, all models are on each other and I would like to place them like the one on the right.
I tried this:
m = mdlrefCountBlocks(diagrammeName)+500;
add_block('simulink/Ports & Subsystems/Model',[diagrammeName '/' component_NameValue]);
set_param(sprintf('%s/%s',diagrammeName,component_NameValue), 'ModelFile',component_NameValue);
size_blk = get_param(sprintf('%s/%s',diagrammeName,component_NameValue),'Position');
X = size_blk(1,1);
Y = size_blk(1,2);
Width = size_blk(1,3);
Height = size_blk(1,4);
set_param(sprintf('%s/%s',diagrammeName,component_NameValue),'Position',[X+m Y X+Width Y+Height]);
Inside the loop but it returns an error Invalid definition of rectangle. Width and height should be positive.
Thanks for helping!
The position property of a block does actually not contain its width and height, but the positions of the corners on the canvas (see Common Block Properties):
vector of coordinates, in pixels: [left top right bottom]
The origin is the upper-left corner of the Simulink Editor canvas before any canvas resizing. Supported coordinates are between -1073740824 and 1073740823, inclusive. Positive values are to the right of and down from the origin. Negative values are to the left of and up from the origin.
So change your code to e.g.:
size_blk = get_param(sprintf('%s/%s',diagrammeName,component_NameValue),'Position');
set_param(sprintf('%s/%s',diagrammeName,component_NameValue),'Position', size_blk + [m 0 0 0]);
I have an image that is 300px width and has to be set at runtime. At design time, the image is a different size and depending on a flag, the image has to be changed. How do I set the image width in C#/VB.NET.
I cast the object as a Picture. The Width property only takes a SINGLE value and presume its inches. How do I tell the picture control that I'm passing in is the pixel size not inches?
Here's an example of how you can set the size in pixels, convert it to inches (as the GrapeCity Team suggests), and apply it to your picture based on a conditional variable:
The following code is added in the Script section of your report:
Sub Detail_Format
Dim intSizeInPixels As Integer = 300
Dim dblSizeInInches as Double = intSizeInPixels / 96
Dim mfFlag As Boolean = True
If mfFlag Then
Picture1.Width = dblSizeInInches
End If
End Sub
I'm looking to take in an image of 162x193 pixels and basically scale it down by 0.125 i.e 162/8 = 20.25 and 193/8 = 24.125. Thus I would like a picture of size 20x24 The only problem I'm currently having is that when I use the imresize function it rounds up the images pixel values i.e I get an image of size 21x25 instead of 20x24. Any way of getting 20x24 or is this problem something I'm going to have to live with? Here is some code:
//Read in original Image
imageBig = imread(strcat('train/',files(i).name));
//Resize the image
image = imresize(imageBig,0.125);
disp(size(image));
It appears that with the scale argument being provided, imresize ceils up the dimensions as your results show. So, I guess an obvious choice is to manually provide it the rounded values as dimensions.
Code
%%// Scaling ratio
scale1 = 0.125;
%%// Get scaled up/down version
[M,N,~] = size(imageBig);
image = imresize(imageBig,[round(scale1*M) round(scale1*N)]);