I've been given a array of center points(longitude and latitude) and corresponding radius,
and try to find all points in these circles.
I known how to find points in the specified circle (the center is (CPLng, CPLat), and radius is 3000m), using the below sql
SELECT l.*, ST_Distance(workplace_geom, ref_geom) as distance
FROM locations AS l
CROSS JOIN (SELECT ST_MakePoint(CPLng, CPLat)::geography AS ref_geom) AS r
WHERE ST_DWithin(workplace_geom, ref_geom, 3000)
In order to get all point in series of circles, should I just union every set of points? or any other alternatives?
As in the question, I computed the contours of each object in an image, using the findContours() function and specifing the RETR_CCOMP hierarchy.
If I compute the area of a parent contour, using the function contourArea(), is opencv considering the whole area comprising all the holes or is it automatically removing the childs contours areas?
I'm asking this in order to be able to remove the area of the holes, after having retrieved the areas of the objects and the holes, if any hole exists.
This is part of the (working) code:
[...]
_, contours0, hierarchy = cv.findContours(thresholded.copy(), cv.RETR_CCOMP, cv.CHAIN_APPROX_SIMPLE)
contours = [cv.approxPolyDP(cnt, 3, True) for cnt in contours0]
for cntIndex in range(0, len(hierarchy[0])):
#if the current contour has no parent
if(hierarchy[0, cntIndex][3]==-1):
#then, it is a parent contour and
#compute its bounding box
boundingBox = cv.contourArea(cnt)
[...]
#otherwise, if it has a parent it must be a child
else:
#which means we found a GAP
gap = contours[cntIndex]
boundingBox = cv.contourArea(cnt)
[...]
Of course I'm storing the gaps and the objects areas in two variables which, for now, are subtracted in order to get the exact surface covered by the object. Is this the right approach? I think it is, but I need to be 100% sure and I wasn't able to find this piece of information.
I am trying to use the layered methods to overlay few spatstat spatial objects. All these objects are for the same window. I have an im layer (density) from a ppp. I want to make this layer a bit transparent in order to have a better visibility of the other objects in the layered object.
How can I control the transparency of this density plot (im)? Is there something like alpha or transparency parameter for the plot.im ?
UPDATE:
library(spatstat)
pipes=simplenet
plot(pipes)
point_net = as.ppp(runifpoint(10, win = Window(pipes)))
point_surface = density(point_net)
plot(point_surface)
layers= layered(point_surface, point_net, pipes)
plot(layers)
Here , I have plotted 3 layers. As you can see the density plot has very dark blues and reds. Yes, I can plot lines and points with different colours to make them visible, but it would nice to do simple stacked line, point plots and add a little bit of transparency to the density (im) plots.
The purpose is just to avoid complex customized plot colours and to explain to colleagues.
thank you.
First the commands from the original post:
library(spatstat)
pipes=simplenet
point_net = as.ppp(runifpoint(10, win = Window(pipes)))
point_surface = density(point_net)
layers= layered(point_surface, point_net, pipes)
plot(layers)
You need to provide a different colourmap to plot.im. There are two
ways you can do this:
Plot each layer individually using add = TRUE for subsequent
layers and provide the colour map when you plot the im object.
Pass a list of plot arguments when you plot the layered object you
have created above.
I find the first option easier for illustration, so I will do that
first. The default colourmap of spatstat is the 29th Kovesi colour
sequence (?Kovesi for more details on these sequences):
def_col <- Kovesi$values[[29]]
head(def_col)
#> [1] "#000C7D" "#000D7E" "#000D80" "#000E81" "#000E83" "#000E85"
To add transparency you can use to.transparent with your choice of
fraction for more/less transparency:
def_col_trans <- to.transparent(def_col, fraction = 0.7)
head(def_col_trans)
#> [1] "#000C7DB3" "#000D7EB3" "#000D80B3" "#000E81B3" "#000E83B3" "#000E85B3"
Now you just need to use this as your colourmap:
plot(point_surface, col = def_col_trans)
plot(point_net, add = TRUE)
plot(pipes, add = TRUE)
To do it with the layered object you have to make a list of plot
argument lists (containing NULL if you don't have additional
arguments):
layer_args <- list(list(col = def_col_trans),
list(NULL),
list(NULL))
plot(layers, plotargs = layer_args)
I am trying to set up a series of vertical axis spans to symbolize different switching positions at different times. For example, in the figure below, switching position 1 (green) happens quite a few times, alternating between other positions.
I plot these spans running a for loop in a list of tuples, each containing the initial and final indexes of each interval to plot the axvspan.
def plotShades(timestamp, intervals, colour):
for i in range(len(intervals)):
md.plt.axvspan(timestamp[intervals[i][0]], timestamp[intervals[i][1]], alpha=0.5, color=colour, label="interval")
This function is then called upon another one, that plots the shades for each different switching position:
def plotAllOutcomes(timestamp, switches):
#switches is a list of 7 arrays indicating when the switcher is at each one of the 7 positions. If the array has a 1 value, the switcher is there. 0 otherwise.
colors = ['#d73027', '#fc8d59', '#fee08b', '#ffffbf', '#d9ef8b', '#91cf60', '#1a9850']
intervals = []
for i in range(len(switches)):
intervals.append(getIntervals(switches[i], timestamp))
plotShades(timestamp, intervals[i], colors[i])
md.plt.legend()
Doing so with the code snippets I've put here (not the best code, I know - I'm fairly new in Python!) the legend ends up having one item for each interval, and that's pretty awful. This is how it looks:
I'd like to get a legend with only 7 items, each for a single color in my plot of axvspans. How can I proceed to do so? I've searched quite extensively but haven't managed to find this situation being asked before. Thank you in advance for any help!!
A small trick you can apply using the fact that labels starting with "_" are ignored:
plt.axvspan( ... , label = "_"*i + "interval")
Thereby a label is only created for the case where i==0.
I have a KML file with placemarkers, each of which has polygon coordinates. I'd like to change the fill color of the polygons on the fly, depending on values I read in from a json file. My understanding is that Google caches kml files, so you can't easily change the fill color of polygons on the fly.
So I'm trying to convert my kml polygons into svg paths so that I can use Raphael to place my polygons on my Google map. Then I can change fill colors with javascript.
But how do I convert polygon coordinates to svg paths, does anyone know?
A sample set of coordinates would be:
<Polygon><outerBoundaryIs><LinearRing><coordinates>-80.098181,40.42127 -80.096479,40.421262 -80.096464,40.421409 -80.096448,40.421551 -80.096444,40.421583 -80.096434,40.421666 -80.096406,40.421931 -80.096389,40.422087 -80.096353,40.422423 -80.09583,40.426101 -80.095525,40.428234 -80.095315,40.429714 -80.095276,40.429989 -80.092585,40.428593 -80.092273,40.428431 -80.09069,40.430519 -80.090384,40.430924 -80.08989,40.430618 -80.089699,40.4305 -80.089499,40.430359 -80.088738,40.429886 -80.088418,40.429688 -80.088254,40.429585 -80.087931,40.429384 -80.087086,40.428859 -80.086867,40.428722 -80.086658,40.428592 -80.086493,40.42849 -80.08617,40.428282 -80.086177,40.428265 -80.08621,40.428188 -80.0864,40.427742 -80.086397,40.42749 -80.086394,40.427125 -80.08631,40.426427 -80.086335,40.425887 -80.086235,40.425409 -80.085776,40.425327 -80.085442,40.42527 -80.084993,40.424585 -80.085076,40.42448 -80.085542,40.423842 -80.085679,40.423125 -80.085659,40.423011 -80.085626,40.422827 -80.085191,40.421758 -80.08467,40.420859 -80.084258,40.420336 -80.083828,40.4201 -80.083078,40.420005 -80.082504,40.420072 -80.081444,40.420196 -80.080888,40.420181 -80.080775,40.420178 -80.080604,40.420173 -80.080122,40.420161 -80.079753,40.420151 -80.07947,40.420144 -80.079287,40.420139 -80.078239,40.420296 -80.077661,40.420418 -80.076213,40.420726 -80.075673,40.420766 -80.075298,40.420719 -80.075127,40.420625 -80.074909,40.420307 -80.075028,40.419779 -80.07539,40.419028 -80.07583,40.41836 -80.076065,40.418108 -80.076528,40.417616 -80.077217,40.417124 -80.077503,40.417002 -80.077725,40.416907 -80.078391,40.416622 -80.078614,40.416528 -80.078657,40.41651 -80.078693,40.416491 -80.078755,40.416457 -80.079174,40.416233 -80.079205,40.416217 -80.079292,40.416128 -80.079439,40.415977 -80.079456,40.41596 -80.079614,40.415473 -80.079604,40.415377 -80.079584,40.415179 -80.07958,40.415168 -80.079539,40.415042 -80.079499,40.414915 -80.079407,40.414785 -80.079742,40.414965 -80.08086,40.415568 -80.081458,40.415889 -80.081535,40.41593 -80.082292,40.416343 -80.08238,40.416392 -80.082597,40.41651 -80.082624,40.416525 -80.082787,40.416614 -80.083508,40.417007 -80.083934,40.417239 -80.084422,40.417505 -80.084622,40.417432 -80.084852,40.417348 -80.085329,40.417179 -80.085419,40.417141 -80.085948,40.41695 -80.086252,40.417184 -80.088463,40.418885 -80.088964,40.418631 -80.089036,40.418595 -80.089145,40.418539 -80.089173,40.418525 -80.089346,40.418438 -80.089376,40.418457 -80.089398,40.418471 -80.089964,40.418827 -80.090299,40.419055 -80.091306,40.419739 -80.091642,40.419967 -80.091803,40.420088 -80.091966,40.420043 -80.092445,40.419915 -80.092561,40.419885 -80.096792,40.418748 -80.098853,40.41815 -80.098868,40.418242 -80.09943,40.421273 -80.098181,40.42127</coordinates></LinearRing></outerBoundaryIs></Polygon>
Disclaimer: I'm a bit rusty on geodetics, but think your #1 problem here is the coordinate system - lat, lng are projection-dependent data points, whereas your screen is a flat pixel one. What you need to do is convert these to northing and easting points first.
There is a projection conversion library out there called proj.4 - use this to convert your coordinates. If needed, there is a javascript port of it that you can easily adapt for your use at https://trac.osgeo.org/proj/
Generic conversion process would go like this (LAT, LNG are actual coordinates.)
var source = new Proj4js.Proj('WGS84');
var dest = new Proj4js.Proj('GOOGLE');
var p = new Proj4js.Point( LATITUDE, LONGITUDE ); // replace with actual coords!
var pdest = Proj4js.transform(source, dest, p);
At this point, pdest.x and pdest.y will contain your SVG-compatible coordinates.
After your coordinates are converted to pixel units, simply plot them - and mind the range and units. Northing and easting coordinates will be in 800,000 range, so you will likely be applying some transformations, such as translation and scaling.
End result should look like this (being rusty, I may have messed up and flipped lat/lng around, etc.)
Here's a working jsfiddle with a conversion and plot: http://jsfiddle.net/LPzKV/1/