Blender: How can i exclude an object from another so that I'm left with an object with holes in it?
I'm currently trying to create a 3.951x2.610x0.05 box with holes across it. The holes are 0.1x0.1x0.5. I select them all but I don't know how to exclude them from the box
The hole height should be the same as box height, right?
Say it's both 0.5 in below example script:
import bpy
epsilon = 10e-5
bpy.ops.mesh.primitive_cube_add()
bpy.ops.transform.resize(value=(3.951,2.610,0.5))
obj_A = bpy.context.object
bpy.ops.mesh.primitive_cube_add()
bpy.ops.transform.resize(value=(0.1,0.1,0.5+epsilon))
obj_B = bpy.context.object
bpy.ops.object.select_all(action='DESELECT')
bpy.context.scene.objects.active = obj_A
obj_modifier = obj_A.modifiers.new('myBoolModifier', 'BOOLEAN')
obj_modifier.object = obj_B
obj_modifier.operation = 'DIFFERENCE'
bpy.ops.object.modifier_apply(apply_as='DATA', modifier="myBoolModifier")
bpy.context.scene.objects.unlink(obj_B)
The output:
Related
I want to resize my text in plot_net but none of the options are working for me. I am trying
p <- plot_net(physeqP, maxdist = 0.4, point_label = "ID", color = "Cond", shape = "Timeperiod") p + geom_text(size=15)
This gives me error
"Error: geom_text requires the following missing aesthetics: x, y,
label".
Can anyone please tell me how can I fix the issue?
I dont want to resize legends or the axis, but the nodes text.
this image is drawn using phyloseq but since the font size is very small, i want to make it prominent.
Without an example it's hard to reproduce.
p <- plot_net(physeqP, maxdist = 0.4, point_label = "ID"
, color = "Cond", shape = "Timeperiod", cex_val = 2)
I believe this is with the NeuralNetTools package.
Try using: cex_val numeric value indicating size of text labels, default 1
https://www.rdocumentation.org/packages/NeuralNetTools/versions/1.5.0/topics/plotnet
I am trying to plot two columns of raw data (I have used melt to combine them into one data frame) and then add separate error bars for each. However, I want to make the raw data for each column one pair of colors and the error bars another set of colors, but I can't seem to get it to work. The plot I am getting is at the link below. I want to have different color pairs for the raw data and for the error bars. A simple reproducible example is coded below, for illustrative purposes.
dat2.m<-data.frame(obs=c(2,4,6,8,12,16,2,4,6),variable=c("raw","raw","raw","ip","raw","ip","raw","ip","ip"),value=runif(9,0,10))
c <- ggplot(dat2.m, aes(x=obs, y=value, color=variable,fill=variable,size = 0.02)) +geom_jitter(size=1.25) + scale_colour_manual(values = c("blue","Red"))
c<- c+stat_summary(fun.data="median_hilow",fun.args=(conf.int=0.95),aes(color=variable), position="dodge",geom="errorbar", size=0.5,lty=1)
print(c)
[1]: http://i.stack.imgur.com/A5KHk.jpg
For the record: I think that this is a really, really bad idea. Unless you have a use case where this is crucial, I think you should re-examine your plan.
However, you can get around it by adding a new set of variables, padded with a space at the end. You will want/need to play around with the legends, but this should work (though it is definitely ugly):
dat2.m<- data.frame(obs=c(2,4,6,8,12,16,2,4,6),variable=c("raw","raw","raw","ip","raw","ip","raw","ip","ip"),value=runif(9,0,10))
c <- ggplot(dat2.m, aes(x=obs, y=value, color=variable,fill=variable,size = 0.02)) +geom_jitter(size=1.25) + scale_colour_manual(values = c("blue","Red","green","purple"))
c<- c+stat_summary(fun.data="median_hilow",fun.args=(conf.int=0.95),aes(color=paste(variable," ")), position="dodge",geom="errorbar", size=0.5,lty=1)
print(c)
One way around this would be to use repetitive calls to geom_point and stat_summary. Use the data argument of those functions to feed subsets of your dataset into each call, and set the color attribute outside of aes(). It's repetitive and somewhat defeats the compactness of ggplot, but it'd do.
c <- ggplot(dat2.m, aes(x = obs, y = value, size = 0.02)) +
geom_jitter(data = subset(dat2.m, variable == 'raw'), color = 'blue', size=1.25) +
geom_jitter(data = subset(dat2.m, variable == 'ip'), color = 'red', size=1.25) +
stat_summary(data = subset(dat2.m, variable == 'raw'), fun.data="median_hilow", fun.args=(conf.int=0.95), color = 'pink', position="dodge",geom="errorbar", size=0.5,lty=1) +
stat_summary(data = subset(dat2.m, variable == 'ip'), fun.data="median_hilow", fun.args=(conf.int=0.95), color = 'green', position="dodge",geom="errorbar", size=0.5,lty=1)
print(c)
For my Python class were using turtle graphics.
We have too draw a target that appears at a random location on the screen. Got that.
Then a pop up window appears asking for what you think the coordinates of the target are. First the pop up box asks you to enter the x coordinate then it asks you to enter the y coordinate.
I'm having trouble saving the users inputed integers from my Tkinter window into variables I can use later in the program.
from Tkinter import *
window = Tk()
window.title("Player Input")
window.geometry('+350+130')
thexinput = IntVar()
L1 = Label(window, text="Enter the x coordinate for Mike")
L1.pack( side = LEFT)
E1= Entry(window, textvariable= thexinput, bd =5)
E1.pack(side = RIGHT)
def userinput():
global inp
a = raw_input(thexinput.get())
inp = a
b = Button(window, text = 'Submit', command = userinput)
b.pack(side = BOTTOM)
window.mainloop()
You don't need to use raw_input, you just need to call the get method of the entry widget.
a = thexinput.get()
Hello im new to Gdal and im struggling a with my codes. Everything seems to go well in my code mut the output bands at the end is empty. The no data value is set to 256 when i specify 255, so I don't really know whats wrong. Thanks any help will be appreciated!!!
Here is my code
from osgeo import gdal
from osgeo import gdalconst
from osgeo import osr
from osgeo import ogr
import numpy
#graticule
src_ds = gdal.Open("E:\\NFI_photo_plot\\photoplotdownloadAllCanada\\provincial_merge\\Aggregate\\graticule1.tif")
band = src_ds.GetRasterBand(1)
band.SetNoDataValue(0)
graticule = band.ReadAsArray()
print('graticule done')
band="none"
#Biomass
dataset1 = gdal.Open("E:\\NFI_photo_plot\\photoplotdownloadAllCanada\provincial_merge\\Aggregate\\Biomass_NFI.tif")
band1 = dataset1.GetRasterBand(1)
band1.SetNoDataValue(-1)
Biomass = band1.ReadAsArray()
maskbiomass = numpy.greater(Biomass, -1).astype(int)
print("biomass done")
Biomass="none"
band1="none"
dataset1="none"
#Baseline
dataset2 = gdal.Open("E:\\NFI_photo_plot\\Baseline\\TOTBM_250.tif")
band2 = dataset2.GetRasterBand(1)
band2.SetNoDataValue(0)
baseline = band2.ReadAsArray()
maskbaseline = numpy.greater(baseline, 0).astype(int)
print('baseline done')
baseline="none"
band2="none"
dataset2="none"
#sommation
biosource=(graticule+maskbiomass+maskbaseline)
biosource1=numpy.uint8(biosource)
biosource="none"
#Écriture
dst_file="E:\\NFI_photo_plot\\photoplotdownloadAllCanada\\provincial_merge\\Aggregate\\Biosource.tif"
dst_driver = gdal.GetDriverByName('GTiff')
dst_ds = dst_driver.Create(dst_file, src_ds.RasterXSize,
src_ds.RasterYSize, 1, gdal.GDT_Byte)
#projection
dst_ds.SetProjection( src_ds.GetProjection() )
dst_ds.SetGeoTransform( src_ds.GetGeoTransform() )
outband=dst_ds.GetRasterBand(1)
outband.WriteArray(biosource1,0,0)
outband.SetNoDataValue(255)
biosource="none"
graticule="none"
A few pointers:
Where you have ="none", these need to be = None to close/cleanup the objects, otherwise you are setting the objects to an array of characters: n o n e, which is not what you intend to do.
Why do you have band1.SetNoDataValue(-1), while other NoData values are 0? Is this data source signed or unsigned? If unsigned, then -1 doesn't exist.
When you open rasters with gdal.Open without the access option, it defaults to gdal.GA_ReadOnly, which means your subsequent SetNoDataValue calls do nothing. If you want to modify the dataset, you need to use gdal.GA_Update as your second parameter to gdal.Open.
Another strategy to create a new raster is to use driver.CreateCopy; see the tutorial for details.
I asked this question yesterday about storing a plot within an object. I tried implementing the first approach (aware that I did not specify that I was using qplot() in my original question) and noticed that it did not work as expected.
library(ggplot2) # add ggplot2
string = "C:/example.pdf" # Setup pdf
pdf(string,height=6,width=9)
x_range <- range(1,50) # Specify Range
# Create a list to hold the plot objects.
pltList <- list()
pltList[]
for(i in 1 : 16){
# Organise data
y = (1:50) * i * 1000 # Get y col
x = (1:50) # get x col
y = log(y) # Use natural log
# Regression
lm.0 = lm(formula = y ~ x) # make linear model
inter = summary(lm.0)$coefficients[1,1] # Get intercept
slop = summary(lm.0)$coefficients[2,1] # Get slope
# Make plot name
pltName <- paste( 'a', i, sep = '' )
# make plot object
p <- qplot(
x, y,
xlab = "Radius [km]",
ylab = "Services [log]",
xlim = x_range,
main = paste("Sample",i)
) + geom_abline(intercept = inter, slope = slop, colour = "red", size = 1)
print(p)
pltList[[pltName]] = p
}
# close the PDF file
dev.off()
I have used sample numbers in this case so the code runs if it is just copied. I did spend a few hours puzzling over this but I cannot figure out what is going wrong. It writes the first set of pdfs without problem, so I have 16 pdfs with the correct plots.
Then when I use this piece of code:
string = "C:/test_tabloid.pdf"
pdf(string, height = 11, width = 17)
grid.newpage()
pushViewport( viewport( layout = grid.layout(3, 3) ) )
vplayout <- function(x, y){viewport(layout.pos.row = x, layout.pos.col = y)}
counter = 1
# Page 1
for (i in 1:3){
for (j in 1:3){
pltName <- paste( 'a', counter, sep = '' )
print( pltList[[pltName]], vp = vplayout(i,j) )
counter = counter + 1
}
}
dev.off()
the result I get is the last linear model line (abline) on every graph, but the data does not change. When I check my list of plots, it seems that all of them become overwritten by the most recent plot (with the exception of the abline object).
A less important secondary question was how to generate a muli-page pdf with several plots on each page, but the main goal of my code was to store the plots in a list that I could access at a later date.
Ok, so if your plot command is changed to
p <- qplot(data = data.frame(x = x, y = y),
x, y,
xlab = "Radius [km]",
ylab = "Services [log]",
xlim = x_range,
ylim = c(0,10),
main = paste("Sample",i)
) + geom_abline(intercept = inter, slope = slop, colour = "red", size = 1)
then everything works as expected. Here's what I suspect is happening (although Hadley could probably clarify things). When ggplot2 "saves" the data, what it actually does is save a data frame, and the names of the parameters. So for the command as I have given it, you get
> summary(pltList[["a1"]])
data: x, y [50x2]
mapping: x = x, y = y
scales: x, y
faceting: facet_grid(. ~ ., FALSE)
-----------------------------------
geom_point:
stat_identity:
position_identity: (width = NULL, height = NULL)
mapping: group = 1
geom_abline: colour = red, size = 1
stat_abline: intercept = 2.55595281266726, slope = 0.05543539319091
position_identity: (width = NULL, height = NULL)
However, if you don't specify a data parameter in qplot, all the variables get evaluated in the current scope, because there is no attached (read: saved) data frame.
data: [0x0]
mapping: x = x, y = y
scales: x, y
faceting: facet_grid(. ~ ., FALSE)
-----------------------------------
geom_point:
stat_identity:
position_identity: (width = NULL, height = NULL)
mapping: group = 1
geom_abline: colour = red, size = 1
stat_abline: intercept = 2.55595281266726, slope = 0.05543539319091
position_identity: (width = NULL, height = NULL)
So when the plot is generated the second time around, rather than using the original values, it uses the current values of x and y.
I think you should use the data argument in qplot, i.e., store your vectors in a data frame.
See Hadley's book, Section 4.4:
The restriction on the data is simple: it must be a data frame. This is restrictive, and unlike other graphics packages in R. Lattice functions can take an optional data frame or use vectors directly from the global environment. ...
The data is stored in the plot object as a copy, not a reference. This has two
important consequences: if your data changes, the plot will not; and ggplot2 objects are entirely self-contained so that they can be save()d to disk and later load()ed and plotted without needing anything else from that session.
There is a bug in your code concerning list subscripting. It should be
pltList[[pltName]]
not
pltList[pltName]
Note:
class(pltList[1])
[1] "list"
pltList[1] is a list containing the first element of pltList.
class(pltList[[1]])
[1] "ggplot"
pltList[[1]] is the first element of pltList.
For your second question: Multi-page pdfs are easy -- see help(pdf):
onefile: logical: if true (the default) allow multiple figures in one
file. If false, generate a file with name containing the
page number for each page. Defaults to ‘TRUE’.
For your main question, I don't understand if you want to store the plot inputs in a list for later processing, or the plot outputs. If it is the latter, I am not sure that plot() returns an object you can store and retrieve.
Another suggestion regarding your second question would be to use either Sweave or Brew as they will give you complete control over how you display your multi-page pdf.
Have a look at this related question.