I need to create a Jython script to calculate a minimal threshold value from a
stack of images. It doesn't have to be on one image at a time but on the entire
stack histogram at once.
Is there any method to get this threshold from a stack processor?
This is how I tried to do it but it didn't work:
tempStackps = StackProcessor(tempStack)
minThresholdValue = tempStackps.getMinThreshold()
Thanks, jose.
getMinThreshold() is a method of the ImageProcessor class, returning the current lower threshold level of the image (if it has been set). What I guess you want is the auto-threshold based on the whole stack histogram. You can get it via IJ.setAutoThreshold:
imp = IJ.getImage()
IJ.setAutoThreshold(imp, "Default dark stack")
minThresholdValue = imp.getProcessor().getMinThreshold()
IJ.log(IJ.d2s(minThresholdValue))
Hope that helps.
Related
I am currently implementing an optimization problem with pyomo and since now some hours I get the message that my problem is unbounded. After searching for the issue, I came along one term which seems to be unbounded. I excluded this term from the objective function and it shows that it takes a very high negative value, which supports the assumption that it is unbounded to -Inf.
But I have checked the problem further and it is impossible that the term is unbounded, as following code and results show:
model.nominal_cap_storage = Var(model.STORAGE, bounds=(0,None)) #lower bound is 0
#I assumed very high CAPEX for each storage (see print)
dict_capex_storage = {'battery': capex_battery_storage,
'co2': capex_co2_storage,
'hydrogen': capex_hydrogen_storage,
'heat': capex_heat_storage,
'syncrude': capex_syncrude_storage}
print(dict_capex_storage)
>>> {'battery': 100000000000000000, 'co2': 100000000000000000,
'hydrogen': 1000000000000000000, 'heat': 1000000000000000, 'syncrude': 10000000000000000000}
From these assumptions I already assume that it is impossible that the one term can be unbounded towards -Inf as the capacity has the lower bound of 0 and the CAPEX is a positive fixed value. But now it gets crazy. The following term is has the issue of being unbounded:
model.total_investment_storage = Var()
def total_investment_storage_rule(model):
return model.total_investment_storage == sum(model.nominal_cap_storage[storage] * dict_capex_storage[storage] \
for storage in model.STORAGE)
model.total_investment_storage_con = Constraint(rule=total_investment_storage_rule)
If I exclude the term from the objective function, I get following value after the optimization. It seems, that it can take high negative values.
>>>>
Variable total_investment_storage
-1004724108.3426505
So I checked the term regarding the component model.nominal_cap_storage to see the value of the capacity:
model.total_cap_storage = Var()
def total_cap_storage_rule(model):
return model.total_cap_storage == sum(model.nominal_cap_storage[storage] for storage in model.STORAGE)
model.total_cap_storage_con = Constraint(rule=total_cap_storage_rule)
>>>>
Variable total_cap_storage
0.0
I did the same for the dictionary, but made a mistake: I forgot to delete the model.nominal_cap_storage. But the result is confusing:
model.total_capex_storage = Var()
def total_capex_storage_rule(model):
return model.total_capex_storage == sum(model.nominal_cap_storage[storage] * dict_capex_storage[storage] \
for storage in model.STORAGE)
model.total_capex_storage_con = Constraint(rule=total_capex_storage_rule)
>>>>
Variable total_capex_storage
0.0
So my question is why is the term unbounded and how is it possible that model.total_investment_storage and model.total_capex_storage have different solutions though both are calculated equally? Any help is highly appreciated.
I think you are misinterpreting "unbounded." When the solver says the problem is unbounded, that means the objective function value is unbounded based on the variables and constraints in the problem. It has nothing to do with bounds on variables, unless one of those variable bounds prevents the objective from being unbound.
If you want help on above problem, you need to edit and post the full problem, with the objective function, and (if possible) the error. What you have now is a collection of different snippets of different variations of a problem, which isn't really informative on the overall issue.
I solved the problem by setting a lower bound to the term, which takes a negative value:
model.total_investment_storage = Var(bounds=(0, None)
I am still not sure why this term can take negative values but this solved at least my problem
I am beginner.I just started coding in codeacademy.In a certain level,the gave me a task which is relatate with threshold.So,my question is what is mouseResponse threshold and why should we set a specific threshold?
The actual question is give below:
1.
Three variables let you experiment with the animation physics: mouseResponseThreshold, friction, and rotationForce.
mouseResponseThreshold affects how close the mouse pointer needs to be to affect the dots that make up the letters. The larger the number, the more powerful the effect of the mouse interaction. Experiment with changing the mouseResponseThreshold to different numbers and running your code!
And the hint is "Try starting out by setting the threshold to 150."
What is mouseResponse threshold
This is distance from the mouse position to your target's position (in this case, the target is the "...dots that make up your letters").
Why should I set it
You need to set it so that your code knows at what distance it needs to do a certain operation.
I have a basic implementation of Conway's game of life written in elm running at uminokirin.com.
The source is visible here.
The program let users adjust the size of the toroïdal grid, click on cells to change their status, and randomize the world. It works well for small values (less than 50) on my computer.
However when attempting to use the randomize grid function on bigger grids (the threshold value doesn't seem to be always the same), the program becomes unresponsive without any warning and the only way to recover is to reload the app.
There is zero optimization in the GOL algorithm and using a single svg rectangle for every cell is probably horribly inefficient, but it sill doesn't explain why the program behaves in this way instead of say, slowing down.
Is this the elm runtime giving up? Or some kind of browser safeguard?
More importantly is there a way to prevent this behavior other than arbitrarily capping the maximum size of the grid?
The behavior you are observing is due to a Javascript stack overflow. After pressing the "randomize" button, in the browser console you can see the message "Uncaught RangeError: Maximum call stack size exceeded"
This happens because the randomize function allocates several large temporary variables. In particular, the shuffle function (which is called from the randomize function) appears to allocate two temporary lists that each have one element for every cell in the life grid. Elm may be smart about releasing these on a timely basis but this appears to push it too far.
To fix this you can use a simpler randomize function. The version shown below uses Elm Generators to generate a single list of Dead/Alive values and then initializes the randomized array from that list.
randomize2 : Array Cell -> Int -> Int -> Int -> Array Cell
randomize2 grid gs sd n =
let floatGen = Random.float 0.0 1.0
lifeGen = Random.map (\b -> if (b < toFloat n/100) then Alive else Dead) floatGen
listGen = Random.list (gs*gs) lifeGen
in fst (Random.step listGen (initialSeed sd)) |> fromList
Using this randomize function I was able to resize the grid up to 600x600 and randomize successfully. At that point I stopped testing.
I am trying to detect objects in image on an iphone app.
I am using the cvMatchTemplate function, I manage to see some patterns returned by the cvMatchTemplate function (I chose CV_TM_CCOEFF_NORMED).
Positive Results (result image is 163x371):
http://encryptedpixel.files.wordpress.com/2011/07/photo-13-7-11-11-52-19-am.jpeg
cvMinMaxLoc returns: min (102,244) max(11,210)
The min point is making some sense here, the position of the dark spot is really 102,244 in the result image of 163x371
Negative Results:
cvMinMaxLoc returns: min (114,370) max(0,0)
This is not making sense, there is totally no results, why is there still a min point at 114,370?
I need to know how to analyze these results programatically so that I can say "Hey I found the object!" in objectiveC for iPhone app?
Thanks!
cvMinMaxLoc will always return the position of the minimum and maximum values of their input. It only "doesn't make sense" in your particular application. You should check the value at the returned position for the minimum and do something like threshold it to see if that's a probable match for your template. A template match will yield a very low or a very high value, depending on the method you chose.
Most of my GUI programming was done in Java, where you could use a .pack() method that would set the preferred size the window should have. I'm learning PyGTK now and wondering if such a thing exists in it.
You don't need a pack method. if you don't set a size, the window will adjust to its minimum size.
You can use window.set_size_request(-1,-1) to unset any previous size.
Unfortunately... not that I know of. I use the following trick that uses a variety of GTK and GDK methods to work out the screen size of the current monitor at app startup and resizes the root window to have a certain proportion of fill.
Note that root is a GtkWindow. You could, of course, have two values for SCREEN_FILL for horizontal and vertical fill.
SCREEN_FILL = 0.7
class MainApp(object):
def set_initial_size(self):
screen = self.root.get_screen()
monitor = screen.get_monitor_at_window(self.root.get_window())
geom = screen.get_monitor_geometry(monitor)
self.root.set_resize_mode(gtk.RESIZE_QUEUE)
self.root.resize(
int(geom.width * SCREEN_FILL),
int(geom.height * SCREEN_FILL))