The project aims to build a program counter.
The description are as follows:
// This file is part of www.nand2tetris.org
// and the book "The Elements of Computing Systems"
// by Nisan and Schocken, MIT Press.
// File name: projects/03/a/PC.hdl
/**
* A 16-bit counter with load and reset control bits.
* if (reset[t] == 1) out[t+1] = 0
* else if (load[t] == 1) out[t+1] = in[t]
* else if (inc[t] == 1) out[t+1] = out[t] + 1 (integer addition)
* else out[t+1] = out[t]
*/
I figured out all the possibilities as follows
All possible output
Then here I go:
CHIP PC
{
IN in[16],load,inc,reset;
OUT out[16];
PARTS:
// Put your code here:
Register(in=in, load=true, out=thein);
Register(in=in, load=false, out=theout);
Inc16(in=theout, out=forinc);
Register(in=forinc, load=true, out=theinc);
Mux8Way16(a=theout, b=false, c=theinc, d=false, e=thein, f=false, g=thein, h=false, sel[2]=load, sel[1]=inc, sel[0]=reset, out=out);
}
I tried many times but all failed when the clock load to time 1+ or something like this.
Since the register defined here is out(t+1) = out(t)
what is the output of time ?+.I found it really annoying.
Any suggestions will be appreciated.
Some observations:
You're storing the output in a register, which is good. However, note that the register output is also one of your inputs -- it is out[t].
You don't need a big Mux8Way16. There are 4 possible different outputs, so you can either use multiple Mux16s in a cascade or (extra credit) a single Mux4Way16 with some extra logic to compute the two selection bits.
I usually found that the simplest way to do things was first compute all the possible outputs (in this case, 0, input, register+1 or register) and then have the logic to decide which one of those actually gets output.
Good luck. You are very close.
Related
I have 25K tif files (please don't ask why) that I want to organize into stacks on image J. Basically for each region of interest (ROI), there are 50 images which breaks down into 25 z-planes for two channels. I want everything in a single stack. And I'd like to batch process the whole folder without opening 50 images 500 times at a time. I've attached a picture of what the file names look like:
Folder organization
r01c01f01p01-ch1.tif - the first 10 characters are unique ID to each ROI, then plane number (p01) then channel - ch1 or ch2, then file extension
Here's what I have so far (which I cobbled together based on other macros so this may not make sense...).This is using the ImageJ macros language.
//Processing loop to process each file in the folder.
for (i=0; i<list.length; i++) {
showProgress(i+1, list.length);
if (endsWith(list[i], ".tif")) { // skip the subfolder (I create a subfolder earlier in the macros)
print("-- Processing file: " + list[i] + " --");
open(dir+list[i]);
imageTitle= getTitle();
newTitle = substring(imageTitle, 0, lengthOf(imageTitle)-10); // r01c01f01p, cutting off plane number and then the rest to just get the ROI ID
//This is where I'm stuck:
// find all files containing newTitle and open them (which would be 50 at a time), then run the following macros on them
run("Images to Stack", "name=Ch1 title=[] use");
run("Duplicate...", "title=Ch2 duplicate");
selectWindow("Ch1");
run("Slice Remover", "first=1 last=50 increment=2");
selectWindow("Ch2");
run("Slice Remover", "first=2 last=50 increment=2");
run("Merge Channels...", "c1=Ch1 c2=Ch2 create");
saveAs("tiff", dirNew + newTitle + "_Stack.tif");
//Close(All)?
}
}
print("-- Done --");
showStatus("Finished.");
setBatchMode(false); // Exit batch mode
run("Collect Garbage");
Thank you!
You could do something like:
for (plane=1; plane<51; plane++) {
open(newTitle+plane+"-ch1.tif");
open(newTitle+place+"-ch2.tif");
}
Which would take care of the opening. I would be inclined to have a loop prior to this which would collate the number of unique "newTitle"'s, as your current setup would end up doing something like opening the first item, assembling the combined TIF, and then repeat the process 25K times if I understand it correctly.
Given that you know the number of unique "r01c01f01p" values, in principle you could do a set of stacked loops akin to:
newTitleArray = newArray();
for (r=1; r<50; r++) {
titleBit = "r0" + toString(r);
for (c=1; c<501; c++) {
titleBit = titleBit + "f0"...
Alternatively, you could set up a loop where you check for unique "r01c01f01p" values and add them to an array. In any case, you'd replace the for "list" loop with the for "newTitleArray" loop, and then continue onto the opener I listed above, instead of your existing one.
If I am understanding correctly, it seems like you might do well to stack by channel first, then merge the two. I am not 100% sure, but I think you could potentially use a macro I have already created to do that. It was originally meant to batch process terabytes of 5D data, so it should be very comfortable handling your volume of images. It is not exactly what you are looking for, but should be super easy to modify (I went a little overboard with the commenting in the code), and I think the only thing it does that you might rather it not is produce max projects from the inputs. I'll throw a link here and look for your reply. If it's of interest, let me know and we can work to make it suit your needs together :-) Otherwise, if you could provide a little more detail about where you're getting stuck and/or where I may have misunderstood, I will do my very best to help!
https://github.com/evanjkiely/FIJIMacros
I'm using late acceptance as local search algorithm and here is how it actually picks moves:
If my forager is 5, it'll pick 5 moves and then get 1 random move to be applied for every step.
At every step it only picks moves that are increasing scores ie greedy picking across steps.
Forager.pickMove()
public LocalSearchMoveScope pickMove(LocalSearchStepScope stepScope) {
stepScope.setSelectedMoveCount(selectedMoveCount);
stepScope.setAcceptedMoveCount(acceptedMoveCount);
if (earlyPickedMoveScope != null) {
return earlyPickedMoveScope;
}
List<LocalSearchMoveScope> finalistList = finalistPodium.getFinalistList();
if (finalistList.isEmpty()) {
return null;
}
if (finalistList.size() == 1 || !breakTieRandomly) {
return finalistList.get(0);
}
int randomIndex = stepScope.getWorkingRandom().nextInt(finalistList.size());// should have checked for best here
return finalistList.get(randomIndex);
}
I have two questions:
In first, can we make forager to pick the best of 5 instead of pick 1 randomly.
Can we allow move to pick that degrades score but can increase score later(no way to know it)?
Look for acceptedCountLimit and selectedCountLimit in the docs. Those do exactly that.
That's already the case (especially with Late Acceptance and Simulated Annealing). In the DEBUG log, just look at the step score vs the best score. Or ask for the step score statistic in optaplanner-benchmark.
I am new to coding, and would like help in understanding the script used by the PsychoPy program.
To be more specific, I would like to understand the codes that are in line 6 to 15. I am aware that this is used to manage the multiple trials, but I am hoping someone can help me clarify those bits? I also noted that removing the codes from line 6-8 doesn't change the experiment, but removing the codes from line 10-15 essentially stop the experiment from running.
trialsAll = data.TrialHandler(trialList=data.importConditions('trialType.xlsx'), nReps=10, method='random', name='trialsAll', dataTypes='corr')
thisExp = data.ExperimentHandler(name='Ours')
thisExp.addLoop(trialsAll) #adds a loop to the experiment
thisTrial = trialsAll.trialList[0]
if thisTrial != None:
for paramName in thisTrial.keys():
exec(paramName + '= thisTrial.' + paramName)
# Loop through trials
for thisTrial in trialsAll:
currentLoop=trialsAll
if thisTrial != None:
for paramName in thisTrial.keys():
exec(paramName + '=thisTrial.' + paramName)
My second question would be about getting responses. Is there a reason that thisResp is equalled to None?
#get response
thisResp=None
while thisResp==None:
allKeys=event.waitKeys()
Thanks a lot for any help. I appreciate it.
Regards,
Cash
if thisTrial != None:
for paramName in thisTrial.keys():
exec(paramName + '= thisTrial.' + paramName)
This code allows the use of abbreviations. For example, say your conditions file has a field called 'angle', you can refer to this directly rather than via the keys of that trial's dictionary (e.g. thisTrial['angle'] ) or using dot notation ( thisTrial.angle ). i.e., in this example:
angle = thisTrial.angle
for thisTrial in trialsAll:
is fundamental to running a psychoPy trial loop. It will cycle though each trial that is contained in the TrialHandler object that is created to manage trials, connected to a given conditions file.
#get response
thisResp=None
while thisResp==None:
allKeys=event.waitKeys()
The line 'while thisResp==None:' requires that the variable 'thisResp' actually exists if we are going to be able to check its value. So in the immediately preceding line, it is created and given an initial null value so that the next line will run OK. Note that at this stage, it is just an arbitrary variable, which doesn't have any actual connection to the subject's response. That will presumably occur later in the code, when it gets assigned a value other than None.
I would like to write a Gatan DigitalMicrograph script to acquire multiple EELS spectrum images continuously. If there is a command to obtain Spectrum Image (SI) data, and store the three-dimensional image to an array, I will achieve my plan. However, I could not find appropriate commands for SI imaging mode from reference manual. What command should I use in this case? Do you have a helpful knowledge for my purpose? It will be appreciated if you share some wisdom.
A short demo-script of how to use the SIAcquisition commands for multiple iterations of SI acquisition and "renaming" the acquired data sets.
// Assumptions:
// - GMS 2.3 used
// - Valid survey image and ROI already assigned
// - SI array size already defined
// - Signals and other SI settings made
number SIx, SIy
SIGetFieldValue( "2D Array, X samples", SIx )
SIGetFieldValue( "2D Array, Y samples", SIy )
Result("\n SI size:"+ SIx + "x" + SIy )
// Start SI
number nSI = 3
for (number i=0; i<nSI; i++ )
{
SIInvokeButton( "Start/Stop", 1 )
while(SIIsAcquisitionActive()) yield()
sleep(0.5) // Small delay needed to allow DM finish SI acquisition clean-up
// Find (and rename) SI DataSets
number nImgDoc = CountImageDocuments()
string findStr = "Spectrum Image"
for (number d=0; d<nImgDoc; d++ )
{
string docName = GetImageDocument(d).ImageDocumentGetName()
if ( find(docName,findStr) == (len(docName)-len(findStr)) )
{
GetImageDocument(d).ImageDocumentSetName( docName + "#"+(d+1) )
}
}
}
OKDialog( "Done" )
If you have the spectrum-imaging plugin installed, then the F1 help file will have a section on STEM SI scripting commands here...
However, the commands described there will allow the acquisition of one SI after the other. Each will start anew with the same overhead you get when repeatedly starting SI acquisition via the UI.
I've got the impression you want to get a "faster" repeated SI.
Unfortunately, no commands exist which could easily give you that.
However, you might be able to create a "work-arround" solution by the following idea (untested):
Set up a STEM SI with multiple-frames (Each frame pass will be summed into the same container)
Use the "SI HookUP Scripts" on a per-pixel basis (Pixel end) to catch the "last" acquired SI point (before the new frame starts). Use this to copy the existing data into a new container and set the orignal back to zero.
Alternative:
You might also be able to use the "Correction start" HookUp script point, if you set spatial drift-correction to perform at end of frame...
The above will only work with software-synchronized SI's. For hardware-synchronized, it becomes more tricky, but you might be able to do something similar with a "ImageUpdate" event-listener.
I know other people have asked similar questions in past but I am still stuck on how to solve the problem and was hoping someone could offer some help. Using PsychoPy, I would like to present different images, specifically 16 emotional trials, 16 neutral trials and 16 face trials. I would like to pseudo randomize the loop such that there would not be more than 2 consecutive emotional trials. I created the experiment in Builder but compiled a script after reading through previous posts on pseudo randomization.
I have read the previous posts that suggest creating randomized excel files and using those, but considering how many trials I have, I think that would be too many and was hoping for some help with coding. I have tried to implement and tweak some of the code that has been posted for my experiment, but to no avail.
Does anyone have any advice for my situation?
Thank you,
Rae
Here's an approach that will always converge very quickly, given that you have 16 of each type and only reject runs of more than two emotion trials. #brittUWaterloo's suggestion to generate trials offline is very good--this what I do myself typically. (I like to have a small number of random orders, do them forward for some subjects and backwards for others, and prescreen them to make sure there are no weird or unintended juxtapositions.) But the algorithm below is certainly safe enough to do within an experiment if you prefer.
This first example assumes that you can represent a given trial using a string, such as 'e' for an emotion trial, 'n' neutral, 'f' face. This would work with 'emo', 'neut', 'face' as well, not just single letters, just change eee to emoemoemo in the code:
import random
trials = ['e'] * 16 + ['n'] * 16 + ['f'] * 16
while 'eee' in ''.join(trials):
random.shuffle(trials)
print trials
Here's a more general way of doing it, where the trial codes are not restricted to be strings (although they are strings here for illustration):
import random
def run_of_3(trials, obj):
# detect if there's a run of at least 3 objects 'obj'
for i in range(2, len(trials)):
if trials[i-2: i+1] == [obj] * 3:
return True
return False
tr = ['e'] * 16 + ['n'] * 16 + ['f'] * 16
while run_of_3(tr, 'e'):
random.shuffle(tr)
print tr
Edit: To create a PsychoPy-style conditions file from the trial list, just write the values into a file like this:
with open('emo_neu_face.csv', 'wb') as f:
f.write('stim\n') # this is a 'header' row
f.write('\n'.join(tr)) # these are the values
Then you can use that as a conditions file in a Builder loop in the regular way. You could also open this in Excel, and so on.
This is not quite right, but hopefully will give you some ideas. I think you could occassionally get caught in an infinite cycle in the elif statement if the last three items ended up the same, but you could add some sort of a counter there. In any case this shows a strategy you could adapt. Rather than put this in the experimental code, I would generate the trial sequence separately at the command line, and then save a successful output as a list in the experimental code to show to all participants, and know things wouldn't crash during an actual run.
import random as r
#making some dummy data
abc = ['f']*10 + ['e']*10 + ['d']*10
def f (l1,l2):
#just looking at the output to see how it works; can delete
print "l1 = " + str(l1)
print l2
if not l2:
#checks if second list is empty, if so, we are done
out = list(l1)
elif (l1[-1] == l1[-2] and l1[-1] == l2[0]):
#shuffling changes list in place, have to copy it to use it
r.shuffle(l2)
t = list(l2)
f (l1,t)
else:
print "i am here"
l1.append(l2.pop(0))
f(l1,l2)
return l1
You would then run it with something like newlist = f(abc[0:2],abc[2:-1])