Clonezilla Clone Partition Only – Super User

I am trying to clone a 120GB system partition from a 160GB source drive.
The remaining 40GB on the source drive is empty & un-formatted.

The target drive is a 120GB drive. I do not want to use
a larger drive because of BIOS constraints.

Can Clonezilla do it ?
What are the steps or line parameters ?

FFPLAY/FFMPEG (Capture Device) – Super User

I’m copying some VHS tapes with my Windows 10 computer using FFPLAY/FFMPEG (Capture Device) in a Batch File.

FFPLAY can view the tape this way, and it’s great.

FFPLAY.EXE -hide_banner -f dshow -rtbufsize 1024M -i video=”Roxio Video Capture USB”:audio=”Line (Roxio Video Capture USB)”

and this will Convert to MP4, and it’s great too. (I had some Synch problems but I added “-async 1 -vsync 1” and it’s OK)

ffmpeg -fflags +genpts -async 1 -vsync 1 -f dshow -rtbufsize 1024M -i video=”Roxio Video Capture USB”:audio=”Line (Roxio Video Capture USB)” -filter:v fps=29.97 -aspect 4:3 -c:v libx264 -preset ultrafast -tune zerolatency -crf 20 -pix_fmt yuv420p -c:a aac -strict -2 -ac 2 -b:a 128k -t 03:00:00 -async 1 -vsync 1 “Good Movie.MP4”

BUT, is there anyway to both runs simultaneously so I can view the tape and stop the Convert?

here’s the Batch File:

@ECHO OFF
cd /d C:Movies

Cls
@Echo.
@Echo.
@Echo.
@Echo Converting
title File Good Movie.MP4
@Echo.

FFPLAY.EXE -hide_banner -f dshow -rtbufsize 1024M -i video=”Roxio Video Capture USB”:audio=”Line (Roxio Video Capture USB)”

@Echo.
@ping 127.0.0.1 -n 2 -w 2000 > nul
@ping 127.0.0.1 -n %1% -w 2000> nul

ffmpeg -fflags +genpts -async 1 -vsync 1 -f dshow -rtbufsize 1024M -i video=”Roxio Video Capture USB”:audio=”Line (Roxio Video Capture USB)” -filter:v fps=29.97 -aspect 4:3 -c:v libx264 -preset ultrafast -tune zerolatency -crf 20 -pix_fmt yuv420p -c:a aac -strict -2 -ac 2 -b:a 128k -t 03:00:00 -async 1 -vsync 1 “Good Movie.MP4”

@Echo.
@Echo.

pause

Thanx Guys

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mesh – Which Terrain LOD algorithm should I use for super large terrain?

My game needs a terrain, the requirements are:

  1. Freely Zoom in & zoom out, like GoogleEarth. Max resolution when zooming in ~100 meter, Max range when zooming out ~2000km (a whole country scale).
  2. Freely fly over to any direction with any height; Freely rotate camera; Framerate should not a bottleneck for all those basic camera movement.
  3. Support large heightmap data. I got mine real world elevation data from NASA with 7.5arc resolution, around 30k * 15k for a whole country.
  4. Also I need to consider the spherical earth surface curvature other than using a planar map. But this should be easy if I just map each vertex into spherical coordinates. I am not build the whole planetary LOD so it’s not even a problem.

I noticed there are many different LOD algorithm out there. For example:

  • ROAM: very classic algorithm, most done on CPU;
  • Geomipmapping: store the whole heightmap with best resolution as vertex buffer, with different LOD in vertex index. Then determine LOD and draw range in vertex index at runtime.
  • CDLOD:
  • Geo Clipmapping: I am feeling excited about this one since it claims to load all 200k * 100k US heightmap into video card memory and compressed ~300M, it seems to meet all my requirements. see source paper. And this is paper in 2004 and think about the video card at that time!

That’s pretty much all I know about terrain LOD.
I am not familiar recently study/research in this area.
Is Geo clipmapping my best option? What else algorithms are also useful to consider?

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python – Super Greedy Algorithm for Exact Three Cover

I had trouble solving instances of Exact Three Cover with 100 units in input C. All in a reasonable amount of time. Mainly because the problem is NP-complete. So I came up with an approximate solution (Don’t ask me the ratio for correctness, because I don’t know) I have gotten 100, 500 and 1000 units in C to return correct solutions. Screenshot of 3000 units in C. And, here is a link to my approximation algorithm where C has 100 units.

I believe that if I don’t have significant amounts of chaff (sets that could cause my algorithm to fail) I can solve instances of Exact Three Cover I usually come upon quite quickly.

Now, I don’t have to wait for millennia to solve C with 500 units when I encounter these cases.

Please don’t ask me to change my constants; because I’m testing for 10,000 units in C. So I need a large constant for my while-loop.

import random
from itertools import combinations
from itertools import permutations
import sympy
import json


s =  input("Input set of integers for S : ").split(',')
c =  input('enter list for C (eg. ((1,2,3),(4,5,6))): ')
c = json.loads(c)


for a in range(0, len(s)):
    s(a) = int(s(a))

# Need a prime
# seems to help spread
# 3sets apart.

count = len(s)//3
while True:
    count = count + 1
    if sympy.isprime(count) == True:
        prime = count
        break



# This is a SUPER Greedy
# Algorithim that runs
# in polynomial time.
# It is impractical
# for NO instances
# It will TAKE FOREVER (constant of 241.. Duhh...)
# to halt and
# return an approximated
# no.

# The purpose of why I got
# such a large constant
# is because I needed
# to find Exact Three
# Covers in lists of C with
# lengths of 100, 500, 1000
# units long.

# The Exact 2^n solution
# is unreasonably to long
# for me.


# This is a formula
# to count all
# possible combinations
# of THREE except
# I am using a constant
# value of 241.

while_loop_steps = len(s)*241*((len(s)*241)-1)*((len(s)*241)-2)//6


# Don't worry about this.
#p = (len(s)//3)/while_loop_steps * 100


if len(s) % 3 != 0:
    print('invalid input')
    quit()


# Sort list to remove
# sets like (1,2,3) and (1,3,2)
# but leave (1,2,3)

delete = ()
for a in range(0, len(c)):
    for i in permutations(c(a), 3):
        if list(i) in c(a:):
            if list(i) != c(a):
                delete.append(list(i))

for a in range(0, len(delete)):
    if delete(a) in c:
        del c(c.index(delete(a)))

# remove sets
# that have
# repeating
# elements

remove = ()
for rem in range(0, len(c)):
    if len(c(rem)) != len(set(c(rem))):
        remove.append(c(rem))

for rem_two in range(0, len(remove)):
    if remove(rem_two) in c:
        del c(c.index(remove(rem_two)))

# remove sets
# that have
# elements
# that don't
# exist in S.

remove=()
for j in range(0, len(c)):
   for jj in range(0, len(c(j))):
        if any(elem not in s for elem in c(j)):
            remove.append(c(j))

for rem_two in range(0, len(remove)):
    if remove(rem_two) in c:
        del c(c.index(remove(rem_two)))


# Remove repeating sets

solutions =(c(x) for x in range(len(c)) if not(c(x) in c(:x)))


# check left and right for solutions

def check_for_exact_cover(jj):
    jj_flat = (item for sub in jj for item in sub)
    jj_set = set(jj_flat)
    if set(s) == jj_set and len(jj_set) == len(jj_flat):
        print('yes', jj)
        quit()
 

# Well if length(c) is small
# use brute force with polynomial constant


if len(c) <= len(s)//3*2:
    for jj in combinations(c, len(s)//3):
        check_for_exact_cover(jj)
        
if len(c) >= len(s)//3*2:
  for jj in combinations(c(0:len(s)//3*2), len(s)//3):
      check_for_exact_cover(jj)
      
if len(c) >= len(s)//3*2:
    X = list(reversed(c))
    for jj in combinations(X(0:len(s)//3*2), len(s)//3):
        check_for_exact_cover(jj)




# Well, I have to quit
# if the loop above
# didn't find anything.
# when len(c) <= len(s)//3*2

if len(c) <= len(s)//3*2:
    quit()

# will need these Three (what a prime!)
# just in case my algorithim
# needs to reverse in loop.

length = len(solutions)
ss = s
c = solutions

# Primes
# have been
# observed
# in nature
# to help
# avoid conflict.
# So why not
# pre shuffle C
# prime times?

for a in range(0, prime):
    random.shuffle(c)
    

# while loop to see
# if we can find
# an Exact Three Cover
# in poly-time.

stop = 0
Potential_solution = ()
opps = 0
failed_sets = 0

#Don't worry about this. (100/p*while_loop_steps)

while stop <= while_loop_steps:

    # Shuffling c randomly
    # this seems to help
    # select a correct set
    
    opps = opps + 1
    stop = stop + 1
    random.shuffle(c)

    if len(Potential_solution) == len(ss) // 3:
        # break if Exact
        # three cover is
        # found.
        print('YES SOLUTION FOUND!',Potential_solution)
        print('took',stop,'steps in while loop')
        failed_sets = failed_sets + 1
        break

    # opps helps
    # me see
    # if I miss a correct
    # set
    
    if opps > len(c):
        if failed_sets < 1:
            s = set()
            opps = 0
        

    # Keep c(0)
    # and append to
    # end of list
    # del c(0)
    # to push >>
    # in list.
    
    c.append(c(0))
    del (c(0))
    Potential_solution = ()
    s = set()
    
    for l in c:
        if not any(v in s for v in l):
            Potential_solution.append(l)
            s.update(l)


    
    if len(Potential_solution) != len(ss)//3:
        if stop == length:
          # Reverse list just
          # to see if I missed a solution
         for cc in range(0, len(c)):
              c = list(reversed(c))
              random.shuffle(c)

Question

  • What parts of my sorting algorithms could be shortened and improved?
  • Is the usage of primes to theoretically space out sets pointless?
  • What variable names would you use in my code?

python – Rewriting code so functions don’t require super long entries

I have 2 scripts, one is a tkinter GUI script where the user gives specific inputs, the 2nd script takes those inputs, does some modification, and then sends it back to the GUI script to be written/results printed. However, in dealing with multiple user inputs, the entries for the functions started getting longer and longer, and uglier. As you’ll see in the GUI script, when I use the function I imported, it has 7 entries which make it quite long. Is there a better way to call user inputs from one script to another?

#GUI Script (NOTE: I'm not posting all the global and input functions, since they are basically the same thing. Don't want to be reptitious)
#basic tkinter setup root=tk.Tk() with the loop and everything setup

#globals where filenames and directories to files are saved, to be called on in the functions
sparta_file=()
sparta_directory=()
seq_file=()
seq_directory=()
#browse options to choose files
def input_file():
    fullpath = filedialog.askopenfilename(parent=root, title='Choose a file')
    global sparta_directory
    global sparta_file
    sparta_directory=os.path.dirname(fullpath)
    sparta_file= os.path.basename(fullpath)
    label2=Label(root,text=fullpath).grid(row=0,column=1)

def input_seq():
    fullpath = filedialog.askopenfilename(parent=root, title='Choose a file')
    global seq_file
    global seq_directory
    seq_directory=os.path.dirname(fullpath)
    seq_file= os.path.basename(fullpath)
    label3=Label(root,text=fullpath).grid(row=1,column=1)
#All the user inputs are designed more or less the same, user browses, clicks on file, and files directory and filename are saved as globals. 

#function that will be run to use user inputs, modify them, and then write modifications
def sparta_gen_only():
        from sparta_file_formatter import check_sparta_file_boundaries
        os.chdir(save_directory)
        with open(save_file_sparta,'w') as file:
            for stuff_to_write in check_sparta_file_boundaries(seq_file,seq_directory,mutation_list1,mutation_list2,sparta_file,sparta_directory,seq_start):
                file.write(stuff_to_write+'n')

So right off the bat, you can see the exact issue I’m having (check_sparta_file boundaries has a lot of inputs).

#2nd sparta_file_formatter
import re
import os



def create_seq_list(seq_file,seq_directory,seq_start):
    os.chdir(seq_directory)
    amino_acid_count=(0+seq_start)-1
    sequence_list=()
    with open(seq_file) as sequence_file:
        for amino_acid in sequence_file:
            stripped_amino_acid=amino_acid.strip().upper()
            for word in stripped_amino_acid:
                amino_acid_count+=1
                sequence_list.append(str(amino_acid_count)+word)
    return sequence_list

def format_sparta(sparta_file,sparta_directory):
    os.chdir(sparta_directory)
    sparta_file_list1=()
    proline_counter=0
    with open(sparta_file) as sparta_predictions:
        for line in sparta_predictions:
            modifier=line.strip().upper()
            if re.findall('^d+',modifier):
                A=modifier.split()
                del A(5:8)
                del A(3)
                A(0:3)=("".join(A(0:3)))
                joined=" ".join(A)
                proline_searcher=re.search('BP',joined)
                if proline_searcher != None:
                    proline_counter+=1
                    if proline_counter<2:
                        proline_count=re.search('^d+',joined)
                        sparta_file_list1.append(f'{proline_count.group(0)}PN'+' 1000'+' 1000')
                    else:
                        if proline_count == 4:
                            proline_count=re.search('^d+',joined)
                            sparta_file_list1.append(f'{proline_count.group(0)}PHN'+' 1000'+' 1000')
                            proline_counter=0
                sparta_file_list1.append(joined)
    return sparta_file_list1

#Each function the entries get longer and longer as they start using the outputs of the previous functions
def add_mutation(mutation_list1,mutation_list2,sparta_file,sparta_directory):
    sparta_file_list2=()
    if mutation_list1==() or mutation_list2==():
        for amino_acids in format_sparta(sparta_file,sparta_directory):
            sparta_file_list2.append(amino_acids)
    else:
        for mutations,mutations2 in zip(mutation_list1,mutation_list2):
            for amino_acids in format_sparta(sparta_file,sparta_directory):
                if re.findall(mutations,amino_acids):
                    splitting=amino_acids.split()
                    mutation=re.sub(mutations,mutations2,splitting(0))
                    mutation_value=re.sub('d+.d+',' 1000',splitting(1))
                    mutation_value2=re.sub('d+.d+',' 1000',splitting(2))
                    mutation_replacement=mutation+mutation_value+mutation_value2
                    sparta_file_list2.append(mutation_replacement)
                else:
                    sparta_file_list2.append(amino_acids)
    return sparta_file_list2

def filter_sparta_using_seq(seq_file,seq_directory,mutation_list1,mutation_list2,sparta_file,sparta_directory,seq_start):
    sparta_file_list3=()
    sparta_comparison=create_seq_list(seq_file,seq_directory,seq_start)
    for aa in add_mutation(mutation_list1,mutation_list2,sparta_file,sparta_directory):
        modifiers=aa.strip()
        splitter=modifiers.split()
        searcher=re.search('^d+(A-Z)',splitter(0))
        compiler=re.compile(searcher.group(0))
        sparta_sequence_comparison=list(filter(compiler.match,sparta_comparison))
        if sparta_sequence_comparison != ():
            sparta_file_list3.append(aa)

    return sparta_file_list3


def check_sparta_file_boundaries(seq_file,seq_directory,mutation_list1,mutation_list2,sparta_file,sparta_directory,seq_start):
    temp_list=()
    temp_counter=0
    sparta_filtered_list=filter_sparta_using_seq(seq_file,seq_directory,mutation_list1,mutation_list2,sparta_file,sparta_directory,seq_start)
    for checker in sparta_filtered_list:
        temp_modifier=checker.strip()
        temp_split=temp_modifier.split()
        temp_finder=re.search('^d+',temp_split(0))
        temp_list.append(temp_finder.group(0))
        temp_counter+=1
        if temp_counter==5:
            if int(temp_finder.group(0))==int(temp_list(0)):
                break
            else:
                del sparta_filtered_list(0:4)
                break
    if len(sparta_filtered_list)%6 != 0:
        del sparta_filtered_list(-5:-1)

    return sparta_filtered_list

Edit:

In terms of exactly what sparta is and what my code is doing. I won’t go into too much detail regarding sparta, outside of it is a text file with information we want. This is the format:

REMARK SPARTA+ Protein Chemical Shift Prediction Table
REMARK  All chemical shifts are reported in ppm:
....

   3    Y   HA     0.000     4.561     4.550     0.018     0.000     0.201
   3    Y    C     0.000   175.913   175.900     0.021     0.000     1.272
   3    Y   CA     0.000    58.110    58.100     0.017     0.000     1.940
   3    Y   CB     0.000    38.467    38.460     0.011     0.000     1.050
   4    Q    N     3.399   123.306   119.800     0.179     0.000     2.598
...

We only care about the lines with the numbers, so I use a regex search to only extract that. Now the info I want is the first 3 columns, with the 4 column. I want each data formatted 3YHA 4.561 (2nd function). Now every number should have 6 values associated with it, those that are P, will only have 4, so I add 2 extra values (you may note in the above, the format is HA,C,CA,CB,etc. So I add the values so the format of P is N,HA,C,CA,CB.

Sometimes the user will wish to change a specific letter (mutation). So they indicate which letter, the number, and what to change it to (3rd loop).

Finally, these files can sometimes have extra info we don’t care about. The user specifies the range of info they want by using a seq file (1st and 4rd loop).

As stated, every letter should have 6 values. However, the first letter will always have 4. The last letter will also only have 5. So these need to be removed (loop 5).

Here is some sample input files as examples:

seq_number=1
#seq.txt
MSYQVLARKW
#sparta_pred.tab
   3    Y   HA     0.000     4.561     4.550     0.018     0.000     0.201
   3    Y    C     0.000   175.913   175.900     0.021     0.000     1.272
   3    Y   CA     0.000    58.110    58.100     0.017     0.000     1.940
   3    Y   CB     0.000    38.467    38.460     0.011     0.000     1.050
   4    Q    N     3.399   123.306   119.800     0.179     0.000     2.598
   4    Q   HA     0.146     4.510     4.340     0.039     0.000     0.237
   4    Q    C    -2.091   173.967   176.000     0.097     0.000     0.914
   4    Q   CA    -0.234    55.623    55.803     0.092     0.000     1.065
   4    Q   CB     3.207    32.000    28.738     0.092     0.000     1.586
   4    Q   HN     0.131     8.504     8.270     0.173     0.000     0.484
   5    V    N     0.131   120.091   119.914     0.078     0.000     2.398
   5    V   HA     0.407     4.575     4.120     0.080     0.000     0.286
   5    V    C     0.162   176.322   176.094     0.109     0.000     1.026
   5    V   CA    -1.507    60.840    62.300     0.078     0.000     0.868
   5    V   CB     0.770    32.625    31.823     0.052     0.000     0.982
   5    V   HN     0.418     8.642     8.190     0.057     0.000     0.443
   6    L    N     7.083   128.385   121.223     0.130     0.000     2.123
   6    L   HA    -0.504     4.085     4.340     0.415     0.000     0.217
   6    L    C     1.827   178.814   176.870     0.195     0.000     1.081
   6    L   CA     3.308    58.271    54.840     0.205     0.000     0.772
   6    L   CB    -1.005    41.051    42.059    -0.005     0.000     0.890
   6    L   HN     0.241     8.694     8.230     0.097    -0.164     0.437
   7    A    N    -4.063   118.812   122.820     0.092     0.000     2.131
   7    A   HA    -0.337     4.023     4.320     0.067     0.000     0.220
   7    A    C     0.433   178.071   177.584     0.090     0.000     1.158
   7    A   CA     2.471    54.552    52.037     0.073     0.000     0.665
   7    A   CB    -0.332    18.690    19.000     0.036     0.000     0.795
   7    A   HN    -0.517     7.889     8.150     0.063    -0.219     0.460
   8    R    N    -4.310   116.247   120.500     0.096     0.000     2.191
   8    R   HA    -0.056     4.313     4.340     0.048     0.000     0.196
   8    R    C     2.152   178.488   176.300     0.060     0.000     0.991
   8    R   CA     1.349    57.485    56.100     0.060     0.000     1.075
   8    R   CB     0.834    31.147    30.300     0.023     0.000     1.040
   8    R   HN     0.244     8.408     8.270     0.109     0.172     0.526
   9    K    N     0.144   120.608   120.400     0.108     0.000     2.283
   9    K   HA    -0.130     4.148     4.320    -0.069     0.000     0.202
   9    K    C     0.691   177.214   176.600    -0.129     0.000     1.048
   9    K   CA     2.415    58.707    56.287     0.008     0.000     0.948
   9    K   CB    -0.114    32.430    32.500     0.074     0.000     0.742
   9    K   HN    -0.617     7.728     8.250     0.159     0.000     0.458
  10    W    N    -4.007   117.283   121.300    -0.016     0.000     2.846
  10    W   HA     0.195     4.850     4.660    -0.009     0.000     0.391
  10    W    C    -1.455   175.056   176.519    -0.013     0.000     1.011
  10    W   CA    -1.148    56.191    57.345    -0.011     0.000     1.832
  10    W   CB     0.166    29.622    29.460    -0.007     0.000     1.151
  10    W   HN    -0.634     7.728     8.180     0.377     0.045     0.582
  11    R    N     1.894   122.475   120.500     0.134     0.000     2.483
  11    R   HA    -0.096     4.293     4.340     0.083     0.000     0.329
  11    R    C    -1.368   174.959   176.300     0.045     0.000     0.961
  11    R   CA    -0.713    55.431    56.100     0.073     0.000     1.041
  11    R   CB     0.187    30.506    30.300     0.033     0.000     0.930
  11    R   HN    -0.880     7.272     8.270     0.107     0.182     0.413
  12    P   HA    -0.173     4.278     4.420     0.051     0.000     0.257
  12    P    C    -1.027   176.281   177.300     0.014     0.000     1.162
  12    P   CA     0.741    63.865    63.100     0.040     0.000     0.762
  12    P   CB     0.046    31.768    31.700     0.036     0.000     0.753
  13    Q    N     1.152   120.951   119.800    -0.001     0.000     2.396
  13    Q   HA     0.193     4.514     4.340    -0.032     0.000     0.220
  13    Q    C     0.275   176.261   176.000    -0.024     0.000     0.900
  13    Q   CA     0.394    56.181    55.803    -0.027     0.000     0.925
  13    Q   CB     2.516    31.223    28.738    -0.051     0.000     1.065
  13    Q   HN     0.012     8.472     8.270     0.002    -0.188     0.535

Windows explorer Column properties – Super User

My OS : Windows 10

In windows explorer, there are hundreds of properties including filename, type, size, modified date. Define them column properties.

It seems most of column properties are stored separately from file content.

Is there any column properties that really analyze file content(in real time), to pass information to windows explorer?

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