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 ?
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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I noticed there are many different LOD algorithm out there. For example:
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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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
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
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?
ABOUT US
Super ROI Ltd.
Is an UK Registered Company since 2020, having its base in London. We call ourself Super ROI Hour as we pay Hourly earnings.Our role is to trade in FOREX, Crypto Currency Exchanges, and Stock market from where we daily generate Profits and share some part with investors. Being 4 years old company and trading in the most profitable and futuristic platform, we are able to achieve huge Profits for our offline Investors and thus now planned to be online to reach the world and make the exchange of benefit among our investors and us.
We believe in great results and hence, our team of 50 members with 15 years and above experience, generate Hourly profits for us and we share some part with our investors. Our long run target is not only unique but it will give immersive results in the future if we get more investors getting associated with us. We aim for everyone’s success. Join us today without wasting more time as time is money.