eni=soleloge.split(" ")
res = [int(sub.split(':')[1]) for sub in yeni]
there is only one line up here
solmatris=numpy.array(res)
if solmatris.size>0:
print(solmatris)
f.write(solmatrisStr)
here the output is as follows:
[ 835 732 474 519 831 834 847 852 841 834 801
-9344
-3660 13808 1648 -463 86]
I want to out:
[ 835 732 474 519 831 834 847 852 841 834 801 -9344 -3660 13808 1648 -463 86 ]
After converting to matrix, I print out to notebook. I don't use console.
https://prnt.sc/10c0m85 I don't want it to be like this.
I apologize for not expressing my problem clearly at first.
Why does it give such a printout and how can I fix it.
Remove the numpy.array type cast and instead try this print(', '.join(str(r) for r in res)).
numpy's representation of arrays has an automatic wrap-around that is not based on the window size. You could do print(*solmatris) or print(list(solmatris)) instead to get it on a single line.
Related
I'm struggling with this problem:
I've 2 large 2D numpy arrays (about 5 GB) and I want to save them in a .mat file loadable from Matlab
I tried scipy.io and wrote
from scipy.io import savemat
data = {'A': a, 'B': b}
savemat('myfile.mat', data, appendmat=True, format='5',
long_field_names=False, do_compression=False, oned_as='row')
but I get the error: OverflowError: Python int too large to convert to C long
EDIT:
Python 3.8, Matlab 2017b
Here the traceback
a.shape (600,1048261) of type <class 'numpy.float64'>
b.shape (1048261) of type <class 'numpy.float64'>
data = {'A': a, 'B': b}
savemat('myfile.mat', data, appendmat=True, format='5',
long_field_names=False, do_compression=False, oned_as='row')
---------------------------------------------------------------------------
OverflowError Traceback (most recent call last)
<ipython-input-19-4d1d08a54148> in <module>
1 data = {'A': a, 'B': b}
----> 2 savemat('myfile.mat', data, appendmat=True, format='5',
3 long_field_names=False, do_compression=False, oned_as='row')
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio.py in savemat(file_name, mdict, appendmat, format, long_field_names, do_compression, oned_as)
277 else:
278 raise ValueError("Format should be '4' or '5'")
--> 279 MW.put_variables(mdict)
280
281
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio5.py in put_variables(self, mdict, write_header)
847 self.file_stream.write(out_str)
848 else: # not compressing
--> 849 self._matrix_writer.write_top(var, asbytes(name), is_global)
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio5.py in write_top(self, arr, name, is_global)
588 self._var_name = name
589 # write the header and data
--> 590 self.write(arr)
591
592 def write(self, arr):
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio5.py in write(self, arr)
627 self.write_char(narr, codec)
628 else:
--> 629 self.write_numeric(narr)
630 self.update_matrix_tag(mat_tag_pos)
631
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio5.py in write_numeric(self, arr)
653 self.write_element(arr.imag)
654 else:
--> 655 self.write_element(arr)
656
657 def write_char(self, arr, codec='ascii'):
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio5.py in write_element(self, arr, mdtype)
494 self.write_smalldata_element(arr, mdtype, byte_count)
495 else:
--> 496 self.write_regular_element(arr, mdtype, byte_count)
497
498 def write_smalldata_element(self, arr, mdtype, byte_count):
~\miniconda3\envs\work\lib\site-packages\scipy\io\matlab\mio5.py in write_regular_element(self, arr, mdtype, byte_count)
508 tag = np.zeros((), NDT_TAG_FULL)
509 tag['mdtype'] = mdtype
--> 510 tag['byte_count'] = byte_count
511 self.write_bytes(tag)
512 self.write_bytes(arr)
OverflowError: Python int too large to convert to C long
I tried also with hdf5storage
hdf5storage.write(data, 'myfile.mat', matlab_compatible=True)
but it fails too.
EDIT:
gives this warning
\miniconda3\envs\work\lib\site-packages\hdf5storage\__init__.py:1306:
H5pyDeprecationWarning: The default file mode will change to 'r' (read-only)
in h5py 3.0. To suppress this warning, pass the mode you need to
h5py.File(), or set the global default h5.get_config().default_file_mode, or
set the environment variable H5PY_DEFAULT_READONLY=1. Available modes are:
'r', 'r+', 'w', 'w-'/'x', 'a'. See the docs for details.
f = h5py.File(filename)
Anyway, it creates a 5GB file but when I load it in Matlab I get a variable named with the file path and apparently without data.
Lastly I tried with h5py:
import h5py
hf = h5py.File('C:/Users/flavio/Desktop/STRA-pattern.mat', 'w')
hf.create_dataset('A', data=a)
hf.create_dataset('B', data=b)
hf.close()
but the output file in not recognized/readable in Matlab.
Is splitting the only solution? Hope there is a better way to fix this issue.
Anyone still looking for an answer, this works with hdf5storage
hdf5storage.savemat(
save_path,
data_dict,
format=7.3,
matlab_compatible=True,
compress=False
)
I'm trying to minimize a value dependant of a function (and therefore optimize the arguments of the function) so the latter matches some experimental data.
Problem is that I don't actually know if I'm coding what I want correctly, or even if I'm using the correct function, because my program gives me an error.
import scipy.optimize as op
prac3 = pd.read_excel('Buena.xlsx', sheetname='nl1')
print(prac3.columns)
tmed = 176
te = np.array(prac3['tempo'])
t = te[0:249]
K = np.array(prac3['cond'])
Kexp = K[0:249]
Kinf = 47.8
K0 = 3.02
DK = Kinf - K0
def f(Kinf,DK,k,t):
return (Kinf-DK*np.exp(-k*t))
def err(Kexp,Kcal):
return ((Kcal-Kexp)**2)
Kcal = np.array(f(Kinf,DK,k,t))
print(Kcal)
dif = np.array(err(Kexp,Kcal))
sumd = sum(dif)
print(sumd)
op.minimize(f, (Kinf,DK,k,t))
The error the program gives me reads as it follows:
ValueError Traceback (most recent call last)
<ipython-input-91-fd51b4735eed> in <module>()
48 print(sumd)
49
---> 50 op.minimize(f, (Kinf,DK,k,t))
51
52
~/anaconda3_501/lib/python3.6/site-packages/scipy/optimize/_minimize.py in minimize(fun, x0, args, method, jac, hess, hessp, bounds, constraints, tol, callback, options)
352
353 """
--> 354 x0 = np.asarray(x0)
355 if x0.dtype.kind in np.typecodes["AllInteger"]:
356 x0 = np.asarray(x0, dtype=float)
~/anaconda3_501/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order)
529
530 """
--> 531 return array(a, dtype, copy=False, order=order)
532
533
ValueError: setting an array element with a sequence.
The exception says that you're passing an array to something that expects a callable. Without seeing your traceback or knowing more of what you're trying to do, I can only guess where this is happening, but my guess is here:
op.minimize(f(Kinf,DK,k,t),sumd)
From the docs, the first parameter is a callable (function). But you're passing whatever f(Kinf,DK,k,t) returns as the first argument. And, looking at your f function, it looks like it's returning an array, not a function.
My first guess is that you want to minimize f over the args (Kinf, DK, k, t)? if so, you pass f as the function, and the tuple (Kinf, DK, k, t) as the args, like this:
op.minimize(f, sumd, (Kinf,DK,k,t))
sorry for my english.
My Arduino serial give 3 values like this, at 300 Hz:
-346 54 -191
-299 12 -123
-497 -214 77
-407 -55 -19
45 129 46
297 123 -197
393 71 -331
544 115 -273
515 -355 -89
510 -183 -47
Whit this python code I read and write correctly serial to file but after the while cycle do not terminate, and the shell remain open, and do not print stop:
...
ard=serial.Serial(portname,baudrate)
print"start"
while True:
x = ard.readline()
#print x
a=open(filename,'ab')
a.write(x)
a.close
print "stop"
...
I a biginner programmer, can you tell me a solution, to write serial to file and go forward.
Tanks
You're never breaking from the while loop. You should:
Add a timeout to the serial reader
When there are no bytes received, break the loop
Taking your code as a base, try something like this:
...
ard=serial.Serial(addr,baud)
ard.timeout = 1 # in seconds
print"start"
while True:
x = ard.readline()
if len(x) == 0:
break
a=open(fname,'ab')
a.write(x)
a.close
print "stop"
...
It works!
I have use ard.timeout and if condition (just if condition alone do not work).
An other question,
My arduino serial start and terminate like this:
Start
-663 -175 76
361 47 157
425 -229 -174
531 -283 -288
518 -40 -28
538 -228 206
581 188 174
445 5 176
end
It's possible to start write file after "Start" string and terminate before "end" string?
I have tried something like this but do not work:
while True:
x = ard.readline()
if x=="end":
break
#print x
a=open(fname,'ab')
a.write(x)
a.close
Blockquote
enter code here
I have got counters based on 2 sec interval.
I need to verify that the count should be in range 1200 to 1600. Is there any way we can do it without parsing whole output?
If for any particular time interval, the count doesn't fall into matching range, some error/warning message should get printed.
Is there any method to get average for this counters?
# tshark -r q4-mme.pcap -qz io,stat,2,"COUNT(frame.time)frame.time"
===================================================================
IO Statistics
Interval: 2.000 secs
Column #0: COUNT(frame.time)frame.time
| Column #0
Time | COUNT
000.000-002.000 1241
002.000-004.000 1272
004.000-006.000 1315
006.000-008.000 1371
008.000-010.000 1195
010.000-012.000 1299
012.000-014.000 1305
014.000-016.000 1391
016.000-018.000 1463
018.000-020.000 1454
020.000-022.000 1392
022.000-024.000 1438
024.000-026.000 1362
026.000-028.000 1491
028.000-030.000 1392
030.000-032.000 1422
032.000-034.000 1425
034.000-036.000 1486
036.000-038.000 1449
038.000-040.000 1487
040.000-042.000 1402
042.000-044.000 1420
044.000-046.000 1330
046.000-048.000 1458
048.000-050.000 1420
050.000-052.000 144
===================================================================
Please let me know how can I achieve the desired results.
I am not familiar with python. But here is an attempt using awk. You may call it from python using appropriate system commands.
Verify the count range between 1200 to 1600
awk '( $1~/[0-9]+\.[0-9]+-[0-9]+\.[0-9]+/ && ($2<1200||$2>1600) ) {print $2}' file
Output:
1195
144
Calculate Average
awk '$1 ~ /[0-9]+\.[0-9]+-[0-9]+\.[0-9]+/ {total+=$2; cnt++;} END {printf "Average = %.2f\n", total/cnt}' file
Output:
Average = 1339.38
All my unit tests succeed running in Python 2.6.5; one fails when I run through Python 2.7.3. The code being tested is complex and involves lots of working in floats and converting to Decimal along the way, by converting to str first as was needed in Python 2.6.
Before I start digging, I was wondering if I could be a bit lazy and see if someone has seen this before and has suggestions on what to search for. Here's the result of the test run:
======================================================================
FAIL: test_hor_tpost_winsize_inside_mm (__main__.Test_ShutterCalculator)
----------------------------------------------------------------------
Traceback (most recent call last):
File "test_ShutterCalculator.py", line 506, in test_hor_tpost_winsize_inside_mm
self.assertEqual(o.net_width_closing_tolerance, Decimal("6.4"))
AssertionError: Decimal('6.3') != Decimal('6.4')
----------------------------------------------------------------------
Here's the unit test code for test_hor_tpost_winsize_inside_mm():
490 def test_hor_tpost_winsize_inside_mm(self):
491 """
492 Same as above but test mm
493 """
494 o = self.opening
495 o.unit_of_measure = "millimeters"
496 o.formula_mode = "winsize"
497 o.mount = "inside"
498 o.given_width = Decimal("1117.6")
499 o.given_height = Decimal("2365.4")
500 o.louver_spacing = Decimal("101.6")
501 self.make4SidedFrame("9613", '9613: 2-1/2" Face Deco Z', Decimal("63.5"), Decimal("19.1"))
502 so1 = o.subopenings[(0,0)]
503 so1.fold_left = 1
504 so1.fold_right = 1
505 self.calc()
506 self.assertEqual(o.net_width_closing_tolerance, Decimal("6.4"))
507 self.assertEqual(o.net_height_closing_tolerance, Decimal("6.4"))
508 self.assertEqual(o.horizontal_shim, Decimal(".125")) # in inches
509 self.assertEqual(o.vertical_shim, Decimal(".125")) # in inches
510 self.assertEqual(o.width, Decimal("1069.8")) ## 1070 converted directly from inches
511 self.assertEqual(o.height, Decimal("2317.6")) ## 2317.8 converted directy from inches
512 tpost = o.add_hor_tpost()
513 so2 = o.subopenings[(0,1)]
514 so2.fold_left = 1
515 so2.fold_right = 1
516 self.calc()
517 #self.cs()
518 self.assertEqual(o.net_width_closing_tolerance, Decimal("6.4"))
519 self.assertEqual(o.net_height_closing_tolerance, Decimal("12.7"))
520 self.assertEqual(o.horizontal_shim, Decimal(".125")) # in inches
521 self.assertEqual(o.vertical_shim, Decimal(".125")) # in inches
522 self.assertEqual(o.width, Decimal("1069.8")) ## Rick had 42 but agreed that mine is right
523 self.assertEqual(o.height, Decimal("2311.3"))
524 self.assertEqual(so1.width, Decimal("1069.8"))
525 self.assertEqual(so2.width, Decimal("1069.8"))
526 self.assertEqual(so1.height, Decimal("1139.7")) ## Rick had 44.8125 but agreed mine is right
527 self.assertEqual(so2.height, Decimal("1139.7"))
528 self.assertEqual(tpost.center_pos, Decimal("1182.7"))
529 top_panel_section = so1.panels[0].sections[(0,0)]
530 bottom_panel_section = so2.panels[0].sections[(0,0)]
531 self.assertEqual(top_panel_section.louver_count, 9)
532 self.assertEqual(bottom_panel_section.louver_count, 9)
533 self.assertEqual(top_panel_section.top_rail.width, Decimal("112.6")) ## Rick had 4.40625, but given the changes to net
534 self.assertEqual(bottom_panel_section.bottom_rail.width, Decimal("112.7"))
535 self.assertEqual(top_panel_section.bottom_rail.width, Decimal("112.7"))
536 self.assertEqual(bottom_panel_section.top_rail.width, Decimal("112.6"))
Any hint on what to search for in my code to find the source of the discrepancy?
Python 2.7 introduced changes to the Decimal class and float type to help improve accuracy when converting from strings. This could be the source of the change.
Conversions between floating-point numbers and strings are now correctly rounded on most platforms. These conversions occur in many different places: str() on floats and complex numbers; the float and complex constructors; numeric formatting; serializing and deserializing floats and complex numbers using the marshal, pickle and json modules; parsing of float and imaginary literals in Python code; and Decimal-to-float conversion.
You can see the change details here, under "Other language changes"