[ITEM]
27.08.2018

Windows 7 Loader From Matrix

86

In computing, booting is starting up a computer or computer appliance until it can be used. The firmware or the boot manager then loads the boot loader into the. Of software is able to place an operating system kernel like Windows or Linux into. For example, on the System/370 Model 158, the keyboard sequence 0-7-X.

How do you save/load a scipy sparse csr_matrix in a portable format? The scipy sparse matrix is created on Python 3 (Windows 64-bit) to run on Python 2 (Linux 64-bit). Initially, I used pickle (with protocol=2 and fix_imports=True) but this didn't work going from Python 3.2.2 (Windows 64-bit) to Python 2.7.2 (Windows 32-bit) and got the error: TypeError: ('data type not understood',, (, (0,), '[98]')). Next, tried numpy.save and numpy.load as well as scipy.io.mmwrite() and scipy.io.mmread() and none of these methods worked either. Edit: SciPy 1.19 now has.

From scipy import sparse sparse.save_npz('yourmatrix.npz', your_matrix) your_matrix_back = sparse.load_npz('yourmatrix.npz') For both functions, the file argument may also be a file-like object (i.e. The result of open) instead of a filename. Got an answer from the Scipy user group: A csr_matrix has 3 data attributes that matter:.data,.indices, and.indptr. All are simple ndarrays, so numpy.save will work on them. Save the three arrays with numpy.save or numpy.savez, load them back with numpy.load, and then recreate the sparse matrix object with: new_csr = csr_matrix((data, indices, indptr), shape=(M, N)) So for example: def save_sparse_csr(filename, array): np.savez(filename, data=array.data, indices=array.indices, indptr=array.indptr, shape=array.shape) def load_sparse_csr(filename): loader = np.load(filename) return csr_matrix((loader['data'], loader['indices'], loader['indptr']), shape=loader['shape']). Though you write, scipy.io.mmwrite and scipy.io.mmread don't work for you, I just want to add how they work.

This question is the no. 1 Google hit, so I myself started with np.savez and pickle.dump before switching to the simple and obvious scipy-functions. They work for me and shouldn't be overseen by those who didn't tried them yet. From scipy import sparse, io m = sparse.csr_matrix([[0,0,0],[1,0,0],[0,1,0]]) m # ' with 2 stored elements in Compressed Sparse Row format> io.mmwrite('test.mtx', m) del m newm = io.mmread('test.mtx') newm # ' with 2 stored elements in COOrdinate format> newm.tocsr() # ' with 2 stored elements in Compressed Sparse Row format> newm.toarray() # array([[0, 0, 0], [1, 0, 0], [0, 1, 0]], dtype=int32).

Here is performance comparison of the three most upvoted answers using Jupyter notebook. Assuming you have scipy on both machines, you can just use pickle. However, be sure to specify a binary protocol when pickling numpy arrays.

This computer runs updated version of webroot securities. Download system32 drivers pci sys 512 ethernet controller. I had the same problem on my computer about a year ago and your help was the only way i got rid of it on my computer. I know this is one of your common problems to fix.

Otherwise you'll wind up with a huge file. At any rate, you should be able to do this: import cPickle as pickle import numpy as np import scipy.sparse # Just for testing, let's make a dense array and convert it to a csr_matrix x = np.random.random((10,10)) x = scipy.sparse.csr_matrix(x) with open('test_sparse_array.dat', 'wb') as outfile: pickle.dump(x, outfile, pickle.HIGHEST_PROTOCOL) You can then load it with: import cPickle as pickle with open('test_sparse_array.dat', 'rb') as infile: x = pickle.load(infile).

Will someone at Nokia Development provide some kind of a matrix of Windows 7 compatibility for the most widely used Nokia software? I'd like to be able to plan for my Windows 7 upgrade properly, and it would help out if Nokia can provide information as to what current version of what Nokia software works with Windows 7, what doesn't, which future release is planned, and if each software can run on 64 bit Windows 7 as well. Currently, the Nokia software I run on my Windows XP are: PC Suite Nokia Software Updater Nokia Maps Updater Nokia Map Loader Nokia Car Kit Software Updater My current plan is to upgrade to Windows 7 64-bit, and I have accounted for every software and driver, and am ready except for the Nokia part of the story. Nokia's group of software is the only set that's holding me back. This will be very helpful. Thanks in advance! Halo station outdoor wifi usb driver.

I'm not so worried about 'if' Nokia will port their software over to Windows 7 compatible space, but 'when,' if ever. But more importantly is the device drivers for 64-bit Windows 7, versus 32-bit. A compatibility matrix, like all other software and hardware manufacturers are doing, will be nice and handy. John @ Chicago // 5160 (1999.07.20) > 7160 (2001.06.09) > 6340i (2003.04.26) > 6620 (2004.08.24) > 7610b (2005.05.08) > N91 (2006.06.07) > N95-3 (2007.09.28) > N95-3 #2 (2007.12.05) > E51 (2008.03.10). No hard work at all. On Windows 7 32bit Home Premium PC Suite installed with no trouble at all. That includes using BlueTooth as the initial form of connection once it was running.

[/ITEM]
[/MAIN]
27.08.2018

Windows 7 Loader From Matrix

29

In computing, booting is starting up a computer or computer appliance until it can be used. The firmware or the boot manager then loads the boot loader into the. Of software is able to place an operating system kernel like Windows or Linux into. For example, on the System/370 Model 158, the keyboard sequence 0-7-X.

How do you save/load a scipy sparse csr_matrix in a portable format? The scipy sparse matrix is created on Python 3 (Windows 64-bit) to run on Python 2 (Linux 64-bit). Initially, I used pickle (with protocol=2 and fix_imports=True) but this didn't work going from Python 3.2.2 (Windows 64-bit) to Python 2.7.2 (Windows 32-bit) and got the error: TypeError: ('data type not understood',, (, (0,), '[98]')). Next, tried numpy.save and numpy.load as well as scipy.io.mmwrite() and scipy.io.mmread() and none of these methods worked either. Edit: SciPy 1.19 now has.

From scipy import sparse sparse.save_npz('yourmatrix.npz', your_matrix) your_matrix_back = sparse.load_npz('yourmatrix.npz') For both functions, the file argument may also be a file-like object (i.e. The result of open) instead of a filename. Got an answer from the Scipy user group: A csr_matrix has 3 data attributes that matter:.data,.indices, and.indptr. All are simple ndarrays, so numpy.save will work on them. Save the three arrays with numpy.save or numpy.savez, load them back with numpy.load, and then recreate the sparse matrix object with: new_csr = csr_matrix((data, indices, indptr), shape=(M, N)) So for example: def save_sparse_csr(filename, array): np.savez(filename, data=array.data, indices=array.indices, indptr=array.indptr, shape=array.shape) def load_sparse_csr(filename): loader = np.load(filename) return csr_matrix((loader['data'], loader['indices'], loader['indptr']), shape=loader['shape']). Though you write, scipy.io.mmwrite and scipy.io.mmread don't work for you, I just want to add how they work.

This question is the no. 1 Google hit, so I myself started with np.savez and pickle.dump before switching to the simple and obvious scipy-functions. They work for me and shouldn't be overseen by those who didn't tried them yet. From scipy import sparse, io m = sparse.csr_matrix([[0,0,0],[1,0,0],[0,1,0]]) m # ' with 2 stored elements in Compressed Sparse Row format> io.mmwrite('test.mtx', m) del m newm = io.mmread('test.mtx') newm # ' with 2 stored elements in COOrdinate format> newm.tocsr() # ' with 2 stored elements in Compressed Sparse Row format> newm.toarray() # array([[0, 0, 0], [1, 0, 0], [0, 1, 0]], dtype=int32).

Here is performance comparison of the three most upvoted answers using Jupyter notebook. Assuming you have scipy on both machines, you can just use pickle. However, be sure to specify a binary protocol when pickling numpy arrays.

This computer runs updated version of webroot securities. Download system32 drivers pci sys 512 ethernet controller. I had the same problem on my computer about a year ago and your help was the only way i got rid of it on my computer. I know this is one of your common problems to fix.

Otherwise you'll wind up with a huge file. At any rate, you should be able to do this: import cPickle as pickle import numpy as np import scipy.sparse # Just for testing, let's make a dense array and convert it to a csr_matrix x = np.random.random((10,10)) x = scipy.sparse.csr_matrix(x) with open('test_sparse_array.dat', 'wb') as outfile: pickle.dump(x, outfile, pickle.HIGHEST_PROTOCOL) You can then load it with: import cPickle as pickle with open('test_sparse_array.dat', 'rb') as infile: x = pickle.load(infile).

Will someone at Nokia Development provide some kind of a matrix of Windows 7 compatibility for the most widely used Nokia software? I'd like to be able to plan for my Windows 7 upgrade properly, and it would help out if Nokia can provide information as to what current version of what Nokia software works with Windows 7, what doesn't, which future release is planned, and if each software can run on 64 bit Windows 7 as well. Currently, the Nokia software I run on my Windows XP are: PC Suite Nokia Software Updater Nokia Maps Updater Nokia Map Loader Nokia Car Kit Software Updater My current plan is to upgrade to Windows 7 64-bit, and I have accounted for every software and driver, and am ready except for the Nokia part of the story. Nokia's group of software is the only set that's holding me back. This will be very helpful. Thanks in advance! Halo station outdoor wifi usb driver.

I'm not so worried about 'if' Nokia will port their software over to Windows 7 compatible space, but 'when,' if ever. But more importantly is the device drivers for 64-bit Windows 7, versus 32-bit. A compatibility matrix, like all other software and hardware manufacturers are doing, will be nice and handy. John @ Chicago // 5160 (1999.07.20) > 7160 (2001.06.09) > 6340i (2003.04.26) > 6620 (2004.08.24) > 7610b (2005.05.08) > N91 (2006.06.07) > N95-3 (2007.09.28) > N95-3 #2 (2007.12.05) > E51 (2008.03.10). No hard work at all. On Windows 7 32bit Home Premium PC Suite installed with no trouble at all. That includes using BlueTooth as the initial form of connection once it was running.