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Numpy Help - BlackHeart - Oct-23-2017 Hey everyone, This is my first time posting on this forum. I am very very new to python, so please bare with me. I'll try and give as much accurate information as possible. First off I'm using Ubuntu 16. I have Anaconda 5.0 installed, with the python3 package. What I'm attempting to do is learn python while working on a real world project at the same time, since I think it will keep me motivated. My goal/project is to understand and create a working artificial neural network for solving non linear problems. I have some code, that I found on the internet. It's what I'm working from to try and understand how an ANN works. Code: import numpy as np # sigmoid function def nonlin(x,deriv=False): if(deriv==True): return x*(1-x) return 1/(1+np.exp(-x)) # input dataset X = np.array([ [0,0,1], [0,1,1], [1,0,1], [1,1,1] ]) # output dataset y = np.array([[0,0,1,1]]).T # seed random numbers to make calculation # deterministic (just a good practice) np.random.seed(1) # initialize weights randomly with mean 0 syn0 = 2*np.random.random((3,1)) - 1 for iter in xrange(10000): # forward propagation l0 = X l1 = nonlin(np.dot(l0,syn0)) # how much did we miss? l1_error = y - l1 # multiply how much we missed by the # slope of the sigmoid at the values in l1 l1_delta = l1_error * nonlin(l1,True) # update weights syn0 += np.dot(l0.T,l1_delta) print ("Output After Training:") print (l1)I currently have an Anaconda environment set up using python2.7 to handle this code in Spyder. This is because I think that's what the author of this code was using. I'm trying to run this code to see if it works, and to see if my work space is set up to handle a ANN. When I run it this is the error I keep getting, and I don't understand how to fix it. Python 2.7.14 |Anaconda, Inc.| (default, Oct 16 2017, 17:29:19) Type "copyright", "credits" or "license" for more information. IPython 5.4.1 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details. In [1]: debugfile('/home/b/.config/spyder/temp.py', wdir='/home/b/.config/spyder') > /home/b/.config/spyder/temp.py(1)<module>() ----> 1 import numpy as np 2 3 # sigmoid function 4 def nonlin(x,deriv=False): 5 if(deriv==True):Is this happening because Spyder doesn't have the right modules loaded up (numpy)? Thanks guys RE: Numpy Help - metulburr - Oct-23-2017 Quote:I currently have an Anaconda environment set up using python2.7 to handle this code in Spyder. This is because I think that's what the author of this code was using. I'm trying to run this code to see if it works, and to see if my work space is set up to handle a ANN. When I run it this is the error I keep getting, and I don't understand how to fix it.Your just trying to run the above code? I dont use Anaconda, so i cant really help with that issue. But to run the first snippet all you would need is python2.x and numpy for that same version. I say 2.x because the code has xrange() If your on linux....you can just do pip install numpy and then run the code in python2.x from the terminal If you want to run it under python3.x then remove the x from xrange() and pip3 install numpy and then run the same code with the python3.x interpreter
RE: Numpy Help - Larz60+ - Oct-23-2017 packages are loaded for particular versions of python, this is where the problem may lie. I'm not familiar with Anaconda. Is there a way to list installed packages in one of their tools? I use: import pip pip.get_installed_distributions()on windows, but not sure if you can use the same on Linux. RE: Numpy Help - metulburr - Oct-23-2017 Quote:Is there a way to list installed packages in one of their tools?it appears you would have to do conda list based on this below. But i was under the impression that anaconda lready came iwth numpy, that is where it shines, pre-installed packages. https://conda.io/docs/_downloads/conda-cheatsheet.pdf Quote:but not sure if you can use the same on Linux.yes it does appear so RE: Numpy Help - BlackHeart - Oct-24-2017 Honestly I just used Anaconda because it seemed like it had all the tools I needed. Maybe I should just uninstall it and use the native python that Ubuntu comes with. Conda list does give me a list in the terminal. Here are the current packages: _ipyw_jlab_nb_ext_conf 0.1.0 py36he11e457_0 alabaster 0.7.10 py36h306e16b_0 anaconda custom py36_0 anaconda-client 1.6.5 py36h19c0dcd_0 anaconda-navigator 1.6.8 py36h672ccc7_0 anaconda-project 0.8.0 py36h29abdf5_0 asn1crypto 0.22.0 py36h265ca7c_1 astroid 1.5.3 py36hbdb9df2_0 astropy 2.0.2 py36ha51211e_4 babel 2.5.0 py36h7d14adf_0 backports 1.0 py36hfa02d7e_1 backports.shutil_get_terminal_size 1.0.0 py36hfea85ff_2 beautifulsoup4 4.6.0 py36h49b8c8c_1 bitarray 0.8.1 py36h5834eb8_0 bkcharts 0.2 py36h735825a_0 blaze 0.11.3 py36h4e06776_0 bleach 2.0.0 py36h688b259_0 bokeh 0.12.7 py36h169c5fd_1 boto 2.48.0 py36h6e4cd66_1 bottleneck 1.2.1 py36haac1ea0_0 ca-certificates 2017.08.26 h1d4fec5_0 cairo 1.14.10 h58b644b_4 certifi 2017.7.27.1 py36h8b7b77e_0 cffi 1.10.0 py36had8d393_1 chardet 3.0.4 py36h0f667ec_1 click 6.7 py36h5253387_0 cloudpickle 0.4.0 py36h30f8c20_0 clyent 1.2.2 py36h7e57e65_1 colorama 0.3.9 py36h489cec4_0 conda 4.3.30 py36h5d9f9f4_0 conda-build 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py36h90ed295_0 olefile 0.44 py36h79f9f78_0 openpyxl 2.4.8 py36h41dd2a8_1 openssl 1.0.2l h9d1a558_3 packaging 16.8 py36ha668100_1 pandas 0.20.3 py36h842e28d_2 pandoc 1.19.2.1 hea2e7c5_1 pandocfilters 1.4.2 py36ha6701b7_1 pango 1.40.11 hedb6d6b_0 partd 0.3.8 py36h36fd896_0 patchelf 0.9 hf79760b_2 path.py 10.3.1 py36he0c6f6d_0 pathlib2 2.3.0 py36h49efa8e_0 patsy 0.4.1 py36ha3be15e_0 pcre 8.41 hc71a17e_0 pep8 1.7.0 py36h26ade29_0 pexpect 4.2.1 py36h3b9d41b_0 pickleshare 0.7.4 py36h63277f8_0 pillow 4.2.1 py36h9119f52_0 pip 9.0.1 py36h30f8307_2 pixman 0.34.0 ha72d70b_1 pkginfo 1.4.1 py36h215d178_1 ply 3.10 py36hed35086_0 prompt_toolkit 1.0.15 py36h17d85b1_0 psutil 5.2.2 py36h74c8701_0 ptyprocess 0.5.2 py36h69acd42_0 py 1.4.34 py36h0712aa3_1 pycodestyle 2.3.1 py36hf609f19_0 pycosat 0.6.2 py36h1a0ea17_1 pycparser 2.18 py36hf9f622e_1 pycrypto 2.6.1 py36h6998063_1 pycurl 7.43.0 py36h5e72054_3 pyflakes 1.5.0 py36h5510808_1 pygments 2.2.0 py36h0d3125c_0 pylint 1.7.2 py36h484ab97_0 pyodbc 4.0.17 py36h999153c_0 pyopenssl 17.2.0 py36h5cc804b_0 pyparsing 2.2.0 py36hee85983_1 pyqt 5.6.0 py36h0386399_5 pysocks 1.6.7 py36hd97a5b1_1 pytables 3.4.2 py36hdce54c9_1 pytest 3.2.1 py36h11ad3bb_1 python 3.6.2 hdfe5801_15 python-dateutil 2.6.1 py36h88d3b88_1 pytz 2017.2 py36hc2ccc2a_1 pywavelets 0.5.2 py36he602eb0_0 pyyaml 3.12 py36hafb9ca4_1 pyzmq 16.0.2 py36h3b0cf96_2 qt 5.6.2 h974d657_12 qtawesome 0.4.4 py36h609ed8c_0 qtconsole 4.3.1 py36h8f73b5b_0 qtpy 1.3.1 py36h3691cc8_0 readline 7.0 hac23ff0_3 requests 2.18.4 py36he2e5f8d_1 rope 0.10.5 py36h1f8c17e_0 ruamel_yaml 0.11.14 py36ha2fb22d_2 scikit-image 0.13.0 py36had3c07a_1 scikit-learn 0.19.0 py36h97ac459_2 scipy 0.19.1 py36h9976243_3 seaborn 0.8.0 py36h197244f_0 setuptools 36.5.0 py36he42e2e1_0 simplegeneric 0.8.1 py36h2cb9092_0 singledispatch 3.4.0.3 py36h7a266c3_0 sip 4.18.1 py36h51ed4ed_2 six 1.10.0 py36hcac75e4_1 snowballstemmer 1.2.1 py36h6febd40_0 sortedcollections 0.5.3 py36h3c761f9_0 sortedcontainers 1.5.7 py36hdf89491_0 sphinx 1.6.3 py36he5f0bdb_0 sphinxcontrib 1.0 py36h6d0f590_1 sphinxcontrib-websupport 1.0.1 py36hb5cb234_1 spyder 3.2.4 py36hbe6152b_0 sqlalchemy 1.1.13 py36hfb5efd7_0 sqlite 3.20.1 h6d8b0f3_1 statsmodels 0.8.0 py36h8533d0b_0 sympy 1.1.1 py36hc6d1c1c_0 tblib 1.3.2 py36h34cf8b6_0 terminado 0.6 py36ha25a19f_0 testpath 0.3.1 py36h8cadb63_0 tk 8.6.7 h5979e9b_1 toolz 0.8.2 py36h81f2dff_0 tornado 4.5.2 py36h1283b2a_0 traitlets 4.3.2 py36h674d592_0 typing 3.6.2 py36h7da032a_0 unicodecsv 0.14.1 py36ha668878_0 unixodbc 2.3.4 hc36303a_1 urllib3 1.22 py36hbe7ace6_0 wcwidth 0.1.7 py36hdf4376a_0 webencodings 0.5.1 py36h800622e_1 werkzeug 0.12.2 py36hc703753_0 wheel 0.29.0 py36he7f4e38_1 widgetsnbextension 3.0.2 py36hd01bb71_1 wrapt 1.10.11 py36h28b7045_0 xlrd 1.1.0 py36h1db9f0c_1 xlsxwriter 0.9.8 py36hf41c223_0 xlwt 1.3.0 py36h7b00a1f_0 xz 5.2.3 h2bcbf08_1 yaml 0.1.7 h96e3832_1 zeromq 4.2.2 hb0b69da_1 zict 0.1.2 py36ha0d441b_0 zlib 1.2.11 hfbfcf68_1 I've got a conda environment for both 2.7 and 3.6 I took the (x) our of xrange for the 3.6 and I'm still getting the same debugging error as I did up top with arrow pointing at the import function. I installed numpy into my conda 3.6 environment using the conda install --spyder2 numpycommand. RE: Numpy Help - metulburr - Oct-24-2017 Quote:I just used Anaconda because it seemed like it had all the tools I needed.To be honest i would just use the default python install or install python3.x if you wanted that. Anaconda isnt as used by as many people doing just a base install. All you have to do to install packages to OS python is pip install package_name1 package_name2 etc.then just link whatever IDE you want with that python interpreter that you installed those packages to. RE: Numpy Help - BlackHeart - Oct-24-2017 (Oct-24-2017, 01:10 AM)metulburr Wrote:Quote:I just used Anaconda because it seemed like it had all the tools I needed.To be honest i would just use the default python install or install python3.x if you wanted that. Anaconda isnt as used by as many people doing just a base install. All you have to do to install packages to OS python is I unintalled Anaconda. We'll see if this works a bit smoother. I appreciate all your responses guys. Hey guys, just wanted to let you know that I got it to work! metulburr you were totally right on. I got rid of Anaconda, installed pip, and then installed numpy. I decided to use pycharm as my IDE and I was able to specify my projects interpreter. Ran the script and I got an actual output! Thanks again everyone, you guys are awesome. |