I have downloaded the ipopt solver and set in its path into the environmental variables. If I type in ipopt in the terminal it shows:
No stub!
usage: ipopt [options] stub [-AMPL] [<assignment> ...]
Options:
-- {end of options}
-= {show name= possibilities}
-? {show usage}
-bf {read boundsfile f}
-e {suppress echoing of assignments}
-of {write .sol file to file f}
-s {write .sol file (without -AMPL)}
-v {just show version}
It is version: Ipopt-3.14.2-win64-msvs2019-md downloaded from here.
My model in pyomo looks like that:
from pyomo.environ import minimize, ConcreteModel, Var, Objective, SolverFactory
model = ConcreteModel()
model.x = Var()
model.y = Var()
def rosenbrock(m):
return (1.0-m.x)**2 + 100.0*(m.y - m.x**2)**2
model.obj = Objective(rule=rosenbrock, sense=minimize)
SolverFactory('mindtpy').solve(model, mip_solver='cplex', nlp_solver='ipopt')
The error is:
pyomo.common.errors.ApplicationError: No executable found for solver 'ipopt'
Other solutions that have been suggested on StackOverflow could not solve my problem. I hope someone can help me.
Related
I'm trying to create a script that will populate my model families with informations extracted from a text file.
This is my first post in StackOverflow, please be gentle, sorry if the question is not well expressed or not correctly formatted.
Django V 1.9 and running on Python 3.5
Django-extensions installed
This is my model: it's in an app called browse
from django.db import models
from django_extensions.db.models import TimeStampedModel
class families(TimeStampedModel):
rfam_acc = models.CharField(max_length=7)
rfam_id = models.CharField(max_length=40)
description = models.CharField(max_length=75)
author = models.CharField(max_length=50)
comment = models.CharField(max_length=500)
rfam_URL = models.URLField()
Here I have my script familiespopulate.py. Positioned in the PROJECT_ROOT/scripts directory.
import csv
from browse.models import families
file_path = "/Users/work/Desktop/StructuRNA/website/scripts/RFAMfamily12.1.txt"
def run(file_path):
listoflists = list(csv.reader(open(file_path, 'rb'), delimiter='\t'))
for row in listoflists:
families.objects.create(
rfam_acc=row[0],
rfam_id=row[1],
description=row[3],
author=row[4],
comment=row[9],
)
When from Terminal i run:
python manage.py runscript familiespopulate
it returns:
No (valid) module for script 'familiespopulate' found
Try running with a higher verbosity level like: -v2 or -v3
The problem must be in importing the model families, I'm new to django, and I cannot find any solution here on StackOverflow or anywhere else online.
This is why I ask for your help!
Do you know how the model should be imported?
Or... Am I doing something else wrong.
Important piece of information is that the script runs if I modify it to PRINT out the parameters, instead of creating an object in families.
For your information and curiosity I will also post here an extract of the textfile that I'm using.
RF00001 5S_rRNA 1302 5S ribosomal RNA Griffiths-Jones SR, Mifsud W, Gardner PP Szymanski et al, 5S ribosomal database, PMID:11752286 38.00 38.00 37.90 5S ribosomal RNA (5S rRNA) is a component of the large ribosomal subunit in both prokaryotes and eukaryotes. In eukaryotes, it is synthesised by RNA polymerase III (the other eukaryotic rRNAs are cleaved from a 45S precursor synthesised by RNA polymerase I). In Xenopus oocytes, it has been shown that fingers 4-7 of the nine-zinc finger transcription factor TFIIIA can bind to the central region of 5S RNA. Thus, in addition to positively regulating 5S rRNA transcription, TFIIIA also stabilises 5S rRNA until it is required for transcription. NULL cmbuild -F CM SEED cmcalibrate --mpi CM cmsearch --cpu 4 --verbose --nohmmonly -T 24.99 -Z 549862.597050 CM SEQDB 712 183439 0 0 Gene; rRNA; Published; PMID:11283358 7946 0 0.59496 -5.32219 1600000 213632 305 119 1 -3.78120 0.71822 2013-10-03 20:41:44 2016-04-21 23:07:03
This is the first line and the result of the extraction from the listoflists is :
RF00002
5_8S_rRNA
5.8S ribosomal RNA
Griffiths-Jones SR, Mifsud W
5.8S ribosomal RNA (5.8S rRNA) is a component of the large subunit of the eukaryotic ribosome. It is transcribed by RNA polymerase I as part of the 45S precursor that also contains 18S and 28S rRNA. Functionally, it is thought that 5.8S rRNA may be involved in ribosome translocation [2]. It is also known to form covalent linkage to the p53 tumour suppressor protein [3]. 5.8S rRNA is also found in archaea.
Try adding empty file __init__.py (double underscore) into your /scipts folder and run with:
python manage.py runscript scipts.familiespopulate
Apart from adding init.py you are not supposed to pass any parameters in the run method.
def run():
<your code goes here>
Thanks for the useful comments.
I modified my code in this way:
import csv
from browse.models import families
def run():
file_path = "/Users/work/Desktop/StructuRNA/website/scripts/RFAMfamily12.1.txt"
listoflists = list(csv.reader(open(file_path, 'r'),delimiter='\t'))
print(listoflists)
for row in listoflists:
families.objects.create(
rfam_acc=row[0],
rfam_id=row[1],
description=row[3],
author=row[4],
comment=row[9],
)
This is all. Now it worked smoothly.
I want to confirm to everyone that my file: familiespopulate.py was in the folder script with the file init.py
The problem seemed to be resolved when I put
file_path = "/Users/work/Desktop/StructuRNA/website/scripts/RFAMfamily12.1.txt"
Inside the run function, removing the parameter file_path from run(file_path).
Another modify to my code was the argument r inside open(file_path, 'r'), before it was open(file_path, 'rb') that should corrispond to read binary.
I was also getting exactly the same error, I tried all of the solution above but unfortunately did not worked for me. Then I realized my mistake, and I found it.
Inside the script file (which is inside the script/ folder) I used different name for the function, which should be named as 'run'. So, make sure you checked it as well, if you get this error.
Here you can read more about "runscript"
I've exhausted what I'm capable of currently regarding the script that I have posted below. I am unable to properly call gdal_calc.py with this script. I have received various error message regarding a lack of .dll files to a win32 error.
I have installed and reinstalled GDAL, however I continue to receive an error message that suggests I don't have osgeo, and I cannot install GDAL properly within my Python27 pathway because of an issue with Visual C++ for Python because I either don't have the proper .bat file OR I get this message.
fatal error C1083: Cannot open include file: 'cpl_port.h': No such file or directory
I would appreciate even a direction to be point in, because I am a novice and this is over my head.
Thanks,
import os
import sys
from osgeo import gdal
from gdalconst import *
import numpy as np
import math
import subprocess
from subprocess import call
import math
import PIL
from PIL import Image
# constants
gdalTranslate = r'C:\\Program Files (x86)\\GDAL\\gdal_translate.exe'
src = r"C:\Users\jack\Desktop\RUA_FIL\IMG-HV-ALOS2110871010-160611-HBQR1.5RUA.img"
srcVH = r"C:\Users\jack\Desktop\RUA_FIL\IMG-VH-ALOS2110871010-160611-HBQR1.5RUA.img"
dstVH = r"C:\Users\jack\Desktop\New_Trash\vhFloat32-3.img"
dst = r"C:\\Users\jack\Desktop\\New_Trash\hvFloat32-3.img"
cmd = "-ot Float32 -of HFA" # hopefully this works
#gdalCalc = r'C:\Python27\ArcGIS10.4\Scripts\dist\gdal_calc.exe'
#hvFloat32 = r"C:\Users\jack\Desktop\New_Trash\hvFloat32-1.img"
#vhFloat32 = r"C:\Users\jack\Desktop\New_Trash\hvFloat32-1.img"
#prevName = r"C:\Users\jack\Desktop\RUA_FIL\IMG-HV-ALOS2110871010-160611-HBQR1.5RUA"
#newName = r"C:\Users\jack\Desktop\RUA_FIL\IMG-HV-ALOS2110871010-160611-HBQR1.5RUA.img"
#os.rename(prevName,newName)
# setting def
#def gdal_Translate (item):
#return item
hvfullCmd = ' '.join([gdalTranslate, cmd, gdal_Translate(src), gdal_Translate(dst)])
subprocess.Popen(hvfullCmd)
vhfullCmd = ' '.join([gdalTranslate,cmd,gdal_Translate(srcVH),gdal_Translate(dstVH)])
subprocess.Popen(vhfullCmd)
# Run gdal_calc.py for HV
try:
os.system('C:\Users\jack\Python\QGIS Python Scripts\ridofZs.py')
except:
print ("This isn't working")
sys.exit()
subprocess.call([sys.executable,'C:\Program Files (x86)\GDAL\gdal_calc.py', '-A', 'C:\Users\jack\Desktop\New_Trash\hvFloat32.img', '--outfile=C:\Users\jack\Desktop\New_Trash\NEWCALCHV-2.img','--calc=A*(A>=1)'])
# Run gdal_calc.py for VH
#subprocess.call([sys.executable, 'C:\OSGeo4W64\bin\gdal_calc.py', '-A', 'C:\Users\jack\Desktop\New_Trash\vhFloat32.img', '--outfile=C:\Users\jack\Desktop\New_Trash\NEWCALCVH-2.img','--calc=A*(A>=1)'])
# Run gdal_calc.py to dB for HV
#subprocess.call([sys.executable, 'C:\OSGeo4W64\bin\gdal_calc.py', '-A', 'C:\Users\jack\Desktop\New_Trash\NEWCALCHV-2.img', '--outfile=C:\Users\jack\Desktop\New_Trash\HVindB.img','--calc=10*log10(power(A,2))-83'])
# Run gdal_calc.py to dB for HV
#subprocess.call([sys.executable, 'C:\OSGeo4W64\bin\gdal_calc.py', '-A', 'C:\Users\jack\Desktop\New_Trash\NEWCALCVH-2.img', '--outfile=C:\Users\jack\Desktop\New_Trash\VHindB.img','--calc=10*log10(power(A,2))-83'])
# Open Rasters using GDAL
hvRaster = gdal.Open("C:\\Users\\jack\\Desktop\\New_Trash\\hvFloat32.img")
vhRaster = gdal.Open("C:\\Users\\jack\\Desktop\\New_Trash\\vhFloat32.img")
# Get RasterBand
hvRasterBand = hvRaster.GetRasterBand(1)
vhRasterBand = vhRaster.GetRasterBand(1)
# Get Raster Mean
hvMean = hvRasterBand.GetStatistics(0,1)[2]
vhMean = vhRasterBand.GetStatistics(0,1)[2]
#### Maybe not needed
print hvMean
print vhMean
# calculate stDev
rasterList = (hvMean,vhMean)
stDev = np.std(rasterList)
#print stDev
if stDev >= 0.06:
print "The imagery isn't acceptable"
if stDev <= 0.06:
print "The imagery is acceptable"
I am learning TensorFlow and I stumble upon this example code for creating simple multi-layer sigmoid network. The program in the link is for MNIST database and hand written digit classification.
I want to train a network for regression task. I have 30 inputs(float) which is used to predict one output(float). So I tweaked the code to change the task from classification to regression.
My problem is that I'm getting an error in tf.Session.run(). The code and the error log is given below.
import test2
import tensorflow as tf
feed_input = test2.read_data_sets()
learning_rate = 0.001
training_epochs = 100
batch_size = 1716
display_step = 1
n_hidden_1 = 256
n_hidden_2 = 256
n_hidden_3 = 256
n_input = 30
x = tf.placeholder("float", [None, n_input])
y = tf.placeholder("float", [None])
def multilayer_perceptron(_X, _weights, _biases):
#Hidden layer with RELU activation
layer_1 = tf.nn.relu(tf.add(tf.matmul(_X, _weights['h1']), _biases['b1']))
#Hidden layer with RELU activationn_hidden_3
layer_2 = tf.nn.relu(tf.add(tf.matmul(layer_1, _weights['h2']), _biases['b2']))
layer_3 = tf.nn.relu(tf.add(tf.matmul(layer_2, _weights['h3']), _biases['b3']))
return tf.matmul(layer_3, weights['out']) + biases['out']
weights = {
'h1': tf.Variable(tf.random_normal([n_input, n_hidden_1])),
'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),
'h3': tf.Variable(tf.random_normal([n_hidden_2, n_hidden_3])),
'out': tf.Variable(tf.random_normal([n_hidden_3, 1]))
}
biases = {
'b1': tf.Variable(tf.random_normal([n_hidden_1])),
'b2': tf.Variable(tf.random_normal([n_hidden_2])),
'b3': tf.Variable(tf.random_normal([n_hidden_3])),
'out': tf.Variable(tf.random_normal([1]))
}
pred = multilayer_perceptron(x, weights, biases)
n_pred = tf.mul(pred, tf.convert_to_tensor(10000.00))
cost = tf.nn.sigmoid_cross_entropy_with_logits(n_pred, y)
optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate).minimize(cost)
init = tf.initialize_all_variables()
with tf.Session() as sess:
sess.run(init)
# Training cycle
for epoch in range(training_epochs):
avg_cost = 0
total_batch = int(feed_input.train._num_examples / batch_size)
# Loop over all batches
for i in range(total_batch):
batch_xs, batch_ys = feed_input.train.next_batch(batch_size)
# Fit training using batch data
sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys})
# Compute average loss
avg_cost += sess.run(cost, feed_dict={x: batch_xs, y: batch_ys}) / total_batch
# Display logs per epoch step
if epoch % display_step == 0:
print "Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(avg_cost)
print "Optimization Finished!"
runfile('/mnt/sdb6/Projects/StockML/demo1.py',
wdir='/mnt/sdb6/Projects/StockML')
Reloaded modules: tensorflow.python.ops.nn_grad,
tensorflow.python.training.momentum,
. . . .
tensorflow.python.util.protobuf,
google.protobuf.internal.enum_type_wrapper,
tensorflow.python.ops.nn_ops, tensorflow.python,
tensorflow.python.platform.test,
google.protobuf.internal.api_implementation, tensorflow,
google.protobuf.internal.encoder
Traceback (most recent call last):
File "", line 1, in
runfile('/mnt/sdb6/Projects/StockML/demo1.py', wdir='/mnt/sdb6/Projects/StockML')
File
"/usr/lib/python2.7/dist-packages/spyderlib/widgets/externalshell/sitecustomize.py",
line 685, in runfile
execfile(filename, namespace)
File
"/usr/lib/python2.7/dist-packages/spyderlib/widgets/externalshell/sitecustomize.py",
line 78, in execfile
builtins.execfile(filename, *where)
File "/mnt/sdb6/Projects/StockML/demo1.py", line 69, in
sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys})
File
"/home/rammak/.local/lib/python2.7/site-packages/tensorflow/python/client/session.py",
line 345, in run
results = self._do_run(target_list, unique_fetch_targets, feed_dict_string)
File
"/home/rammak/.local/lib/python2.7/site-packages/tensorflow/python/client/session.py",
line 406, in _do_run
except tf_session.StatusNotOK as e:
AttributeError: 'module' object has no attribute 'StatusNotOK'
Protobuf error is usually an installation issue , run it in a virtual env
# On Mac:
$ sudo easy_install pip # If pip is not already installed
$ sudo pip install --upgrade virtualenv
Next, set up a new virtualenv environment. To set it up in the directory ~/tensorflow, run:
$ virtualenv --system-site-packages ~/tensorflow
$ cd ~/tensorflow
Then activate the virtualenv:
$ source bin/activate # If using bash
$ source bin/activate.csh # If using csh
(tensorflow)$ # Your prompt should change
Inside the virtualenv, install TensorFlow:
(tensorflow)$ pip install --upgrade https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl
You can then run your TensorFlow program like:
(tensorflow)$ python tensorflow/models/image/mnist/convolutional.py
# When you are done using TensorFlow:
(tensorflow)$ deactivate # Deactivate the virtualenv
$ # Your prompt should change back
If you just begin to learn TensorFlow, I would suggest you trying out examples in TensorFlow/skflow first and then once you are more familiar with TensorFlow it would be fairly easy for you to insert TensorFlow code to build a custom model you want (there are also examples for this).
Hope those examples for images and text understanding could get you started and let us know if you encounter any issues! (post issues or tag skflow in SO).
Change your logging level from WARN to INFO, so that can get a better visualization of the error you're getting.
For knowledge purpose, you should know there are 5 logging levels:
DEBUG
INFO
WARN
ERROR
FATAL
I just wanted to know if matplotlib is compatible with kivy 1.9.0, and how I do I go about implementing it if it's possible? If it's isn't supported, does kivy have something very similar to it?
I want to able use this particular code from one my programs in my kivy app:
def printPieChart(table, column):
if column == 6:
columnList = table.iloc[:, -1:].values.T.ravel()
else:
columnList = table.iloc[:, (column - 7): (column - 6)].values.T.ravel()
countedList = Counter(columnList)
#set up the size of the pie chart
fig = plt.figure(figsize=[10, 10])
ax = fig.add_subplot(111)
cmap = plt.cm.prism
#input variables for pie function
slices = [float(v) for v in countedList.values()]
colors = cmap(np.linspace(0., 1., len(slices)))
labels = [float(k) for k in countedList]
columnHeaders = list(table.columns.values)
#the pie chart
pie_wedge_collection = ax.pie(slices, colors = colors, labels = labels, labeldistance = 1.05, autopct = '%1.1f%%')
#get rid of the black outlines between the wedges and around the pie
for pie_wedge in pie_wedge_collection[0]:
pie_wedge.set_edgecolor('white')
ax.set_title(columnHeaders[column + 1])
If I wanted to make a compilation recipe for matplotlib would it be along these lines?
#!/bin/bash
VERSION_matplotlib=${VERSION_matplotlib:-1.4.3}
DEPS_matplotlib=(numpy python dateutil pyparsing six linpng pytz freetype agg PyCXX qhull ttconv)
URL_matplotlib=http://pypi.python.org/packages/source/m/matplotlib/matplotlib-$VERSION_matplotlib.tar.gz
MD5_matplotlib=f43c20480a1673185afefc7d4848a1d2
BUILD_matplotlib=$BUILD_PATH/matplotlib/$(get_directory $URL_matplotlib)
RECIPE_matplotlib=$RECIPES_PATH/matplotlib
# function called for preparing source code if needed
# (you can apply patch etc here.)
function prebuild_matplotlib() {
true
}
function shouldbuild_lxml() {
if [ -d "$SITEPACKAGES_PATH/matplotlib" ]; then
DO_BUILD=0
fi
}
# function called to build the source code
function build_matplotlib() {
cd $BUILD_matplotlib
push_arm
export CC="$CC -I$BUILD_numpy/"
export LDFLAGS="-L$BUILD_numpy/numpy/.libs -L$BUILD_numpy/numpy/.libs -L$BUILD_numpy/.libs -L$BUILD_numpy/numpy -L$BUILD_numpy/numpy -L$BUILD_numpy/ $LDFLAGS"
export LDSHARED="$LIBLINK"
chmod +x $BUILD_numpy/numpy-config
export PATH=$PATH:$BUILD_numpy
#plus more for the other dependencies
try $HOSTPYTHON setup.py build_ext -I$BUILD_matplotlib
try find . -iname '*.pyx' -exec $CYTHON {} \;
try $HOSTPYTHON setup.py build_ext -v
try find build/lib.* -name "*.o" -exec $STRIP {} \;
export PYTHONPATH=$BUILD_hostpython/Lib/site-packages
try $BUILD_hostpython/hostpython setup.py install -O2 --root=$BUILD_PATH/python-install --install-lib=lib/python2.7/site-packages
unset LDSHARED
pop_arm
}
# function called after all the compile have been done
function postbuild_matplotlib() {
true
}
You can call matplotlib from a kivy script fine, exactly as you normally would, but kivy has no built in way to display plots - you'd have to get matplotlib to render them (e.g. as png, or you could try kivy's experimental svg support but it might be buggy) then display them in an Image widget or similar.
If you want to do this on android or ios, you'd need a compilation recipe for matplotlib, as I don't think we have one yet. I think that shouldn't be too hard and we'd be happy to discuss if if you're interested.
We do have a GSoC student working on giving us proper matplotlib support, so there may be good news on it in the next few months.
Im trying to execute the following code in Python 2.7 on Windows7. The purpose of the code is to take back up from the specified folder to a specified folder as per the naming pattern given.
However, Im not able to get it work. The output has always been 'Backup Failed'.
Please advise on how I get resolve this to get the code working.
Thanks.
Code :
backup_ver1.py
import os
import time
import sys
sys.path.append('C:\Python27\GnuWin32\bin')
source = 'C:\New'
target_dir = 'E:\Backup'
target = target_dir + os.sep + time.strftime('%Y%m%d%H%M%S') + '.zip'
zip_command = "zip -qr {0} {1}".format(target,''.join(source))
print('This is a program for backing up files')
print(zip_command)
if os.system(zip_command)==0:
print('Successful backup to', target)
else:
print('Backup FAILED')
See if escaping the \'s helps :-
source = 'C:\\New'
target_dir = 'E:\\Backup'