I am using IBM's quantum computing lab, and was following a tutorial made by IBM for getting started, and my code is throwing errors. I followed the tutorial exactly. Here is my code:
#-----------Cell 1:
import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, Aer, IBMQ
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
from qiskit.providers.aer import QasmSimulator
# Loading your IBM Quantum account(s)
provider = IBMQ.load_account()
#-----------Cell 2:
# Build
#------
# Create a Quantum Circuit acting on the q register
circuit = QuantumCircuit(2, 2)
# Add a H gate on qubit 0
circuit.h(0)
# Add a CX (CNOT) gate on control qubit 0 and target qubit 1
circuit.cx(0, 1)
# Map the quantum measurement to the classical bits
circuit.measure([0,1], [0,1])
# END
# Execute
#--------
# Use Aer's qasm_simulator
simulator = Aer.get_backend('qasm_simulator')
# Execute the circuit on the qasm simulator
job = execute(circuit, simulator, shots=1000)
# Grab results from the job
result = job.result()
# Return counts
counts = result.get_counts(circuit)
print("\nTotal count for 00 and 11 are:",counts)
# END
# Visualize
#----------
# Import draw_circuit, then use it to draw the circuit
from ibm_quantum_widgets import draw_circuit
draw_circuit(circuit)
# Analyze
#--------
# Plot a histogram
plot_histogram(counts)
# END
This code throws this error:
Traceback (most recent call last):
File "/tmp/ipykernel_59/1801586149.py", line 26, in <module>
job = execute(circuit, simulator, shots=1000)
NameError: name 'execute' is not defined
Use %tb to get the full traceback.
I am new to IBM and quantum computing, how do I fix this error?
Here is the tutorial I was following if you need it: https://quantum-computing.ibm.com/lab/docs/iql/first-circuit
You did not import execute from qiskit.
Change
from qiskit import QuantumCircuit, transpile, Aer, IBMQ
to
from qiskit import QuantumCircuit, transpile, Aer, IBMQ, execute
Related
When trying to run the ljspeech example, I get the following error, even when the model is moved to the only GPU in the system. I am using Cuda 11.7, Pytorch 1.13.1, and Fairseq 0.12.2.
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument index in method wrapper__index_select)
The code used:
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
from fairseq.models.text_to_speech.hub_interface import TTSHubInterface
import IPython.display as ipd
import torch
models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
"facebook/fastspeech2-en-ljspeech",
arg_overrides={"vocoder": "hifigan", "fp16": False}
)
model = models[0].to(torch.device('cuda'))
models[0] = model
TTSHubInterface.update_cfg_with_data_cfg(cfg, task.data_cfg)
generator = task.build_generator(models, cfg)
text = "Hello, this is a test run."
sample = TTSHubInterface.get_model_input(task, text)
wav, rate = TTSHubInterface.get_prediction(task, model, generator, sample)
ipd.Audio(wav, rate=rate)
I couldn't plot the real time serial data come from arduino.
I working on a project this project details are like that :
I have pressure sensor that detects the pressure on them probs.I transfer the pressure measured on the probes to the computer via serial port communication with the help of arduino uno.
ı can read the data come from arduino on the Spyder Editor(python)
Using this data ( 2 pressure value coming from arduino) ı have to plot real time serial data on the GUI.
I create the GUI.
But I couldn't plot the data.
I would really appreciate any help or comments , thanks for every effort !
`
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 29 03:57:27 2022
#author: Berk
"""
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure
import tkinter as tk
import numpy as np
import serial
import time
import datetime
xs=[]
ys=[]
serialPort=serial.Serial(port="COM5", baudrate=9600,
bytesize=8,timeout=2,stopbits=serial.STOPBITS_ONE)
cond=False
date=str(datetime.datetime.now())
date=date.replace(" ",",")
date=date.replace(":",".")
while (True):
try:
if (serialPort.in_waiting > 0):
serialString=serialPort.readline()
data=serialString.decode("utf8", errors="replace")
replaced_data=data.replace("\r","")
replaced_data=replaced_data.replace("\n","")
# replaced_data=replaced_data.replace(":","-")
print(replaced_data)
###---plot data---###
def plot_data():
global cond,data
data=np.append()
print(data)
if(cond==True):
a=serialPort.readline()
a.decode()
if(len(data<100)):
data=np.append(data,float(a[0:4]))
else:
data[0:99]=data[1:100]
data[99]=float(a[0:4])
print(a)
lines.set_xdata(np.arange(0,len(data)))
lines.set_ydata(data)
canvas.draw()
def plot_start():
global cond
cond=True
serialPort.reset_input_buffer()
def plot_stop():
global cond
cond=False
#######GUI########
root=tk.Tk()
root.title('Pressure Value From Sensor')
root.configure(background='light blue')
root.geometry("700x500")
#####PLOTTİN ON GUI##########
fig=Figure();
ax=fig.add_subplot(111)
ax.set_title('Pressure By Time')
ax.set_xlabel('By Time')
ax.set_ylabel('Pressure')
ax.set_xlim(0,500)
ax.set_ylim(0,500)
lines=ax.plot([],[],0)
canvas=FigureCanvasTkAgg(fig,master=root)
canvas.get_tk_widget().place(x=10,y=10,width=500,height=400)
canvas.draw()
root.after(1,plot_data)
##button##
root.update();
start=tk.Button(root,text='Stop',font=('calibri',12),command=lambda:plot_start())
start.place(x=100,y=450)
root.update();
start=tk.Button(root,text='Start',font=('calibri',12),command=lambda:plot_stop())
start.place(x=start.winfo_x()+start.winfo_reqwidth()+20,y=450)
##startint serial port###
serialPort=serial.Serial(port="COM5", baudrate=9600,
bytesize=8,timeout=2,stopbits=serial.STOPBITS_ONE)
serialPort.reset_input_buffer()
root.after(1,plot_data)
root.mainloop()
`
I was doing some testing with imports, and I wanted to test how fast certain packages get imported using function decorators. Here is my code:
import time
def timeit(func):
def wrapper():
start = time.time()
func()
end = time.time()
print(f'{func.__name__} executed in {end - start} second(s)')
return wrapper
#timeit
def import_matplotlib():
import matplotlib.pyplot
#timeit
def import_numpy():
import numpy
import_matplotlib()
import_numpy()
Output
import_matplotlib executed in 0.4385249614715576 second(s)
import_numpy executed in 0.0 second(s)
This is not the expected output given that numpy isn't imported in an instant. What is happening here, and how can this be fixed? Thank you.
Edit
If I make this change to import_numpy():
#timeit
def import_numpy():
import numpy
time.sleep(2)
The output becomes this:
import_matplotlib executed in 0.4556155204772949 second(s)
import_numpy executed in 2.0041260719299316 second(s)
This tells me that there isn't anything wrong with my decorator function. Why is this behavior occurring?
Try using the timeit module? It was built for this purpose and makes that code simpler.
>>> import timeit
>>> timeit.timeit(stmt='import numpy')
0.13844075199995132
from pydotplus import graph_from_dot_data
from sklearn.tree import export_graphviz
from IPython.display import Image
dot_data = export_graphviz(tree,filled=True,rounded=True,class_names=['Setosa','Versicolor','Virginica'],feature_names=['petal length','petal width'],out_file=None)
graph = graph_from_dot_data(dot_data)
Image(graph.create_png())
Program terminated with status:
1. stderr follows: 'C:\Users\En' is not recognized as an internal or external command,
operable program or batch file.
it seems that it split my username into half.How do i overcome this?
I have a very similar example that I'm trying out, it's based on a ML how-to book which is working with a Taiwan Credit Card dataset predicting default risk. My setup is as follows:
from six import StringIO
from sklearn.tree import export_graphviz
from IPython.display import Image
import pydotplus
Then creating the decision tree plot is done in this way:
dot_data = StringIO()
export_graphviz(decision_tree=class_tree,
out_file=dot_data,
filled=True,
rounded=True,
feature_names = X_train.columns,
class_names = ['pay','default'],
special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
Image(graph.create_png())
I think it's all coming from the out_file=dot_data argument but cannot figure out where the file path is created and stored as print(dot_data.getvalue()) did not show any pathname.
In my research I came across sklearn.plot_tree() which seems to do everything that the graphviz does. So I took the above exporet_graphviz arguments and were matching arguments were in the .plot_tree method I added them.
I ended up with the following which created the same image as was found in the text:
from sklearn import tree
plt.figure(figsize=(20, 10))
tree.plot_tree(class_tree,
filled=True, rounded=True,
feature_names = X_train.columns,
class_names = ['pay','default'],
fontsize=12)
plt.show()
I'm trying to run a code from github that uses Python to classify images but I'm getting an error.
here is the code:
import argparse as ap
import cv2
import imutils
import numpy as np
import os
from sklearn.svm import LinearSVC
from sklearn.externals import joblib
from scipy.cluster.vq import *
# Get the path of the testing set
parser = ap.ArgumentParser()
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("-t", "--testingSet", help="Path to testing Set")
group.add_argument("-i", "--image", help="Path to image")
parser.add_argument('-v',"--visualize", action='store_true')
args = vars(parser.parse_args())
# Get the path of the testing image(s) and store them in a list
image_paths = []
if args["testingSet"]:
test_path = args["testingSet"]
try:
testing_names = os.listdir(test_path)
except OSError:
print "No such directory {}\nCheck if the file exists".format(test_path)
exit()
for testing_name in testing_names:
dir = os.path.join(test_path, testing_name)
class_path = imutils.imlist(dir)
image_paths+=class_path
else:
image_paths = [args["image"]]
and this is the error message I'm getting
usage: getClass.py [-h]
(- C:/Users/Lenovo/Downloads/iris/bag-of-words-master/dataset/test TESTINGSET | - C:/Users/Lenovo/Downloads/iris/bag-of-words-master/dataset/test/test_1.jpg IMAGE)
[- C:/Users/Lenovo/Downloads/iris/bag-of-words-master/dataset]
getClass.py: error: one of the arguments - C:/Users/Lenovo/Downloads/iris/bag-of-words-master/dataset/test/--testingSet - C:/Users/Lenovo/Downloads/iris/bag-of-words-master/dataset/test/test_1.jpg/--image is required
can you please help me with this? where and how should I write the file path?
This is an error your own program is issuing. The message is not about the file path but about the number of arguments. This line
group = parser.add_mutually_exclusive_group(required=True)
says that only one of your command-line arguments (-t, -i) is permitted. But it appears from the error message that you are supplying both --testingSet and --image on your command line.
Since you only have 3 arguments, I have to wonder if you really need argument groups at all.
To get your command line to work, drop the mutually-exclusive group and add the arguments to the parser directly.
parser.add_argument("-t", "--testingSet", help="Path to testing Set")
parser.add_argument("-i", "--image", help="Path to image")
parser.add_argument('-v',"--visualize", action='store_true')