Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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10,000 | <ASSISTANT_TASK:>
Python Code:
import os
PROJECT = "cloud-training-demos" # REPLACE WITH YOUR PROJECT ID
BUCKET = "cloud-training-demos-ml" # REPLACE WITH YOUR BUCKET NAME
REGION = "us-central1" # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
# Do not change these
os.environ["PROJECT"] = PROJECT
os.environ["BUCKET"]... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Create raw dataset
Step3: Create dataset for WALS
Step4: Creating rows and columns datasets
Step5: To summarize, you created the following da... |
10,001 | <ASSISTANT_TASK:>
Python Code:
a = spot.translate('a U b U c')
a.show('.#')
a.highlight_edges([2, 4, 5], 1)
a.highlight_edge(6, 2).highlight_states((0, 1), 0)
a.highlight_states([False, True, True], 5)
print(a.to_str('HOA', '1'))
print()
print(a.to_str('HOA', '1.1'))
b = spot.translate('X (F(Ga <-> b) & GF!b)'); ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The # option of print_dot() can be used to display the internal number of each transition
Step2: Using these numbers you can selectively hightl... |
10,002 | <ASSISTANT_TASK:>
Python Code:
import sys
import pandas as pd
import matplotlib.pyplot as plt
import datetime as dt
import numpy as np
import html5lib
from bs4 import BeautifulSoup
import seaborn.apionly as sns
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Players selected into All-NBA teams
Step2: Players Drafted
Step3: Merge both data tables
|
10,003 | <ASSISTANT_TASK:>
Python Code:
# A bit of setup
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] = 'gray'
# for auto-reloading external modules
# see h... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Implementing a Neural Network
Step2: The neural network parameters will be stored in a dictionary (model below), where the keys are the paramet... |
10,004 | <ASSISTANT_TASK:>
Python Code:
from neon.callbacks.callbacks import Callbacks
from neon.initializers import Gaussian
from neon.layers import GeneralizedCost, Affine, Multicost, SingleOutputTree
from neon.models import Model
from neon.optimizers import GradientDescentMomentum
from neon.transforms import Rectlin, Logisti... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We also set up the backend and load the data.
Step2: Now its your turn! Set up the branch nodes and layer structure above. Some tips
Step3: No... |
10,005 | <ASSISTANT_TASK:>
Python Code:
import osmdigest.pythonify as pythonify
import os
basedir = os.path.join("/media/disk", "OSM_Data")
filename = "illinois-latest.osm.xz"
tags = pythonify.Tags(os.path.join(basedir, filename))
pythonify.pickle(tags, "illinois_tags.pic.xz")
os.stat("illinois_tags.pic.xz").st_size / 1024**2
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Extract tags
Step2: Load tags back in
Step3: Extract nodes
Step4: Extract ways and relations
Step5: Load back node data and recompress
Step6... |
10,006 | <ASSISTANT_TASK:>
Python Code:
### import two datasets
def reindex_xcms_by_mzrt(df):
df.index = (df.loc[:,'mz'].astype('str') +
':' + df.loc[:, 'rt'].astype('str'))
return df
# alzheimers
local_path = '/home/irockafe/Dropbox (MIT)/Alm_Lab/'\
'projects'
alzheimers_path = local_path + '/revo_healt... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <h2> Looks like There aren't too many ppm m/z overlaps </h2>
Step2: <h2> So, about 1/4 of the mass-matches have potential isomers in the other ... |
10,007 | <ASSISTANT_TASK:>
Python Code:
from spectral import *
import spectral.io.envi as envi
import numpy as np
import matplotlib
ls ../../data/D02_SERC
img = envi.open('../../data/D02_SERC/NEON_D02_SERC_DP3_368000_4306000_reflectance.hdr',
'../../data/D02_SERC/NEON_D02_SERC_DP3_368000_4306000_reflectance.dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: For this example, we will read in a reflectance tile from the site SERC (Smithsonian Ecological Research Center) since this has a variety of lan... |
10,008 | <ASSISTANT_TASK:>
Python Code:
# As usual, a bit of setup
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.fc_net import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array
from cs231n.solver impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Dropout
Step2: Dropout forward pass
Step3: Dropout backward pass
Step4: Fully-connected nets with Dropout
Step5: Regularization experiment
|
10,009 | <ASSISTANT_TASK:>
Python Code:
import dogs_vs_cats as dvc
all_files = dvc.image_files()
from keras.applications.nasnet import NASNetMobile
from keras.preprocessing import image
from keras.applications.vgg16 import preprocess_input, decode_predictions
import numpy as np
# https://keras.io/applications/#vgg16
model = NA... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Imagenet pretrained models
Step2: Imagenet 1000 classes
Step3: Using pretrained CNN as feature extractors
|
10,010 | <ASSISTANT_TASK:>
Python Code:
# Useful Libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import t
import scipy.stats
prices1 = get_pricing('TSLA', start_date = '2015-01-01', end_date = '2016-01-01', fields = 'price')
returns_sample_tsla = prices1.pct_change()[1:]
print ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Exercise 1
Step2: Write your hypotheses here
Step3: b. Two tailed test.
Step4: Exercise 2
Step5: b. Mean T-Test
Step6: c. Mean p-value test... |
10,011 | <ASSISTANT_TASK:>
Python Code:
import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BCM)
GPIO.setup(18, GPIO.OUT)
p = GPIO.PWM(18, 50)
p.start(2.5)
p.ChangeDutyCycle(5.0)
p.ChangeDutyCycle(7.0)
p.ChangeDutyCycle(4.0)
time.sleep(0.2)
p.ChangeDutyCycle(10.0)
time.sleep(0.2)
p.ChangeDutyCycle(5.0)
time.sleep(0.2)
p.Ch... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set up the port as a PWM port with a 50Hz frequency
Step2: Start at the 0 degree position (for most motors, this is a 2.5% duty cycle).
Step3: ... |
10,012 | <ASSISTANT_TASK:>
Python Code:
import graphlab
sales = graphlab.SFrame('home_data.gl/')
sales.head(5)
graphlab.canvas.set_target('ipynb')
sales.show(view="Scatter Plot", x="sqft_living", y="price")
train_data,test_data = sales.random_split(.8,seed=123)
sqft_model = graphlab.linear_regression.create(train_data, targ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load some house sales data
Step2: Exploring the data for housing sales
Step3: Create a simple regression model of sqft_living to price
Step4: ... |
10,013 | <ASSISTANT_TASK:>
Python Code:
import csv
import json
import JobsMapResultsFilesToContainerObjs as ImageMap
import DeriveFinalResultSet as drs
import DataStructsHelper as DS
import importlib
import pandas as pd
import htmltag as HT
from collections import OrderedDict
#import matplotlib.pyplot as plt
import plotly.plotl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Rank list of images by share rates with Microsoft Image Tagging API output
Step2: Generate rank list of tags by share rate.
|
10,014 | <ASSISTANT_TASK:>
Python Code::
import tensorflow as tf
from tensorflow.keras.losses import MeanSquaredError
y_true = [1., 0.]
y_pred = [2., 3.]
mse_loss = MeanSquaredError()
loss = mse_loss(y_true, y_pred).numpy()
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
10,015 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = "retina"
from matplotlib import rcParams
rcParams["savefig.dpi"] = 100
rcParams["figure.dpi"] = 100
rcParams["font.size"] = 20
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(42)
true_params = np.array([0.5, -2.3,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: In this post, I will demonstrate how you can use emcee to sample models defined using PyMC3.
Step2: Then, we can code up the model in PyMC3 fol... |
10,016 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('/opt/rhc')
import rhc.micro as micro
import rhc.async as async
import logging
logging.basicConfig(level=logging.DEBUG)
p=micro.load_connection([
'CONNECTION placeholder http://jsonplaceholder.typicode.com',
'RESOURCE document /posts/{id}',
])
async.wai... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create a simple resource
Step2: Define a mock for the resource
Step3: Call the mocked resource
Step4: What is going on here?
|
10,017 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pickle as pkl
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data')
def model_inputs(real_dim, z_dim):
inputs_real = tf.placeholde... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Model Inputs
Step2: Generator network
Step3: Discriminator
Step4: Hyperparameters
Step5: Build network
Step6: Discriminator and Generator L... |
10,018 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
# tutoriel_graphe
noeuds = {0: 'le', 1: 'silences', 2: 'quelques', 3: '\xe9crit', 4: 'non-dits.', 5: 'Et', 6: 'risque', 7: '\xe0', 8: "qu'elle,", 9: 'parfois', 10: 'aim\xe9', 11: 'lorsque', 12: 'que', 13: 'plus', 14: 'les', ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Un graphe
Step2: Partie 1
Step3: Q4
Step4: Q6
Step5: Q7
Step6: On note $d(X_1,X_2)$ la distance euclidienne entre deux points $X_1$ et $X_... |
10,019 | <ASSISTANT_TASK:>
Python Code:
img = np.random.ranf((128,128))
plt.imshow(img, cmap=plt.cm.ocean)
def seed(n, shape=(8,)):
global r
np.random.seed(n)
r = np.random.ranf(shape)
seed(0)
x = np.arange(0, len(r), 1)
plt.plot(x, r[x], 'bo')
plt.axis('tight')
def noise(x):
x = int(x % len(r))
return r[... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: value noise
Step2: We can visualize r by plotting it.
Step3: We can use this table to define a function noise that given an integer value x wi... |
10,020 | <ASSISTANT_TASK:>
Python Code:
# 1. open the text file
infile = open('data/39.txt')
# 2. read the file and assign it to the variable 'text'
text = infile.read()
# 3. close the text file
infile.close()
# 4. split the variable 'text' into distinct word strings
words = text.split()
# 5. define the'count_in_list' function... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now that we have loaded our file, we can begin to work on it. <i>Python</i> offers us a lot of pre-built tools to make the task of coding easier... |
10,021 | <ASSISTANT_TASK:>
Python Code:
import os
from hiclib import mapping
from mirnylib import h5dict, genome
bowtie_path = '/opt/conda/bin/bowtie2'
enzyme = 'DpnII'
bowtie_index_path = '/home/jovyan/GENOMES/HG19_IND/hg19_chr1'
fasta_path = '/home/jovyan/GENOMES/HG19_FASTA/'
chrms = ['1']
genome_db ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: In this case, we have multiple datasets, thus we have to iterate through the list of files.
Step2: <a id="filtering"></a>
Step3: <a id="visual... |
10,022 | <ASSISTANT_TASK:>
Python Code:
!pip install -I "phoebe>=2.2,<2.3"
%matplotlib inline
import phoebe
logger = phoebe.logger()
b = phoebe.default_binary()
b.add_dataset('lc', times=phoebe.linspace(0,1,101), dataset='lc01')
print(b['ld_mode_bol@primary'])
print(b['ld_func_bol@primary'])
print(b['ld_func_bol@primary'].ch... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: As always, let's do imports and initialize a logger and a new bundle. See Building a System for more details.
Step2: We'll just add an 'lc' da... |
10,023 | <ASSISTANT_TASK:>
Python Code:
import glob
from os.path import join
import os
import csv
import shutil
import json
from itertools import product
from qiime2 import Artifact
from qiime2.plugins import feature_classifier
from q2_types.feature_data import DNAIterator
from q2_feature_classifier.classifier import \
spec... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: File Paths and Communities
Step2: Import Reference Databases
Step3: Amplicon and Read Extraction
Step4: Find Class Weights
Step5: Classifier... |
10,024 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import astropy.io.fits as pyfits
import numpy as np
import os
import urllib
import astropy.visualization as viz
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 10.0)
targdir = 'a1835_xmm'
if not os.path.isdi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Download the example data files if we don't already have them.
Step2: The XMM MOS2 image
Step3: imfits is a FITS object, containing multiple d... |
10,025 | <ASSISTANT_TASK:>
Python Code:
try:
get_ipython().magic(u'load_ext autoreload')
get_ipython().magic(u'autoreload 2')
get_ipython().magic(u'matplotlib qt')
except:
pass
import logging
import matplotlib.pyplot as plt
import numpy as np
logging.basicConfig(format=
"%(relativeCreat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Select file(s) to be processed
Step2: Setup a cluster
Step3: Setup some parameters
Step4: Motion Correction
Step5: Load memory mapped file
S... |
10,026 | <ASSISTANT_TASK:>
Python Code:
# index
# index1 = table.cols.date.create_index()
# read the first couple of rows (like df.head)
tbf = tb.open_file("/global/scratch/ryee/symbol_count/agg_count.h5", "a")
table = tbf.root.count_table.read()
table['count'].sum()
df = DataFrame(table)
df.head()
df["count"].sum()
cdf = Dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: naive
Step2: even use pandas
|
10,027 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import suspect
image = suspect.image.load_dicom_volume("00004_MPRAGE/i5881167.MRDC.15.img")
data, wref = suspect.io.load_pfile("P75264.e02941.s00007.7")
voxel_mask = suspect.image.create_mask(data, image)
masked_mask = np.ma.masked_wher... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Here we load the data, in this case a DICOM image set and a GE P-file. For the DICOM volume we pass a single file and the containing folder is p... |
10,028 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'fio-ronm', 'sandbox-1', 'atmos')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
10,029 | <ASSISTANT_TASK:>
Python Code:
#rootname = "/media/p/5F5B-8FCB/PROJECTS/UMAR/Data/chem/" #thumb on ubuntu
rootname = "E:\\PROJECTS\\UMAR\\Data\\chem\\" #thumb on windows
WQPResultsFile = rootname + "result.csv"
WQPStationFile = rootname + "station.csv"
SDWISFile = rootname + "SDWIS_Cache.txt"
AGStationsFile = rootname ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: WQP
Step2: Read csv data into python.
Step3: Rename columns to match with other data later.
Step4: Define unneeded columns that will be dropp... |
10,030 | <ASSISTANT_TASK:>
Python Code:
from tock import *
m1 = Machine([BASE, BASE, BASE, BASE], state=0, input=1)
m1.set_start_state('q1')
m1.add_transition('q1, &, &, & -> q2, &, $, $')
m1.add_transition('q2, a, &, & -> q2, &, a, &')
m1.add_transition('q2, b, &, & -> q2, &, b, &')
m1.add_transition('q2, # # #, &, & -> q3, ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We've seen finite automata, pushdown automata, and Turing machines, but many other kinds of automata can be created by instantiating a Machine d... |
10,031 | <ASSISTANT_TASK:>
Python Code:
# Imports the functionality that we need to display YouTube videos in
# a Jupyter Notebook.
# You need to run this cell before you run ANY of the YouTube videos.
from IPython.display import YouTubeVideo
# Don't forget to watch the video in full-screen mode!
YouTubeVideo("BTXyE3KLIOs"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Some useful numpy references
Step2: Question 2
Step3: Potentially useful links
Step4: Potentially useful links
Step6: Assignment wrapup
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10,032 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import h5py
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] = 'gray'
%load_ext autoreload
%autoreload 2
np.random.seed(1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: 2 - Outline of the Assignment
Step4: Expected Output
Step6: Expected Output
Step8: Expected Output
Step10: Expected Output
Step12: Expected... |
10,033 | <ASSISTANT_TASK:>
Python Code:
import os
from datetime import timedelta
import mne
sample_data_folder = mne.datasets.sample.data_path()
sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
'sample_audvis_raw.fif')
raw = mne.io.read_raw_fif(sample_data_raw_file, ve... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: ~mne.Annotations in MNE-Python are a way of storing short strings of
Step2: Notice that orig_time is None, because we haven't specified it. In
... |
10,034 | <ASSISTANT_TASK:>
Python Code:
import rebound
import numpy as np
def setupSimulation(Nplanets):
sim = rebound.Simulation()
sim.integrator = "ias15" # IAS15 is the default integrator, so we don't need this line
sim.add(m=1.,id=0)
for i in range(1,Nbodies):
sim.add(m=1e-5,x=i,vy=i**(-0.5),id=i)
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now let's do a simple example where we do a short initial integration to isolate the particles that interest us for a longer simulation
Step2: ... |
10,035 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 解码用于医学成像的 DICOM 文件
Step2: 安装要求的软件包，然后重新启动运行时
Step3: 解码 DICOM 图像
Step4: 解码 DICOM 元数据和使用标记
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10,036 | <ASSISTANT_TASK:>
Python Code:
tips = sns.load_dataset("tips")
sns.kdeplot(data=tips, x="total_bill")
sns.kdeplot(data=tips, y="total_bill")
iris = sns.load_dataset("iris")
sns.kdeplot(data=iris)
sns.kdeplot(data=tips, x="total_bill", bw_adjust=.2)
ax= sns.kdeplot(data=tips, x="total_bill", bw_adjust=5, cut=0)
sns... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Flip the plot by assigning the data variable to the y axis
Step2: Plot distributions for each column of a wide-form dataset
Step3: Use less sm... |
10,037 | <ASSISTANT_TASK:>
Python Code:
myvars = {}
with open("Twitter_keys.txt") as myfile:
for line in myfile:
name, var = line.partition("=")[::2]
myvars[name.strip()] = var
APP_KEY = myvars["APP_KEY"].rstrip()
APP_SECRET = myvars["APP_SECRET"].rstrip()
OAUTH_TOKEN = myvars["OAUTH_TOKEN"].rstrip()
OAUTH_T... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: A variable save_path is created which contains the path to the folder where the tweet files in json format will be stored. The folder name is sa... |
10,038 | <ASSISTANT_TASK:>
Python Code:
from Bio import Entrez
Entrez.email = "A.N.Other@example.com"
from Bio import Entrez
Entrez.tool = "MyLocalScript"
from Bio import Entrez
Entrez.email = "A.N.Other@example.com" # Always tell NCBI who you are
handle = Entrez.einfo()
result = handle.read()
print(result)
from Bio impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <span>Bio.Entrez</span> will then use this email address with each
Step2: The tool parameter will default to Biopython.
Step3: Since this is a... |
10,039 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from unidecode import unidecode
import time
from bokeh.charts import Bar, output_file, show
from bokeh.sampledata.autompg import autompg as df
from bokeh.io import output_notebook, show
output_notebook()
jobs = pd.r... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Top cities and countries posting jobs
Step2: Top technologies for a given city (London, Amsterdam and San Francisco)
Step3: Dumping out data t... |
10,040 | <ASSISTANT_TASK:>
Python Code:
# the output of plotting commands is displayed inline within frontends,
# directly below the code cell that produced it
%matplotlib inline
# this python library provides generic shallow (copy) and deep copy (deepcopy) operations
from copy import deepcopy
import time
# import from Ocelot... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Layout of the corrugated structure insertion. Create Ocelot lattice <img src="4_layout.png" />
Step2: Load beam file
Step3: Initialization of ... |
10,041 | <ASSISTANT_TASK:>
Python Code:
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('ticks')
import functools
import importlib.resources
import numpy as np
import os
import pandas as pd
pd.plotting.register_matplotlib_converters()
import xarray as xr
from IPython.display import d... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Helper methods for visualization
Step2: 1. Define the trial
Step3: Choose trial parameters
Step4: 2. Load incidence forecasts
Step5: 3. Simu... |
10,042 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
from sklearn.preprocessing import Imputer
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split as tts
from sklearn.ensemble impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <h3>II. Preprocessing </h3>
Step2: The SVM is sensitive to feature scale so the first step is to center and normalize the data. The train and t... |
10,043 | <ASSISTANT_TASK:>
Python Code:
from IPython.core.display import display, HTML
from string import Template
import pandas as pd
import json, random
HTML('<script src="lib/d3/d3.min.js"></script>')
html_template = Template('''
<style> $css_text </style>
<div id="graph-div"></div>
<script> $js_text </script>
''')
css_text... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Graph Config
Step2: Initial Data, Graph and Update
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10,044 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
def tracePlot(chains, labels=None, truths=None):
n_dim = chains.shape[2]
fig, ax = plt.subplots(n_dim, 1, figsize=(8., 27.), sharex=True)
ax[-1].set_xlabel('Iteration', fontsize=20.)
for i in range... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Defining convergence diagnostics
Step2: Process samples
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10,045 | <ASSISTANT_TASK:>
Python Code:
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, sof... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Introduction to Regular Expressions
Step2: Now that we have a compiled regular expression, we can see if the pattern matches another string.
St... |
10,046 | <ASSISTANT_TASK:>
Python Code:
import ENESNeoTools
from py2neo import Graph, Node, Relationship, authenticate
authenticate("localhost:7474", ENESNeoTools.user_name, ENESNeoTools.pass_word)
# connect to authenticated graph database
graph = Graph("http://localhost:7474/db/data/")
from neo4jrestclient.client import Grap... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: also rest client possible
Step2: Set up a data collection graph
Step3: Data servers graph setup
Step4: Combine data set graph with server gra... |
10,047 | <ASSISTANT_TASK:>
Python Code:
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install empiricaldist
# Get utils.py
from os.path import basename, exists
def download(url):
filename = basename(url)
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This chapter introduces the Poisson process, which is a model used to describe events that occur at random intervals.
Step2: The result is an o... |
10,048 | <ASSISTANT_TASK:>
Python Code:
import my_util as my_util
import cluster_skill_helpers as cluster_skill_helpers
from cluster_skill_helpers import *
import random as rd
HOME_DIR = 'd:/larc_projects/job_analytics/'
SKILL_DAT = HOME_DIR + 'data/clean/skill_cluster/'
SKILL_RES = HOME_DIR + 'results/' + 'skill_cluster/new/'... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Steps of skill clustering
Step1: First, we try it on count matrix as the matrix is already avail.
Step2: There are various choices to initialize NMF i... |
10,049 | <ASSISTANT_TASK:>
Python Code:
import yaml
# Set `PATH` to include the directory containing TFX CLI.
PATH = %env PATH
%env PATH=/home/jupyter/.local/bin:{PATH}
!python -c "import tfx; print('TFX version: {}'.format(tfx.__version__))"
%pip install --upgrade --user tfx==0.25.0
# Use the following command to identify th... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Note
Step2: Note
Step3: CUSTOM_SERVICE_ACCOUNT - In the gcp console Click on the Navigation Menu and navigate to IAM & Admin, then to Serv... |
10,050 | <ASSISTANT_TASK:>
Python Code:
import json
import urllib.request as request
url = 'http://www.omdbapi.com/?t=Scandal&Season=3'
content = request.urlopen(url).read()
data = json.loads(content.decode('UTF-8'))
print(data)
print(data['Episodes'][0])
print(data['Episodes'][6]['imdbRating'])
ratings = []
for episode in... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We're using two params. t (for title) and Season. Change values as you wish
Step2: Now let's take a look at what data we have
Step3: Okay! As... |
10,051 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
x = np.array([[1,2,3],[4,5,6],[7,8,9]])
print x
x.shape
x.sum(axis=0)
x.sum(axis=1)
x.mean(axis=0)
x.mean(axis=1)
np.arange(10)
np.arange(5,10)
np.arange(5,10,0.5)
x = np.arange(1,10).reshape(3,3)
x
x = np.linspace(0,5,5)
x
help(np.linspace)
x = np.array([1,2,3])
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Tablice typu array mają wiele przydatnych wbudowanych metod.
Step2: Do tworzenia sekwencji liczbowych jako obiekty typu array należy wykorzysta... |
10,052 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from rdkit.Chem import AllChem
from rdkit.Chem import rdChemReactions
from rdkit.Chem.AllChem import ReactionFromRxnBlock, ReactionToRxnBlock
from rdkit.Chem.Draw import IPythonConsole
IPythonConsole.ipython_useSVG=True
rxn_data = $RXN
ISIS ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: RDKit Enumeration Toolkit
Step2: Sanitizing Reaction Blocks
Step3: Preprocessing Reaction Blocks
Step4: So now, this scaffold will only match... |
10,053 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as pl
from matplotlib import rcParams
rcParams.keys()
[key for key in rcParams.keys() if 'map' in key]
rcParams['image.cmap']
rcParams['image.cmap'] = 'viridis'
rcParams['image.interpolation'] = 'none'
x = np.array([[1,2,3]... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: little matplotlib config trick
Step2: Now, this config dictionary is huge
Step3: Visualizing Multi-Dimensional Arrays
Step4: Q. What is the r... |
10,054 | <ASSISTANT_TASK:>
Python Code:
import os
import pandas as pd
import numpy as np
import scipy as sp
import seaborn as sns
import matplotlib.pyplot as plt
import json
from IPython.display import Image
from IPython.core.display import HTML
retval=os.chdir("..")
clean_data=pd.read_pickle('./clean_data/clean_data.pkl')
clea... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Training and Testing Split
Step2: Scaling
Step3: Text
Step5: Custom Feature Separator
Step6: Classification Models
Step7: Although tuning i... |
10,055 | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from urllib.request import urlretrieve
import itk
from itkwidgets import compare, checkerboard
dim = 2
ImageType = itk.Image[itk.F, dim]
FixedImageType = ImageType
MovingImageType = ImageType
fixed_img... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Retrieve fixed and moving images for registration
Step2: Prepare images for registration
Step3: Plot the MutualInformationImageToImageMetric s... |
10,056 | <ASSISTANT_TASK:>
Python Code:
from dkrz_forms import form_widgets
form_widgets.show_status('form-submission')
MY_LAST_NAME = "...." # e.gl MY_LAST_NAME = "schulz"
#-------------------------------------------------
from dkrz_forms import form_handler, form_widgets
form_info = form_widgets.check_pwd(MY_LAST_NAME)
sf ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Edit form information
Step2: Save your form
Step3: officially submit your form
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10,057 | <ASSISTANT_TASK:>
Python Code:
from nilearn import datasets
# if you download these from python.
haxby_dataset = datasets.fetch_haxby()
# print basic information on the dataset
print('First subject anatomical nifti image (3D) is at: %s' %
haxby_dataset.anat[0])
print('First subject functional nifti images (4D) ar... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Prepare the data
Step2: The decoding
Step3: Compute prediction scores using cross-validation
Step4: Retrieve the discriminating weights and s... |
10,058 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from datetime import date
date.today()
author = "kyubyong. https://github.com/Kyubyong/tensorflow-exercises"
tf.__version__
np.__version__
w = tf.Variable(1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: NOTE on notation
Step2: Q1. Complete this code.
Step3: Q2. Complete this code.
Step4: Q3-4. Complete this code.
Step5: Q5-8. Complete this c... |
10,059 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', validation_size=0)
img = mnist.train.images[2]
plt.imshow(img.reshape((28, 28)), cmap='G... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Network Architecture
Step2: Training
Step3: Denoising
Step4: Checking out the performance
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10,060 | <ASSISTANT_TASK:>
Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
# Imports
import os
import subprocess
import stat
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib as mat
impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Número de veículos pertencentes a cada marca
Step2: Preço médio dos veículos com base no tipo de veículo, bem como no tipo de caixa de câmbio
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10,061 | <ASSISTANT_TASK:>
Python Code:
# Load library
import cv2
import numpy as np
from matplotlib import pyplot as plt
# Load image as grayscale
image = cv2.imread('images/plane.jpg', cv2.IMREAD_GRAYSCALE)
# Show image
plt.imshow(image, cmap='gray'), plt.axis("off")
plt.show()
# Load image in color
image_bgr = cv2.imread('... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load Image As Greyscale
Step2: Load Image As RGB
Step3: View Image Data
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10,062 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import seaborn as sns
from random import randint as rand
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.linear_model import LinearRegression
from sklearn.metrics.pairwise import euclidean_distances
from scipy.linalg import svd
from s... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Helper functions
Step2: Experiment 1
Step3: Original Lines
Step4: Rotated lines
Step5: Experiment 2
Step6: Compute rotation linear transfor... |
10,063 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from bigbang.archive import Archive
from bigbang.archive import load as load_archive
from bigbang.thread import Thread
from bigbang.thread import Node
from bigbang.utils import remove_quoted
import matplotlib.pyplot as plt
import datetime
import pandas as pd
import csv
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: First, collect data from a public email archive.
Step2: Let's check the number of threads in this mailing list corpus
Step3: We can plot the ... |
10,064 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
table = pd.DataFrame(index=['Bowl 1', 'Bowl 2'])
table['prior'] = 1/2, 1/2
table
table['likelihood'] = 3/4, 1/2
table
table['unnorm'] = table['prior'] * table['likelihood']
table
prob_data = table['unnorm'].sum()
prob_data
table['posterior'] = table['unnorm'] / pr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now I'll add a column to represent the priors
Step2: And a column for the likelihoods
Step3: Here we see a difference from the previous method... |
10,065 | <ASSISTANT_TASK:>
Python Code:
%load_ext oct2py.ipython
%lsmagic
%%octave
addpath ("~/Software/MATLAB/CO2SYS-MATLAB/src")
%%octave
help derivnum
%%octave
# Standard input for CO2SYS:
# --------------------------
# Input Variables:
PAR1 = 2300; % ALK
PAR2 = 2000; % DIC
PAR1TYPE = 1; ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: List all avaiable magics
Step2: Specify the directory where you have put the Matlab routines CO2SYS.m, errors.m, and derivnum.m.
Step3: Note
S... |
10,066 | <ASSISTANT_TASK:>
Python Code:
from polyglot.mapping import Embedding
embeddings = Embedding.load("/home/rmyeid/polyglot_data/embeddings2/en/embeddings_pkl.tar.bz2")
neighbors = embeddings.nearest_neighbors("green")
neighbors
embeddings.distances("green", neighbors)
%matplotlib inline
import matplotlib.pyplot as pl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Formats
Step2: Nearest Neighbors
Step3: to calculate the distance between a word and the nieghbors, we can call the distances method
Step4: T... |
10,067 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne import io
from mne.datasets import sample
from mne.minimum_norm import read_inverse_operator, source_induced_power
pri... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set parameters
|
10,068 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import torch
import torchvision
import torch.utils.data as data
from torchvision import transforms, utils
import torch.nn as nn
import torch.optim as optim
import time
%matplotlib inline
import tiny_imagenet
tiny_imagenet.download(".")
d... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Define helper functions
Step2: Network parameters
Step3: Training and validation images are now in tiny-imagenet-200/train and tiny-imagenet-2... |
10,069 | <ASSISTANT_TASK:>
Python Code:
# variable assignment
# https://www.digitalocean.com/community/tutorials/how-to-use-variables-in-python-3
# strings -- enclose in single or double quotes, just make sure they match
# numbers
# the print function
# booleans
# addition
# subtraction
# multiplication
# division
# etc.
# cr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Basic math
Step2: Lists
Step3: Dictionaries
Step4: Commenting your code
Step6: Type coercion
|
10,070 | <ASSISTANT_TASK:>
Python Code:
import pkg_resources
if pkg_resources.get_distribution('CGRtools').version.split('.')[:2] != ['4', '0']:
print('WARNING. Tutorial was tested on 4.0 version of CGRtools')
else:
print('Welcome!')
# load data for tutorial
from pickle import load
from traceback import format_exc
with ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: CGRtools has subpackage containers with data structures classes
Step2: 1.1. MoleculeContainer
Step3: Each structure has additional atoms attri... |
10,071 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
act_train = pd.read_csv('act_train.csv')
act_test = pd.read_csv('act_test.csv')
people = pd.read_csv('people.csv')
def prepare_acts(data, train_set=True):
data = data.drop(['date', 'activity_id'], axis=1)
if train_set:
data = data.drop(['outcome'], ax... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Preparing the Data
Step2: A Random Forest Model
Step3: Output
|
10,072 | <ASSISTANT_TASK:>
Python Code:
# Load libraries
import pandas as pd
from pytz import all_timezones
# Show ten time zones
all_timezones[0:10]
# Create datetime
pd.Timestamp('2017-05-01 06:00:00', tz='Europe/London')
# Create datetime
date = pd.Timestamp('2017-05-01 06:00:00')
# Set time zone
date_in_london = date.tz... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: View Timezones
Step2: Create Timestamp With Time Zone
Step3: Create Timestamp Without Time Zone
Step4: Add Time Zone
Step5: Convert Time Zon... |
10,073 | <ASSISTANT_TASK:>
Python Code:
import os
import ipywidgets as widgets
import bqplot.pyplot as plt
from bqplot import LinearScale
image_path = os.path.abspath("../../data_files/trees.jpg")
with open(image_path, "rb") as f:
raw_image = f.read()
ipyimage = widgets.Image(value=raw_image, format="jpg")
ipyimage
plt.fig... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Using pyplot's imshow to display the image
Step2: Displaying the image inside a bqplot Figure
Step3: Mixing with other marks
Step4: Its trait... |
10,074 | <ASSISTANT_TASK:>
Python Code:
from numpy import pi
from scipy.constants import hbar
# Find the power for a 3 mm diameter gaussian beam with stated intensity:
r = 0.3/2 # units of cm
A = pi*r**2
P = 2.5e-3 * A
P*1e6 # microWatts
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Notes from Klein et al 2011 (doi
|
10,075 | <ASSISTANT_TASK:>
Python Code:
import gzip
import urllib.request
url = 'ftp://ftp.ncbi.nlm.nih.gov/genomes/archive/old_genbank/Eukaryotes/vertebrates_mammals/Homo_sapiens/GRCh38/non-nuclear/assembled_chromosomes/FASTA/chrMT.fa.gz'
response = urllib.request.urlopen(url)
print(gzip.decompress(response.read()).decode('UTF... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This FASTA file shown above has just one sequence in it. As we saw in the first example above, it's also possible for one FASTA file to contain... |
10,076 | <ASSISTANT_TASK:>
Python Code:
# Author: Marijn van Vliet <w.m.vanvliet@gmail.com>
#
# License: BSD-3-Clause
import os.path as op
import numpy as np
from scipy.signal import welch, coherence, unit_impulse
from matplotlib import pyplot as plt
import mne
from mne.simulation import simulate_raw, add_noise
from mne.datase... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Setup
Step3: Data simulation
Step4: Let's simulate two timeseries and plot some basic information about them.
Step5: Now we put the signals a... |
10,077 | <ASSISTANT_TASK:>
Python Code:
cmin = [0.0, 0.0]
cmax = [1.0, 1.0]
coo = uniform(0, 1, (7,2))
val = uniform(0, 1, coo.shape[0])
n = 100
s = linspace(0,1,n)
x = array(meshgrid(s,s)).transpose([1,2,0]).copy()
def plot_surface(m0):
interp = mba2(cmin, cmax, [m0,m0], coo, val)
error = amax(abs(val - interp(coo)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create $n \times n$ regular grid of coordinates to interpolate onto.
Step2: The plot_surface() function constructs MBA class with the given ini... |
10,078 | <ASSISTANT_TASK:>
Python Code:
def myXOR(x , y ) :
for i in range(31 , - 1 , - 1 ) :
b1 = x &(1 << i )
b2 = y &(1 << i )
b1 = min(b1 , 1 )
b2 = min(b2 , 1 )
xoredBit = 0
if(b1 & b2 ) :
xoredBit = 0
else :
xoredBit =(b1 b2 )
res <<= 1 ;
res |= xoredBit
return res
x = 3
y = 5
p... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
10,079 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: M-layer experiments
Step2: Generate a spiral and show extrapolation
Step3: Train an M-layer on multivariate polynomials such as the determinan... |
10,080 | <ASSISTANT_TASK:>
Python Code:
import sqlite3
import json
DATABASE = "data.sqlite"
conn = sqlite3.connect(DATABASE)
cursor = conn.cursor()
# For getting the maximum row id
QUERY_MAX_ID = "SELECT id FROM interactions ORDER BY id DESC LIMIT 1"
# Get interaction data
QUERY_INTERACTION = "SELECT geneids1, geneids2, probab... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Queries
Step2: Step through every interaction.
|
10,081 | <ASSISTANT_TASK:>
Python Code:
# this embeds plots in the notebook
%matplotlib inline
import numpy as np # for arrays
import pylab as pl # for plotting
lam_sq = np.arange(0.01,1,0.01)
phi_fg = 2.
P_gal = np.sin(2*phi_fg*lam_sq)/(2*phi_fg*lam_sq) + 0*1j
phi_1 = 10.
P_rg = 0.25*np.cos(2*phi_1*lam_sq) + 1j*0.25*np.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Make a function for the Galactic foreground
Step2: We're going to specify that $\phi_{\rm fg}= 2\,{\rm rad\,m^{-2}}$. We can then compute the G... |
10,082 | <ASSISTANT_TASK:>
Python Code:
# Install notebook dependencies
import sys
#!{sys.executable} -m pip install itk itk-ultrasound numpy matplotlib itkwidgets
import itk
from matplotlib import pyplot as plt
from itkwidgets import view, compare
SAMPLING_FREQUENCY = 40e6 # Hz
SAMPLING_PERIOD = SAMPLING_FREQUENCY ** -1
# Ima... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Read RF Image
Step2: The RF image represents transducer results over a certain time period with regards to the axial direction (along the beam)... |
10,083 | <ASSISTANT_TASK:>
Python Code:
import itertools
import sys
import bson
import h5py
import keras.layers
import keras.models
import matplotlib.pyplot
import numpy
import pandas
import sklearn.cross_validation
import sklearn.dummy
import sklearn.linear_model
import sklearn.metrics
sys.path.insert(1, '..')
import crowdastr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We'll just look at a small number of potential hosts for now. I'll have to do batches to scale this up and I just want to check it works for now... |
10,084 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from pydrill.client import PyDrill
%matplotlib inline
#Get a connection to the Apache Drill server
drill = PyDrill(host='localhost', port=8047)
#Get Written questions data - may take some time!
stub='http://lda.data.parliament.uk'.strip('/')
#We're going to have to ca... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Download Written Questions Data for a Session
Step2: We should now have all the data in a single JSON file (writtenQuestions.json).
Step3: Apa... |
10,085 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.special import gammaln
import random
from collections import Counter
import string
import graphviz
import pygraphviz
import pydot
def CRP(topic, phi):
'''
CRP gives the probability of topic assignment for specific vocabulary
Return a 1 * j array,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: B. Function construction
Step2: B.2 Node Sampling
Step3: B.3 Gibbs sampling -- $z_{m,n}$
Step4: B.4 Gibbs sampling -- ${\bf c}_{m}$, CRP prio... |
10,086 | <ASSISTANT_TASK:>
Python Code:
import pineapple
%pip freeze
import pineapple # required for all subsequent cells
# Use %pip line magic to list all installed packages
%pip list
# Use %pip line magic to download and install a specific package
%pip install unittest2
# New package is not available for import
import unitte... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: All preinstalled packages
Step2: %require examples
Step3: Best practices
|
10,087 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-1', 'sandbox-1', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
10,088 | <ASSISTANT_TASK:>
Python Code:
import os
import shogun as sg
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
doc_1 = "this is the first document"
doc_2 = "document classification introduction"
doc_3 = "a third document about classifica... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The <a href="http
Step2: We will take some time off now to assign each document to a category, to ease our work later on. Since the two last do... |
10,089 | <ASSISTANT_TASK:>
Python Code:
from pynq.overlays.base import BaseOverlay
base = BaseOverlay("base.bit")
from pynq.lib.pmod import Grove_ADC
from pynq.lib.pmod import PMOD_GROVE_G4
grove_adc = Grove_ADC(base.PMODA,PMOD_GROVE_G4)
print("{} V".format(round(grove_adc.read(),4)))
grove_adc.set_log_interval_ms(100)
grove_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: 2. Starting logging once every 100 milliseconds
Step2: 3. Try to change the input signal during the logging.
Step3: 4. Plot values over time
S... |
10,090 | <ASSISTANT_TASK:>
Python Code:
# Adapted from
# https://github.com/keras-team/keras/blob/master/examples/addition_rnn.py
import warnings
warnings.filterwarnings('ignore')
%matplotlib inline
%pylab inline
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR)
print(tf.__version__)
# let's see what compute de... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step4: Step 1
Step5: Input is encoded as one-hot, 7 digits times 12 possibilities
Step6: Same for output, but at most 4 digits
Step7: Step 2
Step8: ... |
10,091 | <ASSISTANT_TASK:>
Python Code:
s
clean_s = removeDelimiter(s," ",[".",",",";","_","-",":","!","?","\"",")","("])
wordlist = clean_s.split()
dictionary = {}
for word in wordlist:
if word in dictionary:
tmp = dictionary[word]
dictionary[word]=tmp+1
else:
dictionary[word]=1
import operator
sorted_dict = sorted(dic... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: A better method in Python 3 is -
Step2: These are the words that appear more than 200 times and I have excluded the really common words (greate... |
10,092 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
from scipy.spatial import Delaunay
from metpy.gridding.triangles import find_natural_neighbors
# Create test observations, test points, and plot the triangulation and points.
gx, gy = np.meshgrid(np.arange(0, 20, 4), np.arange(0, 20, 4))
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Since finding natural neighbors already calculates circumcenters and circumradii, return
Step2: We can then use the information in tri_info lat... |
10,093 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Composing Learning Algorithms
Step3: NOTE
Step5: There are a few important points about the code above. First, it keeps track of the number of... |
10,094 | <ASSISTANT_TASK:>
Python Code:
(n_transcripts_per_gene > 1e3).sum()
n_transcripts_per_gene[n_transcripts_per_gene > 1e4]
median_transcripts_per_gene = table1_t.median()
median_transcripts_per_gene.head()
sns.distplot(median_transcripts_per_gene)
fig = plt.gcf()
fig.savefig('median_transcripts_per_gene.png')
data = med... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Look at gene's median transcript count
Step2: Clean data matrix to be compatible with the cluster labels and identities
|
10,095 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = (20,10)
from sklearn import model_selection
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import Deci... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: We'll use all columns except Gender for this tutorial. We could use gender by converting the gender to a numeric value (e.g., 0 for Male, 1 for ... |
10,096 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-1', 'sandbox-3', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
10,097 | <ASSISTANT_TASK:>
Python Code:
from proxy.http.parser import HttpParser, httpParserTypes
from proxy.common.constants import HTTP_1_1
response = HttpParser(httpParserTypes.RESPONSE_PARSER)
response.code = b'200'
response.reason = b'OK'
response.version = HTTP_1_1
print(response.build_response())
from proxy.http.respons... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: But, this is a painful way to construct responses. Hence, other high level abstractions are available.
Step2: Notice how okResponse will alway... |
10,098 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("whitegrid")
%matplotlib inline
# True values
T = 500 # Time steps
sigma2_eps0 = 3 # Variance of the observation noise
sigma2_eta0 = 10 # Variance... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: As a reminder, the equations describing a system in State Space Form are the measurement equation
Step2: First, we will look at the maximum a p... |
10,099 | <ASSISTANT_TASK:>
Python Code:
config = ConfigParser.RawConfigParser()
config.read('synchronization.cfg')
api_key = config.get('Darksky', 'api_key')
geolocator = Nominatim()
location = geolocator.geocode('Muntstraat 10 Leuven')
latitude = location.latitude
longitude = location.longitude
base_url = config.get('Darksky',... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: URL builder
Step2: Fahrenheit to Celsius
Step3: Fetch JSON data from URL
|
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