Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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15,600 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
p = np.poly1d([6., 1., -2.])
p(0), p(1), p(10)
p.order
p.roots
# Comprobando las raíces
p(p.roots)
np.poly1d([2.,-3.,7.]).roots
import matplotlib.pyplot as plt
xvalues = np.linspace(-10.,10.,100)
plt.plot(xvalues, p(xvalues), '-')
plt.show()
y = p(xvalues) + np.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: La clase poly1D representa polinomios unidimensionales con base en sus coeficientes. Sea el polinomio
Step2: Se puede evaluar el valor de $p(x)... |
15,601 | <ASSISTANT_TASK:>
Python Code:
# Run some setup code for this notebook.
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
from __future__ import print_function
# This is a bit of magic to make matplotlib figures appear inline in the notebook
# rather than in a n... | <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 would now like to classify the test data with the kNN classifier. Recall that we can break down this process into two steps
Step2: Inline Qu... |
15,602 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
view_sentence_range = (0, 10)
DON'T MODIFY AN... | <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: Language Translation
Step3: Explore the Data
Step6: Implement Preprocessing Function
Step8: Preprocess all the data and save it
Step10: Chec... |
15,603 | <ASSISTANT_TASK:>
Python Code:
debug_flag = False
import datetime
import glob
import logging
import lxml
import os
import six
import xml
import xmltodict
import zipfile
# paper identifier
paper_identifier = "Newsday"
archive_identifier = "Newsday_20171006230211_00001"
# source
source_paper_folder = "/mnt/hgfs/project... | <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 - Imports
Step2: Setup - working folder paths
Step3: Setup - logging
Step4: Setup - virtualenv jupyter kernel
Step5: Setup - Initializ... |
15,604 | <ASSISTANT_TASK:>
Python Code:
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
from sklearn.pipeline import Pipeline
from sklearn.cross_validation import cross_val_score
n_samples = 1000
np.random.seed(0)
X = np.sort(np.random.rand(n_samples))
y = np.cos(1.5 * np.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:
Step1: 정규화 하이퍼 모수 최적화
Step2: One Standard Error Rule
|
15,605 | <ASSISTANT_TASK:>
Python Code:
from rmtk.vulnerability.derivation_fragility.equivalent_linearization.miranda_2000_firm_soils import miranda_2000_firm_soils
from rmtk.vulnerability.common import utils
%matplotlib inline
capacity_curves_file = "../../../../../../rmtk_data/capacity_curves_Sa-Sd.csv"
capacity_curves = uti... | <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 capacity curves
Step2: Load ground motion records
Step3: Load damage state thresholds
Step4: Obtain the damage probability matrix
Step5:... |
15,606 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import pastas as ps
ps.set_log_level("ERROR")
%matplotlib inline
# This notebook has been developed using Pastas version 0.9.9 and Python 3.7
print("Pastas version: {}".format(ps.__version__))
print("Pandas v... | <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: Step 2. Reading the time series
Step2: Step 3. Creating the model
Step3: Step 4. Adding stress models
Step4: Step 5. Solving the model
Step5:... |
15,607 | <ASSISTANT_TASK:>
Python Code:
odds = [1, 3, 5, 7]
print('odds are:', odds)
print('first element:', odds[0])
print('last element:', odds[3])
print('"-1" element:', odds[-1])
odds[0] = 10
print('first element:', odds[0])
salsa = ['peppers', 'onions', 'cilantro', 'tomatoes']
my_salsa = salsa
salsa[0] = 'hot peppers'
... | <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 can access elements of a list using indices – numbered positions of elements in the list. These positions are numbered starting at 0, so the ... |
15,608 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from itertools import product
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
import matplotlib.pyplot as plt
%matplotlib notebook
# Illustrating the use of itertools product
for ix,va... | <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: Explaination of the conditions
Step3: Studying the trade off
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15,609 | <ASSISTANT_TASK:>
Python Code:
mu = pymc.Uniform('mu', 0, 1e5)
deaths = pymc.Poisson('deaths', mu = 2.0*mu, observed=True, value=[3])
model = pymc.MCMC((mu, deaths))
model.sample(10000, burn=100, burn_till_tuned=True)
print(model.summary())
pymc.Matplot.plot(model)
mu = pymc.Gamma('mu', 3.0, 5.0)
deaths = pymc.Poisson... | <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 does not match the example very well. The example is centered around 0.9
|
15,610 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'Bike-Sharing-Dataset/hour.csv'
rides = pd.read_csv(data_path)
rides.head()
rides[:24*10].plot(x='dteday', y='cnt')
dummy_fields = ['seas... | <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 and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... |
15,611 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# sanity check for python setup
import sys
print(sys.executable)
print(sys.path)
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn.cluster import KMeans
from sklearn import datasets
np.random.seed(5)
centers=[... | <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: 1b. KNN (K=5)
Step2: 2. Evaluation procedure 2 - Train/test split
|
15,612 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
from scipy.spatial import cKDTree
from scipy.spatial.distance import cdist
from metpy.gridding.gridding_functions import calc_kappa
from metpy.gridding.interpolation import barnes_point, cressman_point
from metpy.gridding.triangles import... | <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: Generate random x and y coordinates, and observation values proportional to x * y.
Step2: Set up a cKDTree object and query all of the observat... |
15,613 | <ASSISTANT_TASK:>
Python Code:
%pylab notebook
VB = 120.0 # Battery voltage (V)
r = 0.3 # Resistance (ohms)
l = 1.0 # Bar length (m)
B = 0.6 # Flux density (T)
F = arange(0,51,10) # Force (N)
F # Lets print the variable to check.
# Can you exaplain why "arange(0,50,10)" gives not the 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: Define all the parameters
Step2: Select the forces to apply to the bar
Step3: Calculate the currents flowing in the motor
Step4: Calculate th... |
15,614 | <ASSISTANT_TASK:>
Python Code:
# local
from fludashboard.libs.flu_data import prepare_keys_name
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
df_hist = pd.read_csv('../data/historical_estimated_values.csv', encoding='utf-8')
df_inci = pd.read_csv('../data/current_estimated_values.csv', encodin... | <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 example, we show the current year incidence up to given week.<br>
Step2: UF
Step3: Entries with dfthresholds['se típica do inicio do s... |
15,615 | <ASSISTANT_TASK:>
Python Code:
from deriva.core import ErmrestCatalog, get_credential
scheme = 'https'
hostname = 'dev.facebase.org'
catalog_number = 1
credential = get_credential(hostname)
assert scheme == 'http' or scheme == 'https', "Invalid http scheme used."
assert isinstance(hostname, str), "Hostname not set."... | <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 example uses a development server with a throw away catalog. You will not have sufficient permissions to be able to run this example. This ... |
15,616 | <ASSISTANT_TASK:>
Python Code:
# Authors: Denis Engemann <denis.engemann@gmail.com>
# Jona Sassenhagen <jona.sassenhagen@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import mne
from mne.stats import spatio_temp... | <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
Step2: Read epochs for the channel of interest
Step3: Find the FieldTrip neighbor definition to setup sensor connectivity
Step4... |
15,617 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
class Plan: pass
# Plan 1 = Cigna HDHP/HSA
p1 = Plan()
p1.family_deductible = 4000.00 # Same deductible for both family and individual
p1.individual_deductible = 4000.00
p1.family_oopmax = 6000... | <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: Plan cost functions
Step3: Sanity Tests
Step4: Cost less than HSA
Step5: Cost greater than HSA and deductible
Step6:... |
15,618 | <ASSISTANT_TASK:>
Python Code:
#!pip install -I "phoebe>=2.3,<2.4"
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.default_binary()
b.add_dataset('lc', dataset='lc01')
b.add_dataset('mesh', times=[0], columns=['intensities*'])
print(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: As always, let's do imports and initialize a logger and a new bundle.
Step2: Relevant Parameters
Step3: If you have a logger enabled, PHOEBE w... |
15,619 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
A = np.array([[1,1,1], [3,1,2], [2,3,4]])
b = np.array([6, 11, 20])
A
b
x = np.linalg.solve(A, b)
x
A = np.matrix([[1,1,1], [3,1,2], [2,3,4]])
A
np.linalg.inv(A)
A = np.matrix([[1,2,2],[2,4,1],[3,6,4]])
A
np.linalg.matrix_rank(A)
A = np.matrix([[1,2,3], [4,5,6], [7,... | <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: Gaussian Elimination
Step2: Gaussian-Jordan Elimination
Step3: Column space
Step4: Projection Matrix
|
15,620 | <ASSISTANT_TASK:>
Python Code:
some_digits = X[36001]
some_digits_img = some_digits.reshape(28, 28)
plt.imshow(some_digits_img, cmap=matplotlib.cm.binary, interpolation='Nearest')
plt.axis("off")
plt.show()
### checking out its label
y[36001]
# MNIST dataset is already split into train(first 60000) and test(last 10000)... | <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: Let's try to train a BINARY classification
Step2: A good place to start is with a Stochastic Gradient Descent (SGD) classifier, using Scikit-Le... |
15,621 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import PIL.Image
im = PIL.Image.open("/Users/valeriaalvarez/Documents/rh.jpeg")
col,row = im.size
A = np.zeros((row*col, 5))
pixels = im.load()
print(pixels[187,250])
for i in range(col):
for j in range(row):
#print("i=%d, j=%d" % (i,j))
r,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: - Realizar la descomposición SVD
Step2: - Verificar la descomposición SVD
Step3: con el método anterior, no logré imprimir la imagen con el im... |
15,622 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import math, sys, os, numpy as np
import torch
from matplotlib import pyplot as plt, rcParams, animation, rc
from ipywidgets import interact, interactive, fixed
from ipywidgets.widgets import *
rc('animation', html='html5')
rcParams['figure.figsize'] = 3, 3
%precision 4... | <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: Components of Learning
Step2: You want to find parameters (weights) a and b such that you minimize the error btwn the points and the line a * x... |
15,623 | <ASSISTANT_TASK:>
Python Code:
% matplotlib inline
import os
import numpy as np
import nibabel as nib
from nipy.labs.utils.simul_multisubject_fmri_dataset import surrogate_3d_dataset
import nipy.algorithms.statistics.rft as rft
from __future__ import print_function, division
import math
import matplotlib.pyplot as plt
... | <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: Simulate very large RF
Step2: Show part of the RF (20x20x1)
Step3: Save RF
Step4: Run fsl cluster to extract local maxima
Step5: Read and pr... |
15,624 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig = plt.figure()
ax = fig.add_subplot(111)
N = 10
x = np.random.rand(N)
y = np.random.rand(N)
z = np.random.rand(N)
circles, triangles, dots = ax.plot(x, 'ro', y, 'g^', z, '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: 1. 动画
Step2: 2. 三维绘图
Step3: 3. 绘制等高线图
Step4: 4. 结合三维绘图和等高线图
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15,625 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
s
s = pd.Series([1,3,5,np.nan,6,8])
s
d = {'a' : 0., 'b' : 1., 'c' : 2.}
pd.Series(d)
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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: 数据结构
Step2: From dict
|
15,626 | <ASSISTANT_TASK:>
Python Code:
!pip install git+https://github.com/biothings/biothings_explorer#egg=biothings_explorer
# import modules from biothings_explorer
from biothings_explorer.hint import Hint
from biothings_explorer.user_query_dispatcher import FindConnection
from biothings_explorer.hint import Hint
ht = Hin... | <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: Then import the relevant modules
Step2: Step 1
Step3: Step 2
Step4: The df object contains the full output from BioThings Explorer. Each row ... |
15,627 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from sympy.interactive import printing
printing.init_printing()
from frame import *
import sympy as sp
import numpy as np
import scipy.sparse as sparse
import scipy.sparse.linalg as linalg
class Frame_Buckling(LinearFrame):
def N_local_stress(self,element):
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step5: Project on frame buckling
Step6: Essai sur exercice 2
Step7: Essai sur d'autres structures
Step8: Structure avec deux forces et sans étage re... |
15,628 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint # This is the numerical solver
def rhs(Y,t,omega): # this is the function of the right hand side of the ODE
y,ydot = Y
return ydot,-omega*omega*y
t_arr=np.linspace(0,2*np.pi,... | <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: We start with a second order linear equation, that has the usual harmonic oscillator solutions.
Step2: Now, I would like to test how accurate t... |
15,629 | <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... |
15,630 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
titanic_data = pd.read_csv('train.csv')
titanic_data.head(5)
titanic_data.info()
titanic_data.Age = titanic_data.Age.fillna(np.mean(titanic_data.Age))
titanic_data.info()
survivors = titanic_data[titanic_data.Survived == 1]
survivor_prob = (len(su... | <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: Cleaning and filling data
Step2: Filling all NaN ages with the mean of all the ages and confirming with .info() method. We later compensate for... |
15,631 | <ASSISTANT_TASK:>
Python Code:
import pkg_resources
import sys
import os
import time
from urllib.request import urlretrieve
import indra.util.get_version
import indra.java_vm # make sure INDRA is in charge of the JVM
import pybel
import pybel_tools
from pybel_tools.visualization import to_jupyter
%%bash
java -showvers... | <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: Environment
Step2: Dependencies
Step3: Data
Step4: Conversion
|
15,632 | <ASSISTANT_TASK:>
Python Code:
# the output of plotting commands is displayed inline within frontends,
# directly below the code cell that produced it
%matplotlib inline
from time import time
# this python library provides generic shallow (copy) and deep copy (deepcopy) operations
from copy import deepcopy
# import ... | <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: Change RF parameters for the comparison with ASTRA
Step2: Initializing SpaceCharge
Step3: Comparison with ASTRA
|
15,633 | <ASSISTANT_TASK:>
Python Code:
def print_full(x):
pd.set_option('display.max_rows', len(x))
print(x)
pd.reset_option('display.max_rows')
def get_energy():
import pandas as pd
import numpy as np
energy = pd.read_excel('Energy Indicators.xls', skiprows=16, skip_footer=38, usecols=range(2,6), names... | <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: Question 2 (6.6%)
Step2: <br>
Step3: Question 4 (6.6%)
Step4: Question 5 (6.6%)
Step5: Question 6 (6.6%)
Step6: Question 7 (6.6%)
Step7: Q... |
15,634 | <ASSISTANT_TASK:>
Python Code:
# Preview first 5 edges
list(g.edges(data=True))[0:5]
# Preview first 10 nodes
list(g.nodes(data=True))[0:10]
## Summary Stats
print('# of edges: {}'.format(g.number_of_edges()))
print('# of nodes: {}'.format(g.number_of_nodes()))
# Define node positions data structure (dict) for plotti... | <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: Nodes
Step2: Visualize
Step3: Colors
Step4: Solving the Chinese Postman Problem is quite simple conceptually
Step6: CPP Step 2
Step8: Step ... |
15,635 | <ASSISTANT_TASK:>
Python Code:
permutation = np.random.permutation(len(iris_target))
iris_data = np.take(iris_data, permutation, axis=0)
iris_target = np.take(iris_target, permutation)
# Function to plot data
def plot_data(colors, names, data, target):
plt.figure(figsize=(8, 8))
N = len(names)
for color, 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: Create an incremental PCA object
Step2: IoTPy
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Python Code:
# A bit of setup
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.neural_net import TwoLayerNet
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] ... | <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: We will use the class TwoLayerNet in the file cs231n/classifiers/neural_net.py to represent instances of o... |
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Python Code:
year = 2015
print(year)
print(year)
year = 2016
%reset
print(year)
import cv2
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
# another magic function, this allows you to view plots in the notebook
%matplotlib inline
first = ["tags/first0.png", "tags/firs... | <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 notebook allows you to prototype code and plots quickly without having to reload data in each time. Can can be useful if you're experimentin... |
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Python Code:
!pip install git+https://github.com/google/starthinker
from starthinker.util.configuration import Configuration
CONFIG = Configuration(
project="",
client={},
service={},
user="/content/user.json",
verbose=True
)
FIELDS = {
'auth_write':'service', # Authorization used for w... | <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: 2. Set Configuration
Step2: 3. Enter GA360 Segmentology Recipe Parameters
Step3: 4. Execute GA360 Segmentology
|
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Python Code:
# Python 2 only:
print 'Hello'
# Python 2 and 3:
print('Hello')
# Python 2 only:
print 'Hello', 'Guido'
# Python 2 and 3:
from __future__ import print_function # (at top of module)
print('Hello', 'Guido')
# Python 2 only:
print >> sys.stderr, 'Hello'
# Python 2 and 3:
from __future__ ... | <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: To print multiple strings, import print_function to prevent Py2 from interpreting it as a tuple
Step2: Raising exceptions
Step3: Raising excep... |
15,640 | <ASSISTANT_TASK:>
Python Code:
import time
import sqlite3 as sql
import os
import sys
sys.path.append("/Users/kurner/Documents/classroom_labs")
class NoConnection(Exception):
pass
class SQL_DB: # a database
# class level parameters
backend = 'sqlite3'
user_initials = 'KTU'
timezone = int(tim... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step5: So far, this class hasn't done any work. We'll use the context manager to make the actual connection, using this DB object.
Step6: In the "wit... |
15,641 | <ASSISTANT_TASK:>
Python Code:
import sys
import matplotlib.pyplot as plt
import datetime as dt
import numpy as np
from mpl_toolkits.basemap import Basemap
import pandas as pd
import seaborn as sns
from scipy.stats.stats import pearsonr
prin... | <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: Reading in the Data/Data Cleaning
Step2: Plot 1
Step3: Plot 2
Step4: Plot 3
Step5: Plot 4
Step6: Plot 5
Step7: Plot 6
Step8: Appendix
Ste... |
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Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
t = np.linspace(0, 10.0, 100)
plt.plot(t, np.sin(t))
plt.xlabel('Time')
plt.ylabel('Signal')
plt.title('My Plot'); # supress text output
f = plt.figure(figsize=(9,6)) # 9" x 6", default is 8" x 5.5"
plt.plot(t, np.sin... | <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: Overview
Step2: Basic plot modification
Step3: Here is a list of the single character color strings
Step4: To change the plot's limits, use x... |
15,643 | <ASSISTANT_TASK:>
Python Code:
# To support both python 2 and python 3
from __future__ import division, print_function, unicode_literals
# Common imports
import numpy as np
import os
# to make this notebook's output stable across runs
np.random.seed(42)
# To plot pretty figures
%matplotlib inline
import matplotlib
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: Voting classifiers
Step2: Bagging ensembles
Step3: Random Forests
Step4: Out-of-Bag evaluation
Step5: Feature importance
Step6: AdaBoost
St... |
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Python Code:
import nixio as nix
import numpy as np
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from utils.notebook import print_stats
from utils.video_player import Playback
nix_file = nix.File.open('data/tracking_data.h5', nix.FileMode.ReadOnly)
print_stats(nix_file.blo... | <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: Storing of video data
Step2: Tracking data
Step3: Addtional Information
|
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Python Code:
%matplotlib inline
# To generate the vector fields
import dolfin as df
import mshr
import numpy as np
import plot_vtk_matplotlib as pvm
# Matplotlib parameters can be tuned with rc.Params
# This library has modified values. For example:
# matplotlib.rcParams['font.size'] = 22
mesh = mshr... | <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: Generate 2D Vector Field using Dolfin
Step2: Now we can save the data in a VTK file. By default, Fenics saves XML files (instead of binary) usi... |
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Python Code:
import numpy as np
from sklearn.model_selection import train_test_split
from tensorflow import keras
# Set up code checking
from learntools.core import binder
binder.bind(globals())
from learntools.deep_learning.exercise_8 import *
print("Setup Complete")
img_rows, img_cols = 28, 28
num_c... | <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: 1) Increasing Stride Size in A Layer
Step2: You have the same code in the cell below, but the model is now called fashion_model_1. Change the ... |
15,647 | <ASSISTANT_TASK:>
Python Code:
# change these to try this notebook out
BUCKET = 'cloud-training-demos-ml'
PROJECT = 'cloud-training-demos'
PROJECTNUMBER = '663413318684'
REGION = 'us-central1'
import os
os.environ['BUCKET'] = BUCKET
os.environ['PROJECT'] = PROJECT
os.environ['PROJECTNUMBER'] = PROJECTNUMBER
os.environ[... | <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: Exploring dataset
Step3: <h2> Creating a ML dataset using BigQuery </h2>
Step4: <h2> Creating a scikit-learn model using random forests </h2>
... |
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Python Code:
import torch
from torch import nn
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.figure(figsize=(8,5))
# how many time steps/data pts are in one batch of data
seq_length = 20
# generate evenly spaced data pts
time_steps = np.linspace(start=0, stop=np.pi, num=seq... | <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 the RNN
Step2: Check the input and output dimensions
Step3: Training the RNN
Step4: Loss and Optimization
Step5: Defining the trainin... |
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Python Code:
from crpropa import *
import numpy as np
import matplotlib.pyplot as plt
# define densities
FER = Ferriere()
NAK = Nakanishi()
COR = Cordes()
R = np.linspace(0, 30*kpc, 300)
phi = np.linspace(0, 2*np.pi, 180)
n_FER_HI = np.zeros((R.shape[0],phi.shape[0]))
n_FER_HII = np.zeros((R.shape[0]... | <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 Ferrière
Step2: Model Cordes
Step3: Model Nakanishi
Step4: Advanced use of DensityList
|
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Python Code:
x = 1
y = 2
x + y
x
def add_numbers(x, y):
return x + y
add_numbers(1, 2)
def add_numbers(x,y,z=None):
if (z==None):
return x+y
else:
return x+y+z
print(add_numbers(1, 2))
print(add_numbers(1, 2, 3))
def add_numbers(x, y, z=None, flag=False):
if (flag):
... | <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: <br>
Step2: <br>
Step3: <br>
Step4: <br>
Step5: <br>
Step6: <br>
Step7: <br>
Step8: <br>
Step9: <br>
Step10: <br>
Step11: <br>
Step12:... |
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Python Code:
# set up all the data for the rest of the notebook
import json
from collections import Counter
from itertools import chain
from IPython.display import HTML
def vote_table(votes):
Render a crappy HTML table for easy display. I'd use Pandas, but that seems like
complete overkill for... | <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: Analyzing Shreddit's Q2 Top 5 voting
Step3: Equal Placement Ballots
Step4: And here's the top ten from my computed tally
Step5: Weighted Tall... |
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Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
reviews = pd.read_csv('reviews.txt', header=None)
labels = pd.read_csv('labels.txt', header=None)
from collections import Counter
total_counts = Counter()
for _, 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: Preparing the data
Step2: Counting word frequency
Step3: Let's keep the first 10000 most frequent words. As Andrew noted, most of the words in... |
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Python Code:
import sys
sys.path.append('../deeprl')
import gym
env = gym.make('MountainCar-v0')
print env.action_space
print env.observation_space
print env.observation_space.low
print env.observation_space.high
print env.goal_position
%matplotlib inline
import numpy as np
import matplotlib.pyplot... | <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 OpenAI Gym
Step2: A gym environment contains all relevant data describing the problem. We can directly inspect the action space and the o... |
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Python Code:
from math import pi
%run matplotlib_setup.ipy
from matplotlib import pyplot
import numpy as np
import kwant
lat=kwant.lattice.square()
L,W=30,16
def myshape(R): return (
(R[0]**2 + R[1]**2) > (L-W/2)**2 and
(R[0]**2 + R[1]**2) < (L+W/2)**2)
H=kwant.Builde... | <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: We see that the Aharonov-Bohm effect contains several harmonics
Step2: Now run it, don't forget to change the x-scale of the plot.
|
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Python Code:
import numpy as np
import matplotlib.pyplot as plt
from properimage import single_image as s
%matplotlib inline
pixel = np.random.random((128,128))*5.
# Add some stars to it
star = [[35, 38, 35],
[38, 90, 39],
[35, 39, 34]]
for i in range(25):
x, y = np.random.randint(... | <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 can see that the img object created automatically produces an output
Step2: If you would like to acces the data inside the object img just a... |
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Python Code:
!gvim data/SF_Si_bulk/invar.in
%cd data/SF_Si_bulk/
%run ../../../../../Code/SF/sf.py
cd ../../../
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
# plt.rcParams['figure.figsize'] = (9., 6.)
%matplotlib inline
sf_c = np.genfromtxt(
'data/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: Now I can run my script
Step2: Not very elegant, I know. It's just for demo pourposes.
Step3: I have first to import a few modules/set up a fe... |
15,657 | <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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<USER_TASK:>
Description:
Step1: Feature Engineering using TFX Pipeline and TensorFlow Transform
Step2: Install TFX
Step3: Did you restart the runtime?
Step4: Set up variable... |
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Python Code:
import os
import math
from zipfile import ZipFile
from urllib.request import urlretrieve
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.layers import StringLookup
import matplotlib.pyplo... | <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: Prepare the data
Step2: Create train and eval data splits
Step3: Define dataset metadata and hyperparameters
Step4: Train and evaluate the mo... |
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Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csiro-bom', 'sandbox-1', 'landice')
# 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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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
15,660 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors
from matplotlib.font_manager import FontProperties
%matplotlib inline
from keras.models import model_from_json
from keras.models import Sequential
from keras.layers.core import Dense, Activation
from keras.la... | <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: Now I load the pre-generated artificial data required for the LSTM training and testing. Note that I have used 3000 and 300 images for training ... |
15,661 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2019 The TensorFlow Hub Authors. All Rights Reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE... | <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: TF-Hub CORD-19 Swivel 埋め込みを探索する
Step2: 埋め込みを分析する
Step3: 埋め込みが異なる用語の意味をうまく捉えていることが分かります。それぞれの単語は所属するクラスタの他の単語に類似していますが（「コロナウイルス」は「SARS」や「MERS」と... |
15,662 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
from netgraph import Graph
edges = [(0, 1), (1, 1)]
Graph(edges, node_color='red', node_size=4.)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
from netgraph import Graph
Graph([(0, 1), (1, 2), (2, 0)],
edge_color={(0, 1) : 'g', (1, 2)... | <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: Using a dictionary mapping individual nodes or individual edges to a property
Step2: By directly manipulating the node and edge artists.
|
15,663 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
matplotlib.style.use('ggplot')
# dataframes!
import pandas
# Construct dataframe
columns = ['eggs','sausage','bacon']
indices = ['Novel A', 'Novel B', 'Novel C']
dtm = [[50,60,60],[90,10,10], [20,70,70]]
dtm_df = pandas.DataFrame(dtm, columns = columns, index = indices)
# S... | <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: Create a DTM with a Few Pseudo-Texts
Step2: Visualize
Step3: Vectors
Step4: Vector Semantics
Step5: Word2Vec
Step6: Corpus Description
Step... |
15,664 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from cmt.components import Cem
cem = Cem()
print cem.get_output_var_names()
cem.get_input_var_names()
angle_name = 'sea_surface_water_wave__azimuth_angle_of_opposite_of_phase_velocity'
print "Data type: %s" % cem.get_var_type(angle_name)
print "Units: %s" % cem.get_v... | <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: Import the Cem class, and instantiate it. In Python, a model with a BMI will have no arguments for its constructor. Note that although the class... |
15,665 | <ASSISTANT_TASK:>
Python Code:
df = pd.read_csv('data/test_data2.csv', encoding='latin-1')
print(len(df))
df.head()
df['Released'] = pd.to_datetime(df['Released'])
df['Year'] = pd.DatetimeIndex(df['Released']).year
df['Month'] = pd.DatetimeIndex(df['Released']).month
df.head()
import plotly.plotly as py
from plotly.to... | <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: Convert dates to datetime objects
Step2: fig = FF.create_scatterplotmatrix(df_a, diag='box', index='Prod_Budget',
Step3: Log Transform
|
15,666 | <ASSISTANT_TASK:>
Python Code:
# Let's handle units
from astropy import units as u
# Structure to map healpix' levels to their angular sizes
#
healpix_levels = {
0 : 58.63 * u.deg,
1 : 29.32 * u.deg,
2 : 14.66 * u.deg,
3 : 7.329 * u.deg,
4 : 3.665 * u.deg,
5 : 1.832 * u.deg,
6 : ... | <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: The libraries we can use to generate/manipulate Healpix/MOC maps are
Step5: Let's do the same with healpix_util now
Step6: MOCpy for visualizi... |
15,667 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
from tensorflow.python.client import timeline
import pylab
import numpy as np
import os
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
tf.logging.set_verbosity(tf.logging.INFO)
tf.reset_default_graph()
config = tf.ConfigProto(
log_device_plac... | <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: Reset TensorFlow Graph
Step2: Create TensorFlow Session
Step3: Generate Model Version (current timestamp)
Step4: Load Model Training and Test... |
15,668 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
from math import pi
def y(x):
return np.cos(pi*x)
x = np.linspace(-1, 1, 100)
X = np.random.uniform(-1, 1, 25)
X_data = X.reshape(25, 1)
y_obs_list = []
for i in range(len(X)):
y_o... | <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: We will begin by stating our "true model", defined as $y = \cos(\pi x)$.
Step2: We now add some random "noise" to it in order to generate 25 d... |
15,669 | <ASSISTANT_TASK:>
Python Code:
from veneer.manage import start, create_command_line, kill_all_now
import veneer
veneer_install = 'D:\\src\\projects\\Veneer\\Compiled\\Source 4.1.1.4484 (public version)'
source_version = '4.1.1'
cmd_directory = 'E:\\temp\\veneer_cmd'
path = create_command_line(veneer_install,source_vers... | <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: Also as before, we need a copy of the Veneer client for each copy of the server
Step2: The catchment
Step3: Describing the PEST 'Job'
Step4: ... |
15,670 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division
%matplotlib inline
import numpy as np
import nsfg
import first
import analytic
import thinkstats2
import thinkplot
thinkplot.PrePlot(3)
for lam in [2.0, 1, 0.5]:
xs, ps = thinkstats2.RenderExpoCdf(lam, 0, 3.0, 50)
label = r'$\lambda... | <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: Exponential distribution
Step2: Here's the distribution of interarrival times from a dataset of birth times.
Step3: Here's what the CCDF looks... |
15,671 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import display
from sympy import symbols, simplify, sympify, expand
from sympy import init_printing
from sympy import Eq, Function
from clebschVector import ClebschVec
from clebschVector import div, grad, gradPerp, advVec
from common import rho, theta, poisson
from co... | <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: Calculation of the $E\times B$ advection
Step2: Defining $\mathbf{u}_E$
Step3: NOTE
Step4: Calculation of $\mathbf{u}E\cdot\nabla \left(n\nab... |
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Python Code:
from nipype import Node, Workflow
from nipype.interfaces.fsl import SliceTimer, MCFLIRT, Smooth
# Initiate a node to correct for slice wise acquisition
slicetimer = Node(SliceTimer(index_dir=False,
interleaved=True,
time_repetiti... | <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, we can import the interfaces that we want to use for the preprocessing.
Step2: Next, we will put the three interfaces into a node and defi... |
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Python Code:
import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.pipeline import Pipeline
from sklearn.model_selection import train_test_split
from sklearn.ensemble import VotingCla... | <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: Exploratory Data Analysis
Step2: Observations
Step3: Training and Validation Split
Step4: Image Downloading
Step5: Function to download test... |
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Python Code:
%matplotlib inline
# All the imports
from __future__ import print_function, division
from math import *
import random
import sys
import matplotlib.pyplot as plt
# TODO 1: Enter your unity ID here
__author__ = "tchhabr"
class O:
Basic Class which
- Helps dynamic updates
... | <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: Genetic Algorithm Workshop
Step11: The optimization problem
Step12: Great. Now that the class and its basic methods is defined, we move on to ... |
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Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import classes from thinkbayes2
from thinkbayes2 import Pmf, Suite
import ... | <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: Interpreting medical tests
Step2: Assumptions and interpretation
Step3: So there is a 1.56% chance that this patient has cancer, given that th... |
15,676 | <ASSISTANT_TASK:>
Python Code:
import json
my_tweets = json.load(open('my_tweets.json'))
for id_, tweet_info in my_tweets.items():
print(id_, tweet_info)
break
def run_vader(nlp,
textual_unit,
lemmatize=False,
parts_of_speech_to_consider=set(),
verbose=... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step3: Exercise 3
Step4: Exercise 3a
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Python Code:
import numpy as np
from scipy import linalg
import mne
from mne.datasets import sample
from mne.viz import plot_sparse_source_estimates
data_path = sample.data_path()
fwd_fname = data_path + '/MEG/sample/sample_audvis-meg-eeg-oct-6-fwd.fif'
ave_fname = data_path + '/MEG/sample/sample_audv... | <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: Auxiliary function to run the solver
Step4: Define your solver
Step5: Apply your custom solver
Step6: View in 2D and 3D ("glass" brain like 3... |
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Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
def LSCE(x, y):
beta_1 = np.sum((x - np.mean(x))*(y-np.mean(y))) / np.sum((x-np.mean(x))*(x-np.mean(x)))
beta_0 = np.mean(y) - beta_1 * np.mean(x)
return beta_0, beta_1
advertising = 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: The difference between the population regression line adn the least squres lien many seem quite confusing. The answer is using a sample to estim... |
15,679 | <ASSISTANT_TASK:>
Python Code:
import math
def isPower(x , y ) :
res1 = math . log(y ) // math . log(x )
res2 = math . log(y ) // math . log(x )
return(res1 == res2 )
def check(n ) :
x =(n + 7 ) // 8
if(( n + 7 ) % 8 == 0 and isPower(10 , x ) ) :
return True
else :
return False
n = 73 ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
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15,680 | <ASSISTANT_TASK:>
Python Code:
# make our x array
x = np.linspace(-4, 4, 801)
# f(x) = x^2
def f(x):
return x**2
# derivative of x^2 is 2x
def f_prime(x):
return 2*x
# take a look at the curve
plt.plot(x, f(x), c='black')
sns.despine();
# starting position on the curve
x_start = -4.0
# looking at the values of... | <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: Let's assume we start at the top of the curve, at x = -4, and want to get down to x=0.
Step2: In this algorithm, alpha is known as the "learnin... |
15,681 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import seaborn as sns
import pandas as pd
from matplotlib import pyplot as plt, animation
%matplotlib notebook
#%matplotlib inline
sns.set_context("paper")
# interactive imports
import plotly
import cufflinks as cf
cf.go_offline(connected=True)
plotly.offline.init_noteb... | <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: Information Theory
Step2: Maximum entropy for a discrete random variable is obtained with a uniform distribution. For a continuous random varia... |
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Python Code:
from pseudo_spectral_projection import gauss_quads
gauss_nodes = [nodes for nodes, _ in gauss_quads]
from monte_carlo_integration import sobol_samples
sobol_nodes = [sobol_samples[:, :nodes.shape[1]] for nodes in gauss_nodes]
from matplotlib import pyplot
pyplot.rc("figure", figsize=[12,... | <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 number of Sobol samples to use at each order is arbitrary, but for
Step2: Evaluating model solver
Step3: Select polynomial expansion
Step4... |
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Python Code:
import larch, pandas, os, gzip
larch.__version__
from larch.data_warehouse import example_file
with gzip.open(example_file("arc"), 'rt') as previewfile:
print(*(next(previewfile) for x in range(70)))
itin = pandas.read_csv(example_file("arc"), index_col=['id_case','id_alt'])
itin.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: The example itinerary choice described here is based on data derived from a ticketing database
Step2: The first line of the file contains colum... |
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Python Code:
from __future__ import print_function, division
%matplotlib inline
%precision 6
import warnings
warnings.filterwarnings('ignore')
from thinkbayes2 import Pmf, Cdf
import thinkplot
import numpy as np
from numpy.fft import fft, ifft
from inspect import getsourcelines
def show_code(func):
... | <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: Playing dice with the universe
Step2: Initially the "probabilities" are all 1, so the total probability in the Pmf is 6, which doesn't make a l... |
15,685 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
from pyseidon import *
Station?
station=Station('http://ecoii.acadiau.ca/thredds/dodsC/ecoii/test/Station3D_dngrid_BF_20130730_20130809.nc')
print station.Grid.name
flowDir, velNorm = station.Util2D.flow_dir('GP_120726_BPa')
flowDir, velNorm = station.Util2D.flow_dir('GP... | <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: 1. PySeidon - Station object initialisation
Step2: Star here means all. Usually this form of statements would import the entire library. In th... |
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Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'Bike-Sharing-Dataset/hour.csv'
rides = pd.read_csv(data_path)
rides.head()
rides[:24*10].plot(x='dteday', y='cnt')
dummy_fields = ['seas... | <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 and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... |
15,687 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd # Start by importing the tweets data
X = pd.read_csv('../datasets/tweets.csv')
X.shape
X.columns
X.info()
X.head(5)
min(X.Avg)
max(X.Avg)
X.Avg.hist();
corpusTweets = X.Tweet.tolist() # get a list of all tweets, then is easier to apply preprocessign to each item
#... | <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: It contains 1181 tweets (as text) and one manually labeled sentiment.
Step2: 2 means very positive, 0 is neutral and -2 is very negative
Step3:... |
15,688 | <ASSISTANT_TASK:>
Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
# Generate plots inline
%matplotlib inline
import os
# Support to access the remote target
import devlib
from env import TestEnv
# RTApp configurator for generation of PERIODIC tasks
from wlgen import RTA, Ramp
# Setup 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: Import required modules
Step2: Target Configuration
Step3: Workload Execution and Power Consumptions Samping
Step4: Power Measurements Data
|
15,689 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
ef = pd.read_excel('EIA CO2 factors.xlsx', header=1, skip_footer=1,
index_col='EIA Fuel Code')
ef.columns = [name.strip() for name in ef.columns]
ef['Link'] = 'https://www.eia.gov/electricity/annual/html/epa_a_03.html'
ef.rename_axis({'Factor (Kilogr... | <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: Add EPA emission factors for fossil fuels not included in the EIA file
Step2: Add non-fossil emission factors for a total emission factor colum... |
15,690 | <ASSISTANT_TASK:>
Python Code:
import numpy as np #For numerical programming and multi-dimensional arrays
from pandas import date_range #For date-rate generation
from bqplot import LinearScale, Lines, Axis, Figure, DateScale, ColorScale
security_1 = np.cumsum(np.random.randn(150)) + 100.
security_2 = np.cumsum(np.rand... | <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: Random Data Generation
Step2: Basic Line Chart
Step3: The x attribute refers to the data represented horizontally, while the y attribute refer... |
15,691 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sbn
import pandas as pd
from uuid import uuid4
from lpde.geometry import WidthOf, Window, PointAt, BoundingBox, Mapper, Grid
from lpde.estimators import ParallelEstimator
from lpde.estimators.datatypes import Event, Degr... | <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: Notebook settings
Step2: Density Estimation
Step3: Create mock data streams
Step4: Timings of density estimation
Step5: Timings
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15,692 | <ASSISTANT_TASK:>
Python Code:
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import scipy
from PIL import Image
from scipy import ndimage
import tensorflow as tf
from tensorflow.python.framework import ops
from cnn_utils import *
%matplotlib inline
np.random.seed(1)
# Loading the data (sig... | <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: Run the next cell to load the "SIGNS" dataset you are going to use.
Step2: As a reminder, the SIGNS dataset is a collection of 6 signs represen... |
15,693 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scanpy.api as sc
from anndata import AnnData
from numpy.random import negative_binomial, binomial, seed
seed(1234)
# n_cluster needs to be smaller than n_simulated_cells, n_marker_genes needs to be smaller than n_simulated_genes
n_simulated_cells=1000
n_simulate... | <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, data following a (zero-inflated) negative binomial (ZINB) distribution is created for testing purposes. Test size and distribution parame... |
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Python Code:
# pip install cartoframes
import pandas as pd
stores_df = pd.read_csv('http://libs.cartocdn.com/cartoframes/files/starbucks_brooklyn.csv')
stores_df.head()
from cartoframes.auth import set_default_credentials
set_default_credentials('creds.json')
from cartoframes.data.services import 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: For other ways to install CARTOframes, check out the Installation guide.
Step2: To display your stores as points on a map, you first have to co... |
15,695 | <ASSISTANT_TASK:>
Python Code:
def parse_barcodes(bcfile, bc_id='BC'):
res = {}
with open(bcfile, 'r') as fi:
for line in fi:
fields = line.strip().split(',')
if fields[0].startswith(bc_id):
res[fields[0]] = fields[1]
return res
def parse_exp_config(expfile, 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: Read the counts table
Step2: Normalize to UTR length
Step3: Notation
Step4: Principal Component Analisys (PCA)
Step5: Aside
Step6: +BCM sam... |
15,696 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import nsfg
df = nsfg.ReadFemPreg()
df
df.birthord.value_counts().sort_index()
df.prglngth.value_counts().sort_index()
df.agepreg.hist(by=df.birthord)
df.totalwgt_lb.mean()
df['totalwgt_kg'] = df.totalwgt_lb / 2.20462
df.totalwgt_kg.mean()
df.finalwgt.value_counts... | <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: Print value counts for <tt>birthord</tt> and compare to results published in the codebook
Step2: Print value counts for <tt>prglngth</tt> and c... |
15,697 | <ASSISTANT_TASK:>
Python Code:
path = get_file('nietzsche.txt', origin="https://s3.amazonaws.com/text-datasets/nietzsche.txt")
text = open(path).read()
print('corpus length:', len(text))
chars = sorted(list(set(text)))
vocab_size = len(chars)+1
print('total chars:', vocab_size)
chars.insert(0, "\0")
''.join(chars[1:-6... | <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: Sometimes it's useful to have a zero value in the dataset, e.g. for padding
Step2: Map from chars to indices and back again
Step3: idx will be... |
15,698 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
before = np.loadtxt('Data/questionnaire_before.txt',delimiter=',')
after = np.loadtxt('Data/questionnaire_after.txt',delimiter=',')
form = np.loadtxt('Data/questionnaire_form.txt',delimiter=',')
questions = np.array(ran... | <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 you can see above, the data as provided were arranged with rows for each question, and the responses of each individual as the columns.
Step2... |
15,699 | <ASSISTANT_TASK:>
Python Code:
success = True # We'll use this to keep track of the various tests
failures = []
try:
import numpy as np
import scipy
print "numpy and scipy imported -- success!"
except:
success = False
msg = "* There was a problem importing numpy or scipy. You will definitely need 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: You should see a simple plot below the next cell.
Step5: There should be a Basemap plot displayed below this cell.
|
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