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# numpy

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```NumPy
=====

Provides
1. An array object of arbitrary homogeneous items
2. Fast mathematical operations over arrays
3. Linear Algebra, Fourier Transforms, Random Number Generation

How to use the documentation
----------------------------(more...)
```

```import sys
import logging
import numpy
import scipy.io
import pylab
```
```
# Define a 24-hour load profile with hourly values.
p1h = numpy([0.52, 0.54, 0.52, 0.50, 0.52, 0.57, 0.60, 0.71, 0.89, 0.85, 0.88,
0.94, 0.90, 0.88, 0.88, 0.82, 0.80, 0.78, 0.76, 0.68, 0.68, 0.68,
0.65, 0.58])
```

```import sys
import logging
import numpy
import scipy.io
import pylab
```
```
# Define a 24-hour load profile with hourly values.
p1h = numpy([0.52, 0.54, 0.52, 0.50, 0.52, 0.57, 0.60, 0.71, 0.89, 0.85, 0.88,
0.94, 0.90, 0.88, 0.88, 0.82, 0.80, 0.78, 0.76, 0.68, 0.68, 0.68,
0.65, 0.58])
```

```  def sanity_simultaneousFit(self):
from PyAstronomy import funcFit as fuf
import numpy
import matplotlib.pylab as mpl

```
```  def sanity_MCMCPriorExample(self):
from PyAstronomy import funcFit as fuf
import numpy as np
import matplotlib.pylab as plt
import pymc
```
```  def sanity_autoMCMCExample1(self):
from PyAstronomy import funcFit as fuf
import numpy as np
import matplotlib.pylab as plt

```
```  def sanity_autoMCMCExample2(self):
from PyAstronomy import funcFit as fuf
import numpy as np
import matplotlib.pylab as plt

```
```  def sanity_2dCircularFit(self):
import numpy as np
import matplotlib.pylab as plt
from PyAstronomy import funcFit as fuf

```

```
import numpy as np

from statsmodels.sandbox.tools import cross_val

```
```    from statsmodels.iolib.table import (SimpleTable, default_txt_fmt,
default_latex_fmt, default_html_fmt)
import numpy as np

```

```
import numpy as np

from statsmodels.sandbox.tools import cross_val

```
```    from statsmodels.iolib.table import (SimpleTable, default_txt_fmt,
default_latex_fmt, default_html_fmt)
import numpy as np

```

```from mpl_toolkits.axes_grid1.inset_locator import mark_inset

import numpy as np

def get_demo_image():
from matplotlib.cbook import get_sample_data
import numpy as np
```

```from mpl_toolkits.axes_grid1.inset_locator import mark_inset

import numpy as np

def get_demo_image():
from matplotlib.cbook import get_sample_data
import numpy as np
```

```from mpl_toolkits.axes_grid1.inset_locator import mark_inset

import numpy as np

def get_demo_image():
from matplotlib.cbook import get_sample_data
import numpy as np
```

```import numpy as np
from bokeh.plotting import *
from bokeh.objects import ServerDataSource
import pandas as pd
output_server("remotedata")
server = session().config
import numpy as np
```

```#Loading the required packages
import scipy as sp
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
```
```from scipy import linalg, optimize, constants

import numpy
import algopy
import time
```

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