Scientific Modules¶

Where are the bottlenecks?¶

High-level languages like Python, which are dynamic and, hence, opt for flexibility over strict control, are slower than compiled ones. As shown in the introductory slides, Python’s dynamic typing, automatic memory management, the interpreter overhead and other design choices introduce performance trade-offs that can create bottlenecks. The main bottlenecks are:

  • the dynamic typing system,
  • memory management and data access (allocation, reference counting, garbage collection, etc.).

Various strategies exist to mitigate these issues. The CPython interpreter is optimized in several (and sometimes, in weird) ways. For example, using a list comprehension is generally faster than regular for loops to filter a given list. Such optimizations are useful to know.

However, a priori or micro optimizations can be "the root of all evil" and often yield negligible performance gains compared to the development effort required. Therefore, two general rules to improve your Python code performance are:

  1. rely on mature and well-tested packages that try to overcome performance bottlenecks with different approaches
  2. profile your code to understand where the actual pitfalls rely

In this notebook, the first approach is presented together.

An relevant solution: NumPy¶

NumPy offers efficient multi-dimensional data array for storing and computation (a de facto standard). Under-the-hood, data structures and operations are implemented in C or Fortran, to obtain the very good performances.

Python scientific libraries, such as scipy, matplotlib and, pandas (that you will see in this notebook), make extensive use of NumPy objects as well as on compiled modules for critical computations (yet again, C/C++ or Fortran code).

NumPy¶

Let's import the NumPy packages using a standard name:

In [ ]:
import numpy as np

NumPy provides two main classes:

  • ndarray: NumPy arrays
  • ufunc: "Universal functions", i.e. functions that operates on ndarrays in a element-by-element fashion

ndarray¶

An ndarray is a collection of homogeneous items, an $n$-dimensional array (you can image it as a grid). $n$ is the number of dimentions, in mathematical terms a one-dimensional object is a vector, a two-dimensional one a matrix and for more than three dimensions a tensor.

  • Each item occupies the same number of bytes. Hence, only a single type is allowed per ndarray
  • Items typically are numerical type, however also str and other objects are allowed
  • Once created, the ndarray has fixed dimensions

Initialization¶

There are multiple ways to initialaze them, one of which is through a Python list:

In [ ]:
# Create an array from a Python list
a = np.array([1.0, 2, 3])  # in class language: calling the constructor or __init__ with a list as argument
print(a)
print(a.dtype)

How does Numpy react to inhomogeneous lists?

In [ ]:
c = np.array(["lof", 3, 2])  # doesn't work as expected
c
In [ ]:
print(c.dtype)

As discussed, NumPy to exploit the full potential of C data structures needs to know in advanced the times type. De facto, we loose the dynamic typing feature partially (because a ndarray is force to have a specific and fixed type) but we gain in performances.

How to access elements¶

There are two ways:

  • Basic indexing: similar to lists (single, stride...)
  • Advanced indexing, as called in NumPy terms: triggered when the selection is a non-tuple sequence object or an ndarray (int or bool)

The standard terminology is to have a mask that selects the item of interest inside an ndarray.

In [ ]:
print(a[0], a[:1])  # basic
In [ ]:
mask = np.array([True, True, False])
print(a[mask])  # advanced

One of the main use for fancy indexing is thorugh masks defined by conditions.

In [ ]:
x = np.arange(0, 10, 0.5)
x
In [ ]:
mask = (5 < x) * (x < 7.5) # these operations are done *element-wise*, see ufunc
mask
In [ ]:
x[mask]

dtype¶

A data type object (an instance of numpy.dtype class) describes how bytes in the fixed-size block of memory corresponding to an ndarray should be interpreted.

In [ ]:
a = np.array([1, 2, 3])  # buffer of 24 bytes interpreted as 3 ints
a.dtype  # int64 -> 64 bits -> 8 bytes
In [ ]:
b = a.astype(np.int16)  # Numpy way to cast
print(b)

Going multi-dimensional¶

To initialize a 2-dimensional ndarray, one can use a list of lists:

In [ ]:
b = np.array([[1, 2, 5], [3, 4, 6]], dtype=np.float16) # here we ask to create an array with np.float16 elements
print(b)
print(b.shape)

Each "direction" of the ndarray is called axis. Hence, the index running along rows (in this case we have a matrix) is the first one (axis=0), while the one running along columns is the second one (axis=1).

Indeed, the first index when accessing a multi-dimensional ndarray goes along rows, while the second one along columns

In [ ]:
n_rows, n_cols = b.shape
for idx_row in range(n_rows):
    for idx_col in range(n_cols):
        print(b[idx_row, idx_col]) # first row will be printed, then secondo one

Its shape, hence number of rows and column, can be changed after initialization:

In [ ]:
b.reshape(6, 1) # don't do b.shape = (6, 1) it will be deprecated in Numpy 2.5

Create ndarrays through "intrinsic" numpy functions¶

Efficienty initiate arrays with items with a already known pattern:

In [ ]:
a = np.zeros(10)
a
In [ ]:
b = np.ones(shape=(3, 2))
b
In [ ]:
e = np.linspace(0, 10, 70)  # start, stop, npoints; try also adding endpoint=False
e

Be aware of the existence of special functions to initiate an array (an important example is random) or one can create ad hoc functions to initiate and fill a ndarray

In [ ]:
r_a = np.random.rand(4)
r_a

Below we use a user-defined function that uses indeces to fill every array element

In [ ]:
def func(i, j):
    return i * j + 1


f_a = np.fromfunction(func, (3, 4))  # meshgrid
f_a

Computations with ndarrays¶

Generally, you will use ndarray to perform computations. Broadly speaking, you might use two computation patters:

  1. From one ndarray of $n$ dimensions (ndarray.ndim), the computation return an ndarray of the same dimensions. In this case, computations are done in a element-by-element fashion. For this, ufunc are the tool to use.

ufunc syntax can be like regular funtions, hence they take as input an ndarray and return another ndarray:

In [ ]:
arr = np.arange(1, 65)
arr
In [ ]:
arr_new = np.sqrt(arr)
arr_new

Or have syntactic sugar for it:

In [ ]:
arr_pow = arr**2
arr_pow # as you can see, it has the same ndim of the starting array
  1. From one ndarray of dimension $n$, the computation might return a lower dimensional one.

An example could be, computing the sum of all integer number from 1 to n:

In [ ]:
b = np.array([[1, 2, 5], [3, 4, 6]], dtype=np.float16)
b
In [ ]:
sum_over_rows = np.sum(b, axis=0)
# equivalently, final_sum = seq.sum(axis=0)
sum_over_rows
In [ ]:
sum_over_all_ndarray = np.sum(b)
sum_over_all_ndarray

A small exercise¶

Imagine that you have an array (1D) defining time sampling, for example from 0 to 1 second, with 1000 samples per second. You sampled a sine wave for one second. The goal is:

  • to compute the third power of this signal
  • compute its average value
  • add an error: the last sample is -1, hence update the last element of the sine wave
  • finally, select just the first half of the signal and compute again the average
In [ ]:
# define the time ndarray

# compute the sin from this, there is already a function for this in numpy called np.sin, and save it into a new array called signal

# modify the last element of time

# save in a new array, the first half (from 0 to 0.5s) of the signal array

I/O with NumPy¶

You can even read it from the file system:

In [ ]:
data = np.genfromtxt("./data/solar_system.csv", delimiter=",", skip_header=1, usecols=(1, 2, 3))

NumPy has is own, binary and compressed, file format for saving ndarrays with extension npy. Use it when you are sure that data will be read by NumPy, otherwise prefer more general file formats such as csv, hdf5 ect.

In [ ]:
np.save("./data/output_numpy.npy", data) # save in its npy format
np.savetxt("./data/output_numpy.csv", data, delimiter=",") # save a comma, separated variables
# How do you load a npy?
# data = np.load("./data/output_numpy.npy")

Are ndarray really that efficient?¶

General raccomandation: don't trust any raccomandation, test it yourself!

In [ ]:
long_list = list(range(10000))

t1 = %timeit -o [i**2 for i in long_list]  # list elements squared
In [ ]:
long_array = np.arange(10000)

t2 = %timeit -n 1000 -o long_array**2
In [ ]:
print("numpy best speed-up:", t1.best / t2.best)
print("numpy average speed-up:", t1.average / t2.average)

Copy vs view¶

Be aware that numpy arrays can create efficient views or computationally costly, but sometimes necessary, copies.

To understand this, think about how the computer stores variables into the memory. When an array arr is initialized, the interpreter allocates enough memory to store all attributes of the object (name, reference counter, the actual array, dtype, etc.). Let another array arr2 be a new array built from arr. If arr2 containes a subset of arr, in some cases NumPy avoids asking for a new chunck of memory and re-uses the one already allocated for arr. This creates a view.

However, in certain contexts this is not easily possible (or can be explicitely asked by the user). Hence, the new array arr2 needs to be initialized as a brand new array, allocating memory space for it. This second way creates a copy.

Creating a copy is much more expensive than to create a view, because, in the former, space allocation and (partially) data copy take more time than to create a reference to the already present memory space.

General take away: even for high-level languages such as Python and relative libraries, it is useful (if not fundamental) to have an idea of what is happaning at the low-level (near the hardware) when dealing with performances.

P.s. A similar concept is used for Python objects, in which there are shallow copies (the NumPy view) and deep copies (NumPy copy).

In [ ]:
x_v = np.arange(10)
y_v = x_v[0:3]  # creates a view
print(y_v)
In [ ]:
x_c = np.arange(9).reshape(3, 3)
mask = [1, 2]
y_c = x_c[mask]  # "advanced indexing" creates a copy
print(x_c)
print(y_c)

How to test if it is copy or a view?

The base attribute returns the original array if it is a view, None if it is a copy

In [ ]:
print(y_v.base)
print(y_c.base)

ndarray attributes recap¶

Some useful ndarray attributes are: (let arr be the array)

  • arr.dtype   data-type object for this array
  • arr.shape   returns a tuple with the size of the array. Changing the tuple re-shapes the array
  • arr.ndim   number of dimension in array
  • arr.size   total number of elements
In [ ]:
# Playground: try for yourself ndarray attributes
arr = np.ones((4, 5))

(some) ndarray functions¶

Some useful ndarray functions are:

  • arr.copy()   returns a copy of the array
  • arr.view()   returns a new view of the array using the same data of arr (save memory space)
  • arr.reshape()   returns an array (copy) with a new shape
  • arr.transpose()   returns an array view with the shape transposed
  • arr.sum()
  • arr.min|max()   return min (or max) value
  • arr.argmin|argmax()   return the index of min (max) value
  • arr.var|mean|std|prod()   take the usual meaning
In [ ]:
# Playground: try for yourself ndarray functions
arr = np.ones((4, 5))
In [ ]:
dir(np)

Exercise¶

Row-Column matrix multiplication is defined in the following way:

            [a11, a12, a13]                     [a11*b11+a12*b21+a13*b31, a11*b12+a12*b22+a13*b32]
            [a21, a22, a23]        [b11, b12]   [a21*b11+a22*b21+a23*b31, a21*b12+a22*b22+a23*b32]
        a = [a31, a32, a33]  @ b = [b21, b22] = [a31*b11+a32*b21+a33*b31, a31*b12+a32*b22+a33*b32]
            [a41, a42, a43]        [b31, b32]   [a41*b11+a42*b21+a43*b31, a41*b12+a42*b22+a43*b32]
            [a51, a52, a53]                     [a51*b11+a52*b21+a53*b31, a51*b12+a52*b22+a53*b32]
  • Write a function matr_mult(a,b) that performs this operation on 2 ndarrays and compare the numerical results with the 'intrinsic' method available in Numpy np.matmul(a,b) (look for the documentation!)
  • compare performances between the two: how much is the average speed-up?
  • use NumPy I/O to save a tsv file the final matrix

Expected time: 30 min

In [ ]:
mat_a = np.ones((100, 200)) * 0.1
mat_b = np.ones((200, 50)) * 0.3
In [ ]:
# Solution
%pycat solutions/Matr_mult_np.py

matplotlib¶

One of the most wide-spread Python library to create mainly static plots and visuals, from simple to publishing-ready. It is capable of 2D as well as 3D plots.

matplotlib makes use of NumPy to provide good performance with large data arrays.

Main module with a state-based interface to plot with matplotlib:

In [ ]:
import matplotlib.pyplot as plt
# display output images in the output cell
%matplotlib inline

Example of a simple 1D plot:

In [ ]:
x = np.arange(0, 7, 0.00001)
plt.plot(x, x**3, label="$x^3$")  # you can use LateX syntax
plt.plot(x, x**2, label="$x^2$")
plt.legend()
plt.show()
#plt.savefig("figure.png", dpi=300) # save figure with high-res

Anatomy and terminology of a matplotlib figure:

anatomy

Coding style¶

  • Implicit (used in this tutorial): pyplot manages Figure creation and all updates to this objects are performed by plt calls, updating internally (hence, hidden from the user) the state of Figure object.
  • Explicit: the user manages objects (Figure, Axes etc.) explicitely in an object-oriented fashion

Showing-off¶

Reference with the code to produce such image

In [ ]:
from IPython.display import Image
Image(url="data:image/png;base64,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", width=1200, height=800)

Useful resources¶

  • Collection of plots and cheatsheets
  • all possible examples of plot

Other common libraries for plotting¶

  • Seaborn: quite used in statistics due to already baked-in functions for statistical plotting
  • Plotly: designed for interactive plots for web apps (indeed it is actually a JavaScript library!)
  • Bokeh: built for interactive plots

scipy¶

scipy implements fundamental algorithms for scientific computing. Built on top of numpy and other scientific modules (e.g. blas). key advantages of this library are:

  • a complete documentation describing the science and the implementation behind each module
  • attention to perfomances
  • well-tested suite of function (important for scientific accuracy)

Some of the topics that SciPy covers are:

  • Special functions (scipy.special)
  • Integration (scipy.integrate)
  • Optimization (scipy.optimize)
  • Interpolation (scipy.interpolate)
  • Fourier Transforms (scipy.fft)
  • Signal Processing (scipy.signal)
  • Linear Algebra (scipy.linalg)
  • Sparse Eigenvalue Problems (scipy.sparse)
  • Statistics (scipy.stats)
  • Multi-dimensional image processing (scipy.ndimage)
  • File IO (scipy.io)

Each of these submodules provides a number of functions and classes that can be used to solve problems in their respective topics.

Just an example: Fast Fourier Trasform¶

Starting from a periodic signal, think of electromagnetic waves used for trasmit radio frequences or a signal from a distant pulsar, you can find the most prominent frequences from this signal using the mathematical tool of Fourier Trasfromations.

These are ubiquous in STEM areas and fundamental for many applications, therefore is of fundamental importance that their computational footprint is minimal.

An optimized algorithm for this is the fast discrete fourier transform, implemented in the scipy.fft module.

Let's define a wave signal through sin funtions:

In [ ]:
import numpy as np

time = np.linspace(0, 10, 1000)

# create a signal from the overlap of two sin signals, with different frequences
first_wave = 1.5*np.sin(time*6.28 + 0.1)
second_wave = 0.9*np.sin(time*3 - 0.2)
signal = first_wave + second_wave

plt.plot(time, signal)
plt.xlabel("Time")
plt.ylabel("Signal [arbitrary units]")
plt.show()

Now let's imagine that we don't know anything about the original signal and we want to discover which are the prominent frequences of it (can you spot, beforehand, which are the frequences of the signal frmo how first_wave and second_wave are defined?):

In [ ]:
from scipy import fft

# Define the x axis of the fft trasformation (the signal is over time, hence the fft is over frequences)
freq = fft.fftfreq(1000, time[1]-time[0])

# We perform the transformation
transformation = fft.fft(signal)
# Than get only where frequences are most prominent (a.k.a. the power spectrum)
power_spectrum = np.abs(transformation)**2

# Finally we plot it
plt.plot(freq, power_spectrum)
plt.xlim(-2, 2) # restrict the freq window
plt.xlabel("Frequences [2*pi]")
plt.ylabel("Power Spectrum [a.u.]")
plt.show()

You should be able to see two peaks, symmetric with respect to the origin, highlighting the frequences present in our signal from the first_wave (which is $2\pi$) and frmo the second_wave (which is $3$, slightly less than \pi).

A note between NumPy and Scipy: be awere that, due to historical reasons, there is an overlap of functions between NumPy and Scipy (e.g. the inverse of a matrix function, that is present in both libraries). Usually, on uses the NumPy version but as of today (02/2026), a feature parity is present. Moreover, every time a function is implemented twice, this is explicitated in both documentations.

pandas¶

pandas provides data structures and tools for data manipulations of tabular data and time series.

It provides two primary data structures:

  • Series is built for 1-dimensional data series and homogeneous data
  • DataFrame is built for 2-dimensional collections of tabular data, heterogeneous data composed of multiple Series

Both are built on top of NumPy arrays.

DataFrame¶

In [ ]:
# conventional way to import pandas
import pandas as pd

It's best practice to inspect the data to work with before load it:

In [ ]:
%cat data/chipotle.tsv

And now try to load it into the IPython session and within a DataFrame object:

In [ ]:
# a new DataFrame read from a file of Chipotle orders
orders = pd.read_table("data/chipotle.tsv")
orders

What if the columns names in our file are wrong and you want to add them manually?

Usually it is the case to have badly formatted data to work with.

In [ ]:
# define a list of columns that we expect to have
cols = [
    "order_id",
    "quantity",
    "item_name",
    "choice_description",
    "item_price",
]

orders_manual = pd.read_table(
    "data/chipotle.tsv",
    header=None,   # do not use file header
    names=cols,    # set column names manually
    skiprows=1     # ignore first line
)

Inspect a DataFrame¶

Use the method DataFrame.head() to inspect the first few rows of data:

In [ ]:
orders.head()
In [ ]:
# How to set the number of rows to be visualized
pd.options.display.max_rows = 8

# How to visualize all DataFrame
orders

Pause and see how DataFrame are structured:

  1. The actual data loaded from file is found in the central part.
  2. The data is separated in rows and columns
  3. Each row is identified by an index (most left column) which Pandas automatically set to a sequentially increasing integer. However, it can be anything (even strings!)
  4. On the header (very first row), columns names

Indexes and columns names helps you to access data

Use info() to get Pandas to return more details on the loaded tabular data

In [ ]:
orders.info()

We get the name of each column, the NumPy dtype of each column, how many actual values are present and the amount of memory used. All informations that can be relevant to further manipulate data.

As a side note: Pandas has excellent support for not-a-number (NaN) entries in DataFrames and Series.

Typical operation performed over tabular data are related to statistics on this. DataFrame objects implement various methods on this regards. Generally one can get broad and general info with:

In [ ]:
orders.describe()

However this is a bit too generic. Let's take the column "quantity", that we can check with:

In [ ]:
orders.columns

And compute its average to have some more details:

In [ ]:
orders["quantity"].mean()

DataFrame implements various methods to perform statistical analysis over both rows and columns.

Note: it could be interesting to have compute similar quantities for the "item_price" column, but with the DataFrame as it is we cannot do that. Why?

How to represent a time-series: Pandas Series¶

  • A Pandas Series is a single vector of data (like a one dimensional ndarray), with an index that labels each element in the vector
  • It supports both integer-based and label-based indexing

Note: a single DataFrame column, or a single DataFrame row, is actually a Pandas Series

In [ ]:
type(orders["item_price"])

One can use 1D containers, a plain list a 1D ndarray, to initialize a Series:

In [ ]:
S = pd.Series([632, 1638, 569, 115])
S

How to access the underlying ndarray of a Series¶

This can be done also for a single row/column DataFrame:

In [ ]:
S.values
In [ ]:
# How to get the index of a series
S.index

Data manipulation¶

Let's load a new DataFrame from the file system to the memory:

In [ ]:
# How to read a DataFrame from the first 3 columns of a .csv.gz file
A = pd.read_csv(
    "data/num.csv.gz",
    header=None,
    names=["Elevation", "Aspect", "Slope"],
    usecols=range(0, 3),
)
In [ ]:
A

Filter rows, based on column condition¶

How do I access all rows that has in the "Aspect" column a 20?

In [ ]:
A[A["Aspect"] == 20]

This notation recalls the one of ndarrays or Python list. The return type is again a DataFrame and you can access the underlying data in an ndarray form as you saw above.

On can use also multiple conditions on columns to select the rows of interest

In [ ]:
condition = (A.Elevation < 2400) & (A.Slope == 17)
# note, condition is a Series and work as a mask!
B = A[condition]
# or alternatively: B = A.loc[condition]
B

filter column too¶

If one wants to store only relevant columns, the notation is:

In [ ]:
cols = ["Slope", "Aspect"]
B = A[condition][cols]
# alternatively, a cleaner syntax could be: B = A.loc[condition, cols]
B

Talking about selecting rows and columns, one can also use indexes to select them, although it is not raccommended:

In [ ]:
B = A.iloc[[0,1,2,3], [0]] # only the first 4 rows, and the first column
B

Yet another example of Pandas flexibility¶

read_csv allows you also to download dataset from public repositories:

In [ ]:
baseball = pd.read_csv(
    "https://raw.githubusercontent.com/fonnesbeck/statistical-analysis-python-tutorial/master/data/baseball.csv",
    index_col="id",
)
In [ ]:
baseball.head(10)
In [ ]:
# Multiple index
baseball_h = baseball.set_index(["year", "team", "player"])
baseball_h.head(10)

A notable alternative to Pandas¶

Polars is a Python/Rust/JS library used to work with tables of data and based on another data structure which are Apache arrays (rather than NumPy ones). It is designed to be fast, especially when working with large datasets. Polars can automatically use multiple CPU cores, perform computation lazily, etc. Therefore, it has a different focus with respect to Pandas, a different syntax to handle data manipulation and selection etc.

It is a project to be aware of if you are interested in data science or data engeneering and you need to work on big (> 100Mb) tables or where performances are crucial.

Examples¶

  • solar_system notebook: example/exercise that contains a real-ish use case of classes, functions, pandas
  • LinSolve_exe notebook: example that contains a real use case of scipy and matplotlib

That's all folks!¶

In [ ]:
import antigravity