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    <title>calculus on Ciência Programada</title>
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    <description>Recent content in calculus on Ciência Programada</description>
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    <managingEditor>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</managingEditor>
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    <copyright>© 2026 Francisco Bustamante</copyright>
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      <title>Differential Equations with SciPy</title>
      <link>https://cienciaprogramada.com/2026/10/differential-equations-scipy/</link>
      <pubDate>Wed, 21 Oct 2026 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2026/10/differential-equations-scipy/</guid>
      <description>The classic pendulum period formula only holds for small oscillations, and the exact equation has no closed-form solution. With SciPy&amp;rsquo;s solve_ivp, we measure the real period and solve stiff systems, Lotka-Volterra, falling with drag, and consecutive reactions.</description>
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      <title>Numerical Integration with SciPy</title>
      <link>https://cienciaprogramada.com/2026/10/numerical-integration-scipy/</link>
      <pubDate>Wed, 14 Oct 2026 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2026/10/numerical-integration-scipy/</guid>
      <description>The Gaussian function has no elementary antiderivative, and that is a theorem of Liouville. When the antiderivative does not exist, or all you have is a table of measurements, the way forward is numerical: quad, trapezoid and Simpson, from scipy.integrate, with the care each one demands.</description>
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      <title>Numerical Derivatives with SciPy</title>
      <link>https://cienciaprogramada.com/2026/10/numerical-derivatives-scipy/</link>
      <pubDate>Wed, 07 Oct 2026 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2026/10/numerical-derivatives-scipy/</guid>
      <description>Is the reactor temperature rising too fast? The question is a derivative, but all we have are numbers in a table. We will see finite differences, numpy.gradient and scipy.differentiate, and why shrinking the step does not always improve the derivative, because of rounding and noise.</description>
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      <title>Infinite Series - Calculus with Python and SymPy</title>
      <link>https://cienciaprogramada.com/2022/05/infinite-series-calculus-python/</link>
      <pubDate>Thu, 05 May 2022 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2022/05/infinite-series-calculus-python/</guid>
      <description>A good part of the study of calculus is devoted to what are called infinite series. But what, exactly, are infinite series? And how are they related to the paradox of Achilles and the tortoise, one of the so-called paradoxes of Zeno of Elea, the Greek philosopher? What is the connection with quantum mechanics and the uncertainty principle? And where does Python come in? That is what we will find out in this article.</description>
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      <title>Integrals - Calculus with Python and SymPy</title>
      <link>https://cienciaprogramada.com/2022/04/calculus-python-sympy-integrals/</link>
      <pubDate>Fri, 15 Apr 2022 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2022/04/calculus-python-sympy-integrals/</guid>
      <description>We have already written here on the site about the concepts of limit and derivative and how we can do the related computations with Python. Continuing our journey through calculus, in this article we will see how to work with integrals using SymPy and SciPy, Python packages. Along the way, we will pick up some notions of numerical methods.</description>
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      <title>Optimization Problems with Python</title>
      <link>https://cienciaprogramada.com/2022/04/optimization-problems-python/</link>
      <pubDate>Tue, 05 Apr 2022 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2022/04/optimization-problems-python/</guid>
      <description>Engineers and scientists are always trying to get the most performance out of their equipment and projects at the lowest cost. This search gives rise to so-called optimization problems. In this article, we will see how to use Python, with the help of the SymPy package, to solve them.</description>
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      <title>Calculus with Python and SymPy - Derivatives</title>
      <link>https://cienciaprogramada.com/2022/03/calculus-python-sympy-derivatives/</link>
      <pubDate>Sun, 20 Mar 2022 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2022/03/calculus-python-sympy-derivatives/</guid>
      <description>The start of a calculus course tends to feel abstract because of the concept of a limit. But it soon becomes more tangible with the introduction of the derivative, which has many obvious practical applications. In this article, we will see how to work with derivatives using SymPy, a Python package.</description>
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      <title>Calculus with Python and SymPy: limits</title>
      <link>https://cienciaprogramada.com/2022/03/calculus-python-sympy-limits/</link>
      <pubDate>Thu, 10 Mar 2022 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2022/03/calculus-python-sympy-limits/</guid>
      <description>The concept of a limit is the most important one in the study of calculus. Many other concepts and ideas are built on the definition of a limit. In this article, we will see how to find the limit of functions using SymPy and how this package can be a teaching aid in the study of calculus.</description>
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