Pycse Manual
User Manual: Pdf
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- Overview
- Basic python usage
- Basic math
- Advanced mathematical operators
- Creating your own functions
- Defining functions in python
- Advanced function creation
- Lambda Lambda Lambda
- Creating arrays in python
- Functions on arrays of values
- Some basic data structures in python
- Indexing vectors and arrays in Python
- Controlling the format of printed variables
- Advanced string formatting
- Math
- Numeric derivatives by differences
- Vectorized numeric derivatives
- 2-point vs. 4-point numerical derivatives
- Derivatives by polynomial fitting
- Derivatives by fitting a function and taking the analytical derivative
- Derivatives by FFT
- A novel way to numerically estimate the derivative of a function - complex-step derivative approximation
- Vectorized piecewise functions
- Smooth transitions between discontinuous functions
- Smooth transitions between two constants
- On the quad or trapz'd in ChemE heaven
- Polynomials in python
- Wilkinson's polynomial
- The trapezoidal method of integration
- Numerical Simpsons rule
- Integrating functions in python
- Integrating equations in python
- Function integration by the Romberg method
- Symbolic math in python
- Is your ice cream float bigger than mine
- Linear algebra
- Potential gotchas in linear algebra in numpy
- Solving linear equations
- Rules for transposition
- Sums products and linear algebra notation - avoiding loops where possible
- Determining linear independence of a set of vectors
- Reduced row echelon form
- Computing determinants from matrix decompositions
- Calling lapack directly from scipy
- Nonlinear algebra
- Statistics
- Data analysis
- Fit a line to numerical data
- Linear least squares fitting with linear algebra
- Linear regression with confidence intervals (updated)
- Linear regression with confidence intervals.
- Nonlinear curve fitting
- Nonlinear curve fitting by direct least squares minimization
- Parameter estimation by directly minimizing summed squared errors
- Nonlinear curve fitting with parameter confidence intervals
- Nonlinear curve fitting with confidence intervals
- Graphical methods to help get initial guesses for multivariate nonlinear regression
- Fitting a numerical ODE solution to data
- Reading in delimited text files
- Interpolation
- Optimization
- Differential equations
- Ordinary differential equations
- Numerical solution to a simple ode
- Plotting ODE solutions in cylindrical coordinates
- ODEs with discontinuous forcing functions
- Simulating the events feature of Matlab's ode solvers
- Mimicking ode events in python
- Solving an ode for a specific solution value
- A simple first order ode evaluated at specific points
- Stopping the integration of an ODE at some condition
- Finding minima and maxima in ODE solutions with events
- Error tolerance in numerical solutions to ODEs
- Solving parameterized ODEs over and over conveniently
- Yet another way to parameterize an ODE
- Another way to parameterize an ODE - nested function
- Solving a second order ode
- Solving Bessel's Equation numerically
- Phase portraits of a system of ODEs
- Linear algebra approaches to solving systems of constant coefficient ODEs
- Delay Differential Equations
- Differential algebraic systems of equations
- Boundary value equations
- Partial differential equations
- Ordinary differential equations
- Plotting
- Plot customizations - Modifying line, text and figure properties
- Plotting two datasets with very different scales
- Customizing plots after the fact
- Fancy, built-in colors in Python
- Picasso's short lived blue period with Python
- Interactive plotting
- key events not working on Mac/org-mode
- Peak annotation in matplotlib
- Programming
- Some of this, sum of that
- Sorting in python
- Unique entries in a vector
- Lather, rinse and repeat
- Brief intro to regular expressions
- Working with lists
- Making word files in python
- Interacting with Excel in python
- Using Excel in Python
- Running Aspen via Python
- Using an external solver with Aspen
- Redirecting the print function
- Getting a dictionary of counts
- About your python
- Automatic, temporary directory changing
- Miscellaneous
- Worked examples
- Peak finding in Raman spectroscopy
- Curve fitting to get overlapping peak areas
- Estimating the boiling point of water
- Gibbs energy minimization and the NIST webbook
- Finding equilibrium composition by direct minimization of Gibbs free energy on mole numbers
- The Gibbs free energy of a reacting mixture and the equilibrium composition
- Water gas shift equilibria via the NIST Webbook
- Constrained minimization to find equilibrium compositions
- Using constrained optimization to find the amount of each phase present
- Conservation of mass in chemical reactions
- Numerically calculating an effectiveness factor for a porous catalyst bead
- Computing a pipe diameter
- Reading parameter database text files in python
- Calculating a bubble point pressure of a mixture
- The equal area method for the van der Waals equation
- Time dependent concentration in a first order reversible reaction in a batch reactor
- Finding equilibrium conversion
- Integrating a batch reactor design equation
- Uncertainty in an integral equation
- Integrating the batch reactor mole balance
- Plug flow reactor with a pressure drop
- Solving CSTR design equations
- Meet the steam tables
- What region is a point in
- Units
- GNU Free Documentation License
- References
- Index