.. _curves-doc:

.. ipython:: python
   :suppress:

   from rateslib.curves import *
   from rateslib.instruments import *
   import matplotlib.pyplot as plt
   from datetime import datetime as dt
   import numpy as np

********************
Constructing Curves
********************

*Rateslib* has six different curve classes. Three of these are fundamental base
curves of different types and for different purposes. Three are objects which are
constructed via references to other curves to allow certain combinations.

The three fundamental curve classes are:

.. autosummary::
   rateslib.curves.Curve
   rateslib.curves.LineCurve
   rateslib.curves.IndexCurve

The remaining, more complex, combination classes are:

.. autosummary::
   rateslib.curves.CompositeCurve
   rateslib.curves.ProxyCurve
   rateslib.curves.MultiCsaCurve

In *rateslib* **defining curves** and then **solving them with calibrating
instruments** are two separate processes. This provides maximal flexibility whilst
providing a process that is fully generalised and consistent throughout.

.. warning::
   *Rateslib* **does not bootstrap**. Bootstrapping is an analytical process that
   determines curve parameters sequentially and exactly by solving a series of
   equations for a well defined set of parameters and instruments. All curves that
   can be bootstrapped can also be solved by a numerical optimisation routine.

The following pages describe these two processes.

.. toctree::
    :maxdepth: 0
    :titlesonly:

    c_curves.rst
    c_solver.rst

The below provides a basic introduction, exemplifying how a SOFR curve,
which might otherwise be bootstrapped, can be constructed in *rateslib* using the
generalised process of:

- **defining the** ``Curves``,
- **defining the calibrating** ``Instruments``,
- **combining** in the :class:`~rateslib.solver.Solver` with target market prices.

.. ipython:: python

   from rateslib.curves import Curve
   from rateslib.solver import Solver
   from rateslib.instruments import IRS
   from rateslib import dt

   sofr = Curve(
       nodes={
           dt(2022, 1, 1): 1.0,
           dt(2022, 2, 1): 1.0,  # 1M node
           dt(2022, 3, 1): 1.0,  # 2M node
           dt(2022, 4, 1): 1.0,  # 3M node
           dt(2022, 7, 1): 1.0,  # 6M node
           dt(2023, 1, 1): 1.0,  # 1Y node
           dt(2024, 1, 1): 1.0,  # 2Y node
       },
       id="sofr",
   )
   instruments = [
       IRS(dt(2022, 1, 1), "1M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "2M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "3M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "6M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "1Y", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "2Y", "A", curves="sofr"),
   ]
   rates = [2.4, 2.55, 2.7, 3.1, 3.6, 3.9]
   solver = Solver(
       curves=[sofr],
       instruments=instruments,
       s=rates,
   )
   sofr.nodes
   sofr.plot("1d", labels=["example sofr o/n curve"])

.. plot::

   from rateslib.curves import Curve
   from rateslib.solver import Solver
   from rateslib.instruments import IRS
   from rateslib import dt

   sofr = Curve(
       nodes={
           dt(2022, 1, 1): 1.0,
           dt(2022, 2, 1): 1.0,  # 1M node
           dt(2022, 3, 1): 1.0,  # 2M node
           dt(2022, 4, 1): 1.0,  # 3M node
           dt(2022, 7, 1): 1.0,  # 6M node
           dt(2023, 1, 1): 1.0,  # 1Y node
           dt(2024, 1, 1): 1.0,  # 2Y node
       },
       id="sofr",
   )
   instruments = [
       IRS(dt(2022, 1, 1), "1M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "2M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "3M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "6M", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "1Y", "A", curves="sofr"),
       IRS(dt(2022, 1, 1), "2Y", "A", curves="sofr"),
   ]
   rates = [2.4, 2.55, 2.7, 3.1, 3.6, 3.9]
   solver = Solver(
       curves=[sofr],
       instruments=instruments,
       s=rates,
   )
   fig, ax, line = sofr.plot("1D", labels=["example sofr o/n curve"])
   plt.show()
   plt.close()