#!/usr/bin/env python
# coding: utf-8

# # Simulate

# This example gives a "hello world" example to use AMS.

# ## Import and Setting the Verbosity Level

# We first import the `ams` library.

# In[1]:


import ams


# We can configure the verbosity level for logging (output messages) by passing a verbosity level (10-DEBUG, 20-INFO, 30-WARNING, 40-ERROR, 50-CRITICAL) to the `stream_level` argument of `ams.main.config_logger()`. Verbose level 10 is useful for getting debug output.
# 
# The logging level can be altered by calling ``config_logger`` again with new ``stream_level`` and ``file_level``.

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ams.config_logger(stream_level=20)


# Note that the above ``ams.config_logger()`` is a shorthand to ``ams.main.config_logger()``.
# 
# If this step is omitted, the default `INFO` level (`stream_level=20`) will be used.

# ## Run Simulations

# ### Load Case

# AMS supports multiple input file formats, including AMS ``.xlsx`` file, MATPOWER ``.m`` file, PYPOWER ``.py`` file, and PSS/E ``.raw`` file.
# 
# Here we use the AMS ``.xlsx`` file as an example. The source file locates at ``$HOME/ams/ams/cases/ieee39/ieee39_uced.xlsx``.

# In[3]:


sp = ams.load(ams.get_case('5bus/pjm5bus_uced.xlsx'),
              setup=True,
              no_output=True,)


# ### Inspect Models and Routines

# In AMS, ``model`` refers to the device-level models, and they are registered to an OrderedDict ``models``.

# In[4]:


sp.models


# We can inspect the detailed model data in the form of DataFrame.

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sp.PQ.as_df()


# In AMS, all supported routines are registered to an OrderedDict ``routines``.

# In[6]:


sp.routines


# ### Solve a Routine

# Before solving a routine, we need to initialize it first.
# Here Real-time Economic Dispatch (RTED) is used as an example.

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sp.RTED.init()


# Then, one can solve it by calling ``run()``.
# Here, argument `solver` can be passed to specify the solver to use, such as `solver='ECOS'`.
# 
# Installed solvers can be listed by ``ams.shared.installed_solvers``,
# and more detailes of solver can be found at [CVXPY-Choosing a solver](https://www.cvxpy.org/tutorial/advanced/index.html#choosing-a-solver).

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ams.shared.installed_solvers


# In[9]:


sp.RTED.run(solver='CLARABEL')


# The solved results are stored in each variable itself.
# For example, the solved power generation of ten generators
# are stored in ``pg.v``.

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sp.RTED.pg.v


# Here, ``get_all_idxes()`` can be used to get the index of a variable.

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sp.RTED.pg.get_all_idxes()


# Part of the solved results can be accessed with given indices.

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sp.RTED.get(src='pg', attr='v', idx=['PV_1', 'PV_3'])


# All Vars are listed in an OrderedDict ``vars``.

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sp.RTED.vars


# The Objective value can be accessed with ``obj.v``.

# In[14]:


sp.RTED.obj.v


# Similarly, all Constrs are listed in an OrderedDict ``constrs``,
# and the expression values can also be accessed.

# In[15]:


sp.RTED.constrs


# We can also inspect the `Constraint` values.

# In[16]:


sp.RTED.rgu.v