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    alanlujan91
    @alanlujan91
    hi!
    Mridul Seth
    @MridulS
    Hi!
    Mateo Velásquez-Giraldo
    @Mv77
    u(ct)=βRE[u(ct+1)]u'(c_t)=\beta R E[u'(c_{t+1})]
    Oh, I like this.
    Can't figure out how to create new "conversations"
    2 replies
    alanlujan91
    @alanlujan91
    you can do latex!!? game changer
    Mateo Velásquez-Giraldo
    @Mv77
    y(e(s(sir)))y(e(s(\text{sir})))
    Mridul Seth
    @MridulS
    you want to get more crazy? This is federated via matrix so you don't even need to use a webpage to interact with gitter. You can use something like https://element.io
    AMonninger
    @AMonninger
    Well, here is a question. Is there a HARK equivalent to the quantecon nelder_mead optimization function?
    Unfortuantely, it only works with @nijt functions which I'm not familiar with.
    https://quanteconpy.readthedocs.io/en/latest/optimize/nelder_mead.html
    4 replies
    Mateo Velásquez-Giraldo
    @Mv77
    Hey, wanted to put this team on our radar https://github.com/SparseGridsForDynamicEcon . They are coming out with a continuous-time toolbox that might not be as relevant to us. However, the SparseGrid technology might be highly relevant, and they have examples on how to use it.
    2 replies
    Mateo Velásquez-Giraldo
    @Mv77
    Another tool I wanted to share: https://github.com/pytask-dev/pytask . It's a workflow tool aimed at facilitating reproducible analyses. It might be worth exploring it as a framework for the REMARKS that could replace the do_all/do_min setup
    Durgesh Patel
    @pat749
    Hi, My Name Is Durgesh Patel and I am an Undergraduate Student Studying At NIT Trichy. Looking Forward to contribute on econ-ark . Thank you
    1 reply
    Durgesh Patel
    @pat749
    Hi is there any progress on this (https://github.com/EconForge/heterogeneous-agent-computing/wiki ) documentation or should I work on it?
    Sebastian Benthall
    @sbenthall
    I don't know what's up with that EconForge HACK group, but I don't think it's been active for some time. There is still a lot of heterogeneous agent modeling going on around here though.
    Sebastian Benthall
    @sbenthall
    @pat749 if you are interested in helping on documentation, this issue needs some attention: econ-ark/HARK#1147
    The issue is that there are modules that are in the HARK library but not yet in the API documentation: https://hark.readthedocs.io/en/latest/reference/index.html
    That's because the documentation directory is missing the corresponding sphinx files: https://github.com/econ-ark/HARK/tree/master/Documentation/reference
    Somebody needs to add .rst files to the Documentation/reference directories to get Sphinx to process the docstrings and produce autodocs
    Durgesh Patel
    @pat749
    Ok so I will start working on this documentation if I need help I will talk through this group.
    alanlujan91
    @alanlujan91
    wdu9
    @wdu9
    Hi, here is a link to a github repo that provides an easy to use toolkit to solve HANK models https://github.com/shade-econ/nber-workshop-2022
    Mateo Velásquez-Giraldo
    @Mv77
    I've just merged a PR fixing the DemARKs that were broken by my Array-valued distributions: econ-ark/DemARK#185
    AMonninger
    @AMonninger

    Hi,
    I have a question regarding plotting solutions for different time periods. After solving a model, say IndShockConsumerType, how do I extract the consumption functions for different periods?
    Take the example:

    Import

    import numpy as np
    from copy import deepcopy
    from HARK.ConsumptionSaving.ConsIndShockModel import IndShockConsumerType, ConsumerSolution, init_idiosyncratic_shocks
    import time # to time

    from HARK.utilities import plot_funcs_der, plot_funcs
    import matplotlib.pyplot as plt

    init_indshock = dict(
    init_idiosyncratic_shocks,
    **{

        ### No income shocks
        "PermGroFac": [1.0],
        "PermShkCount": 7,
        "PermShkStd": [0.0],
        "TranShkStd": [0.0],
        "UnempPrb": 0.0,
        "UnempPrbRet": 0.0,
        "LivPrb": [1.0],
        ### For simulation
        "aNrmInitMean": 0.0,
        "aNrmInitStd": 0.0,
        "T_sim": 5,
        "AgentCount": 10,
        ### Others
        "BoroCnstArt": 0,
    }

    )

    Solve IndShockConsumerType

    IndShockExample = IndShockConsumerType(**init_indshock)
    IndShockExample.update_income_process()
    IndShockExample.solve()

    To get the consumption Function, I use:
    IndShockExample.solution[0].cFunc

    But how do I get the cFunc for different periods? Say t=0, 1, 2, 3, 4

    Mateo Velásquez-Giraldo
    @Mv77
    That'd be in agent.solution[t]
    1 reply
    With t=0,1,2...
    alanlujan91
    @alanlujan91
    @AMonninger the model you have above has default parameter IndShockExample.cycles = 1 which means it runs the solver once and thus only has two solutions, [0] is the solved solution and [1] is the terminal solution of consuming everything
    1 reply
    If you go to https://github.com/econ-ark/HARK/blob/master/examples/ConsIndShockModel/IndShockConsumerType.ipynb and check out LifecycleExample you should be able to do what Mateo suggested
    AMonninger
    @AMonninger
    Thanks @Mv77 and @alanlujan91 !
    My problem was that my income variables had just one element. It works now