run_experiment.py

#!/usr/bin/env python

""" run GDAY, plot LAI, NPP, transpiration """

import os
import sys
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import datetime as dt
import example

__author__  = "Martin De Kauwe"
__version__ = "1.0 (11.02.2014)"
__email__   = "mdekauwe@gmail.com"

def main(experiment_id, site, treatment):

    # run new simulations
    example.ambient_sim(experiment_id, site, treatment)

    # load data
    amb = read_data("outputs/D1GDAY%s%s.csv" % (site, treatment.upper()))

    plt.rcParams['figure.subplot.hspace'] = 0.15
    plt.rcParams['figure.subplot.wspace'] = 0.15
    plt.rcParams['font.size'] = 10
    plt.rcParams['legend.fontsize'] = 10
    plt.rcParams['xtick.labelsize'] = 10.0
    plt.rcParams['ytick.labelsize'] = 10.0
    plt.rcParams['axes.labelsize'] = 10.0
    plt.rcParams['font.family'] = "sans-serif"
    plt.rcParams['font.style'] = "normal"
    plt.rcParams['font.serif'] = "Helvetica"
    fig = plt.figure()

    #years = np.unique(amb.YEAR).values
    years = np.unique(amb.YEAR)
    years = [int(float(i)) for i in years]

    ax1 = fig.add_subplot(311)

    ax1.plot(years, amb.groupby("YEAR").NPP.sum(), "b-", label="Amb")

    obs_npp = np.array([1010.363435,1052.484494,930.9501267,1132.113908,\
                        1204.210228,1020.08473,662.2080009,953.6588582,\
                        1038.468081,909.183305,1220.6568,965.8984])
    ax1.plot(years, obs_npp, "ro", label="Obs")
    ax1.legend(numpoints=1, loc="best")
    ax1.set_ylabel("NPP (g m$^{2}$ yr$^{-1}$)")
    plt.setp(ax1.get_xticklabels(), visible=False)
    ax1.set_ylim(0., 1800)
    ax1.set_xlim(1995, 2008)

    ax2 = fig.add_subplot(312)
    ax2.plot(years, amb.groupby("YEAR").LAI.max(), "b-", label="Amb")
    #ax2.legend(numpoints=1, loc="best")
    ax2.set_ylabel("LAI (m$^{2}$ m$^{-2}$)")
    #ax2.set_xlabel("Year")
    ax2.set_ylim(0., 5)
    plt.setp(ax2.get_xticklabels(), visible=False)

    ax3 = fig.add_subplot(313)
    ax3.plot(years, amb.groupby("YEAR").T.sum(), "b-", label="Amb")
    ax3.set_ylabel("Transpiration (mm yr$^{-1}$)")
    ax3.set_xlabel("Year")
    ax3.set_ylim(0., 800)
    plt.show()
    #fig.savefig("example_plot.png", dpi=100)


def date_converter(*args):
    return dt.datetime.strptime(str(int(float(args[0]))) + " " +\
                                str(int(float(args[1]))), '%Y %j')

def read_data(fname):
    df = pd.read_csv(fname, parse_dates=[[0,1]], index_col=0, sep=",",
                     keep_date_col=True, date_parser=date_converter,
                     na_values=["-999.9"], skiprows=3)
    return df




if __name__ == "__main__":

    # Ambient
    experiment_id = "NCEAS"
    site = "DUKE"
    treatment="amb"

    main(experiment_id, site, treatment)