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"""
Make X and Z Cuts:
- Kinetic Energy Density
- Internal Energy Density
- Total Energy
"""

import matplotlib as mpl
from pymses import RamsesOutput
from pymses.filters import CellsToPoints
from pymses.analysis.visualization import Camera, ScalarOperator, SliceMap
import matplotlib.pyplot as plt
import numpy as np
import sys


"""
Main Routine. Define Cameras. Take Slices. Plot.
"""
def main():

    # Defaults
    iout = 1

    # Parse Arguments
    if len(sys.argv) == 2:
        iout = int(sys.argv[1])

    # Give Feedback
    print "Creating Cuts for Output %i." % iout
    print ""

    # Link AMR Data
    output = RamsesOutput(".", iout)
    source = output.amr_source(["rho", "vel", "P"])

    # Define Cameras
    camZ = Camera(center=[0.5, 0.5, 0.5], line_of_sight_axis='z',
        region_size=[1., 1.], up_vector='y', map_max_size=512, log_sensitive=True)
    camX = Camera(center=[0.5, 0.5, 0.5], line_of_sight_axis='x',
        region_size=[1., 1.], up_vector='y', map_max_size=512, log_sensitive=True)

    # Functions to Get Data
    func_rho = lambda dset: dset["rho"]
    func_vel = lambda dset: np.sqrt(np.sum(dset["vel"]**2, axis=1))
    # func_vel = lambda dset: dset["vel"][:,0]
    func_pre = lambda dset: dset["P"]

    # Operator to Get Data
    op_rho = ScalarOperator(func_rho)
    op_vel = ScalarOperator(func_vel)
    op_pre = ScalarOperator(func_pre)

    # Compute Slice Maps
    rhoZ = SliceMap(source, camZ, op_rho, z=0.0)
    rhoX = SliceMap(source, camX, op_rho, z=0.0)
    velZ = SliceMap(source, camZ, op_vel, z=0.0)
    velX = SliceMap(source, camX, op_vel, z=0.0)
    preZ = SliceMap(source, camZ, op_pre, z=0.0)
    preX = SliceMap(source, camX, op_pre, z=0.0)

    # Energy
    intZ = ( preZ / rhoZ ) / (1.4-1.)
    intX = ( preX / rhoX ) / (1.4-1.)
    kinZ = velZ * 0.5
    kinX = velX * 0.5
    totZ = (velZ + intZ) * rhoZ
    totX = (velX + intX) * rhoX

    # Log10?
    intZ = np.log10(intZ)
    intX = np.log10(intX)
    kinZ = np.log10(kinZ)
    kinX = np.log10(kinX)
    totZ = np.log10(totZ)
    totX = np.log10(totX)

    # Mark Arrays vs. NaN
    intZ = np.ma.masked_array(intZ, mask=np.isnan(intZ))
    intX = np.ma.masked_array(intX, mask=np.isnan(intX))
    kinZ = np.ma.masked_array(kinZ, mask=np.isnan(kinZ))
    kinX = np.ma.masked_array(kinX, mask=np.isnan(kinX))
    totZ = np.ma.masked_array(totZ, mask=np.isnan(totZ))
    totX = np.ma.masked_array(totX, mask=np.isnan(totX))
    
    # Set Masked Colormap
    # cmap = mpl.cm.hot
    cmap = mpl.cm.jet
    cmap.set_bad([0.5, 0.5, 0.5])

    # Colormaps:
    # http://matplotlib.org/examples/pylab_examples/show_colormaps.html
    # rho_cm = 'hot'
    # vel_cm = 'hot'
    # pre_cm = 'hot'
    int_cm = cmap
    kin_cm = cmap
    tot_cm = cmap

    # Compute Image Extent
    ext = output.info["boxlen"] * np.array([-0.5, 0.5, -0.5, 0.5])

    # Plot Internal Energy Density
    f1 = plt.figure(1)
    plt.imshow(intZ, cmap=int_cm, extent=ext, interpolation='none')
    plt.colorbar()
    plt.grid()
    plt.title('Log10 Internal Energy Density Cut, t=%.2f' % output.info["time"])
    plt.xlabel('X')
    plt.ylabel('Y')

    f2 = plt.figure(2)
    plt.imshow(intX, cmap=int_cm, extent=ext, interpolation='none')
    plt.colorbar()
    plt.grid()
    plt.title('Log10 Interal Energy Density Cut, t=%.2f' % output.info["time"])
    plt.xlabel('Y')
    plt.ylabel('Z')

    # Plot Kinetic Energy Density
    f3 = plt.figure(3)
    plt.imshow(kinZ, cmap=kin_cm, extent=ext, interpolation='none')
    plt.colorbar()
    plt.grid()
    plt.title('Log10 Kinetic Energy Density Cut, t=%.2f' % output.info["time"])
    plt.xlabel('X')
    plt.ylabel('Y')

    f4 = plt.figure(4)
    plt.imshow(kinX, cmap=kin_cm, extent=ext, interpolation='none')
    plt.colorbar()
    plt.grid()
    plt.title('Log10 Kinetic Energy Density Cut, t=%.2f' % output.info["time"])
    plt.xlabel('Y')
    plt.ylabel('Z')

    # Plot Total Energy
    f5 = plt.figure(5)
    plt.imshow(totZ, cmap=tot_cm, extent=ext, interpolation='none')
    plt.colorbar()
    plt.grid()
    plt.title('Log10 Total Energy Cut, t=%.2f' % output.info["time"])
    plt.xlabel('X')
    plt.ylabel('Y')

    f6 = plt.figure(6)
    plt.imshow(totX, cmap=tot_cm, extent=ext, interpolation='none')
    plt.colorbar()
    plt.grid()
    plt.title('Log10 Total Energy Cut, t=%.2f' % output.info["time"])
    plt.xlabel('Y')
    plt.ylabel('Z')

    # plt.close(f1)
    # plt.close(f2)
    # plt.close(f3)
    # plt.close(f4)
    # plt.close(f5)
    # plt.close(f6)
 
    plt.show()


"""
Jump into Main().
"""
if __name__ == "__main__":
    main()