import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import cm

exp = np.exp

def Gaussian2D(X, Y, a=1,):
    """
    This function takes meshgrids of X- and Y-values and outputs an array of 
    Z-values in the shape of the Gaussian distribution:
    
    exp(-a(X^2 + Y^2)).
    """
    
    return exp(-a*(X**2 + Y**2))


def plotGaussianSurface(
    X, Y, Z,
    colormap=cm.cividis,  
    title="", 
    filetype="png", 
    saveflag=False, 
    resolution=200, 
    dpi=300,
    numticks_xy=7,
    numticks_z=2,
    numticks_xy_minor=25,
    numticks_z_minor=5,
):
    """
    Plots a 3D-surface of a 2D-Gaussian function.
    
    X, Y: Meshgrids of x- and y-values for the Gaussian.
    
    Z: The output of the Gaussian function.
    
    colormap: The colormap for the surface, mapped to the Z-values of the 
        graph.
    
    title: Title of the graph.
    
    filetype: Three-letter extension of the image filetype for saving the 
        graph. Default is png.
    
    saveflag: Boolean flag to check if the graph should be saved to a file.
        Set to True if you want to save the graph to a file. Default is False.
    
    resolution: Number of pixels to render along the x- and y-axes.
        Default is 200, which gives a 200x200 grid.
    
    dpi: Dots-per-inch of the image. Default is 300.
    """
    
    plt.ioff()
    
    # Set up kwargs:
    limit = int(np.ceil(np.amax(X)))
    zmin = int(np.floor(np.amin(Z)))
    zmax = int(np.ceil(np.amax(Z)))
    norm = mpl.colors.Normalize(vmin=zmin, vmax=zmax)
    aspect = (limit*2 + 1, limit*2 + 1, zmax)
    
    xy_major_params = dict(
        direction = "in",
    )
    xy_minor_params = dict(
        direction = "in",
        which = "minor",
    )
    xy_major_ticks = dict(
        ticks = np.linspace(-limit, limit, numticks_xy, endpoint=True,),
    )
    xy_minor_ticks = dict(
        ticks = np.linspace(-limit, limit, numticks_xy_minor, endpoint=True,), 
        minor = True,
    )
    z_major_params = dict(
        which = "major", 
        labelbottom = True, 
        labeltop = False,
    )
    z_minor_params = dict(
        which = "minor",
    )
    z_major_ticks = dict(
        ticks = np.linspace(0, zmax, numticks_z, endpoint=True,),
    )
    z_minor_ticks = dict(
        ticks = np.linspace(0, zmax, numticks_z_minor, endpoint=True,), 
        minor = True,
    )
    
    tick_labelsize = 7
    
    
    fig = plt.figure(dpi=dpi)
    ax = fig.add_subplot(1, 1, 1, projection ='3d')
    
    # Plot the surface
    surf = ax.plot_surface(
        X, Y, Z, 
        cmap = colormap, 
        linewidth=0, 
        antialiased=False, 
        vmin = zmin, vmax = zmax, 
        rcount = resolution, 
        ccount = resolution,
        norm = norm,
    )
    
    # Customize the z axis.
    ax.set_zlim(zmin, zmax)
    # ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter('{x:.1f}')
    
    
    ax.set_title(
        title, 
        fontdict = dict(verticalalignment = "bottom"),
    )
    
    ax.set_box_aspect(aspect)
    # ax.proj_type("ortho")
    ax.set_facecolor('none')
    
    # Set tick parameters
    ax.xaxis.set_tick_params(**xy_major_params)
    ax.xaxis.set_tick_params(**xy_minor_params)
    ax.yaxis.set_tick_params(**xy_major_params)
    ax.yaxis.set_tick_params(**xy_minor_params)
    ax.zaxis.set_tick_params(**z_major_params)
    ax.zaxis.set_tick_params(**z_minor_params)
    ax.set_xticks(**xy_major_ticks)
    ax.set_xticks(**xy_minor_ticks)
    ax.set_yticks(**xy_major_ticks)
    ax.set_yticks(**xy_minor_ticks)
    ax.set_zticks(**z_major_ticks)
    ax.set_zticks(**z_minor_ticks)
    ax.tick_params(labelsize=tick_labelsize)
    
    cbar = fig.colorbar(
        surf, 
        ax=ax, 
        orientation='vertical', 
        shrink=0.5, 
        aspect=12,
        pad = 0.10,
    )
    
    cbar.ax.tick_params(labelsize=tick_labelsize)
    
    if saveflag:
        savePlot(colormap, filetype)
    
    plt.tight_layout()
    
    plt.show()

x = y = np.linspace(-3, 3, 2**10, endpoint=True)
X, Y = np.meshgrid(x, y)

plotargs = dict(
    saveflag = False,
    dpi = 400,
    resolution = 200,
    numticks_xy=7, 
    numticks_xy_minor=25, 
    numticks_z=2, 
    numticks_z_minor=5,
)

plotGaussianSurface(X, Y, Gaussian2D(X, Y), **plotargs,)