import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap, LinearSegmentedColormap


def plotK_imshow(kk, pdir, logn, xlabel, minfact, maxfact):
    kk = np.rot90(kk)

    if logn == True:
        # kk=np.log(kk)
        vmin, vmax = minfact, maxfact
        # print(vmax)
        colormap = "viridis"
        plt.imshow(kk, vmin=vmin, vmax=vmax)  # ,cmap='binary'
    else:
        # colormap='binary'
        plt.imshow(kk, cmap="binary")  # ,cmap='binary'

    plt.colorbar()
    # cbar.set_label(xlabel)
    plt.title(xlabel)
    plt.tight_layout()
    plt.savefig(pdir + ".png", dpi=1200)
    plt.close()

    return


def plot_hist(k, pdir, logn, xlabel, minfact, maxfact, llg):

    if logn == True:
        vmin, vmax = minfact, maxfact
        # plt.hist(k.reshape(-1),bins=100,range=(vmin,vmax),histtype='step',normed=1,label=llg)#,range=(vmin,vmax))
        plt.hist(
            k.reshape(-1), bins=100, histtype="step", normed=1, label=llg
        )  # ,range=(vmin,vmax))
    else:
        plt.hist(k.reshape(-1))
    plt.xlabel(xlabel)
    plt.ylabel("Counts")

    return


ps = np.linspace(0, 100, 50)
rdir = "./testlc8/"
rdir = "./lc0/"
plt.figure(1)
for j in range(1):
    for i in range(0, 50, 1):

        log = True

        label = r"$\log_{10}(vx/<vx>)$"

        folder = j * 50 + i

        V = np.load(rdir + str(folder) + "/V.npy")[0][:, :, 0]
        perco = np.load(
            rdir + str(folder) + "/ConnectivityMetrics/1024.npy", allow_pickle=True
        ).item()["spanning"][0, 0, 0]
        V = np.log10(np.abs(V))  # /np.mean(np.abs(V)))
        leg = "p = " + str(ps[i])[:4] + "% (" + str(perco) + ")"
        plot_hist(V, rdir + str(folder) + "/HisTabsV", log, label, -0.8, 0.5, leg)
        plotK_imshow(V[512:1536, 512:1536], rdir + str(i) + "/V", log, label, -4, 1)
        plt.legend(loc="upper left")
        plt.savefig(rdir + str(folder) + "VelHistogramB.png")
        plt.close()
"""

label=r'$\log_{10}(|v_x|/<|v_x|>)$'
V=np.load(rdir+str(i)+'/V.npy')[0][:,:,0]
V=np.log10(np.abs(V)/np.mean(np.abs(V)))
plot_hist(V,rdir+str(i)+'/HisTabsVx',log,label,-4,1.5)
plotK_imshow(V[1024:2048,512:1024],rdir+str(i)+'/Vx',log,label,0,2)

label=r'$\log_{10}(|v_y|/<|v_y|>)$'
V=np.load(rdir+str(i)+'/V.npy')[1][:,:,0]
V=np.log10(np.abs(V)/np.mean(np.abs(V)))
plot_hist(V,rdir+str(i)+'/HisTabsVy',log,label,-5,1.5)
plotK_imshow(V[1024:2048,512:1024],rdir+str(i)+'/Vy',log,label,0,1)
#plot_hist(k,rdir+'Res/'+resname,log)



"""