import matplotlib.pyplot as plt
import time, sys, math
import numpy as np

def stream(string, variables) :
    sys.stdout.write(f'\r{string}' % variables)
    
def num_params(model) :
    parameters = filter(lambda p: p.requires_grad, model.parameters())
    parameters = sum([np.prod(p.size()) for p in parameters]) / 1_000_000
    print('Trainable Parameters: %.3f million' % parameters)

def time_since(started) :
    elapsed = time.time() - started
    m = int(elapsed // 60)
    s = int(elapsed % 60)
    if m >= 60 :
        h = int(m // 60)
        m = m % 60
        return f'{h}h {m}m {s}s'
    else :
        return f'{m}m {s}s'

def plot(array) : 
    fig = plt.figure(figsize=(30, 5))
    ax = fig.add_subplot(111)
    ax.xaxis.label.set_color('grey')
    ax.yaxis.label.set_color('grey')
    ax.xaxis.label.set_fontsize(23)
    ax.yaxis.label.set_fontsize(23)
    ax.tick_params(axis='x', colors='grey', labelsize=23)
    ax.tick_params(axis='y', colors='grey', labelsize=23)
    plt.plot(array)

def plot_spec(M) :
    M = np.flip(M, axis=0)
    plt.figure(figsize=(18,4))
    plt.imshow(M, interpolation='nearest', aspect='auto')
    plt.show()