import re, numpy as np, matplotlib.pyplot as plt

# Globals
signal_names=[]		# List of the signals we traced, grabbed from line 1
values=None		# List of np arrays, one array per signal.
x_axis=None		# 0 .002 .004 .006... for the plotting x axis


def plot_signal (signame):
    idx = signal_names.index(signame)
    plt.plot (x_axis, values[idx], label=signame)
    #import pdb; pdb.set_trace()

def plot (filename):
    global signal_names, values, x_axis
    infile = open (filename, "r")
    first = True
    inp_ls=[]; bp_ls=[]; der2_ls=[]; der2sq_ls=[]
    ravg_ls=[]; thresh2_ls=[]; QRS_ls=[]
    for line in infile:
        fields = re.split (r"\s+", line.strip())
        if (first):
            # The top line has the names of the signals we've dumped, such as
            # "input filtered squared".
            first = False
            signal_names = fields
            # For three signal names, values will be a list of 3 empty lists.
            # We'll then populate those lists for each line we read.
            values = [ [] for f in fields]
            continue

        # All lines other than the top one have a whitespace-separated list
        # of signals, such as "12  5  2". Three values would mean we have three
        # signals; append each signal to one of our three lists.
        numbs = [int(f) for f in fields]
        assert len(numbs) == len(values), "Incorrect number of numbers"
        for idx,n in enumerate(numbs):
            values[idx].append(n)

    # Convert the lists to arrays. Now 'values' is a list of numpy arrays.
    for idx in range(len(values)):
        values[idx] = np.array(values[idx])

    n_pts = values[0].size
    x_axis = np.arange (n_pts,dtype=float) * .002

    print ("plotting...")
    plot_signal ("in")
    plot_signal ("filt")
    plt.legend (loc="upper right")
    plt.show()

plot ("run.out13")