import numpy as np
import itertools as it
from PIL import Image
from colour import Color
from random import random
import string

from constants import *

def hash_args(args):
    args = map(lambda arg : arg.__name__ if type(arg) == type(hash_args) else arg, args)
    return str(hash(str(args))%1000) if args else ""

def random_color():
    color = Color()
    color.set_rgb([1 - 0.5 * random() for x in range(3)])
    return color

def to_cammel_case(name):
    parts = name.split("_")
    parts = [
        filter(
            lambda c : c not in string.punctuation + string.whitespace, part
        ).capitalize()
        for part in parts
    ]
    return "".join(parts)

def drag_pixels(frames):
    curr = frames[0]
    new_frames = []
    for frame in frames:
        curr += (curr == 0) * np.array(frame)
        new_frames.append(np.array(curr))
    return new_frames

def invert_image(image):
    arr = np.array(image)
    arr = (255 * np.ones(arr.shape)).astype(arr.dtype) - arr
    return Image.fromarray(arr)

def make_even(iterable_1, iterable_2):
    list_1, list_2 = list(iterable_1), list(iterable_2)
    length = max(len(list_1), len(list_2))
    return (
        [list_1[(n * len(list_1)) / length] for n in xrange(length)],
        [list_2[(n * len(list_2)) / length] for n in xrange(length)]
    )

def make_even_by_cycling(iterable_1, iterable_2):
    length = max(len(iterable_1), len(iterable_2))
    cycle1 = it.cycle(iterable_1)
    cycle2 = it.cycle(iterable_2)
    return (
        [cycle1.next() for x in range(length)],
        [cycle2.next() for x in range(length)]
    )

def sigmoid(x):
    return 1.0/(1 + np.exp(-x))

### Alpha Functions ###

def high_inflection_0_to_1(t, inflection = 10.0):
    error = sigmoid(-inflection / 2)
    return (sigmoid(inflection*(t - 0.5)) - error) / (1 - 2*error)

def there_and_back(t, inflection = 10.0):
    new_t = 2*t if t < 0.5 else 2*(1 - t)
    return high_inflection_0_to_1(new_t, inflection)

def not_quite_there(t, proportion = 0.7):
    return proportion*high_inflection_0_to_1(t)

def wiggle(t, wiggles = 2):
    return there_and_back(t) * np.sin(wiggles*np.pi*t)

### Functional Functions ###

def composition(func_list):
    """
    func_list should contain elements of the form (f, args)
    """
    return reduce(
        lambda (f1, args1), (f2, args2) : (lambda x : f1(f2(x, *args2), *args1)), 
        func_list,
        lambda x : x
    )

def remove_nones(sequence):
    return filter(lambda x : x, sequence)

#Matrix operations
def rotation_matrix(angle, axis):
    """
    Rotation in R^3 about a specified axess of rotation.
    """
    about_z = rotation_about_z(angle)
    z_to_axis = z_to_vector(axis)
    axis_to_z = np.linalg.inv(z_to_axis)
    return reduce(np.dot, [z_to_axis, about_z, axis_to_z])

def rotation_about_z(angle):
    return [
        [np.cos(angle), -np.sin(angle), 0],
        [np.sin(angle),  np.cos(angle), 0],
        [0, 0, 1]
    ]

def z_to_vector(vector):
    """
    Returns some matrix in SO(3) which takes the z-axis to the 
    (normalized) vector provided as an argument
    """
    norm = np.linalg.norm(vector)
    if norm == 0:
        return np.identity(3)
    v = np.array(vector) / norm
    phi = np.arccos(v[2])
    if any(v[:2]):
        #projection of vector to {x^2 + y^2 = 1}
        axis_proj = v[:2] / np.linalg.norm(v[:2])
        theta = np.arccos(axis_proj[0])
        if axis_proj[1] < 0:
            theta = -theta
    else:
        theta = 0
    phi_down = np.array([
        [np.cos(phi), 0, np.sin(phi)],
        [0, 1, 0],
        [-np.sin(phi), 0, np.cos(phi)]
    ])
    return np.dot(rotation_about_z(theta), phi_down)

def rotate_vector(vector, angle, axis):
    return np.dot(rotation_matrix(angle, axis), vector)

def angle_between(v1, v2):
    return np.arccos(np.dot(
        v1 / np.linalg.norm(v1), 
        v2 / np.linalg.norm(v2)
    ))