ipython startup (deprecated)

startup.py

# coding: utf-8
"""
This is the ipython startup script that I used to use in university.
(but not anymore)
Place it in  ~/.ipython/profile_default/startup/startup.py for it to work
"""
import numpy as np
import math
import matplotlib.pyplot as plt
import matplotlib
import itertools as itr


def pairwise(iterable):
    "s -> (s0,s1), (s1,s2), (s2, s3), ..."
    a, b = itr.tee(iterable)
    next(b, None)
    return itr.izip(a, b)

def homogeneous(arr):
    """
    Create 4xN homogeneous representation matrix from 3xN matrix.
    Do NOT pass Nx3 matrix.
    """
    arr = np.asarray(arr)
    arr = np.reshape(arr, (3, -1))
    return np.vstack((arr, np.ones((1, arr.shape[1]))))

def unhomogeneous(arr):
    """
    From 4xN homogeneous, create 3xN normal representation.
    Will NOT warn even if 4th element is non-one.
    """
    arr = np.asarray(arr)
    arr = np.reshape(arr, (4,-1))
    return arr[0:3, :]


def hide_spines():
    """
    Hides the top and rightmost axis spines from view for all active
    figures and their respective axes.
    Copyright Stackoverflow http://stackoverflow.com/questions/3439344/setting-spines-in-matplotlibrc
    Modified 2015/1/24 by Yuta Koreeda
    """
    # Retrieve a list of all current figures.
    figures = [x for x in matplotlib._pylab_helpers.Gcf.get_all_fig_managers()]
    for figure in figures:
        # Get all Axis instances related to the figure.
        for ax in figure.canvas.figure.get_axes():
            # Disable spines.
            ax.spines['right'].set_color('none')
            ax.spines['top'].set_color('none')
            # Disable ticks.
            ax.xaxis.set_ticks_position('bottom')
            ax.yaxis.set_ticks_position('left')
            # Change spine position
            ax.spines['bottom'].set_position('zero')
            ax.spines['bottom'].set_smart_bounds(False)
            ax.spines['left'].set_smart_bounds(False)

def boxplot_kikai(x, vert_=True, positions_=None, widths_=None, usermedians_=None, conf_intervals_=None, showmeans_=False, labels_=None):
    """
    Draw a boxplot in Kikai-ka style
    Whisker shows min-max.
    Based on matplotlib.pyplot.boxplot
    """
    bp = plt.boxplot(x,notch=False, sym='', vert=vert_, whis=200, positions=positions_, widths=widths_, patch_artist=True, bootstrap=None, usermedians=usermedians_, conf_intervals=conf_intervals_, meanline=True, showmeans=showmeans_, showcaps=True, showbox=True, showfliers=False, boxprops=dict(linewidth=1.5), labels=labels_, flierprops=None)
    for med_artist in bp['medians']:
        plt.setp(med_artist, color='black', linewidth=1.5, solid_capstyle="projecting")
    for caps_artist in bp['caps']:
        plt.setp(caps_artist, color='black',linewidth=1.5)
    for whisk_artist in bp['whiskers']:
       plt.setp(whisk_artist,color='black', linestyle='-', linewidth=1.5, solid_capstyle="projecting")
    return bp

def freedmanDiaconisRule(x):
    """
    Calculate appropriate number of bins for histogram using Freedman-Diaconis' Rule
    """
    iqr = np.subtract(*np.percentile(x, [75, 25]))
    h = 2 * iqr / math.pow(len(x), 1.0/ 3.0)
    return math.ceil((np.max(x) - np.min(x)) / h)

def roundToSignificant(val, dig):
    assert dig >=1, "Significant digits must at least 1 digit"
    if val != 0:
        return round(val, -int(math.floor(math.log10(abs(val))))+ (dig - 1))
    else:
        itms = list("0.") + ["0" for i in range(dig - 1)]
        return "".join(itms)

    
def boxplotWithValues(arr_of_arr, significant_digits=2):
    """
    Draw boxplot with value annotations
    Whiskers show min-max
    """
    plt.boxplot(arr_of_arr, showmeans=True, whis=200)
    medians = np.median(arr_of_arr, axis=1)
    means = np.mean(arr_of_arr, axis=1)
    for i in range(len(arr_of_arr)):
        plt.annotate(str(roundToSignificant(medians[i], significant_digits)), xy=(i + 0.9, medians[i]), horizontalalignment='right', verticalalignment='center')
        plt.annotate(str(roundToSignificant(means[i], significant_digits)), xy=(i + 0.9, means[i]), horizontalalignment='right', verticalalignment='center')

def pause():
    """
    Let matplotlib draw graph.
    """
    plt.pause(1.e-6)

def toMillisec(hour, minute, second):
    return ((hour * 60 + minute) * 60 + second) * 1000

def in2px(inches, fig=None):
    import matplotlib.pyplot as plt
    if fig is None:
        fig = plt.gcf()
    return inches * fig.get_dpi()

def pt2in(point): return point/72.0

def pt2px(point, fig=None):
    return in2px(inches(point), fig)

def mm2inch(millimeters):
    return 0.0393700787 * millimeters

def inch2mm(inches):
    return 25.4 * inches