# Path: neurotools/plotting.py
# PILIMAGEUSE = check_dependency('PIL')
# def get_display(display):
# def progress_bar(progress):
# def pylab_params(fig_width_pt=246.0,
#                 ratio=(numpy.sqrt(5)-1.0)/2.0,# Aesthetic golden mean ratio by default
#                 text_fontsize=10, tick_labelsize=8, useTex=False):
# def set_axis_limits(subplot, xmin, xmax, ymin, ymax):
# def set_labels(subplot, xlabel, ylabel):
# def set_pylab_params(fig_width_pt=246.0,
#                     ratio=(numpy.sqrt(5)-1.0)/2.0,# Aesthetic golden mean ratio by default
#                     text_fontsize=10, tick_labelsize=8, useTex=False):
# def save_2D_image(mat, filename):
# def save_2D_movie(frame_list, filename, frame_duration):
#     def __init__(self, nrows, ncolumns, title="", xlabel=None, ylabel=None,
#                  scaling=('linear','linear')):
#     def finalise(self):
#     def save(self, filename):
#     def next_panel(self):
#     def panel(self, i):
#     def set_frame(self, ax, boollist, linewidth=2):
# class SimpleMultiplot(object):


import matplotlib
import unittest
import pylab
import os
        import time
        import numpy
        import numpy
from neurotools import plotting
Unit tests for the neurotools.plotting module
"""
matplotlib.use('Agg')




class PylabParamsTest(unittest.TestCase):

    def runTest(self):

        # define arbitrary values
        fig_width_pt =  123.4
        ratio = 0.1234
        text_fontsize = 10 
        tick_labelsize = 8
        useTex = False

        inches_per_pt = 1.0/72.27               # Convert pt to inch
        fig_width = fig_width_pt*inches_per_pt  # width in inches
        fig_height = fig_width*ratio            # height in inches

        testDict = {
            'axes.labelsize'  : text_fontsize,
            'font.size'       : text_fontsize,
            'xtick.labelsize' : tick_labelsize,
            'ytick.labelsize' : tick_labelsize,
            'text.usetex'     : useTex,
            'figure.figsize'  : [fig_width, fig_height]}


# Path: neurotools/plotting.py
# PILIMAGEUSE = check_dependency('PIL')
# def get_display(display):
# def progress_bar(progress):
# def pylab_params(fig_width_pt=246.0,
#                 ratio=(numpy.sqrt(5)-1.0)/2.0,# Aesthetic golden mean ratio by default
#                 text_fontsize=10, tick_labelsize=8, useTex=False):
# def set_axis_limits(subplot, xmin, xmax, ymin, ymax):
# def set_labels(subplot, xlabel, ylabel):
# def set_pylab_params(fig_width_pt=246.0,
#                     ratio=(numpy.sqrt(5)-1.0)/2.0,# Aesthetic golden mean ratio by default
#                     text_fontsize=10, tick_labelsize=8, useTex=False):
# def save_2D_image(mat, filename):
# def save_2D_movie(frame_list, filename, frame_duration):
#     def __init__(self, nrows, ncolumns, title="", xlabel=None, ylabel=None,
#                  scaling=('linear','linear')):
#     def finalise(self):
#     def save(self, filename):
#     def next_panel(self):
#     def panel(self, i):
#     def set_frame(self, ax, boollist, linewidth=2):
# class SimpleMultiplot(object):


# Path: test/test_plotting.py
import matplotlib
import unittest
import pylab
import os
        import time
        import numpy
        import numpy
from neurotools import plotting

Unit tests for the neurotools.plotting module
"""
matplotlib.use('Agg')




class PylabParamsTest(unittest.TestCase):

    def runTest(self):

        # define arbitrary values
        fig_width_pt =  123.4
        ratio = 0.1234
        text_fontsize = 10 
        tick_labelsize = 8
        useTex = False

        inches_per_pt = 1.0/72.27               # Convert pt to inch
        fig_width = fig_width_pt*inches_per_pt  # width in inches
        fig_height = fig_width*ratio            # height in inches

        testDict = {
            'axes.labelsize'  : text_fontsize,
            'font.size'       : text_fontsize,
            'xtick.labelsize' : tick_labelsize,
            'ytick.labelsize' : tick_labelsize,
            'text.usetex'     : useTex,
            'figure.figsize'  : [fig_width, fig_height]}


        plotting.set_pylab_params(fig_width_pt=fig_width_pt, ratio=ratio,