Filename: display_methods.py
Author: Gene Callahan
A collection of convenience functions
for using matplotlib.

Modules
		io logging matplotlib numpy pandas matplotlib.pyplot seaborn sys

Classes
		builtins.object BarGraph LineGraph ScatterPlot   class BarGraph(builtins.object)     BarGraph(title, varieties, data_points, anim=False, data_func=None, is_headless=False, legend_pos=4)       Methods defined here: __init__(self, title, varieties, data_points, anim=False, data_func=None, is_headless=False, legend_pos=4) Initialize self.  See help(type(self)) for accurate signature. create_bars(self, x, ax, varieties) draw_graph(self, data_points, varieties) Draw all elements of the graph. show(self) Display the barGraph. update_plot(self, i) This is our animation function. For line graphs, redraw the whole thing. Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined)   class LineGraph(builtins.object)     LineGraph(title, varieties, data_points, attrs, anim=False, data_func=None, is_headless=False)   We create a class here to save state for animation. Display a simple matplotlib line graph. The data is a dictionary with the label as the key and a list of numbers as the thing to graph. data_points is the length of the x-axis.     Methods defined here: __init__(self, title, varieties, data_points, attrs, anim=False, data_func=None, is_headless=False) Initialize self.  See help(type(self)) for accurate signature. create_lines(self, x, varieties) Draw just the data portion. draw_graph(self, data_points, varieties, attrs) Draw all elements of the graph. show(self) Display the plot. update_plot(self, i) This is our animation function. For line graphs, redraw the whole thing. Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined)   class ScatterPlot(builtins.object)     ScatterPlot(title, varieties, width, height, attrs, anim=True, data_func=None, is_headless=False)   We are going to use a class here to save state for our animation     Methods defined here: __init__(self, title, varieties, width, height, attrs, anim=True, data_func=None, is_headless=False) Setup a scatter plot. `varieties` contains the different types of entities to show in the plot, which will get assigned different colors and perhaps markers. create_scats(self, varieties) draw_graph(self, title, width, height, varieties, attrs) get_arrays(self, varieties, var) show(self) Display the plot. update_plot(self, i) This is our animation function. Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined)

Functions
		are_graphics_present() draw_graph(graph, title, hierarchy=False, root=None) Drawing networkx graphs. graph is the graph to draw. hierarchy is whether we should draw it as a tree. Network drawings not yet implemented in V3. expects_plt(fn) Should be used to decorate any function that uses matplotlib's pyplot. get_color(var, i) get_marker(var, i) hierarchy_pos(graph, root, width=1.0, vert_gap=0.2, vert_loc=0.0, xcenter=0.5, pos=None, parent=None) This is an attempt to get a tree graph from networkx. If there is a cycle that is reachable from root, then this will infinitely recurse. graph: the graph root: the root node of current branch width: horizontal space allocated for this branch         - avoids overlap with other branches vert_gap: gap between levels of hierarchy vert_loc: vertical location of root xcenter: horizontal location of root pos: a dict saying where all nodes go if they have been assigned parent: parent of this branch.

Data
		API = 'api' BLACK = 'black' BLUE = 'blue' CIRCLE = 'circle' CYAN = 'cyan' DARKRED = 'darkred' DEBUG = <lib.utils.Debug object> DECEASED = 'deceased' DEFAULT_MARKER = 'default' DEF_SIZE = 40 GRAY = 'gray' GREEN = 'green' LIMEGREEN = 'limegreen' MAGENTA = 'magenta' NAVY = 'navy' NUM_COLORS = 18 ORANGE = 'orange' ORANGERED = 'orangered' PERSON = 'person' PURPLE = 'purple' RED = 'red' SPRINGGREEN = 'springgreen' SQUARE = 'square' TAN = 'tan' TERMINAL = 'terminal' TOMATO = 'tomato' TREE = 'tree' WHITE = 'white' X = 0 Y = 1 YELLOW = 'yellow' anim_func = None colors = ['red', 'blue', 'green', 'navy', 'springgreen', 'orange', 'limegreen', 'yellow', 'cyan', 'tan', 'orangered', 'tomato', 'darkred', 'magenta', 'black', 'gray', 'purple', 'white'] colors_dict = {'black': 'black', 'blue': 'blue', 'cyan': 'cyan', 'darkred': 'darkred', 'gray': 'gray', 'green': 'green', 'limegreen': 'limegreen', 'magenta': 'magenta', 'navy': 'navy', 'orange': 'orange', ...} graphics_present = False markers = {'circle': 'o', 'deceased': 'x', 'default': '8', 'person': 'o', 'square': 's', 'tree': '^'} no_graphics_msg = "Cannot load backend 'TkAgg' which requires the '...ive framework, as 'headless' is currently running" seaborn_markers = ['8', 's', '^', 'o', 'x'] user_type = 'test'