import numpy as np import matplotlib.pyplot as plt from src.cocktails.utilities.ingredients_utilities import ingredient_list, extract_ingredients, ingredients_per_type color_codes = dict(ancestral='#000000', spirit_forward='#2320D2', duo='#6E20D2', champagne_cocktail='#25FFCA', complex_highball='#068F25', simple_highball='#25FF57', collins='#77FF96', julep='#25B8FF', simple_sour='#FBD756', complex_sour='#DCAD07', simple_sour_with_juice='#FF5033', complex_sour_with_juice='#D42306', # simple_sour_with_egg='#FF9C54', # complex_sour_with_egg='#CF5700', # almost_simple_sor='#FF5033', # almost_sor='#D42306', # almost_sor_with_egg='#D42306', other='#9B9B9B' ) def get_subcategories(data): subcategories = np.array(data['subcategory']) sub_categories_list = sorted(set(subcategories)) subcat_count = dict(zip(sub_categories_list, [0] * len(sub_categories_list))) for sc in data['subcategory']: subcat_count[sc] += 1 return subcategories, sub_categories_list, subcat_count def get_ingredient_count(data): ingredient_counts = dict(zip(ingredient_list, [0] * len(ingredient_list))) for ing_str in data['ingredients_str']: ingredients, _ = extract_ingredients(ing_str) for ing in ingredients: ingredient_counts[ing] += 1 return ingredient_counts def compute_eucl_dist(a, b): return np.sqrt(np.sum((a - b)**2)) def recipe_contains(ingredients, stuff): if stuff in ingredient_list: return stuff in ingredients elif stuff == 'juice': return any(['juice' in ing and 'lemon' not in ing and 'lime' not in ing for ing in ingredients]) elif stuff == 'bubbles': return any([ing in ['soda', 'tonic', 'cola', 'sparkling wine', 'ginger beer'] for ing in ingredients]) elif stuff == 'acid': return any([ing in ['lemon juice', 'lime juice'] for ing in ingredients]) elif stuff == 'vermouth': return any([ing in ingredients_per_type['vermouth'] for ing in ingredients]) elif stuff == 'plain sweet': plain_sweet = ingredients_per_type['sweeteners'] return any([ing in plain_sweet for ing in ingredients]) elif stuff == 'sweet': sweet = ingredients_per_type['sweeteners'] + ingredients_per_type['liqueur'] + ['sweet vermouth', 'lillet blanc'] return any([ing in sweet for ing in ingredients]) elif stuff == 'spirit': return any([ing in ingredients_per_type['liquor'] for ing in ingredients]) else: raise ValueError def radar_factory(num_vars, frame='circle'): # from stackoverflow's post? Or matplotlib's blog """ Create a radar chart with `num_vars` axes. This function creates a RadarAxes projection and registers it. Parameters ---------- num_vars : int Number of variables for radar chart. frame : {'circle', 'polygon'} Shape of frame surrounding axes. """ import numpy as np from matplotlib.patches import Circle, RegularPolygon from matplotlib.path import Path from matplotlib.projections.polar import PolarAxes from matplotlib.projections import register_projection from matplotlib.spines import Spine from matplotlib.transforms import Affine2D # calculate evenly-spaced axis angles theta = np.linspace(0, 2*np.pi, num_vars, endpoint=False) class RadarAxes(PolarAxes): name = 'radar' # use 1 line segment to connect specified points RESOLUTION = 1 def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) # rotate plot such that the first axis is at the top self.set_theta_zero_location('N') def fill(self, *args, closed=True, **kwargs): """Override fill so that line is closed by default""" return super().fill(closed=closed, *args, **kwargs) def plot(self, *args, **kwargs): """Override plot so that line is closed by default""" lines = super().plot(*args, **kwargs) for line in lines: self._close_line(line) def _close_line(self, line): x, y = line.get_data() # FIXME: markers at x[0], y[0] get doubled-up if x[0] != x[-1]: x = np.append(x, x[0]) y = np.append(y, y[0]) line.set_data(x, y) def set_varlabels(self, labels): self.set_thetagrids(np.degrees(theta), labels) def _gen_axes_patch(self): # The Axes patch must be centered at (0.5, 0.5) and of radius 0.5 # in axes coordinates. if frame == 'circle': return Circle((0.5, 0.5), 0.5) elif frame == 'polygon': return RegularPolygon((0.5, 0.5), num_vars, radius=.5, edgecolor="k") else: raise ValueError("Unknown value for 'frame': %s" % frame) def _gen_axes_spines(self): if frame == 'circle': return super()._gen_axes_spines() elif frame == 'polygon': # spine_type must be 'left'/'right'/'top'/'bottom'/'circle'. spine = Spine(axes=self, spine_type='circle', path=Path.unit_regular_polygon(num_vars)) # unit_regular_polygon gives a polygon of radius 1 centered at # (0, 0) but we want a polygon of radius 0.5 centered at (0.5, # 0.5) in axes coordinates. spine.set_transform(Affine2D().scale(.5).translate(.5, .5) + self.transAxes) return {'polar': spine} else: raise ValueError("Unknown value for 'frame': %s" % frame) register_projection(RadarAxes) return theta def plot_radar_cocktail(representation, labels_dim, labels_cocktails, save_path=None, to_show=False, to_save=False): assert to_show or to_save, 'either show or save' assert representation.ndim == 2 n_data, dim_rep = representation.shape assert len(labels_cocktails) == n_data assert len(labels_dim) == dim_rep assert n_data <= 5, 'max 5 representation_analysis please' theta = radar_factory(dim_rep, frame='circle') fig, ax = plt.subplots(figsize=(9, 9), subplot_kw=dict(projection='radar')) fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05) colors = ['b', 'r', 'g', 'm', 'y'] # Plot the four cases from the example data on separate axes ax.set_rgrids([0.2, 0.4, 0.6, 0.8]) for d, color in zip(representation, colors): ax.plot(theta, d, color=color) for d, color in zip(representation, colors): ax.fill(theta, d, facecolor=color, alpha=0.25) ax.set_varlabels(labels_dim) # add legend relative to top-left plot legend = ax.legend(labels_cocktails, loc=(0.9, .95), labelspacing=0.1, fontsize='small') if to_save: plt.savefig(save_path, bbox_artists=(legend,), dpi=200) else: plt.show()