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utils_mpl.py
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utils_mpl.py
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from matplotlib.widgets import RectangleSelector
from matplotlib.widgets import LassoSelector
import matplotlib.colors as clr
from matplotlib.path import Path
from matplotlib.patches import Rectangle, Ellipse,Polygon
import numpy as np
from matplotlib.ticker import MaxNLocator
class Highlighter(object):
def __init__(self, ax_umap, ax_year, ax_mesh, dfpapers, colors='c', method='lasso', add_text=False,index_list=None,include_nlp=False):
self.ax_umap = ax_umap
self.ax_year = ax_year
self.ax_mesh = ax_mesh
self.canvas_umap = ax_umap.figure.canvas
self.canvas_year = ax_year.figure.canvas
self.canvas_mesh = ax_mesh.figure.canvas
self.x, self.y = dfpapers['umap-x'], dfpapers['umap-y']
self.add_text = add_text
self.df_papers = dfpapers
self.df_selected = None
#self.selected_text = None
self.full_index = dfpapers.index.values
highlight_color = colors
highlight_size = 20
self.object_index = None
self.mask = np.zeros(self.x.shape[0], dtype=bool)
self.scaled_rgb = (65 / 256., 91 / 256., 169 / 256.)
self.selection_method = method
self.x0 = None
self.y0 = None
self.x1 = None
self.y1 = None
self.entities_dict = {}
self._highlight = ax_umap.scatter(
[],[], marker="o", lw=0, s=highlight_size, c=highlight_color
)
self.include_nlp = include_nlp
if include_nlp:
self.nlp = spacy.load('en_ner_bionlp13cg_md')
self.nlp.add_pipe(self.nlp.create_pipe('sentencizer'))
#if self.selected_text != None:
# self.selected_text.remove()
if self.add_text:
self.selected_text = self.ax_umap.text(
0.03,
0.97,
"%3.2f (%i events)" % (0, 0),
ha="left",
va="top",
transform=self.ax_umap.transAxes,
color="k",
fontname="Helvetica",
)
self.name_to_selector = {"lasso": LassoSelector}
selector = self.name_to_selector[method.lower()]
onselect_dict = {
LassoSelector: self._onselect_lasso,
}
self.lasso = selector(self.ax_umap, onselect_dict[selector])
# def remove_text(self):
def disconnect(self):
self.canvas_umap.mpl_disconnect(self.lasso)
def _draw_points(self):
self.object_index = self.full_index[self.mask]
self.nevents = len(self.mask)
self.nselected = np.sum(self.mask)
if self.add_text:
self.selected_text.remove()
if self.add_text:
self.selected_text = self.ax_umap.text(
0.03,
0.97,
"%3.2f (%i events)"
% (self.nselected * 100. / self.nevents, self.nselected),
ha="left",
va="top",
transform=self.ax_umap.transAxes,
color="k",
fontname="Helvetica",
)
xy = np.column_stack([self.x[self.mask], self.y[self.mask]])
self._highlight.set_offsets(xy)
self.canvas_umap.draw()
def _onselect_lasso(self, verts):
self.verts = np.array(verts)
p = Path(self.verts)
pix = np.array([self.x, self.y]).T
self.mask = p.contains_points(pix, radius=0)
self._draw_points()
self.df_selected = self.df_papers[self.mask]
print("%s selected" % self.df_selected.shape[0])
if self.df_selected.shape[0] == 0:
self.entities_dict = {}
self.ax_mesh.clear()
self.ax_year.clear()
mterms = []
for idx in self.df_selected.index:
yp = self.df_selected.loc[idx]['pubdate']
mt = self.df_selected.loc[idx]['mesh_terms']
t = self.df_selected.loc[idx]['title']
#sdoc = self.nlp(self.df_selected.loc[idx]['abstract'])
#sen = list(sdoc.sents)
mterms.extend(sorted([mti.split(":")[-1] for mti in mt.split(";")]))
print("(%s) %s" % (yp,t))
doci = self.df_selected.loc[idx]['title'] + self.df_selected.loc[idx]['abstract']
if self.include_nlp:
sdoc = nlp(doci)
#for si in sdoc.ents:
self.entities_dict[idx] = sdoc.ents
#print(" Mesh:",", ".join(mterms))
# print(" ".join(item.split()[:100]))
self.df_selected.to_csv("tmp_selected.csv")
self.mesh_counts = Counter(mterms)
self.mesh_counts_top = self.mesh_counts.most_common(50)
dfcounts = pd.DataFrame.from_dict(dict(self.mesh_counts_top), orient='index')
dfcounts.sort_values(0,inplace=True)
if dfcounts.shape[0]!=0:
dfcounts.plot(kind='barh',ax=self.ax_mesh,fontsize=6,legend=False)
xmin = np.min(self.df_selected['pubdate'])
xmax = np.max(self.df_selected['pubdate'])
self.ax_year.hist(self.df_selected['pubdate'],bins=np.arange(xmin,xmax+1)-0.5)
self.ax_year.set_xlim([xmin,xmax])
self.ax_year.xaxis.set_major_locator(MaxNLocator(integer=True))
for label in self.ax_year.get_xticklabels():
label.set_rotation(45)
label.set_fontsize(6)
label.set_ha('right')
self.canvas_year.draw()
self.canvas_mesh.draw()