Source code for pyrfume.plotting

import io
import warnings

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import plotly.graph_objs as go
from ipywidgets import Image, Layout, VBox

import pyrfume

    from rdkit import Chem
    from rdkit.Chem import Draw
except ImportError:
        "Parts of rdkit could not be imported; try installing rdkit via conda", UserWarning

[docs]def mpl_embedding( xy, colors=None, alpha=0.25, figsize=(6, 6), s=0.5, cmap="hsv", title=None, ax=None ): if not ax: plt.figure(figsize=figsize) plt.margins(0) ax = plt.gca() ax.scatter( xy[:, 0], xy[:, 1], c=(colors if colors is not None else "k"), # set colors of markers cmap=cmap, # set color map of markers alpha=alpha, # set alpha of markers marker="o", # use smallest available marker (square) s=s, # set marker size. single pixel is 0.5 on retina, # 1.0 otherwise lw=0, # don't use edges edgecolor="", ) # don't use edges # remove all axes and whitespace / borders ax.get_xaxis().set_visible(False) ax.get_yaxis().set_visible(False) ax.set_facecolor("white") if title: ax.set_title(title)
[docs]def plotly_embedding(embedding, features=None, show_features=None, colors=None, colorscale='rainbow'): """ params: embedding: A dataframe wrapped around e.g. a fitted TSNE object, with an index of CIDs features: A dataframe of features, e.g. names, SMILES strings, or physicochemical features, with an index of CIDs """ if features is None: features = pyrfume.load_data("odorants/all-cids-properties.csv", usecols=range(5)) # Only retain those rows corresponding to odorants in the embedding features = features.loc[embedding.index] show_features = show_features or list(features) def format_features(col): return "%s: %s" % (index_name, x.values.split('<br>')) try: index_name = or 'Index' names = ( features.loc[:, show_features] .reset_index() .astype("str") .apply(format_features, axis=1) ) except Exception: names = features.index assert embedding.shape[0] == features.shape[0] # The scatter plot scatter = go.Scatter( x=embedding.iloc[:, 0], y=embedding.iloc[:, 1], text=names, mode="markers", hoverinfo="text", opacity=0.5, marker={ "size": 5, "line": {"width": 0.5, "color": "white"}, "color": colors if colors is not None else "black", "colorscale": colorscale, }, ) # The axes, etc. layout = go.Layout( xaxis={"type": "linear", "title": "", "showline": False, "showticklabels": False}, yaxis={"type": "linear", "title": "", "showline": False, "showticklabels": False}, margin={"l": 40, "b": 40, "t": 10, "r": 10}, legend={"x": 0, "y": 1}, hovermode="closest", paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)", width=500, height=500, ) fig = go.FigureWidget(data=[scatter], layout=layout) fig.layout.hovermode = 'closest' # The 2D drawing of the molecule image_widget = Image( value=smiles_to_image("CCCCO"), layout=Layout(height="300px", width="300px") ) def hover_fn(trace, points, state): ind = points.point_inds[0] smiles = features["SMILES"].iloc[ind] image_widget.value = smiles_to_image(smiles) scatter =[0] scatter.on_hover(hover_fn) canvas = VBox([fig, image_widget]) return canvas