def main():
coords, mqns, smiles = load()
data = {"x": [], "y": [], "c": [], "s": [], "labels": smiles}
for i, _ in enumerate(coords):
data["x"].append(coords[i][0])
data["y"].append(coords[i][1])
data["c"].append(mqns[i][0])
data["s"].append(random.randint(1, 5))
df = pd.DataFrame.from_dict(data)
faerun = Faerun()
faerun.add_scatter(
"drugbank",
df,
shader="smoothCircle",
point_scale=2.0,
colormap="jet",
has_legend=True,
categorical=False,
)
with open("example.faerun", "wb+") as f:
pickle.dump(faerun.create_python_data(), f, protocol=pickle.HIGHEST_PROTOCOL)
info = (
"#Welcome to Fearun",
"This is a small demonstration visualising drugs stored in [Drugbank](http://drugbank.ca) using coordinates generated by a PCA projection."
"",
"By the way, this info was generated using markdown, this means that you can easily:",
"- Add lists",
"- Build tables",
"- Insert images and links",
"- Add code examples",
"- ...",
)
host(
"example.faerun",
label_type="smiles",
legend=True,
theme="light",
info="\n".join(info),
)
def main():
coords, mqns, smiles = load()
data = {'x': [], 'y': [], 'z': [], 'c': [], 'labels': smiles}
for i, _ in enumerate(coords):
data['x'].append(coords[i][0])
data['y'].append(coords[i][1])
data['z'].append(coords[i][2])
data['c'].append(mqns[i][0])
df = pd.DataFrame.from_dict(data)
faerun = Faerun()
faerun.add_scatter('drugbank',
df,
shader='sphere',
point_scale=5.0,
colormap='jet',
has_legend=True,
categorical=False)
with open('example.faerun', 'wb+') as f:
pickle.dump(faerun.create_python_data(),
f,
protocol=pickle.HIGHEST_PROTOCOL)
info = (
'#Welcome to Fearun',
'This is a small demonstration visualising drugs stored in [Drugbank](http://drugbank.ca) using coordinates generated by a PCA projection.'
'',
'By the way, this info was generated using markdown, this means that you can easily:',
'- Add lists', '- Build tables', '- Insert images and links',
'- Add code examples', '- ...')
host('example.faerun',
label_type='default',
legend=True,
theme='dark',
info='\n'.join(info),
view='free')
def main():
f = Faerun(clear_color="#222222", coords=True, view="front")
x = np.linspace(0, 12.0, 326)
y = np.sin(np.pi * x)
z = np.cos(np.pi * x)
c = np.random.randint(0, 2, len(x))
labels = [str(l) + "__Test" for l in c]
data = {"x": x, "y": y, "z": z, "c": c, "labels": labels}
f.add_scatter(
"helix",
data,
shader="smoothCircle",
colormap="Dark2",
point_scale=5.0,
categorical=True,
has_legend=True,
legend_labels=[(0, "Zero"), (1, "One")],
selected_labels=["None", "Just a Small Test"],
)
f.add_tree("helixtree", {
"from": [1, 5, 6, 7],
"to": [2, 7, 8, 9]
},
point_helper="helix")
f.plot("helix")
with open("helix.faerun", "wb+") as handle:
pickle.dump(f.create_python_data(),
handle,
protocol=pickle.HIGHEST_PROTOCOL)
def main():
f = Faerun(title="faerun-example",
clear_color="#222222",
coords=False,
view="free")
x = np.linspace(0, 12.0, 326)
y = np.sin(np.pi * x)
z = np.cos(np.pi * x)
c = np.random.randint(0, 2, len(x))
labels = [""] * len(c)
for i, e in enumerate(c):
labels[i] = str(e) + "__" + str(i % 20)
data = {"x": x, "y": y, "z": z, "c": c, "labels": labels}
f.add_scatter(
"helix",
data,
shader="sphere",
colormap="Dark2",
point_scale=5.0,
categorical=True,
has_legend=True,
legend_labels=[(0, "Zero"), (1, "One")],
)
f.plot("helix")
with open("helix.faerun", "wb+") as handle:
pickle.dump(f.create_python_data(),
handle,
protocol=pickle.HIGHEST_PROTOCOL)
def custom_label_formatter(label, index, name):
return f"Example: {label} ({index}, {name})"
def custom_link_formatter(label, index, name):
return f"https://www.google.com/search?q={label}"
info = (
"#Welcome to Fearun",
"This is a small Faerun example."
"",
"Yay markdown! This means that you can easily:",
"- Add lists",
"- Build tables",
"- Insert images and links",
"- Add code examples",
"- ...",
)
host(
"helix.faerun",
label_type="default",
title="Helix",
theme="dark",
label_formatter=custom_label_formatter,
link_formatter=custom_link_formatter,
info="\n".join(info),
)
)
faerun.add_scatter("cosinus",
df2,
shader="sphere",
point_scale=5.0,
colormap="jet",
has_legend=True)
faerun.add_scatter(
"categorical",
data3,
shader="sphere",
point_scale=5.0,
colormap=["Set1", "viridis"],
has_legend=True,
categorical=[True, False],
legend_labels=legend_labels,
series_title=["A", "B"],
ondblclick=["console.log(labels[0])", "console.log('B:' + labels[0])"],
)
with open("index.pickle", "wb+") as handle:
pickle.dump(faerun.create_python_data(),
handle,
protocol=pickle.HIGHEST_PROTOCOL)
file = open("index.pickle", "rb")
obj = pickle.load(file)
file.close()
faerun.plot(template="default")
def main(da, dataset_path):
""" Main function """
# Initialize and configure tmap
# dims = 2048
# enc = tm.Minhash(int(da.emb_dim.count()), 42, dims)
# lf = tm.LSHForest(dims * 4, 256, weighted=True)
# enc = tm.Minhash()
# lf = tm.LSHForest(weighted=True)
labels = []
image_labels = []
# data = []
# da = da.isel(scene_id=0).stack(dict(tile_id=('x', 'y')))
da = da.sel(x=slice(-1000e3, None)).stack(
dict(tile_id=("x", "y", "scene_id")))
# sel(tile_id=da.tile_id.values[:100])
# scene_ids = list(da.unstack().scene_id.values)
x_ = []
y_ = []
z_ = []
for tile_id in tqdm(da.tile_id.values):
try:
da_ = da.sel(tile_id=tile_id)
i0, j0 = da_.i0.item(), da_.j0.item()
try:
scene_id = da_.scene_id.item()
except:
scene_id = tile_id[-1]
# x_.append(tile_id[0])
# y_.append(tile_id[1])
fn = _get_tile_image_path(dataset_path=dataset_path,
scene_id=scene_id,
i0=i0,
j0=j0)
# img_str = base64.b64encode(open(fn, "rb").read())
# "data:image/png;base64," + str(img_str).replace("b'", "").replace("'", "")
# labels.append(scene_ids.index(scene_id))
# c = da_.isel(pca_dim=3).values
# c = 0
# labels.append(c)
image_labels.append("get_image?path=" + str(fn))
# data.append(da_.values)
except FileNotFoundError:
continue
# lf.batch_add(enc.batch_from_weight_array(data))
# lf.index()
# x, y, s, t, _ = tm.layout_from_lsh_forest(lf)
# x = np.array(x_)
# y = np.array(y_)
# z = np.array(z_)
x = da.isel(pca_dim=0).values
y = da.isel(pca_dim=1).values
z = da.isel(pca_dim=2).values
c = da.isel(pca_dim=3).values
# from sklearn.manifold import TSNE
# X = da.values.T
# X_embedded = TSNE(n_components=2,).fit_transform(X)
# x, y = X[:,0], X[:,1]
f = Faerun(
clear_color="#111111",
view="front",
coords=True,
x_title="pca dim 0",
y_title="pca dim 1",
)
f.add_scatter(
"EMB",
{
"x": x,
"y": y,
"z": z,
"c": c,
"labels": image_labels
},
colormap="jet",
# shader="smoothCircle",
shader="sphere",
point_scale=5.0,
max_point_size=10,
has_legend=True,
categorical=False,
)
# f.add_tree(
# "EMB_tree", {"from": s, "to": t}, point_helper="EMB", color="#666666"
# )
with open("tmap.faerun", "wb+") as handle:
pickle.dump(f.create_python_data(),
handle,
protocol=pickle.HIGHEST_PROTOCOL)
df,
shader="circle",
point_scale=5.0,
has_legend=True,
legend_labels=[(0.0, "Low"), (50.0, "Inbetween"), (df["c"].max(), "High")],
)
faerun.add_scatter(
"cosinus", df2, shader="sphere", point_scale=5.0, colormap="jet", has_legend=True
)
faerun.add_scatter(
"categorical",
data3,
shader="sphere",
point_scale=5.0,
colormap=["Set1", "viridis"],
has_legend=True,
categorical=[True, False],
legend_labels=legend_labels,
series_title=["A", "B"],
ondblclick=["console.log(labels[0])", "console.log('B:' + labels[0])"],
)
with open("index.pickle", "wb+") as handle:
pickle.dump(faerun.create_python_data(), handle, protocol=pickle.HIGHEST_PROTOCOL)
file = open("index.pickle", "rb")
obj = pickle.load(file)
file.close()
faerun.plot(template="default")
