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import io
from pathlib import Path
from typing import Callable, Optional, cast
from urllib.parse import parse_qsl
import altair as alt
import numpy as np
import pandas as pd
import reacton.core
import solara
import solara.lab
from cmap import Catalog, Colormap
from ipyvuetify.extra import FileInput
from make_link import encode_url
from viewer import AxisProperties, ColorTransform, ProteinView, RoutedView
DEFAULT_CMAP = "tol:rainbow_PuRd"
NORM_CATEGORIES = ["linear", "diverging", "categorical"]
VMIN_DEFAULT = 0.0
VMAX_DEFAULT = 1.0
HIGHLIGHT_COLOR = "#e933f8"
MISSING_DATA_COLOR = "#8c8c8c"
CMAP_OPTIONS = list(Catalog().namespaced_keys())
# BASE_URL = "http://localhost:8765" # local testing
BASE_URL = "https://huggingface.co/spaces/Jhsmit/ipymolstar-annotate-colors"
pth = Path(__file__).parent
@solara.component
def FileInputComponent(
on_file: Callable[[solara.components.file_drop.FileInfo | None], None],
):
"""Adaptation of _FileDrop."""
file_info, set_file_info = solara.use_state(None)
wired_files, set_wired_files = solara.use_state(
cast(Optional[list[solara.components.file_drop.FileInfo]], None)
)
file_drop = FileInput.element(on_file_info=set_file_info, multiple=False) # type: ignore
def wire_files():
if not file_info:
set_wired_files([])
return
real = cast(FileInput, solara.get_widget(file_drop))
# workaround for @observe being cleared
real.version += 1
real.reset_stats()
set_wired_files(
cast(list[solara.components.file_drop.FileInfo], real.get_files())
)
solara.use_effect(wire_files, [file_info])
def handle_file():
if not wired_files:
on_file(None)
return
if on_file:
f = wired_files[0].copy()
f["data"] = None
on_file(f)
solara.lab.use_task(handle_file, dependencies=[wired_files])
return file_drop
@solara.component
def ColorPickerMenuButton(title: str, color: solara.Reactive[str]):
local_color = solara.use_reactive(color.value)
def on_open(value: bool):
if not value:
color.set(local_color.value)
btn = solara.Button(title, color=local_color.value)
with solara.lab.Menu(
activator=btn, close_on_content_click=False, on_open_value=on_open
):
solara.v.ColorPicker(
v_model=local_color.value,
on_v_model=local_color.set,
)
empty_frame = pd.DataFrame()
R_DEFAULT = ""
V_DEFAULT = ""
# %%
@solara.component
def MainApp():
dark_effective = solara.lab.use_dark_effective()
title = solara.use_reactive("My annotated protein view")
description = solara.use_reactive("")
molecule_id = solara.use_reactive("1QYN")
data = solara.use_reactive(empty_frame)
warning_text = solara.use_reactive("")
residue_column = solara.use_reactive(R_DEFAULT)
color_column = solara.use_reactive(V_DEFAULT)
label = solara.use_reactive("value")
unit = solara.use_reactive("au")
highlight_color = solara.use_reactive(HIGHLIGHT_COLOR)
missing_data_color = solara.use_reactive(MISSING_DATA_COLOR)
autoscale_y = solara.use_reactive(True)
cmap_name = solara.use_reactive(DEFAULT_CMAP)
reverse = solara.use_reactive(False)
full_cmap_name = cmap_name.value + "_r" if reverse.value else cmap_name.value
cmap = Colormap(full_cmap_name)
vmin = solara.use_reactive(VMIN_DEFAULT)
vmax = solara.use_reactive(VMAX_DEFAULT)
norm_type = solara.use_reactive(NORM_CATEGORIES[0])
rc = reacton.core.get_render_context()
def on_file(file_info: solara.components.file_drop.FileInfo | None):
if not file_info:
data.set(pd.DataFrame())
return
try:
df = pd.read_csv(file_info["file_obj"])
except Exception as e:
warning_text.set(str(e))
return
if len(df.columns) < 2:
warning_text.set(f"Expected at least 2 columns, got {len(df.columns)}")
data.set(pd.DataFrame())
return
warning_text.set("")
# order matters!
# with solara.batch_update():
# https://github.com/widgetti/solara/issues/637
with rc:
residue_column.set(df.columns[0])
color_column.set(df.columns[1])
data.set(df)
colors = ColorTransform(
name=full_cmap_name,
norm_type=norm_type.value,
vmin=vmin.value,
vmax=vmax.value,
missing_data_color=missing_data_color.value,
highlight_color=highlight_color.value,
)
axis_properties = AxisProperties(
label=label.value,
unit=unit.value,
autoscale_y=autoscale_y.value,
)
if data.value.empty:
data_view = pd.DataFrame({"residue_number": [], "value": []})
else:
data_view = pd.DataFrame(
{
"residue_number": data.value[residue_column.value],
"value": data.value[color_column.value],
}
)
def load_example_data():
bio = io.BytesIO(Path("example_data.csv").read_bytes())
bio.seek(0)
file_info = solara.components.file_drop.FileInfo(
name="example_data.csv",
size=Path("example_data.csv").stat().st_size,
file_obj=bio,
data=None,
)
# with solara.batch_update():
# https://github.com/widgetti/solara/issues/637
with rc:
molecule_id.set("6GOX")
title.set("SecA HDX-MS protein local flexibility")
on_file(file_info)
vmin.set(4e4)
vmax.set(1e4)
autoscale_y.set(False)
description.set(Path("example_data_description.md").read_text())
with solara.AppBar():
with solara.Tooltip("Load example data and settings"):
solara.Button(
icon_name="mdi-test-tube",
icon=True,
on_click=load_example_data,
)
query_string = encode_url(
title=title.value,
molecule_id=molecule_id.value,
colors=colors,
axis_properties=axis_properties,
data=data_view,
description=description.value,
)
ProteinView(
title.value,
molecule_id=molecule_id.value,
data=data_view,
colors=colors,
axis_properties=axis_properties,
dark_effective=dark_effective,
description=description.value,
)
with solara.Sidebar():
with solara.Card("Settings"):
solara.InputText(label="Title", value=title)
solara.InputText(label="PDB ID", value=molecule_id)
solara.Text("Choose .csv data file:")
FileInputComponent(on_file)
if warning_text.value:
solara.Warning(warning_text.value)
if not data.value.empty:
with solara.Row():
solara.Select(
label="Residue Column",
value=residue_column,
values=list(data.value.columns),
)
solara.Select(
label="Color Column",
value=color_column,
values=list(data.value.columns),
)
with solara.Row():
solara.InputText(label="Label", value=label)
solara.InputText(label="Unit", value=unit)
solara.Text("Colors")
with solara.Row(gap="10px", justify="space-around"):
ColorPickerMenuButton("Highlight", highlight_color)
ColorPickerMenuButton("Missing data", missing_data_color)
# with solara.Row():
solara.v.Autocomplete(
v_model=cmap_name.value,
on_v_model=cmap_name.set,
items=CMAP_OPTIONS,
)
solara.Select(
label="Normalization type", value=norm_type, values=NORM_CATEGORIES
)
with solara.Row():
def set_vmin(value: float):
if norm_type.value == "diverging":
vmin.set(value)
vmax.set(-value)
else:
vmin.set(value)
solara.InputFloat(
label="vmin",
value=vmin.value,
on_value=set_vmin,
disabled=norm_type.value == "categorical",
)
solara.InputFloat(
label="vmax",
value=vmax,
disabled=norm_type.value in ["diverging", "categorical"],
)
with solara.GridFixed(columns=2):
with solara.Tooltip("Reverses the color map"):
solara.Checkbox(label="Reverse", value=reverse)
with solara.Tooltip(
"Uncheck to use color range as the scatterplot y scale"
):
solara.Checkbox(label="Autoscale Y", value=autoscale_y)
solara.Image(cmap._repr_png_(height=24), width="100%")
solara.InputTextArea(
label="Description", value=description, continuous_update=True
)
solara.Div(style={"height": "10px"})
solara.Button(
label="Open view in new tab",
attributes={"href": BASE_URL + "?" + query_string, "target": "_blank"},
block=True,
)
@solara.component
def Page():
route = solara.use_router()
solara.Style(Path("style.css"))
dark_effective = solara.lab.use_dark_effective()
dark_previous = solara.use_previous(dark_effective)
if dark_previous != dark_effective:
if dark_effective:
alt.themes.enable("dark")
else:
alt.themes.enable("default")
# todo: aways true, check valid
if route.search:
query_dict = {k: v for k, v in parse_qsl(route.search)}
# needs more keys but if this is there then at least there has been an attempt
if "molecule_id" in query_dict:
RoutedView()
else:
MainApp()
# %%
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