import holoviews as hv
import numpy as np
import pandas as pd
import panel as pn
import param
from holoviews.operation.datashader import dynspread, rasterize

from utils import (
    DATASET_COLUMNS,
    DATASETS,
    DATASHADER_LOGO,
    DATASHADER_URL,
    DEFAULT_DATASET,
    DESCRIPTION,
    ESA_EASTING,
    ESA_NORTHING,
    MAJOR_TOM_LOGO,
    MAJOR_TOM_LYRICS,
    MAJOR_TOM_PICTURE,
    MAJOR_TOM_REF_URL,
    PANEL_LOGO,
    PANEL_URL,
    get_closest_rows,
    get_image,
    get_meta_data,
)


class DatasetInput(pn.viewable.Viewer):
    value = param.Selector(
        default=DEFAULT_DATASET,
        objects=DATASETS,
        allow_None=False,
        label="Dataset",
        doc="""The name of the dataset""",
    )

    data = param.DataFrame(allow_None=False, doc="""The metadata dataset""")
    columns = param.Dict(allow_None=False, doc="""The columns of the dataset""")

    def __panel__(self):
        return pn.widgets.RadioButtonGroup.from_param(
            self.param.value, button_style="outline"
        )

    @pn.depends("value", watch=True, on_init=True)
    def _update_data(self):
        columns = DATASET_COLUMNS[self.value]
        data = pn.cache(get_meta_data)(dataset=self.value)
        self.param.update(columns=columns, data=data)


class MapInput(pn.viewable.Viewer):
    data = param.DataFrame(allow_refs=True, allow_None=False)

    data_in_view = param.DataFrame(allow_None=False)
    data_selected = param.DataFrame(allow_None=False)

    _plot = param.Parameter(allow_None=False)
    _pointer_x = param.Parameter(allow_None=False)
    _pointer_y = param.Parameter(allow_None=False)
    _range_xy = param.Parameter(allow_None=False)
    _tap = param.Parameter(allow_None=False)

    updating = param.Boolean()

    def __panel__(self):
        return pn.Column(
            pn.pane.HoloViews(
                self._plot, height=550, width=800, loading=self.param.updating
            ),
            self._description,
        )

    @param.depends("data", watch=True, on_init=True)
    def _handle_data_dask_change(self):
        with self.param.update(updating=True):
            data = self.data[["centre_easting", "centre_northing"]].copy()
            points = hv.Points(
                data, kdims=["centre_easting", "centre_northing"], vdims=[]
            )

            rangexy = hv.streams.RangeXY(source=points)
            tap = hv.streams.Tap(source=points, x=ESA_EASTING, y=ESA_NORTHING)

            agg = rasterize(
                points, link_inputs=True, x_sampling=0.0001, y_sampling=0.0001
            )
            dyn = dynspread(agg)
            dyn.opts(cmap="kr_r", colorbar=True)

            pointerx = hv.streams.PointerX(x=ESA_EASTING, source=points)
            pointery = hv.streams.PointerY(y=ESA_NORTHING, source=points)
            vline = hv.DynamicMap(lambda x: hv.VLine(x), streams=[pointerx])
            hline = hv.DynamicMap(lambda y: hv.HLine(y), streams=[pointery])
            tiles = hv.Tiles(
                "https://tile.openstreetmap.org/{Z}/{X}/{Y}.png", name="OSM"
            ).opts(xlabel="Longitude", ylabel="Latitude")

            self.param.update(
                _plot=tiles * agg * dyn * hline * vline,
                _pointer_x=pointerx,
                _pointer_y=pointery,
                _range_xy=rangexy,
                _tap=tap,
            )

            update_viewed = pn.bind(
                self._update_data_in_view,
                rangexy.param.x_range,
                rangexy.param.y_range,
                watch=True,
            )
            update_viewed()

            update_selected = pn.bind(
                self._update_data_selected, tap.param.x, tap.param.y, watch=True
            )
            update_selected()

    def _update_data_in_view(self, x_range, y_range):
        if not x_range or not y_range:
            self.data_in_view = self.data
            return

        data = self.data
        data = data[
            (data.centre_easting.between(*x_range))
            & (data.centre_northing.between(*y_range))
        ]
        self.data_in_view = data.reset_index(drop=True)

    def _update_data_selected(self, tap_x, tap_y):
        self.data_selected = get_closest_rows(self.data, tap_x, tap_y)

    @pn.depends("data_in_view")
    def _description(self):
        return f"Rows: {len(self.data_in_view):,}"


class ImageInput(pn.viewable.Viewer):
    data = param.DataFrame(
        allow_refs=True, allow_None=False, doc="""The metadata selected"""
    )
    columns = param.Dict(
        allow_refs=True, allow_None=False, doc="""The list of columns of the dataset"""
    )
    column_name = param.Selector(
        label="Image Type",
        allow_None=False,
        doc="""The name of the image type to view""",
    )

    updating = param.Boolean()

    meta_data = param.DataFrame()
    image = param.Parameter()
    plot = param.Parameter()

    _timestamp = param.Selector(label="Timestamp", objects=[None], doc="""The timestamp of the sample to view""")

    def __panel__(self):
        return pn.Column(
            pn.Row(
                pn.widgets.RadioButtonGroup.from_param(
                    self.param._timestamp,
                    button_style="outline",
                    align="end",
                    disabled=self.param.updating,
                ),
                pn.widgets.Select.from_param(
                    self.param.column_name, disabled=self.param.updating
                ),
            ),
            pn.Tabs(
                pn.pane.HoloViews(
                    self.param.plot,
                    height=800,
                    width=800,
                    name="Interactive Image",
                ),
                pn.pane.Image(
                    self.param.image,
                    name="Static Image",
                    width=800,
                ),
                pn.widgets.Tabulator(
                    self.param.meta_data,
                    name="Meta Data",
                    disabled=True,
                ),
                pn.pane.Markdown(self.code, name="Code"),
                dynamic=True,
                loading=self.param.updating,
            ),
        )

    @pn.depends("data", watch=True, on_init=True)
    def _update_timestamp(self):
        if self.data.empty:
            default_value = None
            options = [None]
        else:
            options = sorted(self.data["timestamp"].unique())
            default_value = options[0]

        self.param._timestamp.objects = options
        if not self._timestamp in options:
            self._timestamp = default_value

    @pn.depends("columns", watch=True, on_init=True)
    def _update_column_names(self):
        options = sorted(self.columns)
        default_value = "Thumbnail"

        self.param.column_name.objects = options
        if not self.column_name in options:
            self.column_name = default_value

    @property
    def column(self):
        return self.columns[self.column_name]

    @pn.depends("_timestamp", "column_name", watch=True, on_init=True)
    def _update_plot(self):
        if self.data.empty or not self._timestamp or not self.column_name:
            self.meta_data = self.data.T
            self.image = None
            self.plot = hv.RGB(np.array([]))
        else:
            with self.param.update(updating=True):
                row = self.data[self.data.timestamp == self._timestamp].iloc[0]
                self.meta_data = pd.DataFrame(row)
                self.image = image = pn.cache(get_image)(row, self.column)
                image_array = np.array(image)
                if image_array.ndim == 2:
                    self.plot = hv.Image(image_array).opts(
                        cmap="gray_r", xaxis=None, yaxis=None, colorbar=True
                    )
                else:
                    self.plot = hv.RGB(image_array).opts(xaxis=None, yaxis=None)

    @pn.depends("meta_data", "column_name")
    def code(self):
        if self.meta_data.empty:
            return ""

        parquet_url = self.meta_data.T["parquet_url"].iloc[0]
        parquet_row = self.meta_data.T["parquet_row"].iloc[0]
        return f"""\
```bash
pip install aiohttp fsspec holoviews numpy panel pyarrow requests
```

```python
from io import BytesIO

import holoviews as hv
import numpy as np
import panel as pn
import pyarrow.parquet as pq
from fsspec.parquet import open_parquet_file
from PIL import Image

pn.extension()

parquet_url = "{parquet_url}"
parquet_row = {parquet_row}
column = "{self.column}"
with open_parquet_file(parquet_url, columns=[column]) as f:
    with pq.ParquetFile(f) as pf:
        first_row_group = pf.read_row_group(parquet_row, columns=[column])

stream = BytesIO(first_row_group[column][0].as_py())
image = Image.open(stream)
image_array = np.array(image)
if image_array.ndim==2:
    plot = hv.Image(image_array).opts(cmap="gray", colorbar=True)
else:
    plot = hv.RGB(image_array)

plot.opts(xaxis=None, yaxis=None)

pn.panel(plot).servable()
```

```bash
panel serve app.py --autoreload
```

"""


class App(param.Parameterized):
    sidebar = param.Parameter()
    main = param.Parameter()

    def __init__(self, **params):
        super().__init__(**params)

        self.sidebar = self._create_sidebar()
        self.main = pn.FlexBox(
            pn.Column(
                pn.Row(
                    pn.indicators.LoadingSpinner(value=True, size=50),
                    "**Loading data...**",
                ),
                MAJOR_TOM_LYRICS,
            )
        )

        pn.state.onload(self._update_main)

    def _create_sidebar(self):
        return pn.Column(
            pn.pane.Image(
                MAJOR_TOM_LOGO,
                link_url=MAJOR_TOM_REF_URL,
                height=60,
                sizing_mode="stretch_width",
            ),
            pn.pane.Image(
                MAJOR_TOM_PICTURE,
                link_url=MAJOR_TOM_REF_URL,
                sizing_mode="stretch_width",
            ),
            DESCRIPTION,
            pn.pane.Image(PANEL_LOGO, link_url=PANEL_URL, width=200, margin=(10, 20)),
            pn.pane.Image(
                DATASHADER_LOGO, link_url=DATASHADER_URL, width=200, margin=(10, 20)
            ),
        )

    def _create_main_content(self):
        dataset = DatasetInput()
        map_input = MapInput(data=dataset.param.data)
        image_input = ImageInput(
            data=map_input.param.data_selected, columns=dataset.param.columns
        )

        return pn.Column(dataset, map_input), image_input

    def _update_main(self):
        self.main[:] = list(self._create_main_content())