#
# AUTHOR(S): Riya Saxena <29riyasaxena AT gmail>
#
# PURPOSE: This module provides the base class for interactive visualizations
# used by `TimeSeriesMap` and `SeriesMap` in Jupyter Notebooks. It
# includes methods for rendering visualizations and creating interactive
# sliders to navigate through time-series or series data, while reducing
# redundancy and enhancing functionality.
#
# COPYRIGHT: (C) 2024 Riya Saxena, and by the GRASS Development Team
#
# This program is free software under the GNU General Public
# License (>=v2). Read the file COPYING that comes with GRASS
# for details.
"""Base class for SeriesMap and TimeSeriesMap"""
import os
from pathlib import Path
import tempfile
import weakref
import shutil
import multiprocessing
import grass.script as gs
from .map import Map
from .utils import get_number_of_cores, save_gif
[docs]class BaseSeriesMap:
"""
Base class for SeriesMap and TimeSeriesMap
"""
def __init__(self, width=None, height=None, env=None):
"""Creates an instance of the visualizations class.
:param int width: width of map in pixels
:param int height: height of map in pixels
:param str env: environment
"""
# Copy Environment
if env:
self._env = env.copy()
else:
self._env = os.environ.copy()
self.baseseries = None
self._base_layer_calls = []
self._base_calls = []
self._baseseries_added = False
self._layers_rendered = False
self._base_filename_dict = {}
self._width = width
self._height = height
self._slider_description = ""
self._labels = []
self._indices = []
self.base_file = None
# Create a temporary directory for our PNG images
# Resource managed by weakref.finalize.
self._tmpdir = (
# pylint: disable=consider-using-with
tempfile.TemporaryDirectory()
)
def cleanup(tmpdir):
tmpdir.cleanup()
weakref.finalize(self, cleanup, self._tmpdir)
def __getattr__(self, name):
"""
Parse attribute to GRASS display module. Attribute should be in
the form 'd_module_name'. For example, 'd.rast' is called with 'd_rast'.
"""
# Check to make sure format is correct
if not name.startswith("d_"):
raise AttributeError(_("Module must begin with 'd_'"))
# Reformat string
grass_module = name.replace("_", ".")
# Assert module exists
if not shutil.which(grass_module):
raise AttributeError(_("Cannot find GRASS module {}").format(grass_module))
# if this function is called, the images need to be rendered again
self._layers_rendered = False
def wrapper(**kwargs):
if not self._baseseries_added:
self._base_layer_calls.append((grass_module, kwargs))
elif self._base_calls is not None:
for row in self._base_calls:
row.append((grass_module, kwargs))
else:
self._base_calls.append((grass_module, kwargs))
return wrapper
def _render_baselayers(self, img):
"""Add collected baselayers to Map instance"""
for grass_module, kwargs in self._base_layer_calls:
img.run(grass_module, **kwargs)
def _render(self, tasks):
"""
Renders the base image for the dataset.
Saves PNGs to a temporary directory.
This method must be run before creating a visualization (e.g., show or save).
It can be time-consuming to run with large space-time datasets.
Child classes should override the `render` method
to define specific rendering behaviors, such as:
- Rendering images for each time-step in a space-time dataset (e.g., class1).
- Rendering images for each raster in a series (e.g., class2).
"""
# Runtime error in respective classes
# Make base image (background and baselayers)
# Random name needed to avoid potential conflict with layer names
random_name_base = gs.append_random("base", 8) + ".png"
self.base_file = os.path.join(self._tmpdir.name, random_name_base)
img = Map(
width=self._width,
height=self._height,
filename=self.base_file,
use_region=True,
env=self._env,
read_file=True,
)
# We have to call d_erase to ensure the file is created. If there are no
# base layers, then there is nothing to render in random_base_name
img.d_erase()
# Add baselayers
self._render_baselayers(img)
# Render layers in respective classes
cores = get_number_of_cores(len(tasks), env=self._env)
with multiprocessing.Pool(processes=cores) as pool:
results = pool.starmap(self._render_worker, tasks)
for i, filename in results:
self._base_filename_dict[i] = filename
self._layers_rendered = True
[docs] def show(self, slider_width=None):
"""Create interactive timeline slider.
param str slider_width: width of datetime selection slider
The slider_width parameter sets the width of the slider in the output cell.
It should be formatted as a percentage (%) between 0 and 100 of the cell width
or in pixels (px). Values should be formatted as strings and include the "%"
or "px" suffix. For example, slider_width="80%" or slider_width="500px".
slider_width is passed to ipywidgets in ipywidgets.Layout(width=slider_width).
"""
# Lazy Imports
import ipywidgets as widgets # pylint: disable=import-outside-toplevel
# Render images if they have not been already
if not self._layers_rendered:
self.render()
# Set default slider width
if not slider_width:
slider_width = "70%"
lookup = list(zip(self._labels, self._indices))
description = self._slider_description # modify description
# Datetime selection slider
slider = widgets.SelectionSlider(
options=lookup,
value=self._indices[0],
description=description,
disabled=False,
continuous_update=True,
orientation="horizontal",
readout=True,
layout=widgets.Layout(width=slider_width),
)
play = widgets.Play(
interval=500,
value=0,
min=0,
max=len(self._labels) - 1,
step=1,
description="Press play",
disabled=False,
)
out_img = widgets.Image(value=b"", format="png")
def change_slider(change):
slider.value = slider.options[change.new][1]
play.observe(change_slider, names="value")
# Display image associated with datetime
def change_image(index):
filename = self._base_filename_dict[index]
out_img.value = Path(filename).read_bytes()
widgets.interactive_output(change_image, {"index": slider})
layout = widgets.Layout(
width="100%", display="inline-flex", flex_flow="row wrap"
)
return widgets.HBox([play, slider, out_img], layout=layout)
[docs] def save(
self,
filename,
duration=500,
label=True,
font=None,
text_size=12,
text_color="gray",
):
"""
Creates a GIF animation of rendered layers.
Text color must be in a format accepted by PIL ImageColor module. For supported
formats, visit:
https://pillow.readthedocs.io/en/stable/reference/ImageColor.html#color-names
param str filename: name of output GIF file
param int duration: time to display each frame; milliseconds
param bool label: include label on each frame
param str font: font file
param int text_size: size of label text
param str text_color: color to use for the text.
"""
# Render images if they have not been already
if not self._layers_rendered:
self.render()
input_files = []
for index in self._indices:
input_files.append(self._base_filename_dict[index])
save_gif(
input_files,
filename,
duration=duration,
label=label,
labels=self._labels,
font=font,
text_size=text_size,
text_color=text_color,
)
# Display the GIF
return filename
