Source code for tardis.visualization.widgets.custom_abundance
"""Class to create and display Custom Abundance Widget."""
import os
import yaml
import numpy as np
import pandas as pd
import ipywidgets as ipw
import plotly.graph_objects as go
from astropy import units as u
from radioactivedecay import Nuclide
from radioactivedecay.utils import Z_DICT, elem_to_Z
from pathlib import Path
import tardis
from tardis.io.model.readers.generic_readers import read_uniform_abundances
from tardis.util.base import (
quantity_linspace,
is_valid_nuclide_or_elem,
is_notebook,
)
from tardis.io.configuration.config_reader import Configuration
from tardis.model import SimulationState
from tardis.io.model.parse_density_configuration import (
calculate_power_law_density,
calculate_exponential_density,
)
from tardis.io.atom_data.base import AtomData
from tardis.io.configuration.config_validator import validate_dict
from tardis.io.model.readers.csvy import load_csvy
from tardis.io.model.readers.csvy import (
parse_csv_abundances,
)
from tardis.util.base import atomic_number2element_symbol, quantity_linspace
from tardis.visualization.tools.convergence_plot import transition_colors
from tardis.visualization.widgets.util import debounce
BASE_DIR = tardis.__path__[0]
YAML_DELIMITER = "---"
[docs]class CustomAbundanceWidgetData:
"""The model information and data that required in custom
abundance widget.
Attributes
----------
elements : list of str
A list of elements or isotopes' symbols.
"""
def __init__(self, density_t_0, density, abundance, velocity):
"""Initialize CustomAbundanceWidgetData with model information.
Parameters
----------
density_t_0 : astropy.units.quantity.Quantity
Initial time for the density in the model.
density : astropy.units.quantity.Quantity
abundance : pd.DataFrame
velocity : astropy.units.quantity.Quantity
"""
self.density_t_0 = density_t_0.to("day")
self.density = density.to("g cm^-3")
self.abundance = abundance
self.velocity = velocity.to("km/s")
self.elements = self.get_symbols()
[docs] def get_symbols(self):
"""Get symbol string from atomic number and mass number."""
str_symbols = np.array(
self.abundance.index.get_level_values(0).map(
atomic_number2element_symbol
)
)
str_mass = np.array(
self.abundance.index.get_level_values(1), dtype="str"
)
return np.add(str_symbols, str_mass)
[docs] @classmethod
def from_csvy(cls, fpath):
"""Create a new CustomAbundanceWidgetData instance with data
from CSVY file.
Parameters
----------
fpath : str
the path of CSVY file.
Returns
-------
CustomAbundanceWidgetData
"""
csvy_model_config, csvy_model_data = load_csvy(fpath)
csvy_schema_file = os.path.join(
BASE_DIR, "io", "schemas", "csvy_model.yml"
)
csvy_model_config = Configuration(
validate_dict(csvy_model_config, schemapath=csvy_schema_file)
)
if hasattr(csvy_model_config, "velocity"):
velocity = quantity_linspace(
csvy_model_config.velocity.start,
csvy_model_config.velocity.stop,
csvy_model_config.velocity.num + 1,
).cgs
else:
velocity_field_index = [
field["name"] for field in csvy_model_config.datatype.fields
].index("velocity")
velocity_unit = u.Unit(
csvy_model_config.datatype.fields[velocity_field_index]["unit"]
)
velocity = csvy_model_data["velocity"].values * velocity_unit
no_of_shells = len(velocity) - 1
if hasattr(csvy_model_config, "density"):
adjusted_velocity = velocity.insert(0, 0)
v_middle = (
adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5
)
no_of_shells = len(adjusted_velocity) - 1
d_conf = csvy_model_config.density
density_type = d_conf.type
if density_type == "branch85_w7":
density_0 = calculate_power_law_density(
v_middle, d_conf.w7_v_0, d_conf.w7_rho_0, -7
)
time_0 = d_conf.w7_time_0
elif density_type == "uniform":
density_0 = d_conf.value.to("g cm^-3") * np.ones(no_of_shells)
time_0 = d_conf.get("time_0", 0 * u.day)
elif density_type == "power_law":
density_0 = calculate_power_law_density(
v_middle, d_conf.v_0, d_conf.rho_0, d_conf.exponent
)
time_0 = d_conf.get("time_0", 0 * u.day)
elif density_type == "exponential":
density_0 = calculate_exponential_density(
v_middle, d_conf.v_0, d_conf.rho_0
)
time_0 = d_conf.get("time_0", 0 * u.day)
else:
raise ValueError(f"Unrecognized density type " f"{d_conf.type}")
else:
density_field_index = [
field["name"] for field in csvy_model_config.datatype.fields
].index("density")
density_unit = u.Unit(
csvy_model_config.datatype.fields[density_field_index]["unit"]
)
density_0 = csvy_model_data["density"].values * density_unit
time_0 = csvy_model_config.model_density_time_0
if hasattr(csvy_model_config, "abundance"):
abundances_section = csvy_model_config.abundance
abundance, isotope_abundance = read_uniform_abundances(
abundances_section, no_of_shells
)
else:
_, abundance, isotope_abundance = parse_csv_abundances(
csvy_model_data
)
abundance = abundance.loc[:, 1:]
abundance.columns = np.arange(abundance.shape[1])
isotope_abundance = isotope_abundance.loc[:, 1:]
isotope_abundance.columns = np.arange(isotope_abundance.shape[1])
abundance = abundance.replace(np.nan, 0.0)
abundance = abundance[abundance.sum(axis=1) > 0]
isotope_abundance = isotope_abundance.replace(np.nan, 0.0)
isotope_abundance = isotope_abundance[isotope_abundance.sum(axis=1) > 0]
# Combine elements and isotopes to one DataFrame
abundance["mass_number"] = ""
abundance.set_index("mass_number", append=True, inplace=True)
abundance = pd.concat([abundance, isotope_abundance])
abundance.sort_index(inplace=True)
return cls(
density_t_0=time_0,
density=density_0,
abundance=abundance,
velocity=velocity,
)
[docs] @classmethod
def from_yml(cls, fpath, atom_data=None):
"""Create a new CustomAbundanceWidgetData instance with data
from YAML file.
Parameters
----------
fpath : str
The path of YAML file.
Returns
-------
CustomAbundanceWidgetData
"""
config = Configuration.from_yaml(fpath)
if atom_data is None:
atom_data = AtomData.from_hdf(config.atom_data)
if hasattr(config, "csvy_model"):
simulation_state = SimulationState.from_csvy(
config, atom_data=atom_data
)
else:
simulation_state = SimulationState.from_config(
config, atom_data=atom_data
)
velocity = simulation_state.velocity
density_t_0 = simulation_state.time_explosion
density = simulation_state.density
abundance = simulation_state.abundance
isotopic_mass_fraction = (
simulation_state.composition.isotopic_mass_fraction
)
# Combine elements and isotopes to one DataFrame
abundance["mass_number"] = ""
abundance.set_index("mass_number", append=True, inplace=True)
abundance = pd.concat([abundance, isotopic_mass_fraction])
abundance.sort_index(inplace=True)
return cls(
density_t_0=density_t_0,
density=density,
abundance=abundance,
velocity=velocity,
)
[docs] @classmethod
def from_hdf(cls, fpath):
"""Create a new CustomAbundanceWidgetData instance with data
from HDF file.
Parameters
----------
fpath : str
the path of HDF file.
Returns
-------
CustomAbundanceWidgetData
"""
with pd.HDFStore(fpath, "r") as hdf:
abundance = hdf["/simulation/plasma/abundance"]
_density_t_0 = hdf["/simulation/model/homologous_density/scalars"]
_density = hdf["/simulation/model/homologous_density/density_0"]
v_inner = hdf["/simulation/model/v_inner"]
v_outer = hdf["/simulation/model/v_outer"]
density_t_0 = float(_density_t_0) * u.s
density = np.array(_density) * u.g / (u.cm) ** 3
velocity = np.append(v_inner, v_outer[len(v_outer) - 1]) * u.cm / u.s
abundance["mass_number"] = ""
abundance.set_index("mass_number", append=True, inplace=True)
return cls(
density_t_0=density_t_0,
density=density,
abundance=abundance,
velocity=velocity,
)
[docs] @classmethod
def from_simulation(cls, sim):
"""Create a new CustomAbundanceWidgetData instance from a
Simulation object.
Parameters
----------
sim : Simulation
Returns
-------
CustomAbundanceWidgetData
"""
abundance = sim.simulation_state.abundance.copy()
isotope_abundance = (
sim.simulation_state.composition.raw_isotope_abundance.copy()
)
# integrate element and isotope to one DataFrame
abundance["mass_number"] = ""
abundance.set_index("mass_number", append=True, inplace=True)
abundance = pd.concat([abundance, isotope_abundance])
abundance.sort_index(inplace=True)
velocity = sim.simulation_state.velocity
density_t_0 = sim.simulation_state.time_explosion
density = sim.simulation_state.density
return cls(
density_t_0=density_t_0,
density=density,
abundance=abundance,
velocity=velocity,
)
[docs]class CustomYAML(yaml.YAMLObject):
"""A custom YAML object generated by required properties."""
def __init__(
self, name, d_time_0, i_time_0, v_inner_boundary, v_outer_boundary
):
"""Initialize CustomYAML object with given properties.
Parameters
----------
name : str
Name of the YAML file.
d_time_0 : astropy.units.quantity.Quantity
Initial time for the density in the model.
i_time_0 : astropy.units.quantity.Quantity
Initial time for isotope decay. Set to 0 for no isotopes.
v_inner_boundary : astropy.units.quantity.Quantity
Velocity of the inner boundary.
v_outer_boundary : astropy.units.quantity.Quantity
Velocity of the outer boundary.
"""
self.name = name
self.model_density_time_0 = d_time_0
self.model_isotope_time_0 = i_time_0
self.tardis_model_config_version = "v1.0"
self.datatype = {}
self.datatype["fields"] = []
self.v_inner_boundary = v_inner_boundary
self.v_outer_boundary = v_outer_boundary
[docs] def create_fields_dict(self, elements):
"""Create a dictionary to store the items in 'fields' part.
Parameters
----------
elements : list of str
A list of elements or isotopes' symbols.
"""
for i in range(len(elements) + 2):
field = {}
if i == 0:
field["name"] = "velocity"
field["unit"] = "km/s"
elif i == 1:
field["name"] = "density"
field["unit"] = "g/cm^3"
else:
field["name"] = elements[i - 2]
field["desc"] = f"fractional {elements[i-2]} abundance"
self.datatype["fields"].append(field)
[docs]class CustomAbundanceWidget:
"""Widget to edit abundances and densities of simulation model
graphically.
It generates a GUI based on input data. The GUI has a plot section
to visualize the profile, an edit section to allow the user directly
edit abundance and density profile, and an output section to output
the model to CSVY file.
Attributes
----------
shell_no : int
The selected shell number.
no_of_shells : int
The number of shells in the model.
no_of_elements : int
The number of elements in the model.
checked_list : list of bool
A list of bool to record whether the checkbox is checked.
The index of the bool corresponds to the index of checkbox.
fig : plotly.graph_objs._figurewidget.FigureWidget
The figure object of abundance density plot.
plot_cmap : str, default: "jet", optional
String defines the colormap used in abundance density plot.
_trigger : bool
If False, disable the callback when abundance input is changed.
"""
error_view = ipw.Output()
def __init__(self, widget_data):
"""Initialize CustomAbundanceWidget with data and generate
the widgets and plot.
Parameters
----------
widget_data : CustomAbundanceWidgetData
"""
self.data = widget_data
self.fig = go.FigureWidget()
self._trigger = True
self.create_widgets()
self.generate_abundance_density_plot()
self.density_editor = DensityEditor(
self.data,
self.fig,
self.dpd_shell_no,
)
@property
def shell_no(self):
return self.dpd_shell_no.value
@shell_no.setter
def shell_no(self, value):
self.dpd_shell_no.value = value
@property
def no_of_shells(self):
return self.data.abundance.shape[1]
@property
def no_of_elements(self):
return self.data.abundance.shape[0]
@property
def checked_list(self): # A boolean list to store the value of checkboxes.
_checked_list = []
for check in self.checks:
_checked_list.append(check.value)
return _checked_list
[docs] def create_widgets(self):
"""Create widget components in GUI and register callbacks for widgets."""
self.dpd_shell_no = ipw.Dropdown(
options=list(range(1, self.no_of_shells + 1)),
description="Shell No. ",
value=1,
layout=ipw.Layout(width="160px"),
)
self.dpd_shell_no.observe(self.dpd_shell_no_eventhandler, "value")
self.btn_prev = ipw.Button(
icon="chevron-left",
disabled=True,
layout=ipw.Layout(width="30px", height="30px"),
)
self.btn_prev.on_click(self.on_btn_prev)
self.btn_next = ipw.Button(
icon="chevron-right", layout=ipw.Layout(width="30px", height="30px")
)
self.btn_next.on_click(self.on_btn_next)
self.checks = [
ipw.Checkbox(
indent=False,
icon="lock",
layout=ipw.Layout(
width="30px",
),
)
for element in self.data.elements
]
self.input_items = [
ipw.BoundedFloatText(min=0, max=1, step=0.01, description=element)
for element in self.data.elements
]
for i in range(self.no_of_elements):
self.input_items[i].observe(self.input_item_eventhandler, "value")
self.input_items[i].index = i
self.checks[i].observe(self.check_eventhandler, "value")
self.checks[i].index = i
self.btn_norm = ipw.Button(
description="Normalize",
icon="cog",
layout=ipw.Layout(width="100px", margin="0 0 0 50px"),
)
self.btn_norm.on_click(self.on_btn_norm)
self.norm_warning = ipw.Valid(
value=False,
readout="Unnormalized",
style={"description_width": "initial"},
layout=ipw.Layout(visibility="hidden"),
)
self.symb_warning = ipw.Valid(
value=False, layout=ipw.Layout(visibility="hidden")
)
self.input_symb = ipw.Text(
description="Element: ",
style={"description_width": "initial"},
placeholder="symbol",
layout=ipw.Layout(width="125px"),
)
self.input_symb.observe(self.input_symb_eventhandler, "value")
self.btn_add_element = ipw.Button(
icon="plus-square",
description="Add",
disabled=True,
layout=ipw.Layout(width="60px"),
)
self.btn_add_element.on_click(self.on_btn_add_element)
self.irs_shell_range = ipw.IntRangeSlider(
min=1,
max=self.no_of_shells,
step=1,
description="Shell No. ",
disabled=True,
style={"description_width": "initial"},
continuous_update=False,
layout=ipw.Layout(margin="5px 0 0 0"),
)
self.irs_shell_range.observe(self.irs_shell_range_eventhandler, "value")
self.btn_add_shell = ipw.Button(
icon="plus-square",
description="Add",
disabled=True,
layout=ipw.Layout(
width="80px",
),
)
self.btn_add_shell.on_click(self.on_btn_add_shell)
self.input_v_start = ipw.FloatText(
min=0,
description="Add shell(s) with velocity range (km/s): ",
style={"description_width": "initial"},
layout=ipw.Layout(
width="320px",
),
)
self.input_v_end = ipw.FloatText(
min=0,
description="to",
style={"description_width": "initial"},
layout=ipw.Layout(width="110px"),
)
self.input_v_start.observe(self.input_v_eventhandler, "value")
self.input_v_end.observe(self.input_v_eventhandler, "value")
self.overwrite_warning = ipw.HTML(
value="<font color=darkred><b>Warning:</b></font> Existing shell(s) will be overwritten!",
layout=ipw.Layout(visibility="hidden", margin="0 0 0 10px"),
)
self.btn_output = ipw.Button(
description="Output CSVY File",
)
self.btn_output.on_click(self.on_btn_output)
self.input_path = ipw.Text(
description="File path: ", placeholder="Input file name or path"
)
self.input_i_time_0 = ipw.FloatText(
description="Isotope time_0 (day): ",
style={"description_width": "initial"},
)
self.ckb_overwrite = ipw.Checkbox(
description="overwrite",
indent=False,
)
self.tbs_scale = ipw.ToggleButtons(
options=["Linear", "Log"],
description="Scale of yaxes: ",
style={"description_width": "initial"},
value="Linear",
)
self.tbs_scale.observe(self.tbs_scale_eventhandler, "value")
self.rbs_single_apply = ipw.RadioButtons(
options=["Only selected shell"],
layout=ipw.Layout(margin="10px 0 0 0"),
)
self.rbs_single_apply.observe(
self.rbs_single_apply_eventhandler, "value"
)
self.rbs_multi_apply = ipw.RadioButtons(
options=["A range of shells: "],
index=None,
layout=ipw.Layout(width="130px", margin="10px 0 10px 0"),
)
self.rbs_multi_apply.observe(self.rbs_multi_apply_eventhandler, "value")
[docs] def update_input_item_value(self, index, value):
"""Update the value of the widget in the list of abundance inputs.
Keep two decimal places for displayed value and disable
`input_item_eventhandler` while changing the value.
Parameters
----------
index : int
The index of the widget in the list of abundance inputs.
value : float
New abundance value.
"""
self._trigger = False
# `input_items` is the list of abundance input widgets.
self.input_items[index].value = float("{:.2e}".format(value))
self._trigger = True
[docs] def read_abundance(self):
"""Read abundances data in DataFrame to input items box when
shell No. changes.
"""
for i in range(self.no_of_elements):
value = self.data.abundance.iloc[i, self.shell_no - 1]
self.update_input_item_value(i, value)
[docs] def bound_locked_sum_to_1(self, index):
"""Ensure the sum of locked abundances is no more than 1. If the
locked sum is more than 1, calculate the maximum with the sum no
more than 1 and return it.
Parameters
----------
index : int
The index of the widget in the list of abundance inputs.
"""
locked_mask = np.array(self.checked_list)
back_value = self.data.abundance.iloc[
index, self.shell_no - 1
] # abundance value in back end (DataFrame)
front_value = self.input_items[
index
].value # abundance value in front end (widget)
locked_sum = (
self.data.abundance.loc[locked_mask, self.shell_no - 1].sum()
- back_value
+ front_value
)
if locked_sum > 1:
new = 1 - (locked_sum - front_value)
self.data.abundance.iloc[index, self.shell_no - 1] = new
self.update_input_item_value(index, new)
self.update_abundance_plot(index)
[docs] def update_abundance_plot(self, index):
"""Update the abundance line of certain element in the plot.
Parameters
----------
index : int
The index of the widget in the list of abundance inputs.
"""
y = self.data.abundance.iloc[index]
self.fig.data[index + 2].y = np.append(y, y.iloc[-1])
[docs] def update_front_end(self):
"""Update checkbox widgets, input widgets and plot in the front
end when selected shell No. is changed.
"""
# Update checkboxes, input boxes and plot.
for check in self.checks:
check.value = False
self.read_abundance()
self.density_editor.read_density()
with self.fig.batch_update():
# Change bar diagonal
x = list(self.fig.data[0].x)
width = list(self.fig.data[0].width)
x_inner = self.data.velocity[self.shell_no - 1].value
x_outer = self.data.velocity[self.shell_no].value
x[0] = (x_inner + x_outer) / 2
self.fig.data[0].x = x
width[0] = x_outer - x_inner
self.fig.data[0].width = width
[docs] def update_bar_diagonal(self):
"""Update bar diagonal (and shell no dropdown) when the range
of shells changed.
"""
if self.irs_shell_range.disabled:
x = [self.fig.data[0].x[0]]
width = [self.fig.data[0].width[0]]
y = [1]
else:
self.shell_no = self.irs_shell_range.value[0]
self.btn_next.disabled = True
self.btn_prev.disabled = True
(start_shell_no, end_shell_no) = self.irs_shell_range.value
x_inner = self.data.velocity[start_shell_no - 1].value
x_outer = self.data.velocity[end_shell_no].value
x = [self.fig.data[0].x[0], (x_outer + x_inner) / 2]
width = [self.fig.data[0].width[0], x_outer - x_inner]
y = [1, 1]
with self.fig.batch_update():
self.fig.data[0].x = x
self.fig.data[0].width = width
self.fig.data[0].y = y
[docs] def update_line_color(self):
"""Update line color in the plot according to colormap."""
colorscale = transition_colors(self.no_of_elements, self.plot_cmap)
for i in range(self.no_of_elements):
self.fig.data[2 + i].line.color = colorscale[i]
[docs] def overwrite_existing_shells(self, v_0, v_1):
"""Judge whether the existing shell(s) will be overwritten when
inserting a new shell within the entered velocity range.
Parameters
----------
v_0 : float
The velocity of inner boundary.
v_1 : float
The velocity of outer boundary.
Returns
-------
bool
True if the existing shell will be overwritten, False otherwise.
"""
v_vals = self.data.velocity.value
position_0 = np.searchsorted(v_vals, v_0)
position_1 = np.searchsorted(v_vals, v_1)
index_0 = (
position_0 - 1
if np.isclose(v_vals[position_0 - 1], v_0)
else position_0
)
index_1 = (
position_1 - 1
if np.isclose(v_vals[position_1 - 1], v_1)
else position_1
)
if (index_1 - index_0 > 1) or (
index_1 - index_0 == 1 and not np.isclose(v_vals[index_0], v_0)
):
return True
else:
return False
[docs] def on_btn_add_shell(self, obj):
"""Add new shell with given boundary velocities. Triggered if
the button is clicked.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
v_start = self.input_v_start.value
v_end = self.input_v_end.value
v_vals = self.data.velocity.value
position_0 = np.searchsorted(v_vals, v_start)
position_1 = np.searchsorted(v_vals, v_end)
start_index = (
int(position_0 - 1)
if np.isclose(v_vals[position_0 - 1], v_start)
else int(position_0)
)
end_index = (
int(position_1 - 1)
if np.isclose(v_vals[position_1 - 1], v_end)
else int(position_1)
)
if (
end_index < self.no_of_shells
and np.isclose(v_vals[start_index], v_start)
and np.isclose(v_vals[end_index], v_end)
and end_index - start_index == 1
):
return
if start_index < self.no_of_shells and np.isclose(
v_vals[start_index], v_start
):
new_shell_abundances = self.data.abundance[start_index]
else:
index = min(start_index - 1, self.no_of_shells - 1)
new_shell_abundances = self.data.abundance[max(index, 0)]
# Delete the overwritten shell (abundances and velocities).
if end_index < len(v_vals) and np.isclose(v_vals[end_index], v_end):
# New shell will overwrite the original shell that ends at v_end.
v_vals = np.delete(v_vals, end_index)
self.data.abundance.drop(max(0, end_index - 1), 1, inplace=True)
# Insert new velocities calculate new densities according
# to new velocities through interpolation.
v_vals = np.insert(v_vals, [start_index, end_index], [v_start, v_end])
v_vals = np.delete(v_vals, slice(start_index + 1, end_index + 1))
self.data.density = (
np.interp(
v_vals,
self.data.velocity[1:].value,
self.data.density[1:].value,
)
* self.data.density.unit
)
self.data.velocity = v_vals * self.data.velocity.unit
# Change abundances after adding new shell.
if start_index != end_index:
self.data.abundance.insert(start_index, "", new_shell_abundances)
self.data.abundance.drop(
self.data.abundance.iloc[:, start_index : end_index - 1],
1,
inplace=True,
)
else:
if start_index == 0:
self.data.abundance.insert(0, "new", new_shell_abundances)
self.data.abundance.insert(
0, "gap", new_shell_abundances
) # Add a shell to fill the gap.
else:
self.data.abundance.insert(
start_index - 1, "new", new_shell_abundances
)
self.data.abundance.insert(
start_index - 1, "gap", new_shell_abundances
) # Add a shell to fill the gap with original abundances
self.data.abundance.columns = range(self.no_of_shells)
# Update data and x axis in plot.
with self.fig.batch_update():
self.fig.layout.xaxis.autorange = True
self.fig.data[1].x = self.data.velocity
self.fig.data[1].y = np.append(
self.data.density[1:], self.data.density[-1]
)
for i in range(self.no_of_elements):
self.fig.data[i + 2].x = self.data.velocity
self.update_abundance_plot(i)
self.dpd_shell_no.options = list(range(1, self.no_of_shells + 1))
self.update_bar_diagonal()
self.update_front_end()
self.irs_shell_range.max = self.no_of_shells
self.overwrite_warning.layout.visibility = "hidden"
[docs] def tbs_scale_eventhandler(self, obj):
"""Switch the scale type of y axis between linear mode and log
mode. Triggered if the toggle button is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
scale_mode = obj.new
if scale_mode == "Linear":
self.fig.update_layout(
yaxis=dict(
type="linear",
range=[0, 1],
),
yaxis2=dict(type="linear"),
)
else:
self.fig.update_layout(
yaxis=dict(
type="log",
range=[-8, 0],
),
yaxis2=dict(type="log"),
)
[docs] def input_item_eventhandler(self, obj):
"""Update the data and the widget when it gets new abundance
input. Triggered if the abundance input is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
if self._trigger:
item_index = obj.owner.index
is_locked = self.checks[item_index]
if is_locked:
self.bound_locked_sum_to_1(item_index)
self.data.abundance.iloc[
item_index, self.shell_no - 1
] = obj.owner.value
if self.rbs_multi_apply.index is None:
self.update_abundance_plot(item_index)
else:
self.apply_to_multiple_shells(item_index)
if np.isclose(self.data.abundance.iloc[:, self.shell_no - 1].sum(), 1):
self.norm_warning.layout.visibility = "hidden"
else:
self.norm_warning.layout.visibility = "visible"
[docs] def check_eventhandler(self, obj):
"""Triggered if the checkbox is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
item_index = obj.owner.index
if obj.new == True:
self.bound_locked_sum_to_1(item_index)
[docs] def dpd_shell_no_eventhandler(self, obj):
"""Make the data in widgets correspond with the selected shell.
Triggered if the dropdown value is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
# Disable "previous" and "next" buttons when shell no comes to boundaries.
if obj.new == 1:
self.btn_prev.disabled = True
else:
self.btn_prev.disabled = False
if obj.new == self.no_of_shells:
self.btn_next.disabled = True
else:
self.btn_next.disabled = False
self.update_front_end()
[docs] def on_btn_prev(self, obj):
"""Move to previous shell.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
self.shell_no -= 1
[docs] def on_btn_next(self, obj):
"""Move to next shell.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
self.shell_no += 1
[docs] def on_btn_norm(self, obj):
"""Normalize unlocked abundances to 1. Triggered if the
normalize button is clicked.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
locked_mask = np.array(self.checked_list)
locked_sum = self.data.abundance.loc[
locked_mask, self.shell_no - 1
].sum()
unlocked_arr = self.data.abundance.loc[~locked_mask, self.shell_no - 1]
# if abundances are all zero
if unlocked_arr.sum() == 0:
return
self.data.abundance.loc[~locked_mask, self.shell_no - 1] = (
(1 - locked_sum) * unlocked_arr / unlocked_arr.sum()
)
self.read_abundance()
for i in range(self.no_of_elements):
if self.rbs_multi_apply.index is None:
# Only normalize selected shell
self.update_abundance_plot(i)
else:
self.apply_to_multiple_shells(i)
@debounce(0.5)
def input_symb_eventhandler(self, obj):
"""Judge whether the input symbol is valid. Triggered after 0.5s
when the symbol input is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
element_symbol_string = obj.new.capitalize()
if element_symbol_string == "":
self.symb_warning.layout.visibility = "hidden"
self.btn_add_element.disabled = True
return
if element_symbol_string in self.data.elements:
self.symb_warning.layout.visibility = "visible"
self.btn_add_element.disabled = True
self.symb_warning.readout = "Already exists!"
return
try:
if is_valid_nuclide_or_elem(element_symbol_string):
self.symb_warning.layout.visibility = "hidden"
self.btn_add_element.disabled = False
return
except RuntimeError:
pass
self.symb_warning.layout.visibility = "visible"
self.btn_add_element.disabled = True
self.symb_warning.readout = "invalid"
[docs] def on_btn_add_element(self, obj):
"""Add new element and update the display in the front end.
Triggered if the add button is clicked.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
element_symbol_string = self.input_symb.value.capitalize()
if element_symbol_string in Z_DICT.values():
z = elem_to_Z(element_symbol_string)
self.data.abundance.loc[(z, ""), :] = 0
else:
nuc = Nuclide(element_symbol_string)
mass_no = nuc.A
z = nuc.Z
self.data.abundance.loc[(z, mass_no), :] = 0
self.data.abundance.sort_index(inplace=True)
# Add new BoundedFloatText control and Checkbox control.
item = ipw.BoundedFloatText(min=0, max=1, step=0.01)
check = ipw.Checkbox(indent=False, layout=ipw.Layout(width="30px"))
item.index = self.no_of_elements - 1
check.index = self.no_of_elements - 1
item.observe(self.input_item_eventhandler, "value")
check.observe(self.check_eventhandler, "value")
self.input_items.append(item)
self.checks.append(check)
# Keep the order of description same with atomic number
self.data.elements = self.data.get_symbols()
for i in range(self.no_of_elements):
self.input_items[i].description = self.data.elements[i]
self.box_editor.children = [
ipw.VBox(self.input_items),
ipw.VBox(self.checks),
]
with self.fig.batch_update():
# Add new trace to plot.
self.fig.add_scatter(
x=self.data.velocity, # convert to km/s
y=[0] * (self.no_of_shells + 1),
mode="lines+markers",
name=element_symbol_string,
line=dict(shape="hv"),
)
# Sort the legend in atomic order.
fig_data_lst = list(self.fig.data)
fig_data_lst.insert(
np.argwhere(self.data.elements == element_symbol_string)[0][0]
+ 2,
self.fig.data[-1],
)
self.fig.data = fig_data_lst[:-1]
self.update_line_color()
self.read_abundance()
# Clear symbol input box.
self.input_symb.value = ""
[docs] def apply_to_multiple_shells(self, item_index):
"""Apply the changed abundances to specified range of shell(s).
Parameters
----------
item_index : int
The index of the widget in the list of abundance inputs.
"""
start_index = self.irs_shell_range.value[0] - 1
end_index = self.irs_shell_range.value[1]
applied_shell_index = self.shell_no - 1
self.data.abundance.iloc[
item_index, start_index:end_index
] = self.data.abundance.iloc[item_index, applied_shell_index]
self.update_abundance_plot(item_index)
[docs] def input_v_eventhandler(self, obj):
"""Judge whether the input velocity range is valid. Triggered if the
velocity input is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
v_start = self.input_v_start.value
v_end = self.input_v_end.value
if v_start >= v_end or v_start < 0 or v_end < 0:
self.btn_add_shell.disabled = True
return
else:
self.btn_add_shell.disabled = False
# Whether overwrite existing shells
if self.overwrite_existing_shells(v_start, v_end):
self.overwrite_warning.layout.visibility = "visible"
else:
self.overwrite_warning.layout.visibility = "hidden"
[docs] def on_btn_output(self, obj):
"""Triggered if the output button is clicked.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
path = self.input_path.value
overwrite = self.ckb_overwrite.value
self.to_csvy(path, overwrite)
[docs] def rbs_single_apply_eventhandler(self, obj):
"""Switch to single shell editing mode. Triggered if the
first radio button is selected.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
self.abundance_note.layout.visibility = "hidden"
self.rbs_multi_apply.unobserve(
self.rbs_multi_apply_eventhandler, "value"
)
self.rbs_multi_apply.index = None
self.rbs_multi_apply.observe(self.rbs_multi_apply_eventhandler, "value")
self.dpd_shell_no.disabled = False
self.btn_next.disabled = False
self.btn_prev.disabled = False
self.irs_shell_range.disabled = True
self.update_bar_diagonal()
[docs] def rbs_multi_apply_eventhandler(self, obj):
"""Switch to multi-shells editing mode. Triggered if the
second radio button is selected.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
self.abundance_note.layout.visibility = "visible"
self.shell_no = self.irs_shell_range.value[0]
self.rbs_single_apply.unobserve(
self.rbs_single_apply_eventhandler, "value"
)
self.rbs_single_apply.index = None
self.rbs_single_apply.observe(
self.rbs_single_apply_eventhandler, "value"
)
# self.irs_shell_range.value = [self.shell_no, self.shell_no]
self.dpd_shell_no.disabled = True
self.btn_next.disabled = True
self.btn_prev.disabled = True
self.irs_shell_range.disabled = False
self.update_bar_diagonal()
[docs] def irs_shell_range_eventhandler(self, obj):
"""Select the velocity range of new shell and highlight the range
in the plot. Triggered if the shell range slider is changed.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
self.update_bar_diagonal()
[docs] def generate_abundance_density_plot(self):
"""Generate abundance and density plot in different shells."""
title = "Abundance/Density vs Velocity"
abundance = self.data.abundance
velocity = self.data.velocity
density = self.data.density
# Bar Diagonal
self.fig.add_trace(
go.Bar(
x=[(velocity[0].value + velocity[1].value) / 2],
y=[1],
width=[velocity[1].value - velocity[0].value],
name="Selected shell",
marker=dict(
color="rgb(253,205,172)",
),
hoverinfo="none",
)
)
self.fig.add_trace(
go.Scatter(
x=velocity,
y=np.append(density[1:], density[-1]),
mode="lines+markers",
name="<b>Density</b>",
yaxis="y2",
line=dict(color="black", shape="hv"),
marker_symbol="square",
),
)
for i in range(self.no_of_elements):
self.fig.add_trace(
go.Scatter(
x=velocity,
y=np.append(abundance.iloc[i], abundance.iloc[i, -1]),
mode="lines+markers",
line=dict(shape="hv"),
name=self.data.elements[i],
),
)
self.fig.update_layout(
xaxis=dict(
title="Velocity (km/s)",
tickformat="f",
),
yaxis=dict(
title="Fractional Abundance",
exponentformat="e",
range=[0, 1],
),
yaxis2=dict(
title="Density (g/cm^3)",
exponentformat="e",
overlaying="y",
side="right",
),
height=500,
title=title,
hovermode="closest",
legend=dict(
x=1.15,
),
)
[docs] def display(self, cmap="jet"):
"""Display the GUI.
Parameters
----------
cmap : str, default: "jet", optional
String defines the colormap used in abundance density plot.
Returns
-------
ipywidgets.widgets.widget_box.VBox
A box that contains all the widgets in the GUI.
"""
if not is_notebook():
print("Please use a notebook to display the widget")
else:
# --------------Combine widget components--------------
self.box_editor = ipw.HBox(
[
ipw.VBox(self.input_items),
ipw.VBox(
self.checks, layout=ipw.Layout(margin="0 0 0 10px")
),
]
)
box_add_shell = ipw.HBox(
[
self.input_v_start,
self.input_v_end,
self.btn_add_shell,
self.overwrite_warning,
],
layout=ipw.Layout(margin="0 0 0 50px"),
)
box_head = ipw.HBox(
[self.dpd_shell_no, self.btn_prev, self.btn_next, box_add_shell]
)
box_add_element = ipw.HBox(
[self.input_symb, self.btn_add_element, self.symb_warning],
layout=ipw.Layout(margin="0 0 0 80px"),
)
help_note = ipw.HTML(
value="<p style='text-indent: 40px'>* Select a checkbox "
"to lock the abundance of corresponding element. </p>"
"<p style='text-indent: 40px'> On clicking the 'Normalize' "
"button, the locked abundance(s) will <b>not be normalized</b>."
" </p>",
indent=True,
)
self.abundance_note = ipw.HTML(
description="(The following abundances are for the innermost "
"shell in selected range.)",
layout=ipw.Layout(visibility="hidden"),
style={"description_width": "initial"},
)
box_norm = ipw.HBox([self.btn_norm, self.norm_warning])
box_apply = ipw.VBox(
[
ipw.Label(value="Apply abundance(s) to:"),
self.rbs_single_apply,
ipw.HBox(
[
self.rbs_multi_apply,
self.irs_shell_range,
self.abundance_note,
]
),
],
layout=ipw.Layout(margin="0 0 15px 50px"),
)
box_features = ipw.VBox([box_norm, help_note])
box_abundance = ipw.VBox(
[
box_apply,
ipw.HBox([self.box_editor, box_features]),
box_add_element,
]
)
box_density = self.density_editor.display()
main_tab = ipw.Tab([box_abundance, box_density])
main_tab.set_title(0, "Edit Abundance")
main_tab.set_title(1, "Edit Density")
hint = ipw.HTML(
value="<b><font size='3'>Save model as file: </font></b>"
)
box_output = ipw.VBox(
[
hint,
self.input_i_time_0,
ipw.HBox(
[self.input_path, self.btn_output, self.ckb_overwrite]
),
]
)
# Initialize the widget and plot colormap
self.plot_cmap = cmap
self.update_line_color()
self.read_abundance()
self.density_editor.read_density()
return ipw.VBox(
[
self.tbs_scale,
self.fig,
box_head,
main_tab,
box_output,
self.error_view,
]
)
[docs] @error_view.capture(clear_output=True)
def to_csvy(self, path, overwrite):
"""Output CSVY file on the specified path.
Parameters
----------
path : str
Output path.
overwrite : bool
True if overwriting, False otherwise.
"""
posix_path = Path(path)
posix_path = posix_path.with_suffix(".csvy")
if posix_path.exists() and not overwrite:
raise FileExistsError(
"The file already exists. Click the 'overwrite' checkbox to overwrite it."
)
else:
self.write_yaml_portion(posix_path)
self.write_csv_portion(posix_path)
[docs] @error_view.capture(clear_output=True)
def write_yaml_portion(self, path):
"""Write the YAML portion of the output file.
Parameters
----------
path : pathlib.PosixPath
"""
name = path.name
d_time_0 = self.data.density_t_0
i_time_0 = self.input_i_time_0.value * u.day
custom_yaml = CustomYAML(
name,
d_time_0,
i_time_0,
self.data.velocity[0],
self.data.velocity[-1],
)
custom_yaml.create_fields_dict(self.data.elements)
with path.open("w") as f:
yaml_output = yaml.dump(custom_yaml, sort_keys=False)
# Add YAML delimiter
yaml_output_snippets = yaml_output.split("\n")
yaml_output_snippets[0] = yaml_output_snippets[-1] = YAML_DELIMITER
yaml_output = "\n".join(yaml_output_snippets) + "\n"
f.write(yaml_output)
print("Saved Successfully!")
[docs] def write_csv_portion(self, path):
"""Write the CSV portion of the output file.
Parameters
----------
path : pathlib.PosixPath
"""
try:
data = self.data.abundance.T
data.columns = self.data.elements
first_row = [0] * self.no_of_elements
data.loc[-1] = first_row
data.index += 1 # shifting index
data.sort_index(inplace=True)
formatted_v = pd.Series(self.data.velocity.value).apply(
lambda x: "%.3e" % x
)
# Make sure velocity is within the boundary.
formatted_v[0] = self.data.velocity.value[0]
formatted_v[-1] = self.data.velocity.value[-1]
density = self.data.density
data.insert(0, "velocity", formatted_v)
data.insert(1, "density", density)
data.to_csv(path, mode="a", index=False)
except pd.errors.EmptyDataError:
data = None
[docs] @classmethod
def from_csvy(cls, fpath):
"""Create a new CustomAbundanceWidget instance with data from CSVY file.
Parameters
----------
fpath : str
the path of CSVY file.
Returns
-------
CustomAbundanceWidget
"""
widget_data = CustomAbundanceWidgetData.from_csvy(fpath)
return cls(widget_data)
[docs] @classmethod
def from_yml(cls, fpath):
"""Create a new CustomAbundanceWidget instance with data from YAML file.
Parameters
----------
fpath : str
The path of YAML file.
Returns
-------
CustomAbundanceWidget
"""
widget_data = CustomAbundanceWidgetData.from_yml(fpath)
return cls(widget_data)
[docs] @classmethod
def from_hdf(cls, fpath):
"""Create a new CustomAbundanceWidget instance with data from HDF file.
Parameters
----------
fpath : str
the path of HDF file.
Returns
-------
CustomAbundanceWidget
"""
widget_data = CustomAbundanceWidgetData.from_hdf(fpath)
return cls(widget_data)
[docs] @classmethod
def from_simulation(cls, sim):
"""Create a new CustomAbundanceWidget instance from a Simulation object.
Parameters
----------
sim : Simulation
Returns
-------
CustomAbundanceWidget
"""
widget_data = CustomAbundanceWidgetData.from_simulation(sim)
return cls(widget_data)
[docs]class DensityEditor:
"""Widget to edit density profile of the model.
It provides an interface to allow the user directly change
the density, or calculate the density with given type and
parameters.
Attributes
----------
shell_no : int
The selected shell number.
_trigger : bool
If False, disable the callback when density input is changed.
"""
def __init__(self, widget_data, fig, shell_no_widget):
"""Initialize DensityEditor with data and widget components.
Parameters
----------
widget_data : CustomAbundanceWidgetData
Data in the custom abundance widget.
fig : plotly.graph_objs._figurewidget.FigureWidget
The figure object of density plot.
shell_no_widget : ipywidgets.widgets.widget_selection.Dropdown
A widget to record the selected shell number.
"""
self.data = widget_data
self.fig = fig
self.shell_no_widget = shell_no_widget
self.create_widgets()
self._trigger = True
@property
def shell_no(self):
return self.shell_no_widget.value
[docs] def create_widgets(self):
"""Create widget components in density editor GUI and register
callbacks for widgets.
"""
self.input_d = ipw.FloatText(
description="Density",
layout=ipw.Layout(
width="230px",
),
)
self.input_d.observe(self.input_d_eventhandler, "value")
self.input_d_time_0 = ipw.FloatText(
value=self.data.density_t_0.value,
description="Density time_0 (day): ",
style={"description_width": "initial"},
layout=ipw.Layout(margin="0 0 20px 0"),
)
self.input_d_time_0.observe(self.input_d_time_0_eventhandler, "value")
self.input_d_time_0 = ipw.FloatText(
value=self.data.density_t_0.value,
description="Density time_0 (day): ",
style={"description_width": "initial"},
layout=ipw.Layout(margin="0 0 20px 0"),
)
self.input_d_time_0.observe(self.input_d_time_0_eventhandler, "value")
self.dpd_dtype = ipw.Dropdown(
options=["-", "uniform", "exponential", "power_law"],
description="Density type: ",
style={"description_width": "initial"},
layout=ipw.Layout(width="300px"),
)
self.dpd_dtype.observe(self.dpd_dtype_eventhandler, "value")
self.input_rho_0 = ipw.FloatText(
description="rho_0", layout=ipw.Layout(width="300px")
)
self.input_exp = ipw.FloatText(
description="exponent", layout=ipw.Layout(width="300px")
)
self.input_v_0 = ipw.FloatText(
description="v_0", layout=ipw.Layout(width="300px")
)
self.input_value = ipw.FloatText(
description="value", layout=ipw.Layout(width="300px")
)
self.btn_calculate = ipw.Button(
icon="calculator",
description="Calculate Density",
layout=ipw.Layout(width="300px"),
)
self.btn_calculate.on_click(self.on_btn_calculate)
self.uniform_box = ipw.HBox(
[self.input_value, ipw.Label(value="g cm^3")]
)
# Formula to compute density profile
form_exp = ipw.HTMLMath(
value=r"$$\rho = \rho_0 \times \exp \left( -\frac{v}{v_0} \right)$$",
layout=ipw.Layout(margin="0 0 0 100px"),
)
form_pow = ipw.HTMLMath(
value=r"$$\rho = \rho_0 \times \left( \frac{v}{v_0} \right)^n$$",
layout=ipw.Layout(margin="0 0 0 100px"),
)
self.exp_box = ipw.VBox(
[
form_exp,
ipw.HBox([self.input_rho_0, ipw.Label(value="g cm^3")]),
ipw.HBox([self.input_v_0, ipw.Label(value="km/s")]),
]
)
self.pow_box = ipw.VBox(
[
form_pow,
ipw.HBox([self.input_rho_0, ipw.Label(value="g cm^3")]),
ipw.HBox([self.input_v_0, ipw.Label(value="km/s")]),
self.input_exp,
]
)
[docs] def read_density(self):
"""Read density data in DataFrame to density input box when
shell No. changes.
"""
dvalue = self.data.density[self.shell_no].value
self._trigger = False
self.input_d.value = float("{:.3e}".format(dvalue))
self._trigger = True
[docs] def update_density_plot(self):
"""Update the density line in the plot."""
y = np.append(self.data.density[1:], self.data.density[-1])
self.fig.data[1].y = y
[docs] def input_d_eventhandler(self, obj):
"""Update the data and the widgets when the widget gets new
density input.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
if self._trigger:
new_value = obj.new
self.data.density[self.shell_no] = (
new_value * self.data.density.unit
)
self.update_density_plot()
def input_d_time_0_eventhandler(self, obj):
"""Update density time 0 data when the widget gets new input.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
new_value = obj.new
self.data.density_t_0 = new_value * self.data.density_t_0.unit
[docs] def input_d_time_0_eventhandler(self, obj):
"""Update density time 0 data when the widget gets new input.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
"""
new_value = obj.new
self.data.density_t_0 = new_value * self.data.density_t_0.unit
dtype_out = ipw.Output()
[docs] @dtype_out.capture(clear_output=True)
def dpd_dtype_eventhandler(self, obj):
"""Display the input boxes of the specified density type.
Triggered if the density type dropdown is changed.
Parameters
----------
obj : traitlets.utils.bunch.Bunch
A dictionary holding the information about the change.
Returns
-------
ipywidgets.widgets.widget_box.VBox
A box widget that contains the input boxes of certain density
type parameters.
"""
if obj.new == "uniform":
display(self.uniform_box)
elif obj.new == "exponential":
display(self.exp_box)
elif obj.new == "power_law":
display(self.pow_box)
[docs] def on_btn_calculate(self, obj):
"""Calculate density according to density parameters input.
Triggered if the density calculate button is clicked.
Parameters
----------
obj : ipywidgets.widgets.widget_button.Button
The clicked button instance.
"""
dtype = self.dpd_dtype.value
density = self.data.density
velocity = self.data.velocity
if dtype == "-":
return
if dtype == "uniform":
if self.input_value.value == 0:
return
self.data.density = (
self.input_value.value * density.unit * np.ones(len(density))
)
else:
if self.input_v_0.value == 0 or self.input_rho_0.value == 0:
return
adjusted_velocity = velocity.insert(0, 0)
v_middle = (
adjusted_velocity[1:] * 0.5 + adjusted_velocity[:-1] * 0.5
)
v_0 = self.input_v_0.value * velocity.unit
rho_0 = self.input_rho_0.value * density.unit
if dtype == "exponential":
self.data.density = calculate_exponential_density(
v_middle, v_0, rho_0
)
elif dtype == "power_law":
exponent = self.input_exp.value
self.data.density = calculate_power_law_density(
v_middle, v_0, rho_0, exponent
)
self.read_density()
self.update_density_plot()
[docs] def display(self):
"""Display the GUI.
Returns
-------
ipywidgets.widgets.widget_box.VBox
A box that contains all the widgets in the GUI.
"""
hint1 = ipw.HTML(
value="<font size='3'>1) Edit density of the selected shell:</font>"
)
hint2 = ipw.HTML(
value="<font size='3'>2) Edit densities for all shells:</font>"
)
d_box = ipw.HBox(
[self.input_d, ipw.Label(value="g/cm^3")],
layout=ipw.Layout(margin="0 0 20px 0"),
)
return ipw.VBox(
[
self.input_d_time_0,
hint1,
d_box,
hint2,
self.dpd_dtype,
self.dtype_out,
self.btn_calculate,
]
)