# Copyright (C) 2023 - 2025 ANSYS, Inc. and/or its affiliates.
# SPDX-License-Identifier: MIT
#
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import io
import typing
import numpy as np
import pandas as pd
from ansys.dyna.core.lib.card import Card, Field
from ansys.dyna.core.lib.field_writer import write_c_dataframe
from ansys.dyna.core.lib.format_type import format_type
from ansys.dyna.core.lib.io_utils import write_or_return
from ansys.dyna.core.lib.kwd_line_formatter import buffer_to_lines
from ansys.dyna.core.lib.parameters import ParameterSet
def _check_type(value):
global CHECK_TYPE
if CHECK_TYPE:
if not isinstance(value, pd.DataFrame):
raise TypeError("value must be a DataFrame")
[docs]
def try_initialize_table(card, name: str, **kwargs):
"""card is a TableCard or a TableCardGroup"""
if name is not None:
data = kwargs.get(name, None)
if data is not None:
card.table = data
return True
return False
[docs]
def get_first_row(fields: typing.List[Field], **kwargs) -> typing.Dict[str, typing.Any]:
"""Get the first row data from the kwargs."""
result = dict()
for field in fields:
if field.name in kwargs:
result[field.name] = kwargs[field.name]
if len(result) == 0:
return None
return result
class TableCard(Card):
def __init__(
self,
fields: typing.List[Field],
length_func,
active_func: typing.Callable = None,
name: str = None,
format: format_type = format_type.default,
**kwargs,
):
super().__init__(fields, active_func)
self._format = [(field.offset, field.width) for field in self._fields]
if length_func == None:
self._bounded = False
self._length_func = lambda: len(self.table)
else:
self._bounded = True
self._length_func = length_func
self._format_type = format
self._initialized = try_initialize_table(self, name, **kwargs)
if not self._initialized:
self._first_row = get_first_row(self._fields, **kwargs)
def _initialize(self, check: bool = False):
"""Lazy initialization routine for the data frame.
This can not be done in the constructor because the length function
might be unusable until after the keyword is fully initialized.
If the card is bounded, the table should be initialized with the
bounded length
If the card is not bounded, the table should be initialized either
using the input data, if it is given, or with exactly one row
if the constructor **kwargs included any of the fields used by
the table. This is called the "first row"
Since TableCard is used internally by TableCardGroup,
it could be initialized by the table card group, the first
row may contain fields used by other tables in the group.
"""
handle_first_row = self._first_row is not None
if self._bounded:
length = self._length_func()
self._initialize_data(length)
if length == 0:
handle_first_row = False
else:
initial_size = 1 if handle_first_row else 0
self._initialize_data(initial_size)
if handle_first_row:
for k, v in self._first_row.items():
if k in self._table:
self._table.loc[0, k] = v
self._first_row = None
self._initialized = True
@property
def table(self) -> pd.DataFrame:
if not self._initialized:
self._initialize()
return self._table
@table.setter
def table(self, value: pd.DataFrame):
_check_type(value)
self._table = pd.DataFrame()
for field in self._fields:
if field.name in value:
field_type = field.type
if field_type == float:
field_type = np.float64
elif field_type == int:
field_type = pd.Int32Dtype()
self._table[field.name] = value[field.name].astype(field_type)
else:
self._table[field.name] = self._make_column(field, len(value))
self._initialized = True
@property
def format(self) -> format_type:
return self._format_type
@format.setter
def format(self, value: format_type) -> None:
self._format_type = value
def _get_default_value(self, field: Field) -> typing.Optional[typing.Any]:
if field.value is not None:
return field.value
if field.type == float:
return np.nan
return None
def _make_column(self, field, length):
default_value = self._get_default_value(field)
if field.type == float:
arr = np.empty((length,))
arr[:] = default_value
return arr
elif field.type == str:
return [default_value] * length
elif field.type == int:
return pd.Series([default_value] * length, dtype=pd.Int32Dtype())
raise Exception("unexpected type")
def _initialize_data(self, length):
data = {}
num_fields = len(self._fields)
column_names = np.ndarray(num_fields, "object")
for index in range(num_fields):
field = self._fields[index]
value = self._make_column(field, length)
column_names[index] = field.name
data[field.name] = value
self._table = pd.DataFrame(data, columns=column_names)
def _get_row_values(self, index: int) -> list:
# Used by Duplicate Card Group only
if index >= len(self.table):
return [None] * len(self._fields)
values = []
for key in self.table.keys():
col = self.table[key]
val = col[index]
values.append(val)
return values
def _get_read_options(self):
fields = self._get_fields()
colspecs = [(field.offset, field.offset + field.width) for field in fields]
type_mapping = {float: np.float64, int: pd.Int32Dtype(), str: str}
dtype = {field.name: type_mapping[field.type] for field in fields}
names = [field.name for field in fields]
options = {"names": names, "colspecs": colspecs, "dtype": dtype, "comment": "$"}
return options
def _read_buffer_as_dataframe(
self, buffer: typing.TextIO, fields: typing.Iterable[Field], parameter_set: ParameterSet
) -> pd.DataFrame:
read_options = self._get_read_options()
df = pd.read_fwf(buffer, **read_options)
return df
def _get_fields(self) -> typing.List[Field]:
fields = self._fields
if self.format == format_type.long:
fields = self._convert_fields_to_long_format()
return fields
def _load_bounded_from_buffer(self, buf: typing.TextIO, parameter_set: ParameterSet) -> None:
read_options = self._get_read_options()
read_options["nrows"] = self._num_rows()
df = pd.read_fwf(buf, **read_options)
self._table = df
self._initialized = True
def _load_unbounded_from_buffer(self, buf: typing.TextIO, parameter_set: ParameterSet) -> None:
data_lines = buffer_to_lines(buf)
self._load_lines(data_lines, parameter_set)
def read(self, buf: typing.TextIO, parameter_set: ParameterSet = None) -> None:
if self.bounded:
self._initialized = True
self._load_bounded_from_buffer(buf, parameter_set)
else:
self._initialize_data(0)
self._initialized = True
self._load_unbounded_from_buffer(buf, parameter_set)
def _load_lines(self, data_lines: typing.List[str], parameter_set: ParameterSet) -> None:
fields = self._get_fields()
buffer = io.StringIO()
[(buffer.write(line), buffer.write("\n")) for line in data_lines]
buffer.seek(0)
self._table = self._read_buffer_as_dataframe(buffer, fields, parameter_set)
self._initialized = True
def write(
self,
format: typing.Optional[format_type] = None,
buf: typing.Optional[typing.TextIO] = None,
comment: typing.Optional[bool] = True,
) -> str:
if format == None:
format = self._format_type
def _write(buf: typing.TextIO):
if self._num_rows() > 0:
if comment:
buf.write(self._get_comment(format))
buf.write("\n")
write_c_dataframe(buf, self._fields, self.table, format)
return write_or_return(buf, _write)
@property
def bounded(self) -> bool:
return self._bounded
def _num_rows(self) -> int:
if not self.active:
return 0
return self._length_func()
def __repr__(self) -> str:
"""Returns a console-friendly representation of the desired parameters for the card"""
content_lines = []
content_lines.append(self._get_comment(self._format_type))
output = "\n".join(content_lines)
return "TableCard: \n" + output
