# RAD-tools - Sandbox (mainly condense matter plotting).
# Copyright (C) 2022-2024 Andrey Rybakov
#
# e-mail: anry@uv.es, web: rad-tools.org
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import numpy as np
from termcolor import colored
__all__ = ["print_2d_array"]
[docs]
def print_2d_array(
array,
fmt=">.2f",
highlight=False,
print_result=True,
borders=True,
shift=0,
header_row=None,
footer_row=None,
header_column=None,
footer_column=None,
):
r"""
Print 1D and 2D arrays in the terminal.
.. versionadded:: 0.7
.. versionchanged:: 0.7.11 Renamed from ``print_2D_array``
Parameters
----------
array : (N,) or (N, M) |array_like|_
Array to be printed.
fmt : str, default ">.2f"
Format string.
highlight : bool, default False
Whether to highlight positive and negative values.
Only works for real-valued arrays.
.. versionchanged:: 0.7.11 Renamed from ``posneg``
print_result : bool, default True
Whether to print the result or return it as a string.
borders : bool, default True
Whether to print borders around the array.
.. versionadded:: 0.7.11
shift : int, default 0
Shifts the array to the right by ``shift`` columns.
.. versionadded:: 0.7.11
header_row : list, optional
Header of the table (top). Has to have the same length as the number of columns.
Has to had one more element for each if ``header_column`` or ``footer_column`` is not None.
.. versionadded:: 0.8.0
footer_row : list, optional
Footer of the table (bottom). Has to have the same length as the number of columns.
Has to had one more element for each if ``header_column`` or ``footer_column`` is not None.
.. versionadded:: 0.8.0
header_column : list, optional
Header of the table (left). Has to have the same length as the number of rows.
.. versionadded:: 0.8.0
footer_column : list, optional
Footer of the table (right). Has to have the same length as the number of rows.
.. versionadded:: 0.8.0
Returns
-------
string : str
String representation of the array.
Returned only if ``print_result`` is False.
"""
top_border = ("┌", "┬", "┐")
middle_border = ("├", "┼", "┤")
bottom_border = ("└", "┴", "┘")
if borders:
vert = "│"
space_vert = f" {vert}"
else:
vert = ""
space_vert = ""
array = np.array(array)
if (len(array.shape) == 1 and array.shape[0] != 0) or (
len(array.shape) == 2 and array.shape[1] != 0
):
# Convert 1D array to 2D array
if len(array.shape) == 1:
array = np.array([array])
# Array dimensions
N = len(array)
M = len(array[0])
# Check if header_row, footer_row, header_column and footer_column have the correct length
if header_column is not None and len(header_column) != N:
raise ValueError(
f"header_column has to have the same length"
+ f" as the number of rows ({N})."
+ f"It has length of {len(header_column)}. "
)
if footer_column is not None and len(footer_column) != N:
raise ValueError(
f"footer_column has to have the same length"
+ f" as the number of rows ({N})."
+ f"It has length of {len(footer_column)}. "
)
if header_row is not None and len(header_row) != M + int(
header_column is not None
) + int(footer_column is not None):
raise ValueError(
f"header_row has to have the same length "
+ f"({M + int(header_column is not None) + int(footer_column is not None)})"
+ f" as the number of columns ({M}) + one more element for each if "
+ "header_column or footer_column is not None "
+ f"(+{int(header_column is not None) + int(footer_column is not None)}). "
+ f"It has length of {len(header_row)}."
)
if footer_row is not None and len(footer_row) != M + int(
header_column is not None
) + int(footer_column is not None):
raise ValueError(
f"footer_row has to have the same length "
+ f"({M + int(header_column is not None) + int(footer_column is not None)})"
+ f" as the number of columns ({M}) + one more element for each if "
+ "header_column or footer_column is not None "
+ f"(+{int(header_column is not None) + int(footer_column is not None)}). "
+ f"It has length of {len(footer_row)}."
)
# Fix issue#3
array[array == 0] = 0
# Define functions for printing numbers and borders
def print_number(number, fmt, highlight=False, condition=None):
if condition is None:
condition = number
string = ""
if number is None:
return " " * len(f"{1:{fmt}}")
# Highlight positive and negative values with colours
if highlight:
if condition > 0:
string += colored(f"{number:{fmt}}", "red", attrs=["bold"])
elif condition < 0:
string += colored(f"{number:{fmt}}", "blue", attrs=["bold"])
else:
string += colored(f"{number:{fmt}}", "green", attrs=["bold"])
# Print without colours
else:
string += f"{number:{fmt}}"
return string
def print_complex(number, fmt, highlight=False):
string = ""
if number.real != 0:
string += print_number(number.real, fmt, highlight)
else:
string += " " * len(print_number(number.real, fmt))
if number.imag > 0:
sign = "+"
else:
sign = "-"
if number.imag != 0:
string += f" {sign} i"
string += print_number(
abs(number.imag), f"<{fmt}", highlight, condition=number.imag
)
else:
string += " " * (
len(print_number(abs(number.imag), fmt, condition=number.imag)) + 4
)
return string
def print_border(symbol_start, symbol_middle, symbol_end, n):
result = [symbol_start]
if header_column is not None:
result.append(f"{(n[0]+2)*'─'}{symbol_middle}")
n_index_shift = 1
else:
n_index_shift = 0
for j in range(0, M):
# If at least one complex value is present in the column
if np.iscomplex(array[:, j]).any():
result.append(f"{(2*n[j + n_index_shift] + 6)*'─'}")
else:
result.append(f"{(n[j + n_index_shift] + 2)*'─'}")
if j != M - 1 or footer_column is not None:
result.append(symbol_middle)
if footer_column is not None:
result.append(f"{(n[-1]+2)*'─'}")
result.append(f"{symbol_end}\n")
return "".join(result)
# Get maximum string length for each column of an array
n = np.zeros(M, dtype=int)
n_full = np.zeros(M, dtype=int)
for column in range(M):
for row in range(N):
if array[row][column] is None or np.isnan(array[row][column]):
pass
elif np.iscomplex(array[row, column]):
n[column] = max(
n[column], (len(print_complex(array[row][column], fmt)) - 4) / 2
)
n_full[column] = max(
n_full[column], len(print_complex(array[row][column], fmt))
)
else:
n[column] = max(
n[column], len(print_number(array[row][column].real, fmt))
)
# Parse fmt
tmp_fmt, post_fmt = fmt.split(".")
mid_fmt = "".join(c for c in tmp_fmt if c.isdigit())
pre_fmt = "".join(c for c in tmp_fmt if not c.isdigit())
# Force provided fmt
if len(mid_fmt) != 0:
n = np.amax([n, [int(mid_fmt) for _ in n]], axis=0)
# Get format for headers and footers
if header_column is not None:
tmp_n = max([len(str(x)) for x in header_column])
n = np.concatenate(([tmp_n], n))
n_full = np.concatenate(([tmp_n], n_full))
if footer_column is not None:
tmp_n = max([len(str(x)) for x in footer_column])
n = np.concatenate((n, [tmp_n]))
n_full = np.concatenate((n_full, [tmp_n]))
if header_row is not None:
n = np.amax([n, [len(str(x)) for x in header_row]], axis=0)
if footer_row is not None:
n = np.amax([n, [len(str(x)) for x in footer_row]], axis=0)
n_full = np.amax([n, n_full], axis=0)
string = []
# Open borders
if borders:
string.append(" " * shift + print_border(*top_border, n))
# Write header row
if header_row is not None:
string.append(" " * shift + vert)
string.extend(
[
f" {x:{pre_fmt}{n_full[x_i]}}{space_vert}"
for x_i, x in enumerate(header_row)
]
)
string.append("\n")
if borders:
string.append(" " * shift + print_border(*middle_border, n))
# Write array
for i in range(0, N):
substring = [" " * shift, vert]
if header_column is not None:
substring.append(f" {header_column[i]:{pre_fmt}{n[0]}}{space_vert}")
n_index_shift = 1
else:
n_index_shift = 0
for j in range(0, M):
fmt = f"{pre_fmt}{n[j + n_index_shift]}.{post_fmt}"
substring.append(" ")
# Print blank for None
if array[i][j] is None or np.isnan(array[i][j]):
# Highlight positive and negative values with colours
substring.append(
" " * (len(f"{'':{pre_fmt}{n[j + n_index_shift]}}"))
)
# Print complex values
elif np.iscomplex(array[:, j]).any():
# Print complex part if it is non-zero
substring.append(print_complex(array[i][j], fmt, highlight))
# Print real values
else:
# Highlight positive and negative values with colours
substring.append(print_number(array[i][j].real, fmt, highlight))
substring.append(space_vert)
if footer_column is not None:
substring.append(f" {footer_column[i]:{pre_fmt}{n[-1]}}{space_vert}")
substring.append("\n")
if borders and i != N - 1:
# Middle of the table
substring.append(" " * shift + print_border(*middle_border, n))
string.extend(substring)
# Write footer row
if footer_row is not None:
if borders:
string.append(" " * shift + print_border(*middle_border, n))
string.append(" " * shift + vert)
string.extend(
[
f" {x:{pre_fmt}{n_full[x_i]}}{space_vert}"
for x_i, x in enumerate(footer_row)
]
)
string.append("\n")
# Close borders
if borders:
string.append(" " * shift + print_border(*bottom_border, n))
# Print or return result
string = "".join(string)
if string[-1] == "\n":
string = string[:-1]
if print_result:
print(string)
else:
return string
else:
if print_result:
print(None)
else:
return None
if __name__ == "__main__":
array = [[1, 2], [3, 4], [52414345345, 6]]
print_2d_array(array)
array = [[0, 1.0, -0.0], [1, 1, 1]]
print_2d_array(array)
array = [[1, 2], [3, 4], [5, 6]]
print_2d_array(array)
print_2d_array(array, fmt="10.2f")
print_2d_array(array, borders=False)
print_2d_array(array, shift=3)
array = [[1, 2], [3, 4], [52414345345, 6]]
print_2d_array(array, fmt="10.2E")
array = [[1, 2 + 1j], [3, 4], [52, 6]]
print_2d_array(array)
print_2d_array(array, fmt="4.2E")
array = [[1, 2 - 1j], [3, 4], [52, 6]]
print_2d_array(array)
array = [[1, 1j], [3, 4], [52, 6]]
print_2d_array(array)
print_2d_array([])
print_2d_array([[]])
array = [[1, 2], [3, 4], [52414345345, 6]]
print_2d_array(array)
print_2d_array(array, header_row=["a", "b"])
print_2d_array(array, header_row=["a", "adfadsasfdb"])
print_2d_array(array, footer_row=["a", "b"])
print_2d_array(array, header_column=["a", "b", "c"])
print_2d_array(array, footer_column=["a", "b", "c"])
print_2d_array(array, footer_column=["a1234234123", "b", "c"])
print_2d_array(array, header_row=["", "a", "b"], header_column=["a", "b", "c"])
print_2d_array(array, footer_row=["a", "b", ""], footer_column=["a", "b", "c"])
print_2d_array(
array,
header_row=["", "a", "b", ""],
header_column=["a", "b", "c"],
footer_row=["", "a", "b", ""],
footer_column=["a", "b", "c"],
shift=3,
)
print_2d_array(
array,
header_row=["", "a", "b"],
header_column=["a", "b", "c"],
footer_row=["", "a", "b"],
)
print_2d_array([1, None], header_row=["a", "b"])
print_2d_array([None, 1])
print_2d_array([None, 1], header_row=["a", "b"])
print_2d_array([1, None, 1], header_row=["a", "b", "c"])
print_2d_array(
array,
header_row=["", "a", "b", ""],
header_column=["a", "b", "c"],
footer_row=["", "a", "b", ""],
footer_column=["a", "b", "c"],
borders=False,
)
array = [[1, 2], [3, 4], [5, 6 + 1j]]
print_2d_array(array, header_row=["a", "b"], fmt="^.2f")
