/
pycm_output.py
523 lines (474 loc) · 18.1 KB
/
pycm_output.py
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# -*- coding: utf-8 -*-
"""Outputs functions."""
from __future__ import division
from functools import partial
from .pycm_param import *
from .pycm_util import rounder
import webbrowser
def html_init():
"""
Return HTML report file first lines.
:return: html_init as str
"""
return HTML_INIT_TEMPLATE.format(OG_DESCRIPTION, OG_IMAGE_URL)
def html_dataset_type(is_binary, is_imbalanced):
"""
Return HTML report file dataset type.
:param is_binary: is_binary flag (True: binary, False: multi-class)
:type is_binary: bool
:param is_imbalanced: is_imbalanced flag (True: imbalance, False: balance)
:type is_imbalanced: bool
:return: dataset_type as str
"""
result = "<h2>Dataset Type : </h2>\n"
balance_type = "Balanced"
class_type = "Binary Classification"
if is_imbalanced:
balance_type = "Imbalanced"
if not is_binary:
class_type = "Multi-Class Classification"
result += "<ul>\n<li>{0}</li>\n<li>{1}</li>\n</ul>\n".format(
class_type, balance_type)
result += "<p>{0}</p>\n".format(RECOMMEND_HTML_MESSAGE)
result += "<p>{0}</p>\n".format(RECOMMEND_HTML_MESSAGE2)
return result
def color_check(color):
"""
Check input color format.
:param color: input color
:type color: tuple
:return: color as list
"""
if isinstance(color, (tuple, list)):
if all(map(lambda x: isinstance(x, int), color)):
if all(map(lambda x: x < 256, color)):
return list(color)
if isinstance(color, str):
color_lower = color.lower()
if color_lower in TABLE_COLOR.keys():
return TABLE_COLOR[color_lower]
return [0, 0, 0]
def html_table_color(row, item, color=(0, 0, 0)):
"""
Return background color of each cell of the table.
:param row: row dictionary
:type row: dict
:param item: cell number
:type item: int
:param color: input color
:type color: tuple
:return: background color as list [R, G, B]
"""
result = [0, 0, 0]
color_list = color_check(color)
max_color = max(color_list)
back_color_index = 255 - int((item / (sum(list(row.values())) + 1)) * 255)
for i in range(3):
result[i] = back_color_index - (max_color - color_list[i])
if result[i] < 0:
result[i] = 0
return result
def html_table(
classes,
table,
rgb_color,
normalize=False,
shortener=True):
"""
Return the confusion matrix of the HTML report file.
:param classes: confusion matrix classes
:type classes: list
:param table: input confusion matrix
:type table: dict
:param rgb_color: input color
:type rgb_color: tuple
:param normalize: save normalized matrix flag
:type normalize: bool
:param shortener: class name shortener flag
:type shortener: bool
:return: html_table as str
"""
result = ""
result += "<h2>Confusion Matrix "
if normalize:
result += "(Normalized)"
result += ": </h2>\n"
result += '<table>\n'
result += '<tr style="text-align:center;">' + "\n"
result += '<td>Actual</td>\n'
result += '<td>Predict\n'
table_size = str((len(classes) + 1) * 7) + "em"
result += '<table style="border:1px solid black;border-collapse: collapse;height:{0};width:{0};">\n'\
.format(table_size)
result += '<tr style="text-align:center;">\n<td></td>\n'
part_2 = ""
for i in classes:
class_name = str(i)
if len(class_name) > 6 and shortener:
class_name = class_name[:4] + "..."
result += '<td style="border:1px solid ' \
'black;padding:10px;height:7em;width:7em;">' + \
class_name + '</td>\n'
part_2 += '<tr style="text-align:center;">\n'
part_2 += '<td style="border:1px solid ' \
'black;padding:10px;height:7em;width:7em;">' + \
class_name + '</td>\n'
for j in classes:
item = table[i][j]
color = "black"
back_color = html_table_color(table[i], item, rgb_color)
if min(back_color) < 128:
color = "white"
part_2 += '<td style="background-color:rgb({0},{1},{2});color:{3};padding:10px;height:7em;width:7em;">'.format(
str(back_color[0]), str(back_color[1]), str(back_color[2]), color) + str(item) + '</td>\n'
part_2 += "</tr>\n"
result += '</tr>\n'
part_2 += "</table>\n</td>\n</tr>\n</table>\n"
result += part_2
return result
def html_overall_stat(
overall_stat,
digit=5,
overall_param=None,
recommended_list=(),
alt_link=False):
"""
Return the overall stats of HTML report file.
:param overall_stat: overall stats
:type overall_stat: dict
:param digit: scale (number of fraction digits)(default value: 5)
:type digit: int
:param overall_param: overall parameters list for print, Example: ["Kappa", "Scott PI"]
:type overall_param: list
:param recommended_list: recommended statistics list
:type recommended_list: list or tuple
:param alt_link: alternative link for document flag
:type alt_link: bool
:return: html_overall_stat as str
"""
document_link = DOCUMENT_ADR
if alt_link:
document_link = DOCUMENT_ADR_ALT
result = ""
result += "<h2>Overall Statistics : </h2>\n"
result += '<table style="border:1px solid black;border-collapse: collapse;">\n'
overall_stat_keys = sorted(overall_stat.keys())
if isinstance(overall_param, list):
if set(overall_param) <= set(overall_stat_keys):
overall_stat_keys = sorted(overall_param)
if len(overall_stat_keys) < 1:
return ""
for i in overall_stat_keys:
background_color = DEFAULT_BACKGROUND_COLOR
if i in recommended_list:
background_color = RECOMMEND_BACKGROUND_COLOR
result += '<tr style="text-align:center;">\n'
result += '<td style="border:1px solid black;padding:4px;text-align:left;background-color:{};"><a href="'.format(
background_color) + document_link + PARAMS_LINK[i] + '" style="text-decoration:None;">' + str(i) + '</a></td>\n'
if i in BENCHMARK_LIST:
background_color = BENCHMARK_COLOR[i][overall_stat[i]]
result += '<td style="border:1px solid black;padding:4px;background-color:{};">'.format(
background_color)
else:
result += '<td style="border:1px solid black;padding:4px;">'
result += rounder(overall_stat[i], digit) + '</td>\n'
result += "</tr>\n"
result += "</table>\n"
return result
def html_class_stat(
classes,
class_stat,
digit=5,
class_param=None,
recommended_list=(),
alt_link=False):
"""
Return the class-based stats of HTML report file.
:param classes: confusion matrix classes
:type classes: list
:param class_stat: class stat
:type class_stat:dict
:param digit: scale (number of fraction digits)(default value: 5)
:type digit: int
:param class_param: class parameters list for print, Example: ["TPR", "TNR", "AUC"]
:type class_param: list
:param recommended_list: recommended statistics list
:type recommended_list: list or tuple
:param alt_link: alternative link for document flag
:type alt_link: bool
:return: html_class_stat as str
"""
document_link = DOCUMENT_ADR
if alt_link:
document_link = DOCUMENT_ADR_ALT
result = ""
result += "<h2>Class Statistics : </h2>\n"
result += '<table style="border:1px solid black;border-collapse: collapse;">\n'
result += '<tr style="text-align:center;">\n<td>Class</td>\n'
for i in classes:
result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;">' + \
str(i) + '</td>\n'
result += '<td>Description</td>\n'
result += '</tr>\n'
class_stat_keys = sorted(class_stat.keys())
if isinstance(class_param, list):
if set(class_param) <= set(class_stat_keys):
class_stat_keys = class_param
if len(classes) < 1 or len(class_stat_keys) < 1:
return ""
for i in class_stat_keys:
background_color = DEFAULT_BACKGROUND_COLOR
if i in recommended_list:
background_color = RECOMMEND_BACKGROUND_COLOR
result += '<tr style="text-align:center;border:1px solid black;border-collapse: collapse;">\n'
result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;background-color:{};"><a href="'.format(
background_color) + document_link + PARAMS_LINK[i] + '" style="text-decoration:None;">' + str(i) + '</a></td>\n'
for j in classes:
if i in BENCHMARK_LIST:
background_color = BENCHMARK_COLOR[i][class_stat[i][j]]
result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;background-color:{};">'.format(
background_color)
else:
result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;">'
result += rounder(class_stat[i][j], digit) + '</td>\n'
params_text = PARAMS_DESCRIPTION[i]
if i not in CAPITALIZE_FILTER:
params_text = params_text.capitalize()
result += '<td style="border:1px solid black;padding:4px;border-collapse: collapse;text-align:left;">' + \
params_text + '</td>\n'
result += "</tr>\n"
result += "</table>\n"
return result
def html_end(version):
"""
Return HTML report file end lines.
:param version: pycm version
:type version: str
:return: html_end as str
"""
return HTML_END_TEMPLATE.format(version)
def pycm_help():
"""
Print pycm details.
:return: None
"""
print(OVERVIEW)
print("Repo : https://github.com/sepandhaghighi/pycm")
print("Webpage : https://www.pycm.io")
def table_print(classes, table):
"""
Return printable confusion matrix.
:param classes: confusion matrix classes
:type classes: list
:param table: input confusion matrix
:type table: dict
:return: printable table as str
"""
classes_len = len(classes)
table_list = []
for key in classes:
table_list.extend(list(table[key].values()))
table_list.extend(classes)
table_max_length = max(map(len, map(str, table_list)))
shift = "%-" + str(7 + table_max_length) + "s"
result = shift % "Predict" + shift * \
classes_len % tuple(map(str, classes)) + "\n"
result = result + "Actual\n"
for key in classes:
row = [table[key][i] for i in classes]
result += shift % str(key) + \
shift * classes_len % tuple(map(str, row)) + "\n\n"
return result
def sparse_table_print(sparse_matrix):
"""
Return printable confusion matrix in sparse mode.
:param sparse_matrix: list of the sparse matrix and it's classes
:type sparse_matrix: list
:return: printable table as str
"""
[sparse_table, actual_classes, predict_classes] = sparse_matrix
predict_classes.sort()
actual_classes.sort()
classes_len = len(predict_classes)
table_list = []
for key in actual_classes:
table_list.extend(list(sparse_table[key].values()))
table_list.extend(predict_classes)
table_max_length = max(map(len, map(str, table_list)))
shift = "%-" + str(7 + table_max_length) + "s"
result = shift % "Predict" + shift * \
classes_len % tuple(map(str, predict_classes)) + "\n"
result = result + "Actual\n"
for key in actual_classes:
row = [sparse_table[key][i] for i in predict_classes]
result += shift % str(key) + \
shift * classes_len % tuple(map(str, row)) + "\n\n"
return result
def csv_matrix_print(classes, table, header=False):
"""
Return matrix as csv data.
:param classes: confusion matrix classes
:type classes: list
:param table: input confusion matrix
:type table: dict
:param header: add headers to csv file
:type header: bool
:return:
"""
result = ""
header_section = ""
for i in classes:
if header is True:
header_section += '"' + str(i) + '"' + ","
for j in classes:
result += str(table[i][j]) + ","
result = result[:-1] + "\n"
if len(header_section) > 0:
header_section = header_section[:-1] + "\n"
result = header_section + result
return result[:-1]
def csv_print(classes, class_stat, digit=5, class_param=None):
"""
Return csv file data.
:param classes: confusion matrix classes
:type classes: list
:param class_stat: statistic result for each class
:type class_stat:dict
:param digit: scale (number of fraction digits)(default value: 5)
:type digit: int
:param class_param: class parameters list for print, Example: ["TPR", "TNR", "AUC"]
:type class_param: list
:return: csv file data as str
"""
result = "Class"
for item in classes:
result += ',"' + str(item) + '"'
result += "\n"
class_stat_keys = sorted(class_stat.keys())
if isinstance(class_param, list):
if set(class_param) <= set(class_stat_keys):
class_stat_keys = class_param
if len(class_stat_keys) < 1 or len(classes) < 1:
return ""
for key in class_stat_keys:
row = [rounder(class_stat[key][i], digit) for i in classes]
result += key + "," + ",".join(row)
result += "\n"
return result
def stat_print(
classes,
class_stat,
overall_stat,
digit=5,
overall_param=None,
class_param=None):
"""
Return printable statistics table.
:param classes: confusion matrix classes
:type classes: list
:param class_stat: statistic result for each class
:type class_stat: dict
:param overall_stat: overall statistic result
:type overall_stat:dict
:param digit: scale (number of fraction digits)(default value: 5)
:type digit: int
:param overall_param: overall parameters list for print, Example: ["Kappa", "Scott PI"]
:type overall_param: list
:param class_param: class parameters list for print, Example: ["TPR", "TNR", "AUC"]
:type class_param: list
:return: printable result as str
"""
shift = max(map(len, PARAMS_DESCRIPTION.values())) + 5
classes_len = len(classes)
overall_stat_keys = sorted(overall_stat.keys())
result = ""
if isinstance(overall_param, list):
if set(overall_param) <= set(overall_stat_keys):
overall_stat_keys = sorted(overall_param)
if len(overall_stat_keys) > 0:
result = "Overall Statistics : " + "\n\n"
for key in overall_stat_keys:
result += key + " " * (shift - len(key) + 7) + \
rounder(overall_stat[key], digit) + "\n"
class_stat_keys = sorted(class_stat.keys())
if isinstance(class_param, list):
if set(class_param) <= set(class_stat_keys):
class_stat_keys = sorted(class_param)
if len(class_stat_keys) > 0 and len(classes) > 0:
class_shift = max(
max(map(lambda x: len(str(x)), classes)) + 5, digit + 6, 14)
class_shift_format = "%-" + str(class_shift) + "s"
result += "\nClass Statistics :\n\n"
result += "Classes" + shift * " " + class_shift_format * \
classes_len % tuple(map(str, classes)) + "\n"
rounder_map = partial(rounder, digit=digit)
for key in class_stat_keys:
row = [class_stat[key][i] for i in classes]
params_text = PARAMS_DESCRIPTION[key]
if key not in CAPITALIZE_FILTER:
params_text = params_text.capitalize()
result += key + "(" + params_text + ")" + " " * (
shift - len(key) - len(PARAMS_DESCRIPTION[key]) + 5) + class_shift_format * classes_len % tuple(
map(rounder_map, row)) + "\n"
return result
def compare_report_print(sorted_list, scores, best_name):
"""
Return compare report.
:param sorted_list: sorted list of confusion matrices
:type sorted_list: list
:param scores: scores of confusion matrices
:type scores: dict
:param best_name: best confusion matrix name
:type best_name: str
:return: printable result as str
"""
title_items = ["Rank", "Name", "Class-Score", "Overall-Score"]
class_scores_len = map(lambda x: len(
str(x["class"])), list(scores.values()))
shifts = ["%-" +
str(len(sorted_list) +
4) +
"s", "%-" +
str(max(map(lambda x: len(str(x)), sorted_list)) +
4) +
"s", "%-" +
str(max(class_scores_len) + 11) + "s"]
result = ""
result += "Best : " + str(best_name) + "\n\n"
result += ("".join(shifts)
) % tuple(title_items[:-1]) + title_items[-1] + "\n"
prev_rank = 0
for index, cm in enumerate(sorted_list):
rank = index
if scores[sorted_list[rank]] == scores[sorted_list[prev_rank]]:
rank = prev_rank
result += ("".join(shifts)) % (str(rank + 1), str(cm),
str(scores[cm]["class"])) + str(scores[cm]["overall"]) + "\n"
prev_rank = rank
return result
def online_help(param=None, alt_link=False):
"""
Open online document in web browser.
:param param: input parameter
:type param: int or str
:param alt_link: alternative link for document flag
:type alt_link: bool
:return: None
"""
try:
document_link = DOCUMENT_ADR
if alt_link:
document_link = DOCUMENT_ADR_ALT
params_link_keys = sorted(PARAMS_LINK.keys())
if param in params_link_keys:
webbrowser.open_new_tab(document_link + PARAMS_LINK[param])
elif param in range(1, len(params_link_keys) + 1):
webbrowser.open_new_tab(
document_link + PARAMS_LINK[params_link_keys[param - 1]])
else:
print("Please choose one parameter : \n")
print('Example : online_help("J") or online_help(2)\n')
for index, item in enumerate(params_link_keys):
print(str(index + 1) + "-" + item)
except Exception:
print("Error in online help")