file_name large_stringlengths 4 140 | prefix large_stringlengths 0 39k | suffix large_stringlengths 0 36.1k | middle large_stringlengths 0 29.4k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model
try:
from dataset import load_tax_data, prepare_tax_dual
from utils import llprint
from model_keras_new import build
from metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
except ImportError:
from .dataset import load_tax_data, prepare_tax_dual
from .utils import llprint
from .model_keras_new import build
from .metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
parser = argparse.ArgumentParser()
parser = argparse.ArgumentParser(description="attention_and_memory_augmented_networks")
parser.add_argument('--datapath', type=str, default='../tax-data/records.csv', help='data path')
parser.add_argument('--run_mode', type=str, default='test', choices=['train','test'], help='run mode')
parser.add_argument('--debug', action='store_true', help='debug')
parser.add_argument('--no_tensorboard', action='store_true', help='not use tensorboard')
parser.add_argument('--no_embed_trainable', action='store_true', help='embed not trainable')
parser.add_argument('--embed_size', type=int, default=100, help='embed size')
parser.add_argument('--no_position_embed', action='store_true', help='use position embed or not')
parser.add_argument('--position_embed_size', type=int, default=100, help='position embed size')
parser.add_argument('--position_embed_mode', type=str, default='sum', choices=['sum','concat'], help='position embed mode[sum,concat]')
parser.add_argument('--self_attention_units', type=int, default=64, help='self attention units')
parser.add_argument('--self_attention_num_heads', type=int, default=4, help='self attention num heads')
parser.add_argument('--no_history', action='store_true', help='use history attention or not')
parser.add_argument('--no_interaction', action='store_true', help='use interaction attention or not')
parser.add_argument('--no_memory', action='store_true', help='remove memory or not')
parser.add_argument('--memory_word_num', type=int, default=256, help='memory word num')
parser.add_argument('--memory_word_size', type=int, default=64, help='memory word size')
parser.add_argument('--memory_read_heads', type=int, default=4, help='memory read heads')
parser.add_argument('--feature_size', type=int, default=256, help='feature size')
parser.add_argument('--multi', action='store_true', help='multi-label classification or not')
parser.add_argument('--epochs', type=int, default=10, help='epochs')
parser.add_argument('--focal_loss', action='store_false', help='use focal loss')
parser.add_argument('--focal_loss_alpha', type=float, default=0.6, help='focal loss alpha')
parser.add_argument('--focal_loss_gamma', type=float, default=2.0, help='focal loss gamma')
parser.add_argument('--optimizer', type=str, default='adam', help='optimizer')
parser.add_argument('--lr', type=float, default=0.00005, help='learning rate')
parser.add_argument('--lr_decay', type=float, default=1e-6, help='learning rate decay')
parser.add_argument('--model_path', type=str, help='model path')
args = parser.parse_args()
model_name = "AMANet-tax"
# time
time_str = time.strftime("%Y%m%d%H%M%S", time.localtime())
def write_log(callback, names, logs, epoch_no):
for name, value in zip(names, logs):
summary = tf.Summary()
summary_value = summary.value.add()
summary_value.simple_value = value
summary_value.tag = name
callback.writer.add_summary(summary, epoch_no)
callback.writer.flush()
CallBack = TensorBoard(log_dir=('../tb-logs/tax-task/%s/%s' %(model_name, time_str)), # log dir
histogram_freq=0,
write_graph=True,
write_grads=True,
write_images=True,
embeddings_freq=0,
embeddings_layer_names=None,
embeddings_metadata=None)
train_names = ['train_loss']
val_names = ["val_acc", "val_prec", "val_recall", "val_f1", "val_prauc", "val_roc_auc"]
def | (config):
# model save path
model_save_dir = os.path.join("../model/tax-task", model_name, time_str)
if not os.path.exists(model_save_dir):
os.makedirs(model_save_dir)
# log save path
log_save_dir = os.path.join("../logs/tax-task", model_name, time_str)
if not os.path.exists(log_save_dir):
os.makedirs(log_save_dir)
# load data
data_train, data_valid, data_test, voc_size = load_tax_data(config["datapath"])
# input1 vocab size
config["vocab_size1"] = voc_size[0]
# input1 vocab size
config["vocab_size2"] = voc_size[1]
# output vocab size
config["output_size"] = voc_size[2]
# build model
model = build(config)
# plot model graph
model_graph_file = os.path.join(model_save_dir, ("model_%s.png" % time_str))
plot_model(model, to_file=model_graph_file)
# model summary
model.summary()
# model tensorboard logs
CallBack.set_model(model)
# eval logs
file = open(os.path.join(log_save_dir, "statistic_%s.txt" % time_str), "w+")
file.write(str(config)+"\n")
model.summary(print_fn=lambda x: file.write(x + '\n'))
train_size = len(data_train)
best_f1 = 0.0
best_epoch = 0
best_model = ""
# train
for epoch in range(config["epochs"]):
# 新一次迭代，打乱训练集
data_train = shuffle(data_train)
start_time = time.time()
llprint("Epoch %d/%d\n" % (epoch + 1, config["epochs"]))
losses = []
train_pred_output_prob = []
train_pred_output = []
train_real_output = []
file.write("Epoch: %d/%d\n" % ((epoch + 1), config["epochs"]))
for patient_index in range(train_size):
llprint("\rBatch %d/%d" % (patient_index + 1, train_size))
# 获取第index个企业dual序列
input_vec1, input_vec2, output_vec, o = prepare_tax_dual(data_train, index=patient_index)
train_real_output.append(o[0])
res = model.train_on_batch([input_vec1, input_vec2], output_vec)
losses.append(res[0])
prob = res[1][0][0]
train_pred_output_prob.append(prob)
if prob >= 0.5:
train_pred_output.append(1)
else:
train_pred_output.append(0)
end_time = time.time()
elapsed_time = (end_time - start_time) / 60
train_acc, train_prec, train_recall, train_f1 = metrics_non_multi(train_real_output, train_pred_output)
train_roc_auc = roc_auc_non_multi(train_real_output, train_pred_output_prob)
train_prauc = prc_auc_non_multi(train_real_output, train_pred_output_prob)
if config["use_tensorboard"]:
train_logs = [sum(losses)/len(losses)]
write_log(CallBack, train_names, train_logs, epoch+1)
print('')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_valid, config)
if config["use_tensorboard"]:
val_logs = [acc, pre, recall, f1, prauc, roc_auc]
write_log(CallBack, val_names, val_logs, epoch+1)
file.write("spend time to train: %.2f min\n" % elapsed_time)
file.write("train loss: %f\n" % (sum(losses)/ len(losses)))
file.write("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
print("spend time to train: %.2f min" % elapsed_time)
print("train loss: %f, acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % ((sum(losses)/ len(losses)), train_acc, train_prec, train_recall, train_f1, train_prauc, train_roc_auc))
print("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
model_save_path = os.path.join(model_save_dir, 'model_%d_%s_%.4f.h5' % ((epoch+1), time_str, f1))
model.save(model_save_path)
if best_f1 < f1:
best_f1 = f1
best_epoch = epoch + 1
best_model = model_save_path
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("###############################################################\n")
print("###############################################################\n")
file.flush()
os.rename(best_model, best_model.replace(".h5", "_best.h5"))
print("train done. best epoch: %d, best: f1: %f, model path: %s" % (best_epoch, best_f1, best_model))
file.write("train done. best epoch: %d, best: f1: %f, model path: %s\n" % (best_epoch, best_f1, best_model))
CallBack.on_train_end(None)
file.close()
# evaluate
def model_eval(model, dataset, config, type="eval"):
eval_real_output = []
eval_pred_output_prob = []
eval_pred_output = []
data_size = len(dataset)
outputs = [model.get_layer('output').output]
layer_model = Model(inputs=model.input, outputs=outputs)
print("#####################%s#####################" % type)
for patient_index in range(data_size):
llprint("\rBatch: %d/%d" % (patient_index + 1, data_size))
dual = prepare_tax_dual(dataset, index=patient_index)
input_vec1, input_vec2, output_vec, o = dual
layer_model_output = layer_model.predict([input_vec1, input_vec2])
prob = layer_model_output[0][0]
eval_real_output.append(o[0])
eval_pred_output_prob.append(prob)
if prob >= 0.5:
eval_pred_output.append(1)
else:
eval_pred_output.append(0)
print('')
acc, prec, recall, f1 = metrics_non_multi(eval_real_output, eval_pred_output)
roc_auc = roc_auc_non_multi(eval_real_output, eval_pred_output_prob)
prauc = prc_auc_non_multi(eval_real_output, eval_pred_output_prob)
return acc, prec, recall, f1, prauc, roc_auc
if __name__ == "__main__":
print("#####################args#####################")
print(args)
config = {
"datapath": args.datapath,
"run_mode": args.run_mode,
"debug": args.debug,
"use_tensorboard": not args.no_tensorboard,
"has_position_embed": not args.no_position_embed,
"has_memory": not args.no_memory,
"has_history": False, #not args.no_history,
"has_interaction": not args.no_interaction,
"vocab_size1": 2000,
"vocab_size2": 2000,
"output_size": 1,
"embed_trainable": not args.no_embed_trainable,
"embed_size": args.embed_size,
"position_embed_size": args.position_embed_size,
"position_embed_mode": args.position_embed_mode,
"self_attention_units": args.self_attention_units,
"self_attention_num_heads": args.self_attention_num_heads,
"memory_word_num": args.memory_word_num,
"memory_word_size": args.memory_word_size,
"memory_read_heads": args.memory_read_heads,
"feature_size": args.feature_size,
"multi": args.multi,
"epochs": args.epochs,
"optimizer": args.optimizer,
"focal_loss": args.focal_loss,
"focal_loss_alpha": args.focal_loss_alpha,
"focal_loss_gamma": args.focal_loss_gamma,
"lr":args.lr,
"lr_decay":args.lr_decay
}
print("#####################config#####################")
print(config)
if config["run_mode"] == "train":
config["datapath"]='../tax-data/records.csv'
train(config=config)
else:
model = build(config)
model.load_weights(os.path.abspath(args.model_path))
data_train, data_valid, data_test, voc_size = load_tax_data(data_path='../tax-data/records.csv')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
| train | identifier_name |
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model
try:
from dataset import load_tax_data, prepare_tax_dual
from utils import llprint
from model_keras_new import build
from metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
except ImportError:
from .dataset import load_tax_data, prepare_tax_dual
from .utils import llprint
from .model_keras_new import build
from .metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
parser = argparse.ArgumentParser()
parser = argparse.ArgumentParser(description="attention_and_memory_augmented_networks")
parser.add_argument('--datapath', type=str, default='../tax-data/records.csv', help='data path')
parser.add_argument('--run_mode', type=str, default='test', choices=['train','test'], help='run mode')
parser.add_argument('--debug', action='store_true', help='debug')
parser.add_argument('--no_tensorboard', action='store_true', help='not use tensorboard')
parser.add_argument('--no_embed_trainable', action='store_true', help='embed not trainable')
parser.add_argument('--embed_size', type=int, default=100, help='embed size')
parser.add_argument('--no_position_embed', action='store_true', help='use position embed or not')
parser.add_argument('--position_embed_size', type=int, default=100, help='position embed size')
parser.add_argument('--position_embed_mode', type=str, default='sum', choices=['sum','concat'], help='position embed mode[sum,concat]')
parser.add_argument('--self_attention_units', type=int, default=64, help='self attention units')
parser.add_argument('--self_attention_num_heads', type=int, default=4, help='self attention num heads')
parser.add_argument('--no_history', action='store_true', help='use history attention or not')
parser.add_argument('--no_interaction', action='store_true', help='use interaction attention or not')
parser.add_argument('--no_memory', action='store_true', help='remove memory or not')
parser.add_argument('--memory_word_num', type=int, default=256, help='memory word num')
parser.add_argument('--memory_word_size', type=int, default=64, help='memory word size')
parser.add_argument('--memory_read_heads', type=int, default=4, help='memory read heads')
parser.add_argument('--feature_size', type=int, default=256, help='feature size')
parser.add_argument('--multi', action='store_true', help='multi-label classification or not')
parser.add_argument('--epochs', type=int, default=10, help='epochs')
parser.add_argument('--focal_loss', action='store_false', help='use focal loss')
parser.add_argument('--focal_loss_alpha', type=float, default=0.6, help='focal loss alpha')
parser.add_argument('--focal_loss_gamma', type=float, default=2.0, help='focal loss gamma')
parser.add_argument('--optimizer', type=str, default='adam', help='optimizer')
parser.add_argument('--lr', type=float, default=0.00005, help='learning rate')
parser.add_argument('--lr_decay', type=float, default=1e-6, help='learning rate decay')
parser.add_argument('--model_path', type=str, help='model path')
args = parser.parse_args()
model_name = "AMANet-tax"
# time
time_str = time.strftime("%Y%m%d%H%M%S", time.localtime())
def write_log(callback, names, logs, epoch_no):
for name, value in zip(names, logs):
summary = tf.Summary()
summary_value = summary.value.add()
summary_value.simple_value = value
summary_value.tag = name
callback.writer.add_summary(summary, epoch_no)
callback.writer.flush()
CallBack = TensorBoard(log_dir=('../tb-logs/tax-task/%s/%s' %(model_name, time_str)), # log dir
histogram_freq=0,
write_graph=True,
write_grads=True,
write_images=True,
embeddings_freq=0,
embeddings_layer_names=None,
embeddings_metadata=None)
train_names = ['train_loss']
val_names = ["val_acc", "val_prec", "val_recall", "val_f1", "val_prauc", "val_roc_auc"]
def train(config):
# model save path
model_save_dir = os.path.join("../model/tax-task", model_name, time_str)
if not os.path.exists(model_save_dir):
os.makedirs(model_save_dir)
# log save path
log_save_dir = os.path.join("../logs/tax-task", model_name, time_str)
if not os.path.exists(log_save_dir):
os.makedirs(log_save_dir)
# load data
data_train, data_valid, data_test, voc_size = load_tax_data(config["datapath"])
# input1 vocab size
config["vocab_size1"] = voc_size[0]
# input1 vocab size
config["vocab_size2"] = voc_size[1]
# output vocab size
config["output_size"] = voc_size[2]
# build model
model = build(config)
# plot model graph
model_graph_file = os.path.join(model_save_dir, ("model_%s.png" % time_str))
plot_model(model, to_file=model_graph_file)
# model summary
model.summary()
# model tensorboard logs
CallBack.set_model(model)
# eval logs
file = open(os.path.join(log_save_dir, "statistic_%s.txt" % time_str), "w+")
file.write(str(config)+"\n")
model.summary(print_fn=lambda x: file.write(x + '\n'))
train_size = len(data_train)
best_f1 = 0.0
best_epoch = 0
best_model = ""
# train
for epoch in range(config["epochs"]):
# 新一次迭代，打乱训练集
data_train = shuffle(d | .replace(".h5", "_best.h5"))
print("train done. best epoch: %d, best: f1: %f, model path: %s" % (best_epoch, best_f1, best_model))
file.write("train done. best epoch: %d, best: f1: %f, model path: %s\n" % (best_epoch, best_f1, best_model))
CallBack.on_train_end(None)
file.close()
# evaluate
def model_eval(model, dataset, config, type="eval"):
eval_real_output = []
eval_pred_output_prob = []
eval_pred_output = []
data_size = len(dataset)
outputs = [model.get_layer('output').output]
layer_model = Model(inputs=model.input, outputs=outputs)
print("#####################%s#####################" % type)
for patient_index in range(data_size):
llprint("\rBatch: %d/%d" % (patient_index + 1, data_size))
dual = prepare_tax_dual(dataset, index=patient_index)
input_vec1, input_vec2, output_vec, o = dual
layer_model_output = layer_model.predict([input_vec1, input_vec2])
prob = layer_model_output[0][0]
eval_real_output.append(o[0])
eval_pred_output_prob.append(prob)
if prob >= 0.5:
eval_pred_output.append(1)
else:
eval_pred_output.append(0)
print('')
acc, prec, recall, f1 = metrics_non_multi(eval_real_output, eval_pred_output)
roc_auc = roc_auc_non_multi(eval_real_output, eval_pred_output_prob)
prauc = prc_auc_non_multi(eval_real_output, eval_pred_output_prob)
return acc, prec, recall, f1, prauc, roc_auc
if __name__ == "__main__":
print("#####################args#####################")
print(args)
config = {
"datapath": args.datapath,
"run_mode": args.run_mode,
"debug": args.debug,
"use_tensorboard": not args.no_tensorboard,
"has_position_embed": not args.no_position_embed,
"has_memory": not args.no_memory,
"has_history": False, #not args.no_history,
"has_interaction": not args.no_interaction,
"vocab_size1": 2000,
"vocab_size2": 2000,
"output_size": 1,
"embed_trainable": not args.no_embed_trainable,
"embed_size": args.embed_size,
"position_embed_size": args.position_embed_size,
"position_embed_mode": args.position_embed_mode,
"self_attention_units": args.self_attention_units,
"self_attention_num_heads": args.self_attention_num_heads,
"memory_word_num": args.memory_word_num,
"memory_word_size": args.memory_word_size,
"memory_read_heads": args.memory_read_heads,
"feature_size": args.feature_size,
"multi": args.multi,
"epochs": args.epochs,
"optimizer": args.optimizer,
"focal_loss": args.focal_loss,
"focal_loss_alpha": args.focal_loss_alpha,
"focal_loss_gamma": args.focal_loss_gamma,
"lr":args.lr,
"lr_decay":args.lr_decay
}
print("#####################config#####################")
print(config)
if config["run_mode"] == "train":
config["datapath"]='../tax-data/records.csv'
train(config=config)
else:
model = build(config)
model.load_weights(os.path.abspath(args.model_path))
data_train, data_valid, data_test, voc_size = load_tax_data(data_path='../tax-data/records.csv')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
| ata_train)
start_time = time.time()
llprint("Epoch %d/%d\n" % (epoch + 1, config["epochs"]))
losses = []
train_pred_output_prob = []
train_pred_output = []
train_real_output = []
file.write("Epoch: %d/%d\n" % ((epoch + 1), config["epochs"]))
for patient_index in range(train_size):
llprint("\rBatch %d/%d" % (patient_index + 1, train_size))
# 获取第index个企业dual序列
input_vec1, input_vec2, output_vec, o = prepare_tax_dual(data_train, index=patient_index)
train_real_output.append(o[0])
res = model.train_on_batch([input_vec1, input_vec2], output_vec)
losses.append(res[0])
prob = res[1][0][0]
train_pred_output_prob.append(prob)
if prob >= 0.5:
train_pred_output.append(1)
else:
train_pred_output.append(0)
end_time = time.time()
elapsed_time = (end_time - start_time) / 60
train_acc, train_prec, train_recall, train_f1 = metrics_non_multi(train_real_output, train_pred_output)
train_roc_auc = roc_auc_non_multi(train_real_output, train_pred_output_prob)
train_prauc = prc_auc_non_multi(train_real_output, train_pred_output_prob)
if config["use_tensorboard"]:
train_logs = [sum(losses)/len(losses)]
write_log(CallBack, train_names, train_logs, epoch+1)
print('')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_valid, config)
if config["use_tensorboard"]:
val_logs = [acc, pre, recall, f1, prauc, roc_auc]
write_log(CallBack, val_names, val_logs, epoch+1)
file.write("spend time to train: %.2f min\n" % elapsed_time)
file.write("train loss: %f\n" % (sum(losses)/ len(losses)))
file.write("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
print("spend time to train: %.2f min" % elapsed_time)
print("train loss: %f, acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % ((sum(losses)/ len(losses)), train_acc, train_prec, train_recall, train_f1, train_prauc, train_roc_auc))
print("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
model_save_path = os.path.join(model_save_dir, 'model_%d_%s_%.4f.h5' % ((epoch+1), time_str, f1))
model.save(model_save_path)
if best_f1 < f1:
best_f1 = f1
best_epoch = epoch + 1
best_model = model_save_path
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("###############################################################\n")
print("###############################################################\n")
file.flush()
os.rename(best_model, best_model | conditional_block |
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model
try:
from dataset import load_tax_data, prepare_tax_dual
from utils import llprint
from model_keras_new import build
from metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
except ImportError:
from .dataset import load_tax_data, prepare_tax_dual
from .utils import llprint
from .model_keras_new import build
from .metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
parser = argparse.ArgumentParser()
parser = argparse.ArgumentParser(description="attention_and_memory_augmented_networks")
parser.add_argument('--datapath', type=str, default='../tax-data/records.csv', help='data path')
parser.add_argument('--run_mode', type=str, default='test', choices=['train','test'], help='run mode')
parser.add_argument('--debug', action='store_true', help='debug')
parser.add_argument('--no_tensorboard', action='store_true', help='not use tensorboard')
parser.add_argument('--no_embed_trainable', action='store_true', help='embed not trainable')
parser.add_argument('--embed_size', type=int, default=100, help='embed size')
parser.add_argument('--no_position_embed', action='store_true', help='use position embed or not')
parser.add_argument('--position_embed_size', type=int, default=100, help='position embed size')
parser.add_argument('--position_embed_mode', type=str, default='sum', choices=['sum','concat'], help='position embed mode[sum,concat]')
parser.add_argument('--self_attention_units', type=int, default=64, help='self attention units')
parser.add_argument('--self_attention_num_heads', type=int, default=4, help='self attention num heads')
parser.add_argument('--no_history', action='store_true', help='use history attention or not')
parser.add_argument('--no_interaction', action='store_true', help='use interaction attention or not')
parser.add_argument('--no_memory', action='store_true', help='remove memory or not')
parser.add_argument('--memory_word_num', type=int, default=256, help='memory word num')
parser.add_argument('--memory_word_size', type=int, default=64, help='memory word size')
parser.add_argument('--memory_read_heads', type=int, default=4, help='memory read heads')
parser.add_argument('--feature_size', type=int, default=256, help='feature size')
parser.add_argument('--multi', action='store_true', help='multi-label classification or not')
parser.add_argument('--epochs', type=int, default=10, help='epochs')
parser.add_argument('--focal_loss', action='store_false', help='use focal loss')
parser.add_argument('--focal_loss_alpha', type=float, default=0.6, help='focal loss alpha')
parser.add_argument('--focal_loss_gamma', type=float, default=2.0, help='focal loss gamma')
parser.add_argument('--optimizer', type=str, default='adam', help='optimizer')
parser.add_argument('--lr', type=float, default=0.00005, help='learning rate')
parser.add_argument('--lr_decay', type=float, default=1e-6, help='learning rate decay')
parser.add_argument('--model_path', type=str, help='model path')
args = parser.parse_args()
model_name = "AMANet-tax"
# time
time_str = time.strftime("%Y%m%d%H%M%S", time.localtime())
def write_log(callback, names, logs, epoch_no):
|
CallBack = TensorBoard(log_dir=('../tb-logs/tax-task/%s/%s' %(model_name, time_str)), # log dir
histogram_freq=0,
write_graph=True,
write_grads=True,
write_images=True,
embeddings_freq=0,
embeddings_layer_names=None,
embeddings_metadata=None)
train_names = ['train_loss']
val_names = ["val_acc", "val_prec", "val_recall", "val_f1", "val_prauc", "val_roc_auc"]
def train(config):
# model save path
model_save_dir = os.path.join("../model/tax-task", model_name, time_str)
if not os.path.exists(model_save_dir):
os.makedirs(model_save_dir)
# log save path
log_save_dir = os.path.join("../logs/tax-task", model_name, time_str)
if not os.path.exists(log_save_dir):
os.makedirs(log_save_dir)
# load data
data_train, data_valid, data_test, voc_size = load_tax_data(config["datapath"])
# input1 vocab size
config["vocab_size1"] = voc_size[0]
# input1 vocab size
config["vocab_size2"] = voc_size[1]
# output vocab size
config["output_size"] = voc_size[2]
# build model
model = build(config)
# plot model graph
model_graph_file = os.path.join(model_save_dir, ("model_%s.png" % time_str))
plot_model(model, to_file=model_graph_file)
# model summary
model.summary()
# model tensorboard logs
CallBack.set_model(model)
# eval logs
file = open(os.path.join(log_save_dir, "statistic_%s.txt" % time_str), "w+")
file.write(str(config)+"\n")
model.summary(print_fn=lambda x: file.write(x + '\n'))
train_size = len(data_train)
best_f1 = 0.0
best_epoch = 0
best_model = ""
# train
for epoch in range(config["epochs"]):
# 新一次迭代，打乱训练集
data_train = shuffle(data_train)
start_time = time.time()
llprint("Epoch %d/%d\n" % (epoch + 1, config["epochs"]))
losses = []
train_pred_output_prob = []
train_pred_output = []
train_real_output = []
file.write("Epoch: %d/%d\n" % ((epoch + 1), config["epochs"]))
for patient_index in range(train_size):
llprint("\rBatch %d/%d" % (patient_index + 1, train_size))
# 获取第index个企业dual序列
input_vec1, input_vec2, output_vec, o = prepare_tax_dual(data_train, index=patient_index)
train_real_output.append(o[0])
res = model.train_on_batch([input_vec1, input_vec2], output_vec)
losses.append(res[0])
prob = res[1][0][0]
train_pred_output_prob.append(prob)
if prob >= 0.5:
train_pred_output.append(1)
else:
train_pred_output.append(0)
end_time = time.time()
elapsed_time = (end_time - start_time) / 60
train_acc, train_prec, train_recall, train_f1 = metrics_non_multi(train_real_output, train_pred_output)
train_roc_auc = roc_auc_non_multi(train_real_output, train_pred_output_prob)
train_prauc = prc_auc_non_multi(train_real_output, train_pred_output_prob)
if config["use_tensorboard"]:
train_logs = [sum(losses)/len(losses)]
write_log(CallBack, train_names, train_logs, epoch+1)
print('')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_valid, config)
if config["use_tensorboard"]:
val_logs = [acc, pre, recall, f1, prauc, roc_auc]
write_log(CallBack, val_names, val_logs, epoch+1)
file.write("spend time to train: %.2f min\n" % elapsed_time)
file.write("train loss: %f\n" % (sum(losses)/ len(losses)))
file.write("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
print("spend time to train: %.2f min" % elapsed_time)
print("train loss: %f, acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % ((sum(losses)/ len(losses)), train_acc, train_prec, train_recall, train_f1, train_prauc, train_roc_auc))
print("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
model_save_path = os.path.join(model_save_dir, 'model_%d_%s_%.4f.h5' % ((epoch+1), time_str, f1))
model.save(model_save_path)
if best_f1 < f1:
best_f1 = f1
best_epoch = epoch + 1
best_model = model_save_path
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("###############################################################\n")
print("###############################################################\n")
file.flush()
os.rename(best_model, best_model.replace(".h5", "_best.h5"))
print("train done. best epoch: %d, best: f1: %f, model path: %s" % (best_epoch, best_f1, best_model))
file.write("train done. best epoch: %d, best: f1: %f, model path: %s\n" % (best_epoch, best_f1, best_model))
CallBack.on_train_end(None)
file.close()
# evaluate
def model_eval(model, dataset, config, type="eval"):
eval_real_output = []
eval_pred_output_prob = []
eval_pred_output = []
data_size = len(dataset)
outputs = [model.get_layer('output').output]
layer_model = Model(inputs=model.input, outputs=outputs)
print("#####################%s#####################" % type)
for patient_index in range(data_size):
llprint("\rBatch: %d/%d" % (patient_index + 1, data_size))
dual = prepare_tax_dual(dataset, index=patient_index)
input_vec1, input_vec2, output_vec, o = dual
layer_model_output = layer_model.predict([input_vec1, input_vec2])
prob = layer_model_output[0][0]
eval_real_output.append(o[0])
eval_pred_output_prob.append(prob)
if prob >= 0.5:
eval_pred_output.append(1)
else:
eval_pred_output.append(0)
print('')
acc, prec, recall, f1 = metrics_non_multi(eval_real_output, eval_pred_output)
roc_auc = roc_auc_non_multi(eval_real_output, eval_pred_output_prob)
prauc = prc_auc_non_multi(eval_real_output, eval_pred_output_prob)
return acc, prec, recall, f1, prauc, roc_auc
if __name__ == "__main__":
print("#####################args#####################")
print(args)
config = {
"datapath": args.datapath,
"run_mode": args.run_mode,
"debug": args.debug,
"use_tensorboard": not args.no_tensorboard,
"has_position_embed": not args.no_position_embed,
"has_memory": not args.no_memory,
"has_history": False, #not args.no_history,
"has_interaction": not args.no_interaction,
"vocab_size1": 2000,
"vocab_size2": 2000,
"output_size": 1,
"embed_trainable": not args.no_embed_trainable,
"embed_size": args.embed_size,
"position_embed_size": args.position_embed_size,
"position_embed_mode": args.position_embed_mode,
"self_attention_units": args.self_attention_units,
"self_attention_num_heads": args.self_attention_num_heads,
"memory_word_num": args.memory_word_num,
"memory_word_size": args.memory_word_size,
"memory_read_heads": args.memory_read_heads,
"feature_size": args.feature_size,
"multi": args.multi,
"epochs": args.epochs,
"optimizer": args.optimizer,
"focal_loss": args.focal_loss,
"focal_loss_alpha": args.focal_loss_alpha,
"focal_loss_gamma": args.focal_loss_gamma,
"lr":args.lr,
"lr_decay":args.lr_decay
}
print("#####################config#####################")
print(config)
if config["run_mode"] == "train":
config["datapath"]='../tax-data/records.csv'
train(config=config)
else:
model = build(config)
model.load_weights(os.path.abspath(args.model_path))
data_train, data_valid, data_test, voc_size = load_tax_data(data_path='../tax-data/records.csv')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
| for name, value in zip(names, logs):
summary = tf.Summary()
summary_value = summary.value.add()
summary_value.simple_value = value
summary_value.tag = name
callback.writer.add_summary(summary, epoch_no)
callback.writer.flush() | identifier_body |
tax_task.py | #!/usr/bin/env python
# encoding: utf-8
import os
import time
import argparse
import sys
sys.path.append('..')
sys.path.append('.')
import tensorflow as tf
from sklearn.utils import shuffle
from keras.callbacks import TensorBoard
from keras.models import Model, load_model
from keras.utils.vis_utils import plot_model
try:
from dataset import load_tax_data, prepare_tax_dual
from utils import llprint
from model_keras_new import build
from metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
except ImportError:
from .dataset import load_tax_data, prepare_tax_dual
from .utils import llprint
from .model_keras_new import build
from .metrics import metrics_non_multi, roc_auc_non_multi, prc_auc_non_multi
parser = argparse.ArgumentParser()
parser = argparse.ArgumentParser(description="attention_and_memory_augmented_networks")
parser.add_argument('--datapath', type=str, default='../tax-data/records.csv', help='data path')
parser.add_argument('--run_mode', type=str, default='test', choices=['train','test'], help='run mode')
parser.add_argument('--debug', action='store_true', help='debug')
parser.add_argument('--no_tensorboard', action='store_true', help='not use tensorboard')
parser.add_argument('--no_embed_trainable', action='store_true', help='embed not trainable')
parser.add_argument('--embed_size', type=int, default=100, help='embed size')
parser.add_argument('--no_position_embed', action='store_true', help='use position embed or not')
parser.add_argument('--position_embed_size', type=int, default=100, help='position embed size')
parser.add_argument('--position_embed_mode', type=str, default='sum', choices=['sum','concat'], help='position embed mode[sum,concat]')
parser.add_argument('--self_attention_units', type=int, default=64, help='self attention units')
parser.add_argument('--self_attention_num_heads', type=int, default=4, help='self attention num heads')
parser.add_argument('--no_history', action='store_true', help='use history attention or not')
parser.add_argument('--no_interaction', action='store_true', help='use interaction attention or not')
parser.add_argument('--no_memory', action='store_true', help='remove memory or not')
parser.add_argument('--memory_word_num', type=int, default=256, help='memory word num')
parser.add_argument('--memory_word_size', type=int, default=64, help='memory word size')
parser.add_argument('--memory_read_heads', type=int, default=4, help='memory read heads')
parser.add_argument('--feature_size', type=int, default=256, help='feature size')
parser.add_argument('--multi', action='store_true', help='multi-label classification or not')
parser.add_argument('--epochs', type=int, default=10, help='epochs')
parser.add_argument('--focal_loss', action='store_false', help='use focal loss')
parser.add_argument('--focal_loss_alpha', type=float, default=0.6, help='focal loss alpha')
parser.add_argument('--focal_loss_gamma', type=float, default=2.0, help='focal loss gamma')
parser.add_argument('--optimizer', type=str, default='adam', help='optimizer')
parser.add_argument('--lr', type=float, default=0.00005, help='learning rate')
parser.add_argument('--lr_decay', type=float, default=1e-6, help='learning rate decay')
parser.add_argument('--model_path', type=str, help='model path')
args = parser.parse_args()
model_name = "AMANet-tax"
# time
time_str = time.strftime("%Y%m%d%H%M%S", time.localtime())
def write_log(callback, names, logs, epoch_no):
for name, value in zip(names, logs):
summary = tf.Summary()
summary_value = summary.value.add()
summary_value.simple_value = value
summary_value.tag = name
callback.writer.add_summary(summary, epoch_no)
callback.writer.flush()
CallBack = TensorBoard(log_dir=('../tb-logs/tax-task/%s/%s' %(model_name, time_str)), # log dir
histogram_freq=0,
write_graph=True,
write_grads=True,
write_images=True,
embeddings_freq=0,
embeddings_layer_names=None,
embeddings_metadata=None)
train_names = ['train_loss']
val_names = ["val_acc", "val_prec", "val_recall", "val_f1", "val_prauc", "val_roc_auc"]
def train(config):
# model save path
model_save_dir = os.path.join("../model/tax-task", model_name, time_str)
if not os.path.exists(model_save_dir):
os.makedirs(model_save_dir)
# log save path
log_save_dir = os.path.join("../logs/tax-task", model_name, time_str)
if not os.path.exists(log_save_dir):
os.makedirs(log_save_dir)
# load data
data_train, data_valid, data_test, voc_size = load_tax_data(config["datapath"])
# input1 vocab size
config["vocab_size1"] = voc_size[0]
# input1 vocab size
config["vocab_size2"] = voc_size[1]
# output vocab size
config["output_size"] = voc_size[2]
# build model
model = build(config)
# plot model graph
model_graph_file = os.path.join(model_save_dir, ("model_%s.png" % time_str))
plot_model(model, to_file=model_graph_file)
# model summary
model.summary()
# model tensorboard logs
CallBack.set_model(model)
# eval logs
file = open(os.path.join(log_save_dir, "statistic_%s.txt" % time_str), "w+")
file.write(str(config)+"\n")
model.summary(print_fn=lambda x: file.write(x + '\n'))
train_size = len(data_train)
best_f1 = 0.0
best_epoch = 0
best_model = ""
# train
for epoch in range(config["epochs"]):
# 新一次迭代，打乱训练集
data_train = shuffle(data_train)
start_time = time.time()
llprint("Epoch %d/%d\n" % (epoch + 1, config["epochs"]))
losses = []
train_pred_output_prob = []
train_pred_output = []
train_real_output = []
file.write("Epoch: %d/%d\n" % ((epoch + 1), config["epochs"]))
for patient_index in range(train_size):
llprint("\rBatch %d/%d" % (patient_index + 1, train_size))
# 获取第index个企业dual序列
input_vec1, input_vec2, output_vec, o = prepare_tax_dual(data_train, index=patient_index)
train_real_output.append(o[0])
res = model.train_on_batch([input_vec1, input_vec2], output_vec)
losses.append(res[0])
prob = res[1][0][0]
train_pred_output_prob.append(prob)
if prob >= 0.5:
train_pred_output.append(1)
else:
train_pred_output.append(0)
end_time = time.time()
elapsed_time = (end_time - start_time) / 60
train_acc, train_prec, train_recall, train_f1 = metrics_non_multi(train_real_output, train_pred_output)
train_roc_auc = roc_auc_non_multi(train_real_output, train_pred_output_prob)
train_prauc = prc_auc_non_multi(train_real_output, train_pred_output_prob)
if config["use_tensorboard"]:
train_logs = [sum(losses)/len(losses)]
write_log(CallBack, train_names, train_logs, epoch+1)
print('')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_valid, config)
if config["use_tensorboard"]:
val_logs = [acc, pre, recall, f1, prauc, roc_auc]
write_log(CallBack, val_names, val_logs, epoch+1)
file.write("spend time to train: %.2f min\n" % elapsed_time)
file.write("train loss: %f\n" % (sum(losses)/ len(losses)))
file.write("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
print("spend time to train: %.2f min" % elapsed_time)
print("train loss: %f, acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % ((sum(losses)/ len(losses)), train_acc, train_prec, train_recall, train_f1, train_prauc, train_roc_auc))
print("valid acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
model_save_path = os.path.join(model_save_dir, 'model_%d_%s_%.4f.h5' % ((epoch+1), time_str, f1))
model.save(model_save_path)
if best_f1 < f1:
best_f1 = f1
best_epoch = epoch + 1
best_model = model_save_path
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f\n" % (acc, pre, recall, f1, prauc, roc_auc))
file.write("###############################################################\n")
print("###############################################################\n")
file.flush()
os.rename(best_model, best_model.replace(".h5", "_best.h5"))
print("train done. best epoch: %d, best: f1: %f, model path: %s" % (best_epoch, best_f1, best_model))
file.write("train done. best epoch: %d, best: f1: %f, model path: %s\n" % (best_epoch, best_f1, best_model))
CallBack.on_train_end(None)
file.close()
# evaluate
def model_eval(model, dataset, config, type="eval"):
eval_real_output = []
eval_pred_output_prob = []
eval_pred_output = []
data_size = len(dataset)
outputs = [model.get_layer('output').output]
layer_model = Model(inputs=model.input, outputs=outputs)
print("#####################%s#####################" % type)
for patient_index in range(data_size):
llprint("\rBatch: %d/%d" % (patient_index + 1, data_size))
dual = prepare_tax_dual(dataset, index=patient_index)
input_vec1, input_vec2, output_vec, o = dual
layer_model_output = layer_model.predict([input_vec1, input_vec2])
prob = layer_model_output[0][0]
eval_real_output.append(o[0])
eval_pred_output_prob.append(prob)
if prob >= 0.5:
eval_pred_output.append(1)
else:
eval_pred_output.append(0)
print('')
acc, prec, recall, f1 = metrics_non_multi(eval_real_output, eval_pred_output) |
if __name__ == "__main__":
print("#####################args#####################")
print(args)
config = {
"datapath": args.datapath,
"run_mode": args.run_mode,
"debug": args.debug,
"use_tensorboard": not args.no_tensorboard,
"has_position_embed": not args.no_position_embed,
"has_memory": not args.no_memory,
"has_history": False, #not args.no_history,
"has_interaction": not args.no_interaction,
"vocab_size1": 2000,
"vocab_size2": 2000,
"output_size": 1,
"embed_trainable": not args.no_embed_trainable,
"embed_size": args.embed_size,
"position_embed_size": args.position_embed_size,
"position_embed_mode": args.position_embed_mode,
"self_attention_units": args.self_attention_units,
"self_attention_num_heads": args.self_attention_num_heads,
"memory_word_num": args.memory_word_num,
"memory_word_size": args.memory_word_size,
"memory_read_heads": args.memory_read_heads,
"feature_size": args.feature_size,
"multi": args.multi,
"epochs": args.epochs,
"optimizer": args.optimizer,
"focal_loss": args.focal_loss,
"focal_loss_alpha": args.focal_loss_alpha,
"focal_loss_gamma": args.focal_loss_gamma,
"lr":args.lr,
"lr_decay":args.lr_decay
}
print("#####################config#####################")
print(config)
if config["run_mode"] == "train":
config["datapath"]='../tax-data/records.csv'
train(config=config)
else:
model = build(config)
model.load_weights(os.path.abspath(args.model_path))
data_train, data_valid, data_test, voc_size = load_tax_data(data_path='../tax-data/records.csv')
acc, pre, recall, f1, prauc, roc_auc = model_eval(model, data_test, config, type="test")
print("test acc: %f, prec: %f, recall: %f, f1: %f, prauc: %f, roc_auc: %f" % (acc, pre, recall, f1, prauc, roc_auc)) | roc_auc = roc_auc_non_multi(eval_real_output, eval_pred_output_prob)
prauc = prc_auc_non_multi(eval_real_output, eval_pred_output_prob)
return acc, prec, recall, f1, prauc, roc_auc | random_line_split |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given topology and activation functions
pub fn new_random(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_random_weights(&topology);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// create a new network with the given topology and activation functions and initial weights
pub fn new(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>, weights: &[f64]) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_weights(&topology, weights);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// forward evaluation
pub fn forward(&self, inputs :&[f64]) -> Vec<Vec<f64>> |
/// back propagation
pub fn backward(&mut self, inputs :&[f64], outputs :Vec<Vec<f64>>, target :&[f64], learning_rate: f64 ) {
debug!("Error: {}", error(target, outputs.last().expect("outputs")));
let l = outputs.len();
let mut new_weights = self.weights.clone();
let mut new_targets = vec!();
for (order,weights) in self.weights.iter().rev().enumerate() {
let rev_order = l-order-1;
let previous_outputs = if rev_order>0 {
&outputs[rev_order-1]
} else {
inputs
};
let previous_size = size(&weights).0;
debug!("previous size: {}",previous_size);
debug!("weights to update: {:?}",size(&weights));
new_targets.push(vec!(0.0; previous_size));
for (i,o) in outputs[rev_order].iter().enumerate() {
let diff = if order==0 {
o - target[i]
} else {
new_targets[order-1][i]
};
let deriv = self.activations[rev_order].derive(&outputs[rev_order],i);
let d = diff * deriv;
debug!("Output: {} -> {}", o, d);
for r in 0..previous_size{
let w = get(&weights,r,i);
let p = if r<previous_outputs.len() {previous_outputs[r]} else {1.0};
let uw = update_weight(w, d * p, learning_rate);
debug!("Weight for row {}: {} -> {} -> {}", r, w, uw, w*d);
set(&mut new_weights[rev_order],r,i,uw);
new_targets[order][r]+=w*d;
}
}
debug!("New targets: {:?}",new_targets);
}
debug!("Before backprop: {:?}",self.weights);
self.weights=new_weights;
}
/// train for one input and one target
pub fn train(&mut self, inputs :&[f64], target :&[f64], learning_rate: f64, max_iter: usize, max_error: f64) -> (usize,f64) {
let mut err;
for it in 0..max_iter {
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
if err < max_error {
return (it,err);
}
self.backward(inputs,outputs,target,learning_rate);
}
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
(max_iter,err)
}
/// online training for multiple input/targets
pub fn train_online(&mut self, tests: &[Test], learning_rate: f64, max_iter: usize) -> f64 {
for _ in 0..max_iter {
for test in tests {
let outputs = self.forward(&test.input);
self.backward(&test.input,outputs,&test.target,learning_rate);
}
}
tests.iter().map(|t| {
let outputs = self.forward(&t.input);
error(&t.target, outputs.last().expect("outputs"))
}).sum()
}
}
// generate random initial weights
fn initial_random_weights(topology: &Vec<usize>) -> Vec<Matrix> {
let mut v = Vec::new();
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
v.push(Matrix::rand_range(psz+1,sz,0.0,1.0));
}
Some(sz)
}
);
assert_eq!(topology.len()-1,v.len());
v
}
// build a network from initial weights
fn initial_weights(topology: &Vec<usize>, weights: &[f64]) -> Vec<Matrix> {
let mut v = Vec::new();
let mut st = 0;
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
let end =st + (psz+1) * sz;
assert!(end <= weights.len());
v.push(Matrix::new(psz+1,sz,&weights[st..end]));
st = end;
}
Some(sz)
}
);
assert_eq!(st,weights.len());
assert_eq!(topology.len()-1,v.len());
v
}
/// sigmoid function
pub fn sigmoid(i: f64) -> f64 {
f64::powi(1.0 + f64::exp(-i),-1)
}
/// hyperbolic tangent
pub fn hyptan(i: f64) -> f64 {
let minus2 = f64::exp(-2.0 * i);
(1.0-minus2)/(1.0+minus2)
}
/// RELU function
pub fn relu(i:f64) -> f64 {
f64::max(0.0,i)
}
/// softmax function
pub fn softmax(v: &[f64]) -> Vec<f64> {
let mut v2 = Vec::with_capacity(v.len());
let d = v.iter().max_by(|x,y| x.partial_cmp(y).expect("NaN")).expect("empty vector");
let s = v.iter().fold(0.0,|s,w|{
let e=f64::exp(*w-d);
v2.push(e);
s+e
});
if s == 0.0 {
v2
} else {
v2.iter().map(|w| w/s).collect()
}
}
/// error: sum of errors squared
pub fn error(target: &[f64], output: &[f64]) -> f64 {
target.iter().zip(output.iter()).map(|(t,o)| f64::powi(t-o,2)/2.0).sum()
}
/*fn diff_deriv(target: f64, output: f64) -> f64 {
let diff = output - target;
let deriv = output * (1.0 - output);
diff * deriv
}
fn weight_error(target: f64, output: f64, weighted_input: f64) -> f64 {
diff_deriv(target,output) * weighted_input
}*/
// get the updated value for a weight
fn update_weight(old: f64, error: f64, learning_rate: f64) -> f64 {
old - error * learning_rate
}
/// an activation function
pub trait Activation : std::fmt::Debug {
/// forward activation of all inputs
fn activate(&self, inputs: &[f64]) -> Vec<f64>;
/// derivation for one output given all the outputs and the output index
fn derive(&self, outputs: &[f64], index: usize) -> f64;
}
/// Sigmoid activation function
#[derive(Debug)]
pub struct Sigmoid{}
impl Activation for Sigmoid {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| sigmoid(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
outputs[index] * (1.0 - outputs[index])
}
}
/// Relu activation function
#[derive(Debug)]
pub struct Relu{}
impl Activation for Relu {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| relu(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
if outputs[index] > 0.0 {1.0} else {0.0}
}
}
/// Softmax activation function
#[derive(Debug)]
pub struct Softmax{}
impl Activation for Softmax {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
softmax(inputs)
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
let s: f64 = outputs.iter().sum();
let el = outputs[index];
(s-el)*el / s.powi(2)
}
}
/// Encapsulate one possible input and the target output, for training
pub struct Test {
pub input: Vec<f64>,
pub target: Vec<f64>,
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_mattmazur() {
// <https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/>
let mut nn = Network::new(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(2,2,2),&vec!(
0.15, 0.25, 0.2, 0.3, 0.35, 0.35,
0.4, 0.5, 0.45, 0.55, 0.6, 0.6
));
let f1s = nn.forward(&vec!(0.05,0.1));
assert_eq!(f1s[0],vec!(0.5932699921071872, 0.596884378259767));
assert_eq!(f1s[1],vec!(0.7513650695523157, 0.7729284653214625));
assert_eq!(0.2983711087600027,error(&vec!(0.01,0.99), &f1s[1]));
// assert_eq!(0.08216704056423078, weight_error(0.01, 0.7513650695523157, f1s[0][0]));
assert_eq!(0.35891647971788465, update_weight(0.4, 0.08216704056423078, 0.5));
nn.backward(&vec!(0.05,0.1),f1s,&vec!(0.01,0.99), 0.5);
let f2s = nn.forward(&vec!(0.05,0.1));
//assert_eq!(0.29102777369359933,error(&vec!(0.01,0.99), &f2s[1]));
// we update the biases too
assert_eq!(0.28047144679143016,error(&vec!(0.01,0.99), &f2s[1]));
let last_error=nn.train(&vec!(0.05,0.1),&vec!(0.01,0.99),0.5,10000,0.0000000001);
assert!(last_error.1<0.00001);
assert!(last_error.0<=10000);
}
#[test]
fn test_becominghuman(){
// <https://becominghuman.ai/making-a-simple-neural-network-2ea1de81ec20>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(4,4,1));
let tests = vec!(
Test{input:vec!(1.0,0.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,0.0,1.0,0.0),target:vec!(1.0)},
Test{input:vec!(0.0,0.0,0.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,10000);
println!("last: {}",last_error);
assert!(last_error<0.001);
}
#[test]
fn test_towards(){
// <https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(3,4,1));
let tests = vec!(
Test{input:vec!(0.0,0.0,1.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,0.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,1.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,1500);
println!("last: {}",last_error);
assert!(last_error<0.05);
}
#[test]
fn test_softmax(){
assert_eq!(vec!(0.09003057317038046, 0.24472847105479764, 0.6652409557748218),softmax(&vec!(1.0,2.0,3.0)));
assert_eq!(vec!(0.0, 0.0, 1.0),softmax(&vec!(1000.0,2000.0,3000.0)));
}
}
| {
assert_eq!(self.topology[0],inputs.len());
let mut m = Matrix::new(1,inputs.len(),inputs);
let mut all_results = Vec::with_capacity(self.topology.len() - 1);
self.weights.iter().enumerate().for_each(| (ix,wm) | {
add_column(&mut m,vec!(1.0));
m = mul(&m,wm);
//println!("after mul: {:?}",m);
let acts = self.activations[ix].activate(&get_data(&m));
m = Matrix::new(size(&m).0,size(&m).1,&acts);
//println!("after activation: {:?}",m);
all_results.push(acts);
});
assert_eq!(*self.topology.last().expect("empty topology!"),
all_results.last().expect("empty result!").len());
all_results
} | identifier_body |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given topology and activation functions
pub fn new_random(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_random_weights(&topology);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// create a new network with the given topology and activation functions and initial weights
pub fn new(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>, weights: &[f64]) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_weights(&topology, weights);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// forward evaluation
pub fn forward(&self, inputs :&[f64]) -> Vec<Vec<f64>> {
assert_eq!(self.topology[0],inputs.len());
let mut m = Matrix::new(1,inputs.len(),inputs);
let mut all_results = Vec::with_capacity(self.topology.len() - 1);
self.weights.iter().enumerate().for_each(| (ix,wm) | {
add_column(&mut m,vec!(1.0));
m = mul(&m,wm);
//println!("after mul: {:?}",m);
let acts = self.activations[ix].activate(&get_data(&m));
m = Matrix::new(size(&m).0,size(&m).1,&acts);
//println!("after activation: {:?}",m);
all_results.push(acts);
});
assert_eq!(*self.topology.last().expect("empty topology!"),
all_results.last().expect("empty result!").len());
all_results
}
/// back propagation
pub fn backward(&mut self, inputs :&[f64], outputs :Vec<Vec<f64>>, target :&[f64], learning_rate: f64 ) {
debug!("Error: {}", error(target, outputs.last().expect("outputs")));
let l = outputs.len();
let mut new_weights = self.weights.clone();
let mut new_targets = vec!();
for (order,weights) in self.weights.iter().rev().enumerate() {
let rev_order = l-order-1;
let previous_outputs = if rev_order>0 {
&outputs[rev_order-1]
} else {
inputs
};
let previous_size = size(&weights).0;
debug!("previous size: {}",previous_size);
debug!("weights to update: {:?}",size(&weights));
new_targets.push(vec!(0.0; previous_size));
for (i,o) in outputs[rev_order].iter().enumerate() {
let diff = if order==0 {
o - target[i]
} else {
new_targets[order-1][i]
};
let deriv = self.activations[rev_order].derive(&outputs[rev_order],i);
let d = diff * deriv;
debug!("Output: {} -> {}", o, d);
for r in 0..previous_size{
let w = get(&weights,r,i);
let p = if r<previous_outputs.len() {previous_outputs[r]} else {1.0};
let uw = update_weight(w, d * p, learning_rate);
debug!("Weight for row {}: {} -> {} -> {}", r, w, uw, w*d);
set(&mut new_weights[rev_order],r,i,uw);
new_targets[order][r]+=w*d;
}
}
debug!("New targets: {:?}",new_targets);
}
debug!("Before backprop: {:?}",self.weights);
self.weights=new_weights;
}
/// train for one input and one target
pub fn train(&mut self, inputs :&[f64], target :&[f64], learning_rate: f64, max_iter: usize, max_error: f64) -> (usize,f64) {
let mut err;
for it in 0..max_iter {
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
if err < max_error {
return (it,err);
}
self.backward(inputs,outputs,target,learning_rate);
}
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
(max_iter,err)
}
/// online training for multiple input/targets
pub fn train_online(&mut self, tests: &[Test], learning_rate: f64, max_iter: usize) -> f64 {
for _ in 0..max_iter {
for test in tests {
let outputs = self.forward(&test.input);
self.backward(&test.input,outputs,&test.target,learning_rate);
}
}
tests.iter().map(|t| {
let outputs = self.forward(&t.input);
error(&t.target, outputs.last().expect("outputs"))
}).sum()
}
}
// generate random initial weights
fn initial_random_weights(topology: &Vec<usize>) -> Vec<Matrix> {
let mut v = Vec::new();
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
v.push(Matrix::rand_range(psz+1,sz,0.0,1.0));
}
Some(sz)
}
);
assert_eq!(topology.len()-1,v.len());
v
}
// build a network from initial weights
fn initial_weights(topology: &Vec<usize>, weights: &[f64]) -> Vec<Matrix> {
let mut v = Vec::new();
let mut st = 0;
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
let end =st + (psz+1) * sz;
assert!(end <= weights.len());
v.push(Matrix::new(psz+1,sz,&weights[st..end]));
st = end;
}
Some(sz)
}
);
assert_eq!(st,weights.len());
assert_eq!(topology.len()-1,v.len());
v
}
/// sigmoid function
pub fn sigmoid(i: f64) -> f64 {
f64::powi(1.0 + f64::exp(-i),-1)
}
/// hyperbolic tangent
pub fn hyptan(i: f64) -> f64 {
let minus2 = f64::exp(-2.0 * i);
(1.0-minus2)/(1.0+minus2)
}
/// RELU function
pub fn relu(i:f64) -> f64 {
f64::max(0.0,i)
}
/// softmax function
pub fn softmax(v: &[f64]) -> Vec<f64> {
let mut v2 = Vec::with_capacity(v.len());
let d = v.iter().max_by(|x,y| x.partial_cmp(y).expect("NaN")).expect("empty vector");
let s = v.iter().fold(0.0,|s,w|{
let e=f64::exp(*w-d);
v2.push(e);
s+e
});
if s == 0.0 {
v2
} else {
v2.iter().map(|w| w/s).collect()
}
}
/// error: sum of errors squared
pub fn error(target: &[f64], output: &[f64]) -> f64 {
target.iter().zip(output.iter()).map(|(t,o)| f64::powi(t-o,2)/2.0).sum()
}
/*fn diff_deriv(target: f64, output: f64) -> f64 {
let diff = output - target;
let deriv = output * (1.0 - output);
diff * deriv
}
fn weight_error(target: f64, output: f64, weighted_input: f64) -> f64 {
diff_deriv(target,output) * weighted_input
}*/
// get the updated value for a weight
fn update_weight(old: f64, error: f64, learning_rate: f64) -> f64 {
old - error * learning_rate
}
/// an activation function
pub trait Activation : std::fmt::Debug {
/// forward activation of all inputs
fn activate(&self, inputs: &[f64]) -> Vec<f64>;
/// derivation for one output given all the outputs and the output index
fn derive(&self, outputs: &[f64], index: usize) -> f64;
}
/// Sigmoid activation function
#[derive(Debug)]
pub struct Sigmoid{}
impl Activation for Sigmoid {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| sigmoid(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
outputs[index] * (1.0 - outputs[index])
}
}
/// Relu activation function
#[derive(Debug)]
pub struct Relu{}
impl Activation for Relu {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| relu(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
if outputs[index] > 0.0 {1.0} else |
}
}
/// Softmax activation function
#[derive(Debug)]
pub struct Softmax{}
impl Activation for Softmax {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
softmax(inputs)
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
let s: f64 = outputs.iter().sum();
let el = outputs[index];
(s-el)*el / s.powi(2)
}
}
/// Encapsulate one possible input and the target output, for training
pub struct Test {
pub input: Vec<f64>,
pub target: Vec<f64>,
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_mattmazur() {
// <https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/>
let mut nn = Network::new(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(2,2,2),&vec!(
0.15, 0.25, 0.2, 0.3, 0.35, 0.35,
0.4, 0.5, 0.45, 0.55, 0.6, 0.6
));
let f1s = nn.forward(&vec!(0.05,0.1));
assert_eq!(f1s[0],vec!(0.5932699921071872, 0.596884378259767));
assert_eq!(f1s[1],vec!(0.7513650695523157, 0.7729284653214625));
assert_eq!(0.2983711087600027,error(&vec!(0.01,0.99), &f1s[1]));
// assert_eq!(0.08216704056423078, weight_error(0.01, 0.7513650695523157, f1s[0][0]));
assert_eq!(0.35891647971788465, update_weight(0.4, 0.08216704056423078, 0.5));
nn.backward(&vec!(0.05,0.1),f1s,&vec!(0.01,0.99), 0.5);
let f2s = nn.forward(&vec!(0.05,0.1));
//assert_eq!(0.29102777369359933,error(&vec!(0.01,0.99), &f2s[1]));
// we update the biases too
assert_eq!(0.28047144679143016,error(&vec!(0.01,0.99), &f2s[1]));
let last_error=nn.train(&vec!(0.05,0.1),&vec!(0.01,0.99),0.5,10000,0.0000000001);
assert!(last_error.1<0.00001);
assert!(last_error.0<=10000);
}
#[test]
fn test_becominghuman(){
// <https://becominghuman.ai/making-a-simple-neural-network-2ea1de81ec20>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(4,4,1));
let tests = vec!(
Test{input:vec!(1.0,0.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,0.0,1.0,0.0),target:vec!(1.0)},
Test{input:vec!(0.0,0.0,0.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,10000);
println!("last: {}",last_error);
assert!(last_error<0.001);
}
#[test]
fn test_towards(){
// <https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(3,4,1));
let tests = vec!(
Test{input:vec!(0.0,0.0,1.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,0.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,1.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,1500);
println!("last: {}",last_error);
assert!(last_error<0.05);
}
#[test]
fn test_softmax(){
assert_eq!(vec!(0.09003057317038046, 0.24472847105479764, 0.6652409557748218),softmax(&vec!(1.0,2.0,3.0)));
assert_eq!(vec!(0.0, 0.0, 1.0),softmax(&vec!(1000.0,2000.0,3000.0)));
}
}
| {0.0} | conditional_block |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given topology and activation functions
pub fn new_random(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_random_weights(&topology);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// create a new network with the given topology and activation functions and initial weights
pub fn new(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>, weights: &[f64]) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_weights(&topology, weights);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// forward evaluation
pub fn forward(&self, inputs :&[f64]) -> Vec<Vec<f64>> {
assert_eq!(self.topology[0],inputs.len());
let mut m = Matrix::new(1,inputs.len(),inputs);
let mut all_results = Vec::with_capacity(self.topology.len() - 1);
self.weights.iter().enumerate().for_each(| (ix,wm) | {
add_column(&mut m,vec!(1.0));
m = mul(&m,wm);
//println!("after mul: {:?}",m);
let acts = self.activations[ix].activate(&get_data(&m));
m = Matrix::new(size(&m).0,size(&m).1,&acts);
//println!("after activation: {:?}",m);
all_results.push(acts);
});
assert_eq!(*self.topology.last().expect("empty topology!"),
all_results.last().expect("empty result!").len());
all_results
}
/// back propagation
pub fn backward(&mut self, inputs :&[f64], outputs :Vec<Vec<f64>>, target :&[f64], learning_rate: f64 ) {
debug!("Error: {}", error(target, outputs.last().expect("outputs")));
let l = outputs.len();
let mut new_weights = self.weights.clone();
let mut new_targets = vec!();
for (order,weights) in self.weights.iter().rev().enumerate() {
let rev_order = l-order-1;
let previous_outputs = if rev_order>0 {
&outputs[rev_order-1] | inputs
};
let previous_size = size(&weights).0;
debug!("previous size: {}",previous_size);
debug!("weights to update: {:?}",size(&weights));
new_targets.push(vec!(0.0; previous_size));
for (i,o) in outputs[rev_order].iter().enumerate() {
let diff = if order==0 {
o - target[i]
} else {
new_targets[order-1][i]
};
let deriv = self.activations[rev_order].derive(&outputs[rev_order],i);
let d = diff * deriv;
debug!("Output: {} -> {}", o, d);
for r in 0..previous_size{
let w = get(&weights,r,i);
let p = if r<previous_outputs.len() {previous_outputs[r]} else {1.0};
let uw = update_weight(w, d * p, learning_rate);
debug!("Weight for row {}: {} -> {} -> {}", r, w, uw, w*d);
set(&mut new_weights[rev_order],r,i,uw);
new_targets[order][r]+=w*d;
}
}
debug!("New targets: {:?}",new_targets);
}
debug!("Before backprop: {:?}",self.weights);
self.weights=new_weights;
}
/// train for one input and one target
pub fn train(&mut self, inputs :&[f64], target :&[f64], learning_rate: f64, max_iter: usize, max_error: f64) -> (usize,f64) {
let mut err;
for it in 0..max_iter {
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
if err < max_error {
return (it,err);
}
self.backward(inputs,outputs,target,learning_rate);
}
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
(max_iter,err)
}
/// online training for multiple input/targets
pub fn train_online(&mut self, tests: &[Test], learning_rate: f64, max_iter: usize) -> f64 {
for _ in 0..max_iter {
for test in tests {
let outputs = self.forward(&test.input);
self.backward(&test.input,outputs,&test.target,learning_rate);
}
}
tests.iter().map(|t| {
let outputs = self.forward(&t.input);
error(&t.target, outputs.last().expect("outputs"))
}).sum()
}
}
// generate random initial weights
fn initial_random_weights(topology: &Vec<usize>) -> Vec<Matrix> {
let mut v = Vec::new();
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
v.push(Matrix::rand_range(psz+1,sz,0.0,1.0));
}
Some(sz)
}
);
assert_eq!(topology.len()-1,v.len());
v
}
// build a network from initial weights
fn initial_weights(topology: &Vec<usize>, weights: &[f64]) -> Vec<Matrix> {
let mut v = Vec::new();
let mut st = 0;
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
let end =st + (psz+1) * sz;
assert!(end <= weights.len());
v.push(Matrix::new(psz+1,sz,&weights[st..end]));
st = end;
}
Some(sz)
}
);
assert_eq!(st,weights.len());
assert_eq!(topology.len()-1,v.len());
v
}
/// sigmoid function
pub fn sigmoid(i: f64) -> f64 {
f64::powi(1.0 + f64::exp(-i),-1)
}
/// hyperbolic tangent
pub fn hyptan(i: f64) -> f64 {
let minus2 = f64::exp(-2.0 * i);
(1.0-minus2)/(1.0+minus2)
}
/// RELU function
pub fn relu(i:f64) -> f64 {
f64::max(0.0,i)
}
/// softmax function
pub fn softmax(v: &[f64]) -> Vec<f64> {
let mut v2 = Vec::with_capacity(v.len());
let d = v.iter().max_by(|x,y| x.partial_cmp(y).expect("NaN")).expect("empty vector");
let s = v.iter().fold(0.0,|s,w|{
let e=f64::exp(*w-d);
v2.push(e);
s+e
});
if s == 0.0 {
v2
} else {
v2.iter().map(|w| w/s).collect()
}
}
/// error: sum of errors squared
pub fn error(target: &[f64], output: &[f64]) -> f64 {
target.iter().zip(output.iter()).map(|(t,o)| f64::powi(t-o,2)/2.0).sum()
}
/*fn diff_deriv(target: f64, output: f64) -> f64 {
let diff = output - target;
let deriv = output * (1.0 - output);
diff * deriv
}
fn weight_error(target: f64, output: f64, weighted_input: f64) -> f64 {
diff_deriv(target,output) * weighted_input
}*/
// get the updated value for a weight
fn update_weight(old: f64, error: f64, learning_rate: f64) -> f64 {
old - error * learning_rate
}
/// an activation function
pub trait Activation : std::fmt::Debug {
/// forward activation of all inputs
fn activate(&self, inputs: &[f64]) -> Vec<f64>;
/// derivation for one output given all the outputs and the output index
fn derive(&self, outputs: &[f64], index: usize) -> f64;
}
/// Sigmoid activation function
#[derive(Debug)]
pub struct Sigmoid{}
impl Activation for Sigmoid {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| sigmoid(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
outputs[index] * (1.0 - outputs[index])
}
}
/// Relu activation function
#[derive(Debug)]
pub struct Relu{}
impl Activation for Relu {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| relu(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
if outputs[index] > 0.0 {1.0} else {0.0}
}
}
/// Softmax activation function
#[derive(Debug)]
pub struct Softmax{}
impl Activation for Softmax {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
softmax(inputs)
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
let s: f64 = outputs.iter().sum();
let el = outputs[index];
(s-el)*el / s.powi(2)
}
}
/// Encapsulate one possible input and the target output, for training
pub struct Test {
pub input: Vec<f64>,
pub target: Vec<f64>,
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_mattmazur() {
// <https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/>
let mut nn = Network::new(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(2,2,2),&vec!(
0.15, 0.25, 0.2, 0.3, 0.35, 0.35,
0.4, 0.5, 0.45, 0.55, 0.6, 0.6
));
let f1s = nn.forward(&vec!(0.05,0.1));
assert_eq!(f1s[0],vec!(0.5932699921071872, 0.596884378259767));
assert_eq!(f1s[1],vec!(0.7513650695523157, 0.7729284653214625));
assert_eq!(0.2983711087600027,error(&vec!(0.01,0.99), &f1s[1]));
// assert_eq!(0.08216704056423078, weight_error(0.01, 0.7513650695523157, f1s[0][0]));
assert_eq!(0.35891647971788465, update_weight(0.4, 0.08216704056423078, 0.5));
nn.backward(&vec!(0.05,0.1),f1s,&vec!(0.01,0.99), 0.5);
let f2s = nn.forward(&vec!(0.05,0.1));
//assert_eq!(0.29102777369359933,error(&vec!(0.01,0.99), &f2s[1]));
// we update the biases too
assert_eq!(0.28047144679143016,error(&vec!(0.01,0.99), &f2s[1]));
let last_error=nn.train(&vec!(0.05,0.1),&vec!(0.01,0.99),0.5,10000,0.0000000001);
assert!(last_error.1<0.00001);
assert!(last_error.0<=10000);
}
#[test]
fn test_becominghuman(){
// <https://becominghuman.ai/making-a-simple-neural-network-2ea1de81ec20>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(4,4,1));
let tests = vec!(
Test{input:vec!(1.0,0.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,0.0,1.0,0.0),target:vec!(1.0)},
Test{input:vec!(0.0,0.0,0.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,10000);
println!("last: {}",last_error);
assert!(last_error<0.001);
}
#[test]
fn test_towards(){
// <https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(3,4,1));
let tests = vec!(
Test{input:vec!(0.0,0.0,1.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,0.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,1.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,1500);
println!("last: {}",last_error);
assert!(last_error<0.05);
}
#[test]
fn test_softmax(){
assert_eq!(vec!(0.09003057317038046, 0.24472847105479764, 0.6652409557748218),softmax(&vec!(1.0,2.0,3.0)));
assert_eq!(vec!(0.0, 0.0, 1.0),softmax(&vec!(1000.0,2000.0,3000.0)));
}
} | } else { | random_line_split |
nn.rs | //! Neural networks
use crate::matrix::*;
/// a network
#[derive(Debug)]
pub struct Network {
// activation functions
activations: Vec<Box<dyn Activation>>,
// topology
topology: Vec<usize>,
// weights
weights: Vec<Matrix>
}
impl Network {
/// create a new random network with the given topology and activation functions
pub fn new_random(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_random_weights(&topology);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// create a new network with the given topology and activation functions and initial weights
pub fn new(activations: Vec<Box<dyn Activation>>, topology: Vec<usize>, weights: &[f64]) -> Network {
let l = topology.len();
assert!(l>1);
let rw = initial_weights(&topology, weights);
assert_eq!(rw.len(), activations.len());
Network {
activations,
topology,
weights: rw
}
}
/// forward evaluation
pub fn | (&self, inputs :&[f64]) -> Vec<Vec<f64>> {
assert_eq!(self.topology[0],inputs.len());
let mut m = Matrix::new(1,inputs.len(),inputs);
let mut all_results = Vec::with_capacity(self.topology.len() - 1);
self.weights.iter().enumerate().for_each(| (ix,wm) | {
add_column(&mut m,vec!(1.0));
m = mul(&m,wm);
//println!("after mul: {:?}",m);
let acts = self.activations[ix].activate(&get_data(&m));
m = Matrix::new(size(&m).0,size(&m).1,&acts);
//println!("after activation: {:?}",m);
all_results.push(acts);
});
assert_eq!(*self.topology.last().expect("empty topology!"),
all_results.last().expect("empty result!").len());
all_results
}
/// back propagation
pub fn backward(&mut self, inputs :&[f64], outputs :Vec<Vec<f64>>, target :&[f64], learning_rate: f64 ) {
debug!("Error: {}", error(target, outputs.last().expect("outputs")));
let l = outputs.len();
let mut new_weights = self.weights.clone();
let mut new_targets = vec!();
for (order,weights) in self.weights.iter().rev().enumerate() {
let rev_order = l-order-1;
let previous_outputs = if rev_order>0 {
&outputs[rev_order-1]
} else {
inputs
};
let previous_size = size(&weights).0;
debug!("previous size: {}",previous_size);
debug!("weights to update: {:?}",size(&weights));
new_targets.push(vec!(0.0; previous_size));
for (i,o) in outputs[rev_order].iter().enumerate() {
let diff = if order==0 {
o - target[i]
} else {
new_targets[order-1][i]
};
let deriv = self.activations[rev_order].derive(&outputs[rev_order],i);
let d = diff * deriv;
debug!("Output: {} -> {}", o, d);
for r in 0..previous_size{
let w = get(&weights,r,i);
let p = if r<previous_outputs.len() {previous_outputs[r]} else {1.0};
let uw = update_weight(w, d * p, learning_rate);
debug!("Weight for row {}: {} -> {} -> {}", r, w, uw, w*d);
set(&mut new_weights[rev_order],r,i,uw);
new_targets[order][r]+=w*d;
}
}
debug!("New targets: {:?}",new_targets);
}
debug!("Before backprop: {:?}",self.weights);
self.weights=new_weights;
}
/// train for one input and one target
pub fn train(&mut self, inputs :&[f64], target :&[f64], learning_rate: f64, max_iter: usize, max_error: f64) -> (usize,f64) {
let mut err;
for it in 0..max_iter {
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
if err < max_error {
return (it,err);
}
self.backward(inputs,outputs,target,learning_rate);
}
let outputs = self.forward(inputs);
err = error(target, outputs.last().expect("outputs"));
(max_iter,err)
}
/// online training for multiple input/targets
pub fn train_online(&mut self, tests: &[Test], learning_rate: f64, max_iter: usize) -> f64 {
for _ in 0..max_iter {
for test in tests {
let outputs = self.forward(&test.input);
self.backward(&test.input,outputs,&test.target,learning_rate);
}
}
tests.iter().map(|t| {
let outputs = self.forward(&t.input);
error(&t.target, outputs.last().expect("outputs"))
}).sum()
}
}
// generate random initial weights
fn initial_random_weights(topology: &Vec<usize>) -> Vec<Matrix> {
let mut v = Vec::new();
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
v.push(Matrix::rand_range(psz+1,sz,0.0,1.0));
}
Some(sz)
}
);
assert_eq!(topology.len()-1,v.len());
v
}
// build a network from initial weights
fn initial_weights(topology: &Vec<usize>, weights: &[f64]) -> Vec<Matrix> {
let mut v = Vec::new();
let mut st = 0;
topology.iter().fold(None,
|prev, &sz| {
if let Some(psz) = prev {
let end =st + (psz+1) * sz;
assert!(end <= weights.len());
v.push(Matrix::new(psz+1,sz,&weights[st..end]));
st = end;
}
Some(sz)
}
);
assert_eq!(st,weights.len());
assert_eq!(topology.len()-1,v.len());
v
}
/// sigmoid function
pub fn sigmoid(i: f64) -> f64 {
f64::powi(1.0 + f64::exp(-i),-1)
}
/// hyperbolic tangent
pub fn hyptan(i: f64) -> f64 {
let minus2 = f64::exp(-2.0 * i);
(1.0-minus2)/(1.0+minus2)
}
/// RELU function
pub fn relu(i:f64) -> f64 {
f64::max(0.0,i)
}
/// softmax function
pub fn softmax(v: &[f64]) -> Vec<f64> {
let mut v2 = Vec::with_capacity(v.len());
let d = v.iter().max_by(|x,y| x.partial_cmp(y).expect("NaN")).expect("empty vector");
let s = v.iter().fold(0.0,|s,w|{
let e=f64::exp(*w-d);
v2.push(e);
s+e
});
if s == 0.0 {
v2
} else {
v2.iter().map(|w| w/s).collect()
}
}
/// error: sum of errors squared
pub fn error(target: &[f64], output: &[f64]) -> f64 {
target.iter().zip(output.iter()).map(|(t,o)| f64::powi(t-o,2)/2.0).sum()
}
/*fn diff_deriv(target: f64, output: f64) -> f64 {
let diff = output - target;
let deriv = output * (1.0 - output);
diff * deriv
}
fn weight_error(target: f64, output: f64, weighted_input: f64) -> f64 {
diff_deriv(target,output) * weighted_input
}*/
// get the updated value for a weight
fn update_weight(old: f64, error: f64, learning_rate: f64) -> f64 {
old - error * learning_rate
}
/// an activation function
pub trait Activation : std::fmt::Debug {
/// forward activation of all inputs
fn activate(&self, inputs: &[f64]) -> Vec<f64>;
/// derivation for one output given all the outputs and the output index
fn derive(&self, outputs: &[f64], index: usize) -> f64;
}
/// Sigmoid activation function
#[derive(Debug)]
pub struct Sigmoid{}
impl Activation for Sigmoid {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| sigmoid(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
outputs[index] * (1.0 - outputs[index])
}
}
/// Relu activation function
#[derive(Debug)]
pub struct Relu{}
impl Activation for Relu {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
inputs.iter().map(|v| relu(*v)).collect()
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
if outputs[index] > 0.0 {1.0} else {0.0}
}
}
/// Softmax activation function
#[derive(Debug)]
pub struct Softmax{}
impl Activation for Softmax {
fn activate(&self, inputs: &[f64]) -> Vec<f64> {
softmax(inputs)
}
fn derive(&self, outputs: &[f64], index: usize) -> f64 {
let s: f64 = outputs.iter().sum();
let el = outputs[index];
(s-el)*el / s.powi(2)
}
}
/// Encapsulate one possible input and the target output, for training
pub struct Test {
pub input: Vec<f64>,
pub target: Vec<f64>,
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_mattmazur() {
// <https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/>
let mut nn = Network::new(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(2,2,2),&vec!(
0.15, 0.25, 0.2, 0.3, 0.35, 0.35,
0.4, 0.5, 0.45, 0.55, 0.6, 0.6
));
let f1s = nn.forward(&vec!(0.05,0.1));
assert_eq!(f1s[0],vec!(0.5932699921071872, 0.596884378259767));
assert_eq!(f1s[1],vec!(0.7513650695523157, 0.7729284653214625));
assert_eq!(0.2983711087600027,error(&vec!(0.01,0.99), &f1s[1]));
// assert_eq!(0.08216704056423078, weight_error(0.01, 0.7513650695523157, f1s[0][0]));
assert_eq!(0.35891647971788465, update_weight(0.4, 0.08216704056423078, 0.5));
nn.backward(&vec!(0.05,0.1),f1s,&vec!(0.01,0.99), 0.5);
let f2s = nn.forward(&vec!(0.05,0.1));
//assert_eq!(0.29102777369359933,error(&vec!(0.01,0.99), &f2s[1]));
// we update the biases too
assert_eq!(0.28047144679143016,error(&vec!(0.01,0.99), &f2s[1]));
let last_error=nn.train(&vec!(0.05,0.1),&vec!(0.01,0.99),0.5,10000,0.0000000001);
assert!(last_error.1<0.00001);
assert!(last_error.0<=10000);
}
#[test]
fn test_becominghuman(){
// <https://becominghuman.ai/making-a-simple-neural-network-2ea1de81ec20>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(4,4,1));
let tests = vec!(
Test{input:vec!(1.0,0.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,0.0,0.0),target:vec!(0.0)},
Test{input:vec!(0.0,0.0,1.0,0.0),target:vec!(1.0)},
Test{input:vec!(0.0,0.0,0.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,10000);
println!("last: {}",last_error);
assert!(last_error<0.001);
}
#[test]
fn test_towards(){
// <https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6>
let mut nn = Network::new_random(vec!(Box::new(Sigmoid{}),Box::new(Sigmoid{})),vec!(3,4,1));
let tests = vec!(
Test{input:vec!(0.0,0.0,1.0),target:vec!(0.0)},
Test{input:vec!(0.0,1.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,0.0,1.0),target:vec!(1.0)},
Test{input:vec!(1.0,1.0,1.0),target:vec!(0.0)},
);
let last_error=nn.train_online(&tests,0.5,1500);
println!("last: {}",last_error);
assert!(last_error<0.05);
}
#[test]
fn test_softmax(){
assert_eq!(vec!(0.09003057317038046, 0.24472847105479764, 0.6652409557748218),softmax(&vec!(1.0,2.0,3.0)));
assert_eq!(vec!(0.0, 0.0, 1.0),softmax(&vec!(1000.0,2000.0,3000.0)));
}
}
| forward | identifier_name |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple classes addition, hashmaps for syscalls)
// Copyright 2020 Solana Maintainers <maintainers@solana.com>
//
// Licensed under the Apache License, Version 2.0 <http://www.apache.org/licenses/LICENSE-2.0> or
// the MIT license <http://opensource.org/licenses/MIT>, at your option. This file may not be
// copied, modified, or distributed except according to those terms.
//! Virtual machine for eBPF programs.
use crate::{
ebpf,
elf::{Executable, FunctionRegistry, SBPFVersion},
error::EbpfError,
interpreter::Interpreter,
memory_region::MemoryMapping,
static_analysis::{Analysis, TraceLogEntry},
};
use std::{collections::BTreeMap, fmt::Debug, mem, sync::Arc};
/// Same as `Result` but provides a stable memory layout
#[derive(Debug)]
#[repr(C, u64)]
pub enum StableResult<T, E> {
/// Success
Ok(T),
/// Failure
Err(E),
}
impl<T: Debug, E: Debug> StableResult<T, E> {
/// `true` if `Ok`
pub fn is_ok(&self) -> bool {
match self {
Self::Ok(_) => true,
Self::Err(_) => false,
}
}
/// `true` if `Err`
pub fn is_err(&self) -> bool {
match self {
Self::Ok(_) => false,
Self::Err(_) => true,
}
}
/// Returns the inner value if `Ok`, panics otherwise
pub fn unwrap(self) -> T {
match self {
Self::Ok(value) => value,
Self::Err(error) => panic!("unwrap {:?}", error),
}
}
/// Returns the inner error if `Err`, panics otherwise
pub fn unwrap_err(self) -> E {
match self {
Self::Ok(value) => panic!("unwrap_err {:?}", value),
Self::Err(error) => error,
}
}
}
impl<T, E> From<StableResult<T, E>> for Result<T, E> {
fn from(result: StableResult<T, E>) -> Self {
match result {
StableResult::Ok(value) => Ok(value),
StableResult::Err(value) => Err(value),
}
}
}
impl<T, E> From<Result<T, E>> for StableResult<T, E> {
fn from(result: Result<T, E>) -> Self {
match result {
Ok(value) => Self::Ok(value),
Err(value) => Self::Err(value),
}
}
}
/// Return value of programs and syscalls
pub type ProgramResult = StableResult<u64, Box<dyn std::error::Error>>;
/// Syscall function without context
pub type BuiltinFunction<C> =
fn(&mut C, u64, u64, u64, u64, u64, &mut MemoryMapping, &mut ProgramResult);
/// Represents the interface to a fixed functionality program
#[derive(Eq)]
pub struct BuiltinProgram<C: ContextObject> {
/// Holds the Config if this is a loader program
config: Option<Box<Config>>,
/// Function pointers by symbol
functions: FunctionRegistry<BuiltinFunction<C>>,
}
impl<C: ContextObject> PartialEq for BuiltinProgram<C> {
fn eq(&self, other: &Self) -> bool {
self.config.eq(&other.config) && self.functions.eq(&other.functions)
}
}
impl<C: ContextObject> BuiltinProgram<C> {
/// Constructs a loader built-in program
pub fn new_loader(config: Config, functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: Some(Box::new(config)),
functions,
}
}
/// Constructs a built-in program
pub fn new_builtin(functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: None,
functions,
}
}
/// Constructs a mock loader built-in program
pub fn new_mock() -> Self {
Self {
config: Some(Box::default()),
functions: FunctionRegistry::default(),
}
}
/// Get the configuration settings assuming this is a loader program
pub fn get_config(&self) -> &Config {
self.config.as_ref().unwrap()
}
/// Get the function registry
pub fn get_function_registry(&self) -> &FunctionRegistry<BuiltinFunction<C>> {
&self.functions
}
/// Calculate memory size
pub fn mem_size(&self) -> usize {
mem::size_of::<Self>()
+ if self.config.is_some() {
mem::size_of::<Config>()
} else {
0
}
+ self.functions.mem_size()
}
}
impl<C: ContextObject> Debug for BuiltinProgram<C> {
fn fmt(&self, f: &mut std::fmt::Formatter) -> Result<(), std::fmt::Error> {
writeln!(f, "{:?}", unsafe {
// `derive(Debug)` does not know that `C: ContextObject` does not need to implement `Debug`
std::mem::transmute::<
&FunctionRegistry<BuiltinFunction<C>>,
&FunctionRegistry<BuiltinFunction<*const ()>>,
>(&self.functions)
})?;
Ok(())
}
}
/// VM configuration settings
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub struct Config {
/// Maximum call depth
pub max_call_depth: usize,
/// Size of a stack frame in bytes, must match the size specified in the LLVM BPF backend
pub stack_frame_size: usize,
/// Enables the use of MemoryMapping and MemoryRegion for address translation
pub enable_address_translation: bool,
/// Enables gaps in VM address space between the stack frames
pub enable_stack_frame_gaps: bool,
/// Maximal pc distance after which a new instruction meter validation is emitted by the JIT
pub instruction_meter_checkpoint_distance: usize,
/// Enable instruction meter and limiting
pub enable_instruction_meter: bool,
/// Enable instruction tracing
pub enable_instruction_tracing: bool,
/// Enable dynamic string allocation for labels
pub enable_symbol_and_section_labels: bool,
/// Reject ELF files containing issues that the verifier did not catch before (up to v0.2.21)
pub reject_broken_elfs: bool,
/// Ratio of native host instructions per random no-op in JIT (0 = OFF)
pub noop_instruction_rate: u32,
/// Enable disinfection of immediate values and offsets provided by the user in JIT
pub sanitize_user_provided_values: bool,
/// Encrypt the runtime environment in JIT
pub encrypt_runtime_environment: bool,
/// Throw ElfError::SymbolHashCollision when a BPF function collides with a registered syscall
pub external_internal_function_hash_collision: bool,
/// Have the verifier reject "callx r10"
pub reject_callx_r10: bool,
/// Avoid copying read only sections when possible
pub optimize_rodata: bool,
/// Use the new ELF parser
pub new_elf_parser: bool,
/// Use aligned memory mapping
pub aligned_memory_mapping: bool,
/// Allow ExecutableCapability::V1
pub enable_sbpf_v1: bool,
/// Allow ExecutableCapability::V2
pub enable_sbpf_v2: bool,
}
impl Config {
/// Returns the size of the stack memory region
pub fn stack_size(&self) -> usize {
self.stack_frame_size * self.max_call_depth
}
}
impl Default for Config {
fn default() -> Self {
Self {
max_call_depth: 20,
stack_frame_size: 4_096,
enable_address_translation: true,
enable_stack_frame_gaps: true,
instruction_meter_checkpoint_distance: 10000,
enable_instruction_meter: true,
enable_instruction_tracing: false,
enable_symbol_and_section_labels: false,
reject_broken_elfs: false,
noop_instruction_rate: 256,
sanitize_user_provided_values: true,
encrypt_runtime_environment: true,
external_internal_function_hash_collision: true,
reject_callx_r10: true,
optimize_rodata: true,
new_elf_parser: true,
aligned_memory_mapping: true,
enable_sbpf_v1: true,
enable_sbpf_v2: true,
}
}
}
/// Static constructors for Executable
impl<C: ContextObject> Executable<C> {
/// Creates an executable from an ELF file
pub fn from_elf(elf_bytes: &[u8], loader: Arc<BuiltinProgram<C>>) -> Result<Self, EbpfError> {
let executable = Executable::load(elf_bytes, loader)?;
Ok(executable)
}
/// Creates an executable from machine code
pub fn from_text_bytes(
text_bytes: &[u8],
loader: Arc<BuiltinProgram<C>>,
sbpf_version: SBPFVersion,
function_registry: FunctionRegistry<usize>,
) -> Result<Self, EbpfError> {
Executable::new_from_text_bytes(text_bytes, loader, sbpf_version, function_registry)
.map_err(EbpfError::ElfError)
}
}
/// Runtime context
pub trait ContextObject {
/// Called for every instruction executed when tracing is enabled
fn trace(&mut self, state: [u64; 12]);
/// Consume instructions from meter
fn consume(&mut self, amount: u64);
/// Get the number of remaining instructions allowed
fn get_remaining(&self) -> u64;
}
/// Simple instruction meter for testing
#[derive(Debug, Clone, Default)]
pub struct | {
/// Contains the register state at every instruction in order of execution
pub trace_log: Vec<TraceLogEntry>,
/// Maximal amount of instructions which still can be executed
pub remaining: u64,
}
impl ContextObject for TestContextObject {
fn trace(&mut self, state: [u64; 12]) {
self.trace_log.push(state);
}
fn consume(&mut self, amount: u64) {
self.remaining = self.remaining.saturating_sub(amount);
}
fn get_remaining(&self) -> u64 {
self.remaining
}
}
impl TestContextObject {
/// Initialize with instruction meter
pub fn new(remaining: u64) -> Self {
Self {
trace_log: Vec::new(),
remaining,
}
}
/// Compares an interpreter trace and a JIT trace.
///
/// The log of the JIT can be longer because it only validates the instruction meter at branches.
pub fn compare_trace_log(interpreter: &Self, jit: &Self) -> bool {
let interpreter = interpreter.trace_log.as_slice();
let mut jit = jit.trace_log.as_slice();
if jit.len() > interpreter.len() {
jit = &jit[0..interpreter.len()];
}
interpreter == jit
}
}
/// Statistic of taken branches (from a recorded trace)
pub struct DynamicAnalysis {
/// Maximal edge counter value
pub edge_counter_max: usize,
/// src_node, dst_node, edge_counter
pub edges: BTreeMap<usize, BTreeMap<usize, usize>>,
}
impl DynamicAnalysis {
/// Accumulates a trace
pub fn new(trace_log: &[[u64; 12]], analysis: &Analysis) -> Self {
let mut result = Self {
edge_counter_max: 0,
edges: BTreeMap::new(),
};
let mut last_basic_block = usize::MAX;
for traced_instruction in trace_log.iter() {
let pc = traced_instruction[11] as usize;
if analysis.cfg_nodes.contains_key(&pc) {
let counter = result
.edges
.entry(last_basic_block)
.or_default()
.entry(pc)
.or_insert(0);
*counter += 1;
result.edge_counter_max = result.edge_counter_max.max(*counter);
last_basic_block = pc;
}
}
result
}
}
/// A call frame used for function calls inside the Interpreter
#[derive(Clone, Default)]
pub struct CallFrame {
/// The caller saved registers
pub caller_saved_registers: [u64; ebpf::SCRATCH_REGS],
/// The callers frame pointer
pub frame_pointer: u64,
/// The target_pc of the exit instruction which returns back to the caller
pub target_pc: usize,
}
/// A virtual machine to run eBPF programs.
///
/// # Examples
///
/// ```
/// use solana_rbpf::{
/// aligned_memory::AlignedMemory,
/// ebpf,
/// elf::{Executable, FunctionRegistry, SBPFVersion},
/// memory_region::{MemoryMapping, MemoryRegion},
/// verifier::{RequisiteVerifier},
/// vm::{BuiltinProgram, Config, EbpfVm, TestContextObject},
/// };
///
/// let prog = &[
/// 0x95, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 // exit
/// ];
/// let mem = &mut [
/// 0xaa, 0xbb, 0x11, 0x22, 0xcc, 0xdd
/// ];
///
/// let loader = std::sync::Arc::new(BuiltinProgram::new_mock());
/// let function_registry = FunctionRegistry::default();
/// let mut executable = Executable::<TestContextObject>::from_text_bytes(prog, loader, SBPFVersion::V2, function_registry).unwrap();
/// executable.verify::<RequisiteVerifier>().unwrap();
/// let mut context_object = TestContextObject::new(1);
/// let config = executable.get_config();
/// let sbpf_version = executable.get_sbpf_version();
///
/// let mut stack = AlignedMemory::<{ebpf::HOST_ALIGN}>::zero_filled(config.stack_size());
/// let stack_len = stack.len();
/// let mut heap = AlignedMemory::<{ebpf::HOST_ALIGN}>::with_capacity(0);
///
/// let regions: Vec<MemoryRegion> = vec![
/// executable.get_ro_region(),
/// MemoryRegion::new_writable(
/// stack.as_slice_mut(),
/// ebpf::MM_STACK_START,
/// ),
/// MemoryRegion::new_writable(heap.as_slice_mut(), ebpf::MM_HEAP_START),
/// MemoryRegion::new_writable(mem, ebpf::MM_INPUT_START),
/// ];
///
/// let memory_mapping = MemoryMapping::new(regions, config, sbpf_version).unwrap();
///
/// let mut vm = EbpfVm::new(config, sbpf_version, &mut context_object, memory_mapping, stack_len);
///
/// let (instruction_count, result) = vm.execute_program(&executable, true);
/// assert_eq!(instruction_count, 1);
/// assert_eq!(result.unwrap(), 0);
/// ```
#[repr(C)]
pub struct EbpfVm<'a, C: ContextObject> {
/// Needed to exit from the guest back into the host
pub host_stack_pointer: *mut u64,
/// The current call depth.
///
/// Incremented on calls and decremented on exits. It's used to enforce
/// config.max_call_depth and to know when to terminate execution.
pub call_depth: u64,
/// Guest stack pointer (r11).
///
/// The stack pointer isn't exposed as an actual register. Only sub and add
/// instructions (typically generated by the LLVM backend) are allowed to
/// access it when sbpf_version.dynamic_stack_frames()=true. Its value is only
/// stored here and therefore the register is not tracked in REGISTER_MAP.
pub stack_pointer: u64,
/// Pointer to ContextObject
pub context_object_pointer: &'a mut C,
/// Last return value of instruction_meter.get_remaining()
pub previous_instruction_meter: u64,
/// CPU cycles accumulated by the stop watch
pub stopwatch_numerator: u64,
/// Number of times the stop watch was used
pub stopwatch_denominator: u64,
/// ProgramResult inlined
pub program_result: ProgramResult,
/// MemoryMapping inlined
pub memory_mapping: MemoryMapping<'a>,
/// Stack of CallFrames used by the Interpreter
pub call_frames: Vec<CallFrame>,
/// TCP port for the debugger interface
#[cfg(feature = "debugger")]
pub debug_port: Option<u16>,
}
impl<'a, C: ContextObject> EbpfVm<'a, C> {
/// Creates a new virtual machine instance.
pub fn new(
config: &Config,
sbpf_version: &SBPFVersion,
context_object: &'a mut C,
mut memory_mapping: MemoryMapping<'a>,
stack_len: usize,
) -> Self {
let stack_pointer =
ebpf::MM_STACK_START.saturating_add(if sbpf_version.dynamic_stack_frames() {
// the stack is fully descending, frames start as empty and change size anytime r11 is modified
stack_len
} else {
// within a frame the stack grows down, but frames are ascending
config.stack_frame_size
} as u64);
if !config.enable_address_translation {
memory_mapping = MemoryMapping::new_identity();
}
EbpfVm {
host_stack_pointer: std::ptr::null_mut(),
call_depth: 0,
stack_pointer,
context_object_pointer: context_object,
previous_instruction_meter: 0,
stopwatch_numerator: 0,
stopwatch_denominator: 0,
program_result: ProgramResult::Ok(0),
memory_mapping,
call_frames: vec![CallFrame::default(); config.max_call_depth],
#[cfg(feature = "debugger")]
debug_port: None,
}
}
/// Execute the program
///
/// If interpreted = `false` then the JIT compiled executable is used.
pub fn execute_program(
&mut self,
executable: &Executable<C>,
interpreted: bool,
) -> (u64, ProgramResult) {
let mut registers = [0u64; 12];
// R1 points to beginning of input memory, R10 to the stack of the first frame, R11 is the pc (hidden)
registers[1] = ebpf::MM_INPUT_START;
registers[ebpf::FRAME_PTR_REG] = self.stack_pointer;
registers[11] = executable.get_entrypoint_instruction_offset() as u64;
let config = executable.get_config();
let initial_insn_count = if config.enable_instruction_meter {
self.context_object_pointer.get_remaining()
} else {
0
};
self.previous_instruction_meter = initial_insn_count;
self.program_result = ProgramResult::Ok(0);
let due_insn_count = if interpreted {
#[cfg(feature = "debugger")]
let debug_port = self.debug_port.clone();
let mut interpreter = Interpreter::new(self, executable, registers);
#[cfg(feature = "debugger")]
if let Some(debug_port) = debug_port {
crate::debugger::execute(&mut interpreter, debug_port);
} else {
while interpreter.step() {}
}
#[cfg(not(feature = "debugger"))]
while interpreter.step() {}
interpreter.due_insn_count
} else {
#[cfg(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64"))]
{
let compiled_program = match executable
.get_compiled_program()
.ok_or_else(|| Box::new(EbpfError::JitNotCompiled))
{
Ok(compiled_program) => compiled_program,
Err(error) => return (0, ProgramResult::Err(error)),
};
let instruction_meter_final =
compiled_program.invoke(config, self, registers).max(0) as u64;
self.context_object_pointer
.get_remaining()
.saturating_sub(instruction_meter_final)
}
#[cfg(not(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64")))]
{
return (0, ProgramResult::Err(Box::new(EbpfError::JitNotCompiled)));
}
};
let instruction_count = if config.enable_instruction_meter {
self.context_object_pointer.consume(due_insn_count);
initial_insn_count.saturating_sub(self.context_object_pointer.get_remaining())
} else {
0
};
let mut result = ProgramResult::Ok(0);
std::mem::swap(&mut result, &mut self.program_result);
(instruction_count, result)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::syscalls;
#[test]
fn test_program_result_is_stable() {
let ok = ProgramResult::Ok(42);
assert_eq!(unsafe { *(&ok as *const _ as *const u64) }, 0);
let err = ProgramResult::Err(Box::new(EbpfError::JitNotCompiled));
assert_eq!(unsafe { *(&err as *const _ as *const u64) }, 1);
}
#[test]
fn test_builtin_program_eq() {
let mut function_registry_a =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_a
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
function_registry_a
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let mut function_registry_b =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_b
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
function_registry_b
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
let mut function_registry_c =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_c
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let builtin_program_a = BuiltinProgram::new_loader(Config::default(), function_registry_a);
let builtin_program_b = BuiltinProgram::new_loader(Config::default(), function_registry_b);
assert_eq!(builtin_program_a, builtin_program_b);
let builtin_program_c = BuiltinProgram::new_loader(Config::default(), function_registry_c);
assert_ne!(builtin_program_a, builtin_program_c);
}
}
| TestContextObject | identifier_name |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple classes addition, hashmaps for syscalls)
// Copyright 2020 Solana Maintainers <maintainers@solana.com>
//
// Licensed under the Apache License, Version 2.0 <http://www.apache.org/licenses/LICENSE-2.0> or
// the MIT license <http://opensource.org/licenses/MIT>, at your option. This file may not be
// copied, modified, or distributed except according to those terms.
//! Virtual machine for eBPF programs.
use crate::{
ebpf,
elf::{Executable, FunctionRegistry, SBPFVersion},
error::EbpfError,
interpreter::Interpreter,
memory_region::MemoryMapping,
static_analysis::{Analysis, TraceLogEntry},
};
use std::{collections::BTreeMap, fmt::Debug, mem, sync::Arc};
/// Same as `Result` but provides a stable memory layout
#[derive(Debug)]
#[repr(C, u64)]
pub enum StableResult<T, E> {
/// Success
Ok(T),
/// Failure
Err(E),
}
impl<T: Debug, E: Debug> StableResult<T, E> {
/// `true` if `Ok`
pub fn is_ok(&self) -> bool {
match self {
Self::Ok(_) => true,
Self::Err(_) => false,
}
}
/// `true` if `Err`
pub fn is_err(&self) -> bool {
match self {
Self::Ok(_) => false,
Self::Err(_) => true,
}
}
/// Returns the inner value if `Ok`, panics otherwise
pub fn unwrap(self) -> T {
match self {
Self::Ok(value) => value,
Self::Err(error) => panic!("unwrap {:?}", error),
}
}
/// Returns the inner error if `Err`, panics otherwise
pub fn unwrap_err(self) -> E {
match self {
Self::Ok(value) => panic!("unwrap_err {:?}", value),
Self::Err(error) => error,
}
}
}
impl<T, E> From<StableResult<T, E>> for Result<T, E> {
fn from(result: StableResult<T, E>) -> Self {
match result {
StableResult::Ok(value) => Ok(value),
StableResult::Err(value) => Err(value),
}
}
}
impl<T, E> From<Result<T, E>> for StableResult<T, E> {
fn from(result: Result<T, E>) -> Self {
match result {
Ok(value) => Self::Ok(value),
Err(value) => Self::Err(value),
}
}
}
/// Return value of programs and syscalls
pub type ProgramResult = StableResult<u64, Box<dyn std::error::Error>>;
/// Syscall function without context
pub type BuiltinFunction<C> =
fn(&mut C, u64, u64, u64, u64, u64, &mut MemoryMapping, &mut ProgramResult);
/// Represents the interface to a fixed functionality program
#[derive(Eq)]
pub struct BuiltinProgram<C: ContextObject> {
/// Holds the Config if this is a loader program
config: Option<Box<Config>>,
/// Function pointers by symbol
functions: FunctionRegistry<BuiltinFunction<C>>,
}
impl<C: ContextObject> PartialEq for BuiltinProgram<C> {
fn eq(&self, other: &Self) -> bool {
self.config.eq(&other.config) && self.functions.eq(&other.functions)
}
}
impl<C: ContextObject> BuiltinProgram<C> {
/// Constructs a loader built-in program
pub fn new_loader(config: Config, functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: Some(Box::new(config)),
functions,
}
}
/// Constructs a built-in program
pub fn new_builtin(functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: None,
functions,
}
}
/// Constructs a mock loader built-in program
pub fn new_mock() -> Self {
Self {
config: Some(Box::default()),
functions: FunctionRegistry::default(),
}
}
/// Get the configuration settings assuming this is a loader program
pub fn get_config(&self) -> &Config {
self.config.as_ref().unwrap()
}
/// Get the function registry
pub fn get_function_registry(&self) -> &FunctionRegistry<BuiltinFunction<C>> {
&self.functions
}
/// Calculate memory size
pub fn mem_size(&self) -> usize {
mem::size_of::<Self>()
+ if self.config.is_some() {
mem::size_of::<Config>()
} else {
0
}
+ self.functions.mem_size()
}
}
impl<C: ContextObject> Debug for BuiltinProgram<C> {
fn fmt(&self, f: &mut std::fmt::Formatter) -> Result<(), std::fmt::Error> {
writeln!(f, "{:?}", unsafe {
// `derive(Debug)` does not know that `C: ContextObject` does not need to implement `Debug`
std::mem::transmute::<
&FunctionRegistry<BuiltinFunction<C>>,
&FunctionRegistry<BuiltinFunction<*const ()>>,
>(&self.functions)
})?;
Ok(())
}
}
/// VM configuration settings
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub struct Config {
/// Maximum call depth
pub max_call_depth: usize,
/// Size of a stack frame in bytes, must match the size specified in the LLVM BPF backend
pub stack_frame_size: usize,
/// Enables the use of MemoryMapping and MemoryRegion for address translation
pub enable_address_translation: bool,
/// Enables gaps in VM address space between the stack frames
pub enable_stack_frame_gaps: bool,
/// Maximal pc distance after which a new instruction meter validation is emitted by the JIT
pub instruction_meter_checkpoint_distance: usize,
/// Enable instruction meter and limiting
pub enable_instruction_meter: bool,
/// Enable instruction tracing
pub enable_instruction_tracing: bool,
/// Enable dynamic string allocation for labels
pub enable_symbol_and_section_labels: bool,
/// Reject ELF files containing issues that the verifier did not catch before (up to v0.2.21)
pub reject_broken_elfs: bool,
/// Ratio of native host instructions per random no-op in JIT (0 = OFF)
pub noop_instruction_rate: u32,
/// Enable disinfection of immediate values and offsets provided by the user in JIT
pub sanitize_user_provided_values: bool,
/// Encrypt the runtime environment in JIT
pub encrypt_runtime_environment: bool,
/// Throw ElfError::SymbolHashCollision when a BPF function collides with a registered syscall
pub external_internal_function_hash_collision: bool,
/// Have the verifier reject "callx r10"
pub reject_callx_r10: bool,
/// Avoid copying read only sections when possible
pub optimize_rodata: bool,
/// Use the new ELF parser
pub new_elf_parser: bool,
/// Use aligned memory mapping
pub aligned_memory_mapping: bool,
/// Allow ExecutableCapability::V1
pub enable_sbpf_v1: bool,
/// Allow ExecutableCapability::V2
pub enable_sbpf_v2: bool,
}
impl Config {
/// Returns the size of the stack memory region
pub fn stack_size(&self) -> usize {
self.stack_frame_size * self.max_call_depth
}
}
impl Default for Config {
fn default() -> Self {
Self {
max_call_depth: 20,
stack_frame_size: 4_096,
enable_address_translation: true,
enable_stack_frame_gaps: true,
instruction_meter_checkpoint_distance: 10000,
enable_instruction_meter: true,
enable_instruction_tracing: false,
enable_symbol_and_section_labels: false,
reject_broken_elfs: false,
noop_instruction_rate: 256,
sanitize_user_provided_values: true,
encrypt_runtime_environment: true,
external_internal_function_hash_collision: true,
reject_callx_r10: true,
optimize_rodata: true,
new_elf_parser: true,
aligned_memory_mapping: true,
enable_sbpf_v1: true,
enable_sbpf_v2: true,
}
}
}
/// Static constructors for Executable
impl<C: ContextObject> Executable<C> {
/// Creates an executable from an ELF file
pub fn from_elf(elf_bytes: &[u8], loader: Arc<BuiltinProgram<C>>) -> Result<Self, EbpfError> {
let executable = Executable::load(elf_bytes, loader)?;
Ok(executable)
}
/// Creates an executable from machine code
pub fn from_text_bytes(
text_bytes: &[u8],
loader: Arc<BuiltinProgram<C>>,
sbpf_version: SBPFVersion,
function_registry: FunctionRegistry<usize>,
) -> Result<Self, EbpfError> {
Executable::new_from_text_bytes(text_bytes, loader, sbpf_version, function_registry)
.map_err(EbpfError::ElfError)
}
}
/// Runtime context
pub trait ContextObject {
/// Called for every instruction executed when tracing is enabled
fn trace(&mut self, state: [u64; 12]);
/// Consume instructions from meter
fn consume(&mut self, amount: u64);
/// Get the number of remaining instructions allowed
fn get_remaining(&self) -> u64;
}
/// Simple instruction meter for testing
#[derive(Debug, Clone, Default)]
pub struct TestContextObject {
/// Contains the register state at every instruction in order of execution
pub trace_log: Vec<TraceLogEntry>,
/// Maximal amount of instructions which still can be executed
pub remaining: u64,
}
impl ContextObject for TestContextObject {
fn trace(&mut self, state: [u64; 12]) {
self.trace_log.push(state);
}
fn consume(&mut self, amount: u64) {
self.remaining = self.remaining.saturating_sub(amount);
}
fn get_remaining(&self) -> u64 {
self.remaining
}
}
impl TestContextObject {
/// Initialize with instruction meter
pub fn new(remaining: u64) -> Self {
Self {
trace_log: Vec::new(),
remaining,
}
}
/// Compares an interpreter trace and a JIT trace.
///
/// The log of the JIT can be longer because it only validates the instruction meter at branches.
pub fn compare_trace_log(interpreter: &Self, jit: &Self) -> bool {
let interpreter = interpreter.trace_log.as_slice();
let mut jit = jit.trace_log.as_slice();
if jit.len() > interpreter.len() {
jit = &jit[0..interpreter.len()];
}
interpreter == jit
}
}
/// Statistic of taken branches (from a recorded trace)
pub struct DynamicAnalysis {
/// Maximal edge counter value
pub edge_counter_max: usize,
/// src_node, dst_node, edge_counter
pub edges: BTreeMap<usize, BTreeMap<usize, usize>>,
}
impl DynamicAnalysis {
/// Accumulates a trace
pub fn new(trace_log: &[[u64; 12]], analysis: &Analysis) -> Self {
let mut result = Self {
edge_counter_max: 0,
edges: BTreeMap::new(),
};
let mut last_basic_block = usize::MAX;
for traced_instruction in trace_log.iter() {
let pc = traced_instruction[11] as usize;
if analysis.cfg_nodes.contains_key(&pc) {
let counter = result
.edges
.entry(last_basic_block)
.or_default()
.entry(pc)
.or_insert(0);
*counter += 1;
result.edge_counter_max = result.edge_counter_max.max(*counter);
last_basic_block = pc;
}
}
result
}
}
/// A call frame used for function calls inside the Interpreter
#[derive(Clone, Default)]
pub struct CallFrame {
/// The caller saved registers
pub caller_saved_registers: [u64; ebpf::SCRATCH_REGS],
/// The callers frame pointer
pub frame_pointer: u64,
/// The target_pc of the exit instruction which returns back to the caller
pub target_pc: usize,
}
/// A virtual machine to run eBPF programs.
///
/// # Examples
///
/// ```
/// use solana_rbpf::{
/// aligned_memory::AlignedMemory,
/// ebpf,
/// elf::{Executable, FunctionRegistry, SBPFVersion},
/// memory_region::{MemoryMapping, MemoryRegion},
/// verifier::{RequisiteVerifier},
/// vm::{BuiltinProgram, Config, EbpfVm, TestContextObject},
/// };
///
/// let prog = &[
/// 0x95, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 // exit
/// ];
/// let mem = &mut [
/// 0xaa, 0xbb, 0x11, 0x22, 0xcc, 0xdd
/// ];
///
/// let loader = std::sync::Arc::new(BuiltinProgram::new_mock());
/// let function_registry = FunctionRegistry::default();
/// let mut executable = Executable::<TestContextObject>::from_text_bytes(prog, loader, SBPFVersion::V2, function_registry).unwrap();
/// executable.verify::<RequisiteVerifier>().unwrap();
/// let mut context_object = TestContextObject::new(1);
/// let config = executable.get_config();
/// let sbpf_version = executable.get_sbpf_version();
///
/// let mut stack = AlignedMemory::<{ebpf::HOST_ALIGN}>::zero_filled(config.stack_size());
/// let stack_len = stack.len();
/// let mut heap = AlignedMemory::<{ebpf::HOST_ALIGN}>::with_capacity(0);
///
/// let regions: Vec<MemoryRegion> = vec![
/// executable.get_ro_region(),
/// MemoryRegion::new_writable(
/// stack.as_slice_mut(),
/// ebpf::MM_STACK_START,
/// ),
/// MemoryRegion::new_writable(heap.as_slice_mut(), ebpf::MM_HEAP_START),
/// MemoryRegion::new_writable(mem, ebpf::MM_INPUT_START),
/// ];
///
/// let memory_mapping = MemoryMapping::new(regions, config, sbpf_version).unwrap();
///
/// let mut vm = EbpfVm::new(config, sbpf_version, &mut context_object, memory_mapping, stack_len);
///
/// let (instruction_count, result) = vm.execute_program(&executable, true);
/// assert_eq!(instruction_count, 1);
/// assert_eq!(result.unwrap(), 0);
/// ```
#[repr(C)]
pub struct EbpfVm<'a, C: ContextObject> {
/// Needed to exit from the guest back into the host
pub host_stack_pointer: *mut u64,
/// The current call depth.
///
/// Incremented on calls and decremented on exits. It's used to enforce
/// config.max_call_depth and to know when to terminate execution.
pub call_depth: u64,
/// Guest stack pointer (r11).
///
/// The stack pointer isn't exposed as an actual register. Only sub and add
/// instructions (typically generated by the LLVM backend) are allowed to
/// access it when sbpf_version.dynamic_stack_frames()=true. Its value is only
/// stored here and therefore the register is not tracked in REGISTER_MAP.
pub stack_pointer: u64,
/// Pointer to ContextObject
pub context_object_pointer: &'a mut C,
/// Last return value of instruction_meter.get_remaining()
pub previous_instruction_meter: u64,
/// CPU cycles accumulated by the stop watch
pub stopwatch_numerator: u64,
/// Number of times the stop watch was used
pub stopwatch_denominator: u64,
/// ProgramResult inlined
pub program_result: ProgramResult,
/// MemoryMapping inlined
pub memory_mapping: MemoryMapping<'a>,
/// Stack of CallFrames used by the Interpreter
pub call_frames: Vec<CallFrame>,
/// TCP port for the debugger interface
#[cfg(feature = "debugger")]
pub debug_port: Option<u16>,
}
impl<'a, C: ContextObject> EbpfVm<'a, C> {
/// Creates a new virtual machine instance.
pub fn new(
config: &Config,
sbpf_version: &SBPFVersion,
context_object: &'a mut C,
mut memory_mapping: MemoryMapping<'a>,
stack_len: usize,
) -> Self {
let stack_pointer =
ebpf::MM_STACK_START.saturating_add(if sbpf_version.dynamic_stack_frames() {
// the stack is fully descending, frames start as empty and change size anytime r11 is modified
stack_len
} else {
// within a frame the stack grows down, but frames are ascending
config.stack_frame_size
} as u64);
if !config.enable_address_translation {
memory_mapping = MemoryMapping::new_identity();
}
EbpfVm {
host_stack_pointer: std::ptr::null_mut(),
call_depth: 0,
stack_pointer,
context_object_pointer: context_object,
previous_instruction_meter: 0,
stopwatch_numerator: 0,
stopwatch_denominator: 0,
program_result: ProgramResult::Ok(0),
memory_mapping,
call_frames: vec![CallFrame::default(); config.max_call_depth],
#[cfg(feature = "debugger")]
debug_port: None,
}
}
/// Execute the program
///
/// If interpreted = `false` then the JIT compiled executable is used.
pub fn execute_program(
&mut self,
executable: &Executable<C>,
interpreted: bool,
) -> (u64, ProgramResult) |
}
#[cfg(test)]
mod tests {
use super::*;
use crate::syscalls;
#[test]
fn test_program_result_is_stable() {
let ok = ProgramResult::Ok(42);
assert_eq!(unsafe { *(&ok as *const _ as *const u64) }, 0);
let err = ProgramResult::Err(Box::new(EbpfError::JitNotCompiled));
assert_eq!(unsafe { *(&err as *const _ as *const u64) }, 1);
}
#[test]
fn test_builtin_program_eq() {
let mut function_registry_a =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_a
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
function_registry_a
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let mut function_registry_b =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_b
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
function_registry_b
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
let mut function_registry_c =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_c
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let builtin_program_a = BuiltinProgram::new_loader(Config::default(), function_registry_a);
let builtin_program_b = BuiltinProgram::new_loader(Config::default(), function_registry_b);
assert_eq!(builtin_program_a, builtin_program_b);
let builtin_program_c = BuiltinProgram::new_loader(Config::default(), function_registry_c);
assert_ne!(builtin_program_a, builtin_program_c);
}
}
| {
let mut registers = [0u64; 12];
// R1 points to beginning of input memory, R10 to the stack of the first frame, R11 is the pc (hidden)
registers[1] = ebpf::MM_INPUT_START;
registers[ebpf::FRAME_PTR_REG] = self.stack_pointer;
registers[11] = executable.get_entrypoint_instruction_offset() as u64;
let config = executable.get_config();
let initial_insn_count = if config.enable_instruction_meter {
self.context_object_pointer.get_remaining()
} else {
0
};
self.previous_instruction_meter = initial_insn_count;
self.program_result = ProgramResult::Ok(0);
let due_insn_count = if interpreted {
#[cfg(feature = "debugger")]
let debug_port = self.debug_port.clone();
let mut interpreter = Interpreter::new(self, executable, registers);
#[cfg(feature = "debugger")]
if let Some(debug_port) = debug_port {
crate::debugger::execute(&mut interpreter, debug_port);
} else {
while interpreter.step() {}
}
#[cfg(not(feature = "debugger"))]
while interpreter.step() {}
interpreter.due_insn_count
} else {
#[cfg(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64"))]
{
let compiled_program = match executable
.get_compiled_program()
.ok_or_else(|| Box::new(EbpfError::JitNotCompiled))
{
Ok(compiled_program) => compiled_program,
Err(error) => return (0, ProgramResult::Err(error)),
};
let instruction_meter_final =
compiled_program.invoke(config, self, registers).max(0) as u64;
self.context_object_pointer
.get_remaining()
.saturating_sub(instruction_meter_final)
}
#[cfg(not(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64")))]
{
return (0, ProgramResult::Err(Box::new(EbpfError::JitNotCompiled)));
}
};
let instruction_count = if config.enable_instruction_meter {
self.context_object_pointer.consume(due_insn_count);
initial_insn_count.saturating_sub(self.context_object_pointer.get_remaining())
} else {
0
};
let mut result = ProgramResult::Ok(0);
std::mem::swap(&mut result, &mut self.program_result);
(instruction_count, result)
} | identifier_body |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple classes addition, hashmaps for syscalls)
// Copyright 2020 Solana Maintainers <maintainers@solana.com>
//
// Licensed under the Apache License, Version 2.0 <http://www.apache.org/licenses/LICENSE-2.0> or
// the MIT license <http://opensource.org/licenses/MIT>, at your option. This file may not be
// copied, modified, or distributed except according to those terms.
//! Virtual machine for eBPF programs.
use crate::{
ebpf,
elf::{Executable, FunctionRegistry, SBPFVersion},
error::EbpfError,
interpreter::Interpreter,
memory_region::MemoryMapping,
static_analysis::{Analysis, TraceLogEntry},
};
use std::{collections::BTreeMap, fmt::Debug, mem, sync::Arc};
/// Same as `Result` but provides a stable memory layout
#[derive(Debug)]
#[repr(C, u64)]
pub enum StableResult<T, E> {
/// Success
Ok(T),
/// Failure
Err(E),
}
impl<T: Debug, E: Debug> StableResult<T, E> {
/// `true` if `Ok`
pub fn is_ok(&self) -> bool {
match self {
Self::Ok(_) => true,
Self::Err(_) => false,
}
}
/// `true` if `Err`
pub fn is_err(&self) -> bool {
match self {
Self::Ok(_) => false,
Self::Err(_) => true,
}
}
/// Returns the inner value if `Ok`, panics otherwise
pub fn unwrap(self) -> T {
match self {
Self::Ok(value) => value,
Self::Err(error) => panic!("unwrap {:?}", error),
}
}
/// Returns the inner error if `Err`, panics otherwise
pub fn unwrap_err(self) -> E {
match self {
Self::Ok(value) => panic!("unwrap_err {:?}", value),
Self::Err(error) => error,
}
}
}
impl<T, E> From<StableResult<T, E>> for Result<T, E> {
fn from(result: StableResult<T, E>) -> Self {
match result {
StableResult::Ok(value) => Ok(value),
StableResult::Err(value) => Err(value),
}
}
}
impl<T, E> From<Result<T, E>> for StableResult<T, E> {
fn from(result: Result<T, E>) -> Self {
match result {
Ok(value) => Self::Ok(value),
Err(value) => Self::Err(value),
}
}
}
/// Return value of programs and syscalls
pub type ProgramResult = StableResult<u64, Box<dyn std::error::Error>>;
/// Syscall function without context
pub type BuiltinFunction<C> =
fn(&mut C, u64, u64, u64, u64, u64, &mut MemoryMapping, &mut ProgramResult);
/// Represents the interface to a fixed functionality program
#[derive(Eq)]
pub struct BuiltinProgram<C: ContextObject> {
/// Holds the Config if this is a loader program
config: Option<Box<Config>>,
/// Function pointers by symbol
functions: FunctionRegistry<BuiltinFunction<C>>,
}
impl<C: ContextObject> PartialEq for BuiltinProgram<C> {
fn eq(&self, other: &Self) -> bool {
self.config.eq(&other.config) && self.functions.eq(&other.functions)
}
}
impl<C: ContextObject> BuiltinProgram<C> {
/// Constructs a loader built-in program
pub fn new_loader(config: Config, functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: Some(Box::new(config)),
functions,
}
}
/// Constructs a built-in program
pub fn new_builtin(functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: None,
functions,
}
}
/// Constructs a mock loader built-in program
pub fn new_mock() -> Self {
Self {
config: Some(Box::default()),
functions: FunctionRegistry::default(),
}
}
/// Get the configuration settings assuming this is a loader program
pub fn get_config(&self) -> &Config {
self.config.as_ref().unwrap()
}
/// Get the function registry
pub fn get_function_registry(&self) -> &FunctionRegistry<BuiltinFunction<C>> {
&self.functions
}
/// Calculate memory size
pub fn mem_size(&self) -> usize {
mem::size_of::<Self>()
+ if self.config.is_some() {
mem::size_of::<Config>()
} else {
0
}
+ self.functions.mem_size()
}
}
impl<C: ContextObject> Debug for BuiltinProgram<C> {
fn fmt(&self, f: &mut std::fmt::Formatter) -> Result<(), std::fmt::Error> {
writeln!(f, "{:?}", unsafe {
// `derive(Debug)` does not know that `C: ContextObject` does not need to implement `Debug`
std::mem::transmute::<
&FunctionRegistry<BuiltinFunction<C>>,
&FunctionRegistry<BuiltinFunction<*const ()>>,
>(&self.functions)
})?;
Ok(())
}
}
/// VM configuration settings
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub struct Config {
/// Maximum call depth
pub max_call_depth: usize,
/// Size of a stack frame in bytes, must match the size specified in the LLVM BPF backend
pub stack_frame_size: usize,
/// Enables the use of MemoryMapping and MemoryRegion for address translation
pub enable_address_translation: bool,
/// Enables gaps in VM address space between the stack frames
pub enable_stack_frame_gaps: bool,
/// Maximal pc distance after which a new instruction meter validation is emitted by the JIT
pub instruction_meter_checkpoint_distance: usize,
/// Enable instruction meter and limiting
pub enable_instruction_meter: bool,
/// Enable instruction tracing
pub enable_instruction_tracing: bool,
/// Enable dynamic string allocation for labels
pub enable_symbol_and_section_labels: bool,
/// Reject ELF files containing issues that the verifier did not catch before (up to v0.2.21)
pub reject_broken_elfs: bool,
/// Ratio of native host instructions per random no-op in JIT (0 = OFF)
pub noop_instruction_rate: u32,
/// Enable disinfection of immediate values and offsets provided by the user in JIT
pub sanitize_user_provided_values: bool,
/// Encrypt the runtime environment in JIT
pub encrypt_runtime_environment: bool,
/// Throw ElfError::SymbolHashCollision when a BPF function collides with a registered syscall
pub external_internal_function_hash_collision: bool,
/// Have the verifier reject "callx r10"
pub reject_callx_r10: bool,
/// Avoid copying read only sections when possible
pub optimize_rodata: bool,
/// Use the new ELF parser
pub new_elf_parser: bool,
/// Use aligned memory mapping
pub aligned_memory_mapping: bool,
/// Allow ExecutableCapability::V1
pub enable_sbpf_v1: bool,
/// Allow ExecutableCapability::V2
pub enable_sbpf_v2: bool,
}
impl Config {
/// Returns the size of the stack memory region
pub fn stack_size(&self) -> usize {
self.stack_frame_size * self.max_call_depth
}
}
impl Default for Config {
fn default() -> Self {
Self {
max_call_depth: 20,
stack_frame_size: 4_096,
enable_address_translation: true,
enable_stack_frame_gaps: true,
instruction_meter_checkpoint_distance: 10000,
enable_instruction_meter: true,
enable_instruction_tracing: false,
enable_symbol_and_section_labels: false,
reject_broken_elfs: false,
noop_instruction_rate: 256,
sanitize_user_provided_values: true,
encrypt_runtime_environment: true,
external_internal_function_hash_collision: true,
reject_callx_r10: true,
optimize_rodata: true,
new_elf_parser: true,
aligned_memory_mapping: true,
enable_sbpf_v1: true,
enable_sbpf_v2: true,
}
}
}
/// Static constructors for Executable
impl<C: ContextObject> Executable<C> {
/// Creates an executable from an ELF file
pub fn from_elf(elf_bytes: &[u8], loader: Arc<BuiltinProgram<C>>) -> Result<Self, EbpfError> {
let executable = Executable::load(elf_bytes, loader)?;
Ok(executable)
}
/// Creates an executable from machine code
pub fn from_text_bytes(
text_bytes: &[u8],
loader: Arc<BuiltinProgram<C>>,
sbpf_version: SBPFVersion,
function_registry: FunctionRegistry<usize>,
) -> Result<Self, EbpfError> {
Executable::new_from_text_bytes(text_bytes, loader, sbpf_version, function_registry)
.map_err(EbpfError::ElfError)
}
}
/// Runtime context
pub trait ContextObject {
/// Called for every instruction executed when tracing is enabled
fn trace(&mut self, state: [u64; 12]);
/// Consume instructions from meter
fn consume(&mut self, amount: u64);
/// Get the number of remaining instructions allowed
fn get_remaining(&self) -> u64;
}
/// Simple instruction meter for testing
#[derive(Debug, Clone, Default)]
pub struct TestContextObject {
/// Contains the register state at every instruction in order of execution
pub trace_log: Vec<TraceLogEntry>,
/// Maximal amount of instructions which still can be executed
pub remaining: u64,
}
impl ContextObject for TestContextObject {
fn trace(&mut self, state: [u64; 12]) {
self.trace_log.push(state);
}
fn consume(&mut self, amount: u64) {
self.remaining = self.remaining.saturating_sub(amount);
}
fn get_remaining(&self) -> u64 {
self.remaining
}
}
impl TestContextObject {
/// Initialize with instruction meter
pub fn new(remaining: u64) -> Self {
Self {
trace_log: Vec::new(),
remaining,
}
}
/// Compares an interpreter trace and a JIT trace.
///
/// The log of the JIT can be longer because it only validates the instruction meter at branches.
pub fn compare_trace_log(interpreter: &Self, jit: &Self) -> bool {
let interpreter = interpreter.trace_log.as_slice();
let mut jit = jit.trace_log.as_slice();
if jit.len() > interpreter.len() {
jit = &jit[0..interpreter.len()];
}
interpreter == jit
}
}
/// Statistic of taken branches (from a recorded trace)
pub struct DynamicAnalysis {
/// Maximal edge counter value
pub edge_counter_max: usize,
/// src_node, dst_node, edge_counter
pub edges: BTreeMap<usize, BTreeMap<usize, usize>>,
}
impl DynamicAnalysis {
/// Accumulates a trace
pub fn new(trace_log: &[[u64; 12]], analysis: &Analysis) -> Self {
let mut result = Self {
edge_counter_max: 0,
edges: BTreeMap::new(),
};
let mut last_basic_block = usize::MAX;
for traced_instruction in trace_log.iter() {
let pc = traced_instruction[11] as usize;
if analysis.cfg_nodes.contains_key(&pc) {
let counter = result
.edges
.entry(last_basic_block)
.or_default()
.entry(pc)
.or_insert(0);
*counter += 1;
result.edge_counter_max = result.edge_counter_max.max(*counter);
last_basic_block = pc;
}
}
result
}
}
/// A call frame used for function calls inside the Interpreter
#[derive(Clone, Default)]
pub struct CallFrame {
/// The caller saved registers
pub caller_saved_registers: [u64; ebpf::SCRATCH_REGS],
/// The callers frame pointer
pub frame_pointer: u64,
/// The target_pc of the exit instruction which returns back to the caller
pub target_pc: usize,
}
/// A virtual machine to run eBPF programs.
///
/// # Examples
///
/// ```
/// use solana_rbpf::{
/// aligned_memory::AlignedMemory,
/// ebpf,
/// elf::{Executable, FunctionRegistry, SBPFVersion},
/// memory_region::{MemoryMapping, MemoryRegion},
/// verifier::{RequisiteVerifier},
/// vm::{BuiltinProgram, Config, EbpfVm, TestContextObject},
/// };
///
/// let prog = &[
/// 0x95, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 // exit
/// ];
/// let mem = &mut [
/// 0xaa, 0xbb, 0x11, 0x22, 0xcc, 0xdd
/// ];
///
/// let loader = std::sync::Arc::new(BuiltinProgram::new_mock());
/// let function_registry = FunctionRegistry::default();
/// let mut executable = Executable::<TestContextObject>::from_text_bytes(prog, loader, SBPFVersion::V2, function_registry).unwrap();
/// executable.verify::<RequisiteVerifier>().unwrap();
/// let mut context_object = TestContextObject::new(1);
/// let config = executable.get_config();
/// let sbpf_version = executable.get_sbpf_version();
///
/// let mut stack = AlignedMemory::<{ebpf::HOST_ALIGN}>::zero_filled(config.stack_size());
/// let stack_len = stack.len();
/// let mut heap = AlignedMemory::<{ebpf::HOST_ALIGN}>::with_capacity(0);
///
/// let regions: Vec<MemoryRegion> = vec![
/// executable.get_ro_region(),
/// MemoryRegion::new_writable(
/// stack.as_slice_mut(),
/// ebpf::MM_STACK_START,
/// ),
/// MemoryRegion::new_writable(heap.as_slice_mut(), ebpf::MM_HEAP_START),
/// MemoryRegion::new_writable(mem, ebpf::MM_INPUT_START),
/// ];
///
/// let memory_mapping = MemoryMapping::new(regions, config, sbpf_version).unwrap();
///
/// let mut vm = EbpfVm::new(config, sbpf_version, &mut context_object, memory_mapping, stack_len);
///
/// let (instruction_count, result) = vm.execute_program(&executable, true);
/// assert_eq!(instruction_count, 1);
/// assert_eq!(result.unwrap(), 0);
/// ```
#[repr(C)]
pub struct EbpfVm<'a, C: ContextObject> {
/// Needed to exit from the guest back into the host
pub host_stack_pointer: *mut u64,
/// The current call depth.
///
/// Incremented on calls and decremented on exits. It's used to enforce
/// config.max_call_depth and to know when to terminate execution.
pub call_depth: u64,
/// Guest stack pointer (r11).
///
/// The stack pointer isn't exposed as an actual register. Only sub and add
/// instructions (typically generated by the LLVM backend) are allowed to
/// access it when sbpf_version.dynamic_stack_frames()=true. Its value is only
/// stored here and therefore the register is not tracked in REGISTER_MAP.
pub stack_pointer: u64,
/// Pointer to ContextObject
pub context_object_pointer: &'a mut C,
/// Last return value of instruction_meter.get_remaining()
pub previous_instruction_meter: u64,
/// CPU cycles accumulated by the stop watch
pub stopwatch_numerator: u64,
/// Number of times the stop watch was used
pub stopwatch_denominator: u64,
/// ProgramResult inlined
pub program_result: ProgramResult,
/// MemoryMapping inlined
pub memory_mapping: MemoryMapping<'a>,
/// Stack of CallFrames used by the Interpreter
pub call_frames: Vec<CallFrame>,
/// TCP port for the debugger interface
#[cfg(feature = "debugger")] |
impl<'a, C: ContextObject> EbpfVm<'a, C> {
/// Creates a new virtual machine instance.
pub fn new(
config: &Config,
sbpf_version: &SBPFVersion,
context_object: &'a mut C,
mut memory_mapping: MemoryMapping<'a>,
stack_len: usize,
) -> Self {
let stack_pointer =
ebpf::MM_STACK_START.saturating_add(if sbpf_version.dynamic_stack_frames() {
// the stack is fully descending, frames start as empty and change size anytime r11 is modified
stack_len
} else {
// within a frame the stack grows down, but frames are ascending
config.stack_frame_size
} as u64);
if !config.enable_address_translation {
memory_mapping = MemoryMapping::new_identity();
}
EbpfVm {
host_stack_pointer: std::ptr::null_mut(),
call_depth: 0,
stack_pointer,
context_object_pointer: context_object,
previous_instruction_meter: 0,
stopwatch_numerator: 0,
stopwatch_denominator: 0,
program_result: ProgramResult::Ok(0),
memory_mapping,
call_frames: vec![CallFrame::default(); config.max_call_depth],
#[cfg(feature = "debugger")]
debug_port: None,
}
}
/// Execute the program
///
/// If interpreted = `false` then the JIT compiled executable is used.
pub fn execute_program(
&mut self,
executable: &Executable<C>,
interpreted: bool,
) -> (u64, ProgramResult) {
let mut registers = [0u64; 12];
// R1 points to beginning of input memory, R10 to the stack of the first frame, R11 is the pc (hidden)
registers[1] = ebpf::MM_INPUT_START;
registers[ebpf::FRAME_PTR_REG] = self.stack_pointer;
registers[11] = executable.get_entrypoint_instruction_offset() as u64;
let config = executable.get_config();
let initial_insn_count = if config.enable_instruction_meter {
self.context_object_pointer.get_remaining()
} else {
0
};
self.previous_instruction_meter = initial_insn_count;
self.program_result = ProgramResult::Ok(0);
let due_insn_count = if interpreted {
#[cfg(feature = "debugger")]
let debug_port = self.debug_port.clone();
let mut interpreter = Interpreter::new(self, executable, registers);
#[cfg(feature = "debugger")]
if let Some(debug_port) = debug_port {
crate::debugger::execute(&mut interpreter, debug_port);
} else {
while interpreter.step() {}
}
#[cfg(not(feature = "debugger"))]
while interpreter.step() {}
interpreter.due_insn_count
} else {
#[cfg(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64"))]
{
let compiled_program = match executable
.get_compiled_program()
.ok_or_else(|| Box::new(EbpfError::JitNotCompiled))
{
Ok(compiled_program) => compiled_program,
Err(error) => return (0, ProgramResult::Err(error)),
};
let instruction_meter_final =
compiled_program.invoke(config, self, registers).max(0) as u64;
self.context_object_pointer
.get_remaining()
.saturating_sub(instruction_meter_final)
}
#[cfg(not(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64")))]
{
return (0, ProgramResult::Err(Box::new(EbpfError::JitNotCompiled)));
}
};
let instruction_count = if config.enable_instruction_meter {
self.context_object_pointer.consume(due_insn_count);
initial_insn_count.saturating_sub(self.context_object_pointer.get_remaining())
} else {
0
};
let mut result = ProgramResult::Ok(0);
std::mem::swap(&mut result, &mut self.program_result);
(instruction_count, result)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::syscalls;
#[test]
fn test_program_result_is_stable() {
let ok = ProgramResult::Ok(42);
assert_eq!(unsafe { *(&ok as *const _ as *const u64) }, 0);
let err = ProgramResult::Err(Box::new(EbpfError::JitNotCompiled));
assert_eq!(unsafe { *(&err as *const _ as *const u64) }, 1);
}
#[test]
fn test_builtin_program_eq() {
let mut function_registry_a =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_a
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
function_registry_a
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let mut function_registry_b =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_b
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
function_registry_b
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
let mut function_registry_c =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_c
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let builtin_program_a = BuiltinProgram::new_loader(Config::default(), function_registry_a);
let builtin_program_b = BuiltinProgram::new_loader(Config::default(), function_registry_b);
assert_eq!(builtin_program_a, builtin_program_b);
let builtin_program_c = BuiltinProgram::new_loader(Config::default(), function_registry_c);
assert_ne!(builtin_program_a, builtin_program_c);
}
} | pub debug_port: Option<u16>,
} | random_line_split |
vm.rs | #![allow(clippy::arithmetic_side_effects)]
// Derived from uBPF <https://github.com/iovisor/ubpf>
// Copyright 2015 Big Switch Networks, Inc
// (uBPF: VM architecture, parts of the interpreter, originally in C)
// Copyright 2016 6WIND S.A. <quentin.monnet@6wind.com>
// (Translation to Rust, MetaBuff/multiple classes addition, hashmaps for syscalls)
// Copyright 2020 Solana Maintainers <maintainers@solana.com>
//
// Licensed under the Apache License, Version 2.0 <http://www.apache.org/licenses/LICENSE-2.0> or
// the MIT license <http://opensource.org/licenses/MIT>, at your option. This file may not be
// copied, modified, or distributed except according to those terms.
//! Virtual machine for eBPF programs.
use crate::{
ebpf,
elf::{Executable, FunctionRegistry, SBPFVersion},
error::EbpfError,
interpreter::Interpreter,
memory_region::MemoryMapping,
static_analysis::{Analysis, TraceLogEntry},
};
use std::{collections::BTreeMap, fmt::Debug, mem, sync::Arc};
/// Same as `Result` but provides a stable memory layout
#[derive(Debug)]
#[repr(C, u64)]
pub enum StableResult<T, E> {
/// Success
Ok(T),
/// Failure
Err(E),
}
impl<T: Debug, E: Debug> StableResult<T, E> {
/// `true` if `Ok`
pub fn is_ok(&self) -> bool {
match self {
Self::Ok(_) => true,
Self::Err(_) => false,
}
}
/// `true` if `Err`
pub fn is_err(&self) -> bool {
match self {
Self::Ok(_) => false,
Self::Err(_) => true,
}
}
/// Returns the inner value if `Ok`, panics otherwise
pub fn unwrap(self) -> T {
match self {
Self::Ok(value) => value,
Self::Err(error) => panic!("unwrap {:?}", error),
}
}
/// Returns the inner error if `Err`, panics otherwise
pub fn unwrap_err(self) -> E {
match self {
Self::Ok(value) => panic!("unwrap_err {:?}", value),
Self::Err(error) => error,
}
}
}
impl<T, E> From<StableResult<T, E>> for Result<T, E> {
fn from(result: StableResult<T, E>) -> Self {
match result {
StableResult::Ok(value) => Ok(value),
StableResult::Err(value) => Err(value),
}
}
}
impl<T, E> From<Result<T, E>> for StableResult<T, E> {
fn from(result: Result<T, E>) -> Self {
match result {
Ok(value) => Self::Ok(value),
Err(value) => Self::Err(value),
}
}
}
/// Return value of programs and syscalls
pub type ProgramResult = StableResult<u64, Box<dyn std::error::Error>>;
/// Syscall function without context
pub type BuiltinFunction<C> =
fn(&mut C, u64, u64, u64, u64, u64, &mut MemoryMapping, &mut ProgramResult);
/// Represents the interface to a fixed functionality program
#[derive(Eq)]
pub struct BuiltinProgram<C: ContextObject> {
/// Holds the Config if this is a loader program
config: Option<Box<Config>>,
/// Function pointers by symbol
functions: FunctionRegistry<BuiltinFunction<C>>,
}
impl<C: ContextObject> PartialEq for BuiltinProgram<C> {
fn eq(&self, other: &Self) -> bool {
self.config.eq(&other.config) && self.functions.eq(&other.functions)
}
}
impl<C: ContextObject> BuiltinProgram<C> {
/// Constructs a loader built-in program
pub fn new_loader(config: Config, functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: Some(Box::new(config)),
functions,
}
}
/// Constructs a built-in program
pub fn new_builtin(functions: FunctionRegistry<BuiltinFunction<C>>) -> Self {
Self {
config: None,
functions,
}
}
/// Constructs a mock loader built-in program
pub fn new_mock() -> Self {
Self {
config: Some(Box::default()),
functions: FunctionRegistry::default(),
}
}
/// Get the configuration settings assuming this is a loader program
pub fn get_config(&self) -> &Config {
self.config.as_ref().unwrap()
}
/// Get the function registry
pub fn get_function_registry(&self) -> &FunctionRegistry<BuiltinFunction<C>> {
&self.functions
}
/// Calculate memory size
pub fn mem_size(&self) -> usize {
mem::size_of::<Self>()
+ if self.config.is_some() {
mem::size_of::<Config>()
} else {
0
}
+ self.functions.mem_size()
}
}
impl<C: ContextObject> Debug for BuiltinProgram<C> {
fn fmt(&self, f: &mut std::fmt::Formatter) -> Result<(), std::fmt::Error> {
writeln!(f, "{:?}", unsafe {
// `derive(Debug)` does not know that `C: ContextObject` does not need to implement `Debug`
std::mem::transmute::<
&FunctionRegistry<BuiltinFunction<C>>,
&FunctionRegistry<BuiltinFunction<*const ()>>,
>(&self.functions)
})?;
Ok(())
}
}
/// VM configuration settings
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub struct Config {
/// Maximum call depth
pub max_call_depth: usize,
/// Size of a stack frame in bytes, must match the size specified in the LLVM BPF backend
pub stack_frame_size: usize,
/// Enables the use of MemoryMapping and MemoryRegion for address translation
pub enable_address_translation: bool,
/// Enables gaps in VM address space between the stack frames
pub enable_stack_frame_gaps: bool,
/// Maximal pc distance after which a new instruction meter validation is emitted by the JIT
pub instruction_meter_checkpoint_distance: usize,
/// Enable instruction meter and limiting
pub enable_instruction_meter: bool,
/// Enable instruction tracing
pub enable_instruction_tracing: bool,
/// Enable dynamic string allocation for labels
pub enable_symbol_and_section_labels: bool,
/// Reject ELF files containing issues that the verifier did not catch before (up to v0.2.21)
pub reject_broken_elfs: bool,
/// Ratio of native host instructions per random no-op in JIT (0 = OFF)
pub noop_instruction_rate: u32,
/// Enable disinfection of immediate values and offsets provided by the user in JIT
pub sanitize_user_provided_values: bool,
/// Encrypt the runtime environment in JIT
pub encrypt_runtime_environment: bool,
/// Throw ElfError::SymbolHashCollision when a BPF function collides with a registered syscall
pub external_internal_function_hash_collision: bool,
/// Have the verifier reject "callx r10"
pub reject_callx_r10: bool,
/// Avoid copying read only sections when possible
pub optimize_rodata: bool,
/// Use the new ELF parser
pub new_elf_parser: bool,
/// Use aligned memory mapping
pub aligned_memory_mapping: bool,
/// Allow ExecutableCapability::V1
pub enable_sbpf_v1: bool,
/// Allow ExecutableCapability::V2
pub enable_sbpf_v2: bool,
}
impl Config {
/// Returns the size of the stack memory region
pub fn stack_size(&self) -> usize {
self.stack_frame_size * self.max_call_depth
}
}
impl Default for Config {
fn default() -> Self {
Self {
max_call_depth: 20,
stack_frame_size: 4_096,
enable_address_translation: true,
enable_stack_frame_gaps: true,
instruction_meter_checkpoint_distance: 10000,
enable_instruction_meter: true,
enable_instruction_tracing: false,
enable_symbol_and_section_labels: false,
reject_broken_elfs: false,
noop_instruction_rate: 256,
sanitize_user_provided_values: true,
encrypt_runtime_environment: true,
external_internal_function_hash_collision: true,
reject_callx_r10: true,
optimize_rodata: true,
new_elf_parser: true,
aligned_memory_mapping: true,
enable_sbpf_v1: true,
enable_sbpf_v2: true,
}
}
}
/// Static constructors for Executable
impl<C: ContextObject> Executable<C> {
/// Creates an executable from an ELF file
pub fn from_elf(elf_bytes: &[u8], loader: Arc<BuiltinProgram<C>>) -> Result<Self, EbpfError> {
let executable = Executable::load(elf_bytes, loader)?;
Ok(executable)
}
/// Creates an executable from machine code
pub fn from_text_bytes(
text_bytes: &[u8],
loader: Arc<BuiltinProgram<C>>,
sbpf_version: SBPFVersion,
function_registry: FunctionRegistry<usize>,
) -> Result<Self, EbpfError> {
Executable::new_from_text_bytes(text_bytes, loader, sbpf_version, function_registry)
.map_err(EbpfError::ElfError)
}
}
/// Runtime context
pub trait ContextObject {
/// Called for every instruction executed when tracing is enabled
fn trace(&mut self, state: [u64; 12]);
/// Consume instructions from meter
fn consume(&mut self, amount: u64);
/// Get the number of remaining instructions allowed
fn get_remaining(&self) -> u64;
}
/// Simple instruction meter for testing
#[derive(Debug, Clone, Default)]
pub struct TestContextObject {
/// Contains the register state at every instruction in order of execution
pub trace_log: Vec<TraceLogEntry>,
/// Maximal amount of instructions which still can be executed
pub remaining: u64,
}
impl ContextObject for TestContextObject {
fn trace(&mut self, state: [u64; 12]) {
self.trace_log.push(state);
}
fn consume(&mut self, amount: u64) {
self.remaining = self.remaining.saturating_sub(amount);
}
fn get_remaining(&self) -> u64 {
self.remaining
}
}
impl TestContextObject {
/// Initialize with instruction meter
pub fn new(remaining: u64) -> Self {
Self {
trace_log: Vec::new(),
remaining,
}
}
/// Compares an interpreter trace and a JIT trace.
///
/// The log of the JIT can be longer because it only validates the instruction meter at branches.
pub fn compare_trace_log(interpreter: &Self, jit: &Self) -> bool {
let interpreter = interpreter.trace_log.as_slice();
let mut jit = jit.trace_log.as_slice();
if jit.len() > interpreter.len() {
jit = &jit[0..interpreter.len()];
}
interpreter == jit
}
}
/// Statistic of taken branches (from a recorded trace)
pub struct DynamicAnalysis {
/// Maximal edge counter value
pub edge_counter_max: usize,
/// src_node, dst_node, edge_counter
pub edges: BTreeMap<usize, BTreeMap<usize, usize>>,
}
impl DynamicAnalysis {
/// Accumulates a trace
pub fn new(trace_log: &[[u64; 12]], analysis: &Analysis) -> Self {
let mut result = Self {
edge_counter_max: 0,
edges: BTreeMap::new(),
};
let mut last_basic_block = usize::MAX;
for traced_instruction in trace_log.iter() {
let pc = traced_instruction[11] as usize;
if analysis.cfg_nodes.contains_key(&pc) {
let counter = result
.edges
.entry(last_basic_block)
.or_default()
.entry(pc)
.or_insert(0);
*counter += 1;
result.edge_counter_max = result.edge_counter_max.max(*counter);
last_basic_block = pc;
}
}
result
}
}
/// A call frame used for function calls inside the Interpreter
#[derive(Clone, Default)]
pub struct CallFrame {
/// The caller saved registers
pub caller_saved_registers: [u64; ebpf::SCRATCH_REGS],
/// The callers frame pointer
pub frame_pointer: u64,
/// The target_pc of the exit instruction which returns back to the caller
pub target_pc: usize,
}
/// A virtual machine to run eBPF programs.
///
/// # Examples
///
/// ```
/// use solana_rbpf::{
/// aligned_memory::AlignedMemory,
/// ebpf,
/// elf::{Executable, FunctionRegistry, SBPFVersion},
/// memory_region::{MemoryMapping, MemoryRegion},
/// verifier::{RequisiteVerifier},
/// vm::{BuiltinProgram, Config, EbpfVm, TestContextObject},
/// };
///
/// let prog = &[
/// 0x95, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00 // exit
/// ];
/// let mem = &mut [
/// 0xaa, 0xbb, 0x11, 0x22, 0xcc, 0xdd
/// ];
///
/// let loader = std::sync::Arc::new(BuiltinProgram::new_mock());
/// let function_registry = FunctionRegistry::default();
/// let mut executable = Executable::<TestContextObject>::from_text_bytes(prog, loader, SBPFVersion::V2, function_registry).unwrap();
/// executable.verify::<RequisiteVerifier>().unwrap();
/// let mut context_object = TestContextObject::new(1);
/// let config = executable.get_config();
/// let sbpf_version = executable.get_sbpf_version();
///
/// let mut stack = AlignedMemory::<{ebpf::HOST_ALIGN}>::zero_filled(config.stack_size());
/// let stack_len = stack.len();
/// let mut heap = AlignedMemory::<{ebpf::HOST_ALIGN}>::with_capacity(0);
///
/// let regions: Vec<MemoryRegion> = vec![
/// executable.get_ro_region(),
/// MemoryRegion::new_writable(
/// stack.as_slice_mut(),
/// ebpf::MM_STACK_START,
/// ),
/// MemoryRegion::new_writable(heap.as_slice_mut(), ebpf::MM_HEAP_START),
/// MemoryRegion::new_writable(mem, ebpf::MM_INPUT_START),
/// ];
///
/// let memory_mapping = MemoryMapping::new(regions, config, sbpf_version).unwrap();
///
/// let mut vm = EbpfVm::new(config, sbpf_version, &mut context_object, memory_mapping, stack_len);
///
/// let (instruction_count, result) = vm.execute_program(&executable, true);
/// assert_eq!(instruction_count, 1);
/// assert_eq!(result.unwrap(), 0);
/// ```
#[repr(C)]
pub struct EbpfVm<'a, C: ContextObject> {
/// Needed to exit from the guest back into the host
pub host_stack_pointer: *mut u64,
/// The current call depth.
///
/// Incremented on calls and decremented on exits. It's used to enforce
/// config.max_call_depth and to know when to terminate execution.
pub call_depth: u64,
/// Guest stack pointer (r11).
///
/// The stack pointer isn't exposed as an actual register. Only sub and add
/// instructions (typically generated by the LLVM backend) are allowed to
/// access it when sbpf_version.dynamic_stack_frames()=true. Its value is only
/// stored here and therefore the register is not tracked in REGISTER_MAP.
pub stack_pointer: u64,
/// Pointer to ContextObject
pub context_object_pointer: &'a mut C,
/// Last return value of instruction_meter.get_remaining()
pub previous_instruction_meter: u64,
/// CPU cycles accumulated by the stop watch
pub stopwatch_numerator: u64,
/// Number of times the stop watch was used
pub stopwatch_denominator: u64,
/// ProgramResult inlined
pub program_result: ProgramResult,
/// MemoryMapping inlined
pub memory_mapping: MemoryMapping<'a>,
/// Stack of CallFrames used by the Interpreter
pub call_frames: Vec<CallFrame>,
/// TCP port for the debugger interface
#[cfg(feature = "debugger")]
pub debug_port: Option<u16>,
}
impl<'a, C: ContextObject> EbpfVm<'a, C> {
/// Creates a new virtual machine instance.
pub fn new(
config: &Config,
sbpf_version: &SBPFVersion,
context_object: &'a mut C,
mut memory_mapping: MemoryMapping<'a>,
stack_len: usize,
) -> Self {
let stack_pointer =
ebpf::MM_STACK_START.saturating_add(if sbpf_version.dynamic_stack_frames() {
// the stack is fully descending, frames start as empty and change size anytime r11 is modified
stack_len
} else {
// within a frame the stack grows down, but frames are ascending
config.stack_frame_size
} as u64);
if !config.enable_address_translation {
memory_mapping = MemoryMapping::new_identity();
}
EbpfVm {
host_stack_pointer: std::ptr::null_mut(),
call_depth: 0,
stack_pointer,
context_object_pointer: context_object,
previous_instruction_meter: 0,
stopwatch_numerator: 0,
stopwatch_denominator: 0,
program_result: ProgramResult::Ok(0),
memory_mapping,
call_frames: vec![CallFrame::default(); config.max_call_depth],
#[cfg(feature = "debugger")]
debug_port: None,
}
}
/// Execute the program
///
/// If interpreted = `false` then the JIT compiled executable is used.
pub fn execute_program(
&mut self,
executable: &Executable<C>,
interpreted: bool,
) -> (u64, ProgramResult) {
let mut registers = [0u64; 12];
// R1 points to beginning of input memory, R10 to the stack of the first frame, R11 is the pc (hidden)
registers[1] = ebpf::MM_INPUT_START;
registers[ebpf::FRAME_PTR_REG] = self.stack_pointer;
registers[11] = executable.get_entrypoint_instruction_offset() as u64;
let config = executable.get_config();
let initial_insn_count = if config.enable_instruction_meter {
self.context_object_pointer.get_remaining()
} else {
0
};
self.previous_instruction_meter = initial_insn_count;
self.program_result = ProgramResult::Ok(0);
let due_insn_count = if interpreted {
#[cfg(feature = "debugger")]
let debug_port = self.debug_port.clone();
let mut interpreter = Interpreter::new(self, executable, registers);
#[cfg(feature = "debugger")]
if let Some(debug_port) = debug_port {
crate::debugger::execute(&mut interpreter, debug_port);
} else {
while interpreter.step() {}
}
#[cfg(not(feature = "debugger"))]
while interpreter.step() {}
interpreter.due_insn_count
} else | ;
let instruction_count = if config.enable_instruction_meter {
self.context_object_pointer.consume(due_insn_count);
initial_insn_count.saturating_sub(self.context_object_pointer.get_remaining())
} else {
0
};
let mut result = ProgramResult::Ok(0);
std::mem::swap(&mut result, &mut self.program_result);
(instruction_count, result)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::syscalls;
#[test]
fn test_program_result_is_stable() {
let ok = ProgramResult::Ok(42);
assert_eq!(unsafe { *(&ok as *const _ as *const u64) }, 0);
let err = ProgramResult::Err(Box::new(EbpfError::JitNotCompiled));
assert_eq!(unsafe { *(&err as *const _ as *const u64) }, 1);
}
#[test]
fn test_builtin_program_eq() {
let mut function_registry_a =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_a
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
function_registry_a
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let mut function_registry_b =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_b
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
function_registry_b
.register_function_hashed(*b"log", syscalls::bpf_syscall_string)
.unwrap();
let mut function_registry_c =
FunctionRegistry::<BuiltinFunction<TestContextObject>>::default();
function_registry_c
.register_function_hashed(*b"log_64", syscalls::bpf_syscall_u64)
.unwrap();
let builtin_program_a = BuiltinProgram::new_loader(Config::default(), function_registry_a);
let builtin_program_b = BuiltinProgram::new_loader(Config::default(), function_registry_b);
assert_eq!(builtin_program_a, builtin_program_b);
let builtin_program_c = BuiltinProgram::new_loader(Config::default(), function_registry_c);
assert_ne!(builtin_program_a, builtin_program_c);
}
}
| {
#[cfg(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64"))]
{
let compiled_program = match executable
.get_compiled_program()
.ok_or_else(|| Box::new(EbpfError::JitNotCompiled))
{
Ok(compiled_program) => compiled_program,
Err(error) => return (0, ProgramResult::Err(error)),
};
let instruction_meter_final =
compiled_program.invoke(config, self, registers).max(0) as u64;
self.context_object_pointer
.get_remaining()
.saturating_sub(instruction_meter_final)
}
#[cfg(not(all(feature = "jit", not(target_os = "windows"), target_arch = "x86_64")))]
{
return (0, ProgramResult::Err(Box::new(EbpfError::JitNotCompiled)));
}
} | conditional_block |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt::Debug;
#[cfg(feature = "std")]
use rand::Rng;
use digest::BlockInput;
use digest::Digest;
use digest::Input;
use digest::FixedOutput;
use generic_array::typenum::U64;
use curve25519_dalek::constants;
use curve25519_dalek::edwards::CompressedEdwardsY;
use curve25519_dalek::edwards::ExtendedPoint;
use curve25519_dalek::scalar::Scalar;
use subtle::slices_equal;
/// The length of an ed25519 EdDSA `Signature`, in bytes.
pub const SIGNATURE_LENGTH: usize = 64;
/// The length of an ed25519 EdDSA `SecretKey`, in bytes.
pub const SECRET_KEY_LENGTH: usize = 32;
/// The length of an ed25519 EdDSA `PublicKey`, in bytes.
pub const PUBLIC_KEY_LENGTH: usize = 32;
/// An EdDSA signature.
///
/// # Note
///
/// These signatures, unlike the ed25519 signature reference implementation, are
/// "detached"—that is, they do **not** include a copy of the message which has
/// been signed.
#[derive(Copy)]
#[repr(C)]
pub struct Signature(pub [u8; SIGNATURE_LENGTH]);
impl Clone for Signature {
fn clone(&self) -> Self { *self }
}
impl Debug for Signature {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "Signature([{:?}])", &self.0[..])
}
}
impl Eq for Signature {}
impl PartialEq for Signature {
fn eq(&self, other: &Signature) -> bool {
let mut equal: u8 = 0;
for i in 0..64 {
equal |= self.0[i] ^ other.0[i];
}
if equal == 0 {
return true;
} else {
return false;
}
}
}
impl Signature {
/// View this `Signature` as a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SIGNATURE_LENGTH] {
self.0
}
/// View this `Signature` as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SIGNATURE_LENGTH] {
&self.0
}
/// Construct a `Signature` from a slice of bytes.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> Signature {
Signature(*array_ref!(bytes, 0, SIGNATURE_LENGTH))
}
}
/// An EdDSA secret key.
#[repr(C)]
pub struct SecretKey(pub [u8; SECRET_KEY_LENGTH]);
impl Debug for SecretKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "SecretKey: {:?}", &self.0[..])
}
}
impl SecretKey {
/// Convert this secret key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SECRET_KEY_LENGTH] {
self.0
}
/// View this secret key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SECRET_KEY_LENGTH] {
&self.0
}
/// Construct a `SecretKey` from a slice of bytes.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::SECRET_KEY_LENGTH;
///
/// let secret_key_bytes: [u8; SECRET_KEY_LENGTH] = [
/// 157, 097, 177, 157, 239, 253, 090, 096,
/// 186, 132, 074, 244, 146, 236, 044, 196,
/// 068, 073, 197, 105, 123, 050, 105, 025,
/// 112, 059, 172, 003, 028, 174, 127, 096, ];
///
/// let secret_key: SecretKey = SecretKey::from_bytes(&secret_key_bytes[..]);
/// # }
/// ```
///
/// # Returns
///
/// An EdDSA `SecretKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> SecretKey {
SecretKey(*array_ref!(bytes, 0, SECRET_KEY_LENGTH))
}
/// Generate a `SecretKey` from a `csprng`.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::Signature;
///
/// let mut csprng: OsRng = OsRng::new().unwrap();
/// let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// # }
/// ```
///
/// Afterwards, you can generate the corresponding public—provided you also
/// supply a hash function which implements the `Digest` and `Default`
/// traits, and which returns 512 bits of output—via:
///
/// ```
/// # extern crate rand;
/// # extern crate sha2;
/// # extern crate ed25519_dalek;
/// #
/// # fn main() {
/// #
/// # use rand::Rng;
/// # use rand::OsRng;
/// # use sha2::Sha512;
/// # use ed25519_dalek::PublicKey;
/// # use ed25519_dalek::SecretKey;
/// # use ed25519_dalek::Signature;
/// #
/// # let mut csprng: OsRng = OsRng::new().unwrap();
/// # let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// let public_key: PublicKey = PublicKey::from_secret::<Sha512>(&secret_key);
/// # }
/// ```
///
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
///
/// # Input
///
/// A CSPRING with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
#[cfg(feature = "std")]
pub fn generate(csprng: &mut Rng) -> SecretKey {
let mut sk: SecretKey = SecretKey([0u8; 32]);
csprng.fill_bytes(&mut sk.0);
sk
}
}
/// An ed25519 public key.
#[derive(Copy, Clone)]
#[repr(C)]
pub struct PublicKey(pub CompressedEdwardsY);
impl Debug for PublicKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "PublicKey( CompressedPoint( {:?} ))", self.0)
}
}
impl PublicKey {
/// Convert this public key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; PUBLIC_KEY_LENGTH] {
self.0.to_bytes()
}
/// View this public key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; PUBLIC_KEY_LENGTH] {
&(self.0).0
}
/// Construct a `PublicKey` from a slice of bytes.
///
/// # Warning
///
/// The caller is responsible for ensuring that the bytes passed into this
/// method actually represent a `curve25519_dalek::curve::CompressedEdwardsY`
/// and that said compressed point is actually a point on the curve.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::PUBLIC_KEY_LENGTH;
///
/// let public_key_bytes: [u8; PUBLIC_KEY_LENGTH] = [
/// 215, 90, 152, 1, 130, 177, 10, 183, 213, 75, 254, 211, 201, 100, 7, 58,
/// 14, 225, 114, 243, 218, 166, 35, 37, 175, 2, 26, 104, 247, 7, 81, 26];
///
/// let public_key: PublicKey = PublicKey::from_bytes(&public_key_bytes);
/// # }
/// ```
///
/// # Returns
///
/// A `PublicKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> PublicKey {
PublicKey(CompressedEdwardsY(*array_ref!(bytes, 0, 32)))
}
/// Convert this public key to its underlying extended twisted Edwards coordinate.
#[inline]
fn decompress(&self) -> Option<ExtendedPoint> {
self.0.decompress()
}
/// Derive this public key from its corresponding `SecretKey`.
#[cfg(feature = "std")]
#[allow(unused_assignments)]
pub fn from_secret<D>(secret_key: &SecretKey) -> PublicKey
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let pk: [u8; 32];
let mut digest: &mut [u8; 32];
h.input(secret_key.as_bytes());
hash.copy_from_slice(h.fixed_result().as_slice());
digest = array_mut_ref!(&mut hash, 0, 32);
digest[0] &= 248;
digest[31] &= 127;
digest[31] |= 64;
pk = (&Scalar(*digest) * &constants::ED25519_BASEPOINT_TABLE).compress().to_bytes();
PublicKey(CompressedEdwardsY(pk))
}
/// Verify a signature on a message with this keypair's public key.
///
/// # Return
///
/// Returns true if the signature was successfully verified, and
/// false otherwise.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: Digest<OutputSize = U64> + Default {
use curve25519_dalek::edwards::vartime;
let mut h: D = D::default();
let mut a: ExtendedPoint;
let ao: Option<ExtendedPoint>;
let r: ExtendedPoint;
let digest: [u8; 64];
let digest_reduced: Scalar;
if signature.0[63] & 224 != 0 {
return false;
}
ao = self.decompress();
if ao.is_some() {
a = ao.unwrap();
} else {
return false;
}
a = -(&a);
let top_half: &[u8; 32] = array_ref!(&signature.0, 32, 32);
let bottom_half: &[u8; 32] = array_ref!(&signature.0, 0, 32);
h.input(&bottom_half[..]);
h.input(&self.to_bytes());
h.input(&message);
let digest_bytes = h.fixed_result();
digest = *array_ref!(digest_bytes, 0, 64);
digest_reduced = Scalar::reduce(&digest);
r = vartime::double_scalar_mult_basepoint(&digest_reduced, &a, &Scalar(*top_half));
slices_equal(bottom_half, &r.compress().to_bytes()) == 1
}
}
/// An ed25519 keypair.
#[derive(Debug)]
#[repr(C)]
pub struct Keypair {
/// The public half of this keypair.
pub public: PublicKey,
/// The secret half of this keypair.
pub secret: SecretKey,
}
impl Keypair {
/// Construct a `Keypair` from the bytes of a `PublicKey` and `SecretKey`.
///
/// # Inputs
///
/// * `public`: a `[u8; 32]` representing the compressed Edwards-Y
/// coordinate of a point on curve25519.
/// * `secret`: a `[u8; 32]` representing the corresponding secret key.
///
/// # Warning
///
/// Absolutely no validation is done on the key. If you give this function
/// bytes which do not represent a valid point, or which do not represent
/// corresponding parts of the key, then your `Keypair` will be broken and
/// it will be your fault.
///
/// # Returns
///
/// A `Keypair`.
pub fn from_bytes<'a>(public: &'a [u8; 32], secret: &'a [u8; 32]) -> Keypair {
Keypair{ public: PublicKey::from_bytes(public),
secret: SecretKey::from_bytes(secret), }
}
/// Generate an ed25519 keypair.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::Keypair;
/// use ed25519_dalek::Signature;
///
/// let mut cspring: OsRng = OsRng::new().unwrap();
/// let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
///
/// # }
/// ```
///
/// # Input
///
/// A CSPRNG with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
/// The caller must also supply a hash function which implements the
/// `Digest` and `Default` traits, and which returns 512 bits of output.
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
#[cfg(feature = "std")]
pub fn generate<D>(csprng: &mut Rng) -> Keypair
where D: Digest<OutputSize = U64> + Default {
let sk: SecretKey = SecretKey::generate(csprng);
let pk: PublicKey = PublicKey::from_secret::<D>(&sk);
Keypair{ public: pk, secret: sk }
}
/// Sign a message with this keypair's secret key.
pub fn sign<D>(&self, message: &[u8]) -> Signature
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let mut signature_bytes: [u8; 64] = [0u8; SIGNATURE_LENGTH];
let mut expanded_key_secret: Scalar;
let mesg_digest: Scalar;
let hram_digest: Scalar;
let r: ExtendedPoint;
let s: Scalar;
let t: CompressedEdwardsY;
let secret_key: &[u8; 32] = self.secret.as_bytes();
let public_key: &[u8; 32] = self.public.as_bytes();
h.input(secret_key);
hash.copy_from_slice(h.fixed_result().as_slice());
expanded_key_secret = Scalar(*array_ref!(&hash, 0, 32));
expanded_key_secret[0] &= 248;
expanded_key_secret[31] &= 63;
expanded_key_secret[31] |= 64;
h = D::default();
h.input(&hash[32..]);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
mesg_digest = Scalar::reduce(&hash);
r = &mesg_digest * &constants::ED25519_BASEPOINT_TABLE;
h = D::default();
h.input(&r.compress().to_bytes()[..]);
h.input(public_key);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
hram_digest = Scalar::reduce(&hash);
s = Scalar::multiply_add(&hram_digest, &expanded_key_secret, &mesg_digest);
t = r.compress();
signature_bytes[..32].copy_from_slice(&t.0);
signature_bytes[32..64].copy_from_slice(&s.0);
Signature(*array_ref!(&signature_bytes, 0, 64))
}
/// Verify a signature on a message with this keypair's public key.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: FixedOutput<OutputSize = U64> + BlockInput + Default + Input {
self.public.verify::<D>(message, signature)
}
}
#[cfg(test)]
mod test {
use std::io::BufReader;
use std::io::BufRead;
use std::fs::File;
use std::string::String;
use std::vec::Vec;
use curve25519_dalek::edwards::ExtendedPoint;
use rand::OsRng;
use hex::FromHex;
use sha2::Sha512;
use super::*;
#[test]
fn unmarshal_marshal() { // TestUnmarshalMarshal
let mut cspring: OsRng;
let mut keypair: Keypair;
let mut x: Option<ExtendedPoint>;
let a: ExtendedPoint;
let public: PublicKey;
cspring = OsRng::new().unwrap();
// from_bytes() fails if vx²-u=0 and vx²+u=0
loop {
keypair = Keypair::generate::<Sha512>(&mut cspring);
x = keypair.public.decompress();
if x.is_some() {
a = x.unwrap();
break;
}
}
public = PublicKey(a.compress());
assert!(keypair.public.0 == public.0);
}
#[test]
fn sign_ver | TestSignVerify
let mut cspring: OsRng;
let keypair: Keypair;
let good_sig: Signature;
let bad_sig: Signature;
let good: &[u8] = "test message".as_bytes();
let bad: &[u8] = "wrong message".as_bytes();
cspring = OsRng::new().unwrap();
keypair = Keypair::generate::<Sha512>(&mut cspring);
good_sig = keypair.sign::<Sha512>(&good);
bad_sig = keypair.sign::<Sha512>(&bad);
assert!(keypair.verify::<Sha512>(&good, &good_sig) == true,
"Verification of a valid signature failed!");
assert!(keypair.verify::<Sha512>(&good, &bad_sig) == false,
"Verification of a signature on a different message passed!");
assert!(keypair.verify::<Sha512>(&bad, &good_sig) == false,
"Verification of a signature on a different message passed!");
}
// TESTVECTORS is taken from sign.input.gz in agl's ed25519 Golang
// package. It is a selection of test cases from
// http://ed25519.cr.yp.to/python/sign.input
#[cfg(test)]
#[cfg(not(release))]
#[test]
fn golden() { // TestGolden
let mut line: String;
let mut lineno: usize = 0;
let f = File::open("TESTVECTORS");
if f.is_err() {
println!("This test is only available when the code has been cloned \
from the git repository, since the TESTVECTORS file is large \
and is therefore not included within the distributed crate.");
panic!();
}
let file = BufReader::new(f.unwrap());
for l in file.lines() {
lineno += 1;
line = l.unwrap();
let parts: Vec<&str> = line.split(':').collect();
assert_eq!(parts.len(), 5, "wrong number of fields in line {}", lineno);
let sec_bytes: Vec<u8>= FromHex::from_hex(&parts[0]).unwrap();
let pub_bytes: Vec<u8> = FromHex::from_hex(&parts[1]).unwrap();
let message: Vec<u8> = FromHex::from_hex(&parts[2]).unwrap();
let sig_bytes: Vec<u8> = FromHex::from_hex(&parts[3]).unwrap();
// The signatures in the test vectors also include the message
// at the end, but we just want R and S.
let sig1: Signature = Signature::from_bytes(sig_bytes.as_ref());
let keypair: Keypair = Keypair::from_bytes(
array_ref!(*pub_bytes, 0, PUBLIC_KEY_LENGTH),
array_ref!(*sec_bytes, 0, SECRET_KEY_LENGTH));
let sig2: Signature = keypair.sign::<Sha512>(&message);
assert!(sig1 == sig2, "Signature bytes not equal on line {}", lineno);
assert!(keypair.verify::<Sha512>(&message, &sig2),
"Signature verification failed on line {}", lineno);
}
}
}
#[cfg(all(test, feature = "bench"))]
mod bench {
use test::Bencher;
use rand::OsRng;
use sha2::Sha512;
use super::*;
/// A fake RNG which simply returns zeroes.
struct ZeroRng;
impl ZeroRng {
pub fn new() -> ZeroRng {
ZeroRng
}
}
impl Rng for ZeroRng {
fn next_u32(&mut self) -> u32 { 0u32 }
fn fill_bytes(&mut self, bytes: &mut [u8]) {
for i in 0 .. bytes.len() {
bytes[i] = 0;
}
}
}
#[bench]
fn sign(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
b.iter(| | keypair.sign::<Sha512>(msg));
}
#[bench]
fn verify(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
let sig: Signature = keypair.sign::<Sha512>(msg);
b.iter(| | keypair.verify::<Sha512>(msg, &sig));
}
#[bench]
fn key_generation(b: &mut Bencher) {
let mut rng: ZeroRng = ZeroRng::new();
b.iter(| | Keypair::generate::<Sha512>(&mut rng));
}
#[bench]
fn underlying_scalar_mult_basepoint(b: &mut Bencher) {
use curve25519_dalek::constants::ED25519_BASEPOINT_TABLE;
let scalar: Scalar = Scalar([ 20, 130, 129, 196, 247, 182, 211, 102,
11, 168, 169, 131, 159, 69, 126, 35,
109, 193, 175, 54, 118, 234, 138, 81,
60, 183, 80, 186, 92, 248, 132, 13, ]);
b.iter(| | &scalar * &ED25519_BASEPOINT_TABLE);
}
}
| ify() { // | identifier_name |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt::Debug;
#[cfg(feature = "std")]
use rand::Rng;
use digest::BlockInput;
use digest::Digest;
use digest::Input;
use digest::FixedOutput;
use generic_array::typenum::U64;
use curve25519_dalek::constants;
use curve25519_dalek::edwards::CompressedEdwardsY;
use curve25519_dalek::edwards::ExtendedPoint;
use curve25519_dalek::scalar::Scalar;
use subtle::slices_equal;
/// The length of an ed25519 EdDSA `Signature`, in bytes.
pub const SIGNATURE_LENGTH: usize = 64;
/// The length of an ed25519 EdDSA `SecretKey`, in bytes.
pub const SECRET_KEY_LENGTH: usize = 32;
/// The length of an ed25519 EdDSA `PublicKey`, in bytes.
pub const PUBLIC_KEY_LENGTH: usize = 32;
/// An EdDSA signature.
///
/// # Note
///
/// These signatures, unlike the ed25519 signature reference implementation, are
/// "detached"—that is, they do **not** include a copy of the message which has
/// been signed.
#[derive(Copy)]
#[repr(C)]
pub struct Signature(pub [u8; SIGNATURE_LENGTH]);
impl Clone for Signature {
fn clone(&self) -> Self { *self }
}
impl Debug for Signature {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "Signature([{:?}])", &self.0[..])
}
}
impl Eq for Signature {}
impl PartialEq for Signature {
fn eq(&self, other: &Signature) -> bool {
let mut equal: u8 = 0;
for i in 0..64 {
equal |= self.0[i] ^ other.0[i];
}
if equal == 0 {
return true;
} else {
return false;
}
}
}
impl Signature {
/// View this `Signature` as a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SIGNATURE_LENGTH] {
self.0
}
/// View this `Signature` as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SIGNATURE_LENGTH] {
&self.0
}
/// Construct a `Signature` from a slice of bytes.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> Signature {
Signature(*array_ref!(bytes, 0, SIGNATURE_LENGTH))
}
}
/// An EdDSA secret key.
#[repr(C)]
pub struct SecretKey(pub [u8; SECRET_KEY_LENGTH]);
impl Debug for SecretKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "SecretKey: {:?}", &self.0[..])
}
}
impl SecretKey {
/// Convert this secret key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SECRET_KEY_LENGTH] {
self.0
}
/// View this secret key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SECRET_KEY_LENGTH] {
&self.0
}
/// Construct a `SecretKey` from a slice of bytes.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::SECRET_KEY_LENGTH;
///
/// let secret_key_bytes: [u8; SECRET_KEY_LENGTH] = [
/// 157, 097, 177, 157, 239, 253, 090, 096,
/// 186, 132, 074, 244, 146, 236, 044, 196,
/// 068, 073, 197, 105, 123, 050, 105, 025,
/// 112, 059, 172, 003, 028, 174, 127, 096, ];
///
/// let secret_key: SecretKey = SecretKey::from_bytes(&secret_key_bytes[..]);
/// # }
/// ```
///
/// # Returns
///
/// An EdDSA `SecretKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> SecretKey {
SecretKey(*array_ref!(bytes, 0, SECRET_KEY_LENGTH))
}
/// Generate a `SecretKey` from a `csprng`.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::Signature;
///
/// let mut csprng: OsRng = OsRng::new().unwrap();
/// let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// # }
/// ```
///
/// Afterwards, you can generate the corresponding public—provided you also
/// supply a hash function which implements the `Digest` and `Default`
/// traits, and which returns 512 bits of output—via:
///
/// ```
/// # extern crate rand;
/// # extern crate sha2;
/// # extern crate ed25519_dalek;
/// #
/// # fn main() {
/// #
/// # use rand::Rng;
/// # use rand::OsRng;
/// # use sha2::Sha512;
/// # use ed25519_dalek::PublicKey;
/// # use ed25519_dalek::SecretKey;
/// # use ed25519_dalek::Signature;
/// #
/// # let mut csprng: OsRng = OsRng::new().unwrap();
/// # let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// let public_key: PublicKey = PublicKey::from_secret::<Sha512>(&secret_key);
/// # }
/// ```
///
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
///
/// # Input
///
/// A CSPRING with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
#[cfg(feature = "std")]
pub fn generate(csprng: &mut Rng) -> SecretKey {
let mut sk: SecretKey = SecretKey([0u8; 32]);
csprng.fill_bytes(&mut sk.0);
sk
}
}
/// An ed25519 public key.
#[derive(Copy, Clone)]
#[repr(C)]
pub struct PublicKey(pub CompressedEdwardsY);
impl Debug for PublicKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "PublicKey( CompressedPoint( {:?} ))", self.0)
}
}
impl PublicKey {
/// Convert this public key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; PUBLIC_KEY_LENGTH] {
self.0.to_bytes()
}
/// View this public key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; PUBLIC_KEY_LENGTH] {
&(self.0).0
}
/// Construct a `PublicKey` from a slice of bytes.
///
/// # Warning
///
/// The caller is responsible for ensuring that the bytes passed into this
/// method actually represent a `curve25519_dalek::curve::CompressedEdwardsY`
/// and that said compressed point is actually a point on the curve.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::PUBLIC_KEY_LENGTH;
///
/// let public_key_bytes: [u8; PUBLIC_KEY_LENGTH] = [
/// 215, 90, 152, 1, 130, 177, 10, 183, 213, 75, 254, 211, 201, 100, 7, 58,
/// 14, 225, 114, 243, 218, 166, 35, 37, 175, 2, 26, 104, 247, 7, 81, 26];
///
/// let public_key: PublicKey = PublicKey::from_bytes(&public_key_bytes);
/// # }
/// ```
///
/// # Returns
///
/// A `PublicKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> PublicKey {
PublicKey(CompressedEdwardsY(*array_ref!(bytes, 0, 32)))
}
/// Convert this public key to its underlying extended twisted Edwards coordinate.
#[inline]
fn decompress(&self) -> Option<ExtendedPoint> {
self.0.decompress()
}
/// Derive this public key from its corresponding `SecretKey`.
#[cfg(feature = "std")]
#[allow(unused_assignments)]
pub fn from_secret<D>(secret_key: &SecretKey) -> PublicKey
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let pk: [u8; 32];
let mut digest: &mut [u8; 32];
h.input(secret_key.as_bytes());
hash.copy_from_slice(h.fixed_result().as_slice());
digest = array_mut_ref!(&mut hash, 0, 32);
digest[0] &= 248;
digest[31] &= 127;
digest[31] |= 64;
pk = (&Scalar(*digest) * &constants::ED25519_BASEPOINT_TABLE).compress().to_bytes();
PublicKey(CompressedEdwardsY(pk))
}
/// Verify a signature on a message with this keypair's public key.
///
/// # Return
///
/// Returns true if the signature was successfully verified, and
/// false otherwise.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: Digest<OutputSize = U64> + Default {
use curve25519_dalek::edwards::vartime;
let mut h: D = D::default();
let mut a: ExtendedPoint;
let ao: Option<ExtendedPoint>;
let r: ExtendedPoint;
let digest: [u8; 64];
let digest_reduced: Scalar;
if signature.0[63] & 224 != 0 { | if ao.is_some() {
a = ao.unwrap();
} else {
return false;
}
a = -(&a);
let top_half: &[u8; 32] = array_ref!(&signature.0, 32, 32);
let bottom_half: &[u8; 32] = array_ref!(&signature.0, 0, 32);
h.input(&bottom_half[..]);
h.input(&self.to_bytes());
h.input(&message);
let digest_bytes = h.fixed_result();
digest = *array_ref!(digest_bytes, 0, 64);
digest_reduced = Scalar::reduce(&digest);
r = vartime::double_scalar_mult_basepoint(&digest_reduced, &a, &Scalar(*top_half));
slices_equal(bottom_half, &r.compress().to_bytes()) == 1
}
}
/// An ed25519 keypair.
#[derive(Debug)]
#[repr(C)]
pub struct Keypair {
/// The public half of this keypair.
pub public: PublicKey,
/// The secret half of this keypair.
pub secret: SecretKey,
}
impl Keypair {
/// Construct a `Keypair` from the bytes of a `PublicKey` and `SecretKey`.
///
/// # Inputs
///
/// * `public`: a `[u8; 32]` representing the compressed Edwards-Y
/// coordinate of a point on curve25519.
/// * `secret`: a `[u8; 32]` representing the corresponding secret key.
///
/// # Warning
///
/// Absolutely no validation is done on the key. If you give this function
/// bytes which do not represent a valid point, or which do not represent
/// corresponding parts of the key, then your `Keypair` will be broken and
/// it will be your fault.
///
/// # Returns
///
/// A `Keypair`.
pub fn from_bytes<'a>(public: &'a [u8; 32], secret: &'a [u8; 32]) -> Keypair {
Keypair{ public: PublicKey::from_bytes(public),
secret: SecretKey::from_bytes(secret), }
}
/// Generate an ed25519 keypair.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::Keypair;
/// use ed25519_dalek::Signature;
///
/// let mut cspring: OsRng = OsRng::new().unwrap();
/// let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
///
/// # }
/// ```
///
/// # Input
///
/// A CSPRNG with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
/// The caller must also supply a hash function which implements the
/// `Digest` and `Default` traits, and which returns 512 bits of output.
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
#[cfg(feature = "std")]
pub fn generate<D>(csprng: &mut Rng) -> Keypair
where D: Digest<OutputSize = U64> + Default {
let sk: SecretKey = SecretKey::generate(csprng);
let pk: PublicKey = PublicKey::from_secret::<D>(&sk);
Keypair{ public: pk, secret: sk }
}
/// Sign a message with this keypair's secret key.
pub fn sign<D>(&self, message: &[u8]) -> Signature
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let mut signature_bytes: [u8; 64] = [0u8; SIGNATURE_LENGTH];
let mut expanded_key_secret: Scalar;
let mesg_digest: Scalar;
let hram_digest: Scalar;
let r: ExtendedPoint;
let s: Scalar;
let t: CompressedEdwardsY;
let secret_key: &[u8; 32] = self.secret.as_bytes();
let public_key: &[u8; 32] = self.public.as_bytes();
h.input(secret_key);
hash.copy_from_slice(h.fixed_result().as_slice());
expanded_key_secret = Scalar(*array_ref!(&hash, 0, 32));
expanded_key_secret[0] &= 248;
expanded_key_secret[31] &= 63;
expanded_key_secret[31] |= 64;
h = D::default();
h.input(&hash[32..]);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
mesg_digest = Scalar::reduce(&hash);
r = &mesg_digest * &constants::ED25519_BASEPOINT_TABLE;
h = D::default();
h.input(&r.compress().to_bytes()[..]);
h.input(public_key);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
hram_digest = Scalar::reduce(&hash);
s = Scalar::multiply_add(&hram_digest, &expanded_key_secret, &mesg_digest);
t = r.compress();
signature_bytes[..32].copy_from_slice(&t.0);
signature_bytes[32..64].copy_from_slice(&s.0);
Signature(*array_ref!(&signature_bytes, 0, 64))
}
/// Verify a signature on a message with this keypair's public key.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: FixedOutput<OutputSize = U64> + BlockInput + Default + Input {
self.public.verify::<D>(message, signature)
}
}
#[cfg(test)]
mod test {
use std::io::BufReader;
use std::io::BufRead;
use std::fs::File;
use std::string::String;
use std::vec::Vec;
use curve25519_dalek::edwards::ExtendedPoint;
use rand::OsRng;
use hex::FromHex;
use sha2::Sha512;
use super::*;
#[test]
fn unmarshal_marshal() { // TestUnmarshalMarshal
let mut cspring: OsRng;
let mut keypair: Keypair;
let mut x: Option<ExtendedPoint>;
let a: ExtendedPoint;
let public: PublicKey;
cspring = OsRng::new().unwrap();
// from_bytes() fails if vx²-u=0 and vx²+u=0
loop {
keypair = Keypair::generate::<Sha512>(&mut cspring);
x = keypair.public.decompress();
if x.is_some() {
a = x.unwrap();
break;
}
}
public = PublicKey(a.compress());
assert!(keypair.public.0 == public.0);
}
#[test]
fn sign_verify() { // TestSignVerify
let mut cspring: OsRng;
let keypair: Keypair;
let good_sig: Signature;
let bad_sig: Signature;
let good: &[u8] = "test message".as_bytes();
let bad: &[u8] = "wrong message".as_bytes();
cspring = OsRng::new().unwrap();
keypair = Keypair::generate::<Sha512>(&mut cspring);
good_sig = keypair.sign::<Sha512>(&good);
bad_sig = keypair.sign::<Sha512>(&bad);
assert!(keypair.verify::<Sha512>(&good, &good_sig) == true,
"Verification of a valid signature failed!");
assert!(keypair.verify::<Sha512>(&good, &bad_sig) == false,
"Verification of a signature on a different message passed!");
assert!(keypair.verify::<Sha512>(&bad, &good_sig) == false,
"Verification of a signature on a different message passed!");
}
// TESTVECTORS is taken from sign.input.gz in agl's ed25519 Golang
// package. It is a selection of test cases from
// http://ed25519.cr.yp.to/python/sign.input
#[cfg(test)]
#[cfg(not(release))]
#[test]
fn golden() { // TestGolden
let mut line: String;
let mut lineno: usize = 0;
let f = File::open("TESTVECTORS");
if f.is_err() {
println!("This test is only available when the code has been cloned \
from the git repository, since the TESTVECTORS file is large \
and is therefore not included within the distributed crate.");
panic!();
}
let file = BufReader::new(f.unwrap());
for l in file.lines() {
lineno += 1;
line = l.unwrap();
let parts: Vec<&str> = line.split(':').collect();
assert_eq!(parts.len(), 5, "wrong number of fields in line {}", lineno);
let sec_bytes: Vec<u8>= FromHex::from_hex(&parts[0]).unwrap();
let pub_bytes: Vec<u8> = FromHex::from_hex(&parts[1]).unwrap();
let message: Vec<u8> = FromHex::from_hex(&parts[2]).unwrap();
let sig_bytes: Vec<u8> = FromHex::from_hex(&parts[3]).unwrap();
// The signatures in the test vectors also include the message
// at the end, but we just want R and S.
let sig1: Signature = Signature::from_bytes(sig_bytes.as_ref());
let keypair: Keypair = Keypair::from_bytes(
array_ref!(*pub_bytes, 0, PUBLIC_KEY_LENGTH),
array_ref!(*sec_bytes, 0, SECRET_KEY_LENGTH));
let sig2: Signature = keypair.sign::<Sha512>(&message);
assert!(sig1 == sig2, "Signature bytes not equal on line {}", lineno);
assert!(keypair.verify::<Sha512>(&message, &sig2),
"Signature verification failed on line {}", lineno);
}
}
}
#[cfg(all(test, feature = "bench"))]
mod bench {
use test::Bencher;
use rand::OsRng;
use sha2::Sha512;
use super::*;
/// A fake RNG which simply returns zeroes.
struct ZeroRng;
impl ZeroRng {
pub fn new() -> ZeroRng {
ZeroRng
}
}
impl Rng for ZeroRng {
fn next_u32(&mut self) -> u32 { 0u32 }
fn fill_bytes(&mut self, bytes: &mut [u8]) {
for i in 0 .. bytes.len() {
bytes[i] = 0;
}
}
}
#[bench]
fn sign(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
b.iter(| | keypair.sign::<Sha512>(msg));
}
#[bench]
fn verify(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
let sig: Signature = keypair.sign::<Sha512>(msg);
b.iter(| | keypair.verify::<Sha512>(msg, &sig));
}
#[bench]
fn key_generation(b: &mut Bencher) {
let mut rng: ZeroRng = ZeroRng::new();
b.iter(| | Keypair::generate::<Sha512>(&mut rng));
}
#[bench]
fn underlying_scalar_mult_basepoint(b: &mut Bencher) {
use curve25519_dalek::constants::ED25519_BASEPOINT_TABLE;
let scalar: Scalar = Scalar([ 20, 130, 129, 196, 247, 182, 211, 102,
11, 168, 169, 131, 159, 69, 126, 35,
109, 193, 175, 54, 118, 234, 138, 81,
60, 183, 80, 186, 92, 248, 132, 13, ]);
b.iter(| | &scalar * &ED25519_BASEPOINT_TABLE);
}
} | return false;
}
ao = self.decompress();
| random_line_split |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt::Debug;
#[cfg(feature = "std")]
use rand::Rng;
use digest::BlockInput;
use digest::Digest;
use digest::Input;
use digest::FixedOutput;
use generic_array::typenum::U64;
use curve25519_dalek::constants;
use curve25519_dalek::edwards::CompressedEdwardsY;
use curve25519_dalek::edwards::ExtendedPoint;
use curve25519_dalek::scalar::Scalar;
use subtle::slices_equal;
/// The length of an ed25519 EdDSA `Signature`, in bytes.
pub const SIGNATURE_LENGTH: usize = 64;
/// The length of an ed25519 EdDSA `SecretKey`, in bytes.
pub const SECRET_KEY_LENGTH: usize = 32;
/// The length of an ed25519 EdDSA `PublicKey`, in bytes.
pub const PUBLIC_KEY_LENGTH: usize = 32;
/// An EdDSA signature.
///
/// # Note
///
/// These signatures, unlike the ed25519 signature reference implementation, are
/// "detached"—that is, they do **not** include a copy of the message which has
/// been signed.
#[derive(Copy)]
#[repr(C)]
pub struct Signature(pub [u8; SIGNATURE_LENGTH]);
impl Clone for Signature {
fn clone(&self) -> Self { *self }
}
impl Debug for Signature {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "Signature([{:?}])", &self.0[..])
}
}
impl Eq for Signature {}
impl PartialEq for Signature {
fn eq(&self, other: &Signature) -> bool {
let mut equal: u8 = 0;
for i in 0..64 {
equal |= self.0[i] ^ other.0[i];
}
if equal == 0 {
return true;
} else {
return false;
}
}
}
impl Signature {
/// View this `Signature` as a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SIGNATURE_LENGTH] {
self.0
}
/// View this `Signature` as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SIGNATURE_LENGTH] {
&self.0
}
/// Construct a `Signature` from a slice of bytes.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> Signature {
Signature(*array_ref!(bytes, 0, SIGNATURE_LENGTH))
}
}
/// An EdDSA secret key.
#[repr(C)]
pub struct SecretKey(pub [u8; SECRET_KEY_LENGTH]);
impl Debug for SecretKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "SecretKey: {:?}", &self.0[..])
}
}
impl SecretKey {
/// Convert this secret key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SECRET_KEY_LENGTH] {
self.0
}
/// View this secret key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SECRET_KEY_LENGTH] {
&self.0
}
/// Construct a `SecretKey` from a slice of bytes.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::SECRET_KEY_LENGTH;
///
/// let secret_key_bytes: [u8; SECRET_KEY_LENGTH] = [
/// 157, 097, 177, 157, 239, 253, 090, 096,
/// 186, 132, 074, 244, 146, 236, 044, 196,
/// 068, 073, 197, 105, 123, 050, 105, 025,
/// 112, 059, 172, 003, 028, 174, 127, 096, ];
///
/// let secret_key: SecretKey = SecretKey::from_bytes(&secret_key_bytes[..]);
/// # }
/// ```
///
/// # Returns
///
/// An EdDSA `SecretKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> SecretKey {
SecretKey(*array_ref!(bytes, 0, SECRET_KEY_LENGTH))
}
/// Generate a `SecretKey` from a `csprng`.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::Signature;
///
/// let mut csprng: OsRng = OsRng::new().unwrap();
/// let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// # }
/// ```
///
/// Afterwards, you can generate the corresponding public—provided you also
/// supply a hash function which implements the `Digest` and `Default`
/// traits, and which returns 512 bits of output—via:
///
/// ```
/// # extern crate rand;
/// # extern crate sha2;
/// # extern crate ed25519_dalek;
/// #
/// # fn main() {
/// #
/// # use rand::Rng;
/// # use rand::OsRng;
/// # use sha2::Sha512;
/// # use ed25519_dalek::PublicKey;
/// # use ed25519_dalek::SecretKey;
/// # use ed25519_dalek::Signature;
/// #
/// # let mut csprng: OsRng = OsRng::new().unwrap();
/// # let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// let public_key: PublicKey = PublicKey::from_secret::<Sha512>(&secret_key);
/// # }
/// ```
///
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
///
/// # Input
///
/// A CSPRING with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
#[cfg(feature = "std")]
pub fn generate(csprng: &mut Rng) -> SecretKey {
let mut sk: SecretKey = SecretKey([0u8; 32]);
csprng.fill_bytes(&mut sk.0);
sk
}
}
/// An ed25519 public key.
#[derive(Copy, Clone)]
#[repr(C)]
pub struct PublicKey(pub CompressedEdwardsY);
impl Debug for PublicKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "PublicKey( CompressedPoint( {:?} ))", self.0)
}
}
impl PublicKey {
/// Convert this public key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; PUBLIC_KEY_LENGTH] {
| /// View this public key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; PUBLIC_KEY_LENGTH] {
&(self.0).0
}
/// Construct a `PublicKey` from a slice of bytes.
///
/// # Warning
///
/// The caller is responsible for ensuring that the bytes passed into this
/// method actually represent a `curve25519_dalek::curve::CompressedEdwardsY`
/// and that said compressed point is actually a point on the curve.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::PUBLIC_KEY_LENGTH;
///
/// let public_key_bytes: [u8; PUBLIC_KEY_LENGTH] = [
/// 215, 90, 152, 1, 130, 177, 10, 183, 213, 75, 254, 211, 201, 100, 7, 58,
/// 14, 225, 114, 243, 218, 166, 35, 37, 175, 2, 26, 104, 247, 7, 81, 26];
///
/// let public_key: PublicKey = PublicKey::from_bytes(&public_key_bytes);
/// # }
/// ```
///
/// # Returns
///
/// A `PublicKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> PublicKey {
PublicKey(CompressedEdwardsY(*array_ref!(bytes, 0, 32)))
}
/// Convert this public key to its underlying extended twisted Edwards coordinate.
#[inline]
fn decompress(&self) -> Option<ExtendedPoint> {
self.0.decompress()
}
/// Derive this public key from its corresponding `SecretKey`.
#[cfg(feature = "std")]
#[allow(unused_assignments)]
pub fn from_secret<D>(secret_key: &SecretKey) -> PublicKey
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let pk: [u8; 32];
let mut digest: &mut [u8; 32];
h.input(secret_key.as_bytes());
hash.copy_from_slice(h.fixed_result().as_slice());
digest = array_mut_ref!(&mut hash, 0, 32);
digest[0] &= 248;
digest[31] &= 127;
digest[31] |= 64;
pk = (&Scalar(*digest) * &constants::ED25519_BASEPOINT_TABLE).compress().to_bytes();
PublicKey(CompressedEdwardsY(pk))
}
/// Verify a signature on a message with this keypair's public key.
///
/// # Return
///
/// Returns true if the signature was successfully verified, and
/// false otherwise.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: Digest<OutputSize = U64> + Default {
use curve25519_dalek::edwards::vartime;
let mut h: D = D::default();
let mut a: ExtendedPoint;
let ao: Option<ExtendedPoint>;
let r: ExtendedPoint;
let digest: [u8; 64];
let digest_reduced: Scalar;
if signature.0[63] & 224 != 0 {
return false;
}
ao = self.decompress();
if ao.is_some() {
a = ao.unwrap();
} else {
return false;
}
a = -(&a);
let top_half: &[u8; 32] = array_ref!(&signature.0, 32, 32);
let bottom_half: &[u8; 32] = array_ref!(&signature.0, 0, 32);
h.input(&bottom_half[..]);
h.input(&self.to_bytes());
h.input(&message);
let digest_bytes = h.fixed_result();
digest = *array_ref!(digest_bytes, 0, 64);
digest_reduced = Scalar::reduce(&digest);
r = vartime::double_scalar_mult_basepoint(&digest_reduced, &a, &Scalar(*top_half));
slices_equal(bottom_half, &r.compress().to_bytes()) == 1
}
}
/// An ed25519 keypair.
#[derive(Debug)]
#[repr(C)]
pub struct Keypair {
/// The public half of this keypair.
pub public: PublicKey,
/// The secret half of this keypair.
pub secret: SecretKey,
}
impl Keypair {
/// Construct a `Keypair` from the bytes of a `PublicKey` and `SecretKey`.
///
/// # Inputs
///
/// * `public`: a `[u8; 32]` representing the compressed Edwards-Y
/// coordinate of a point on curve25519.
/// * `secret`: a `[u8; 32]` representing the corresponding secret key.
///
/// # Warning
///
/// Absolutely no validation is done on the key. If you give this function
/// bytes which do not represent a valid point, or which do not represent
/// corresponding parts of the key, then your `Keypair` will be broken and
/// it will be your fault.
///
/// # Returns
///
/// A `Keypair`.
pub fn from_bytes<'a>(public: &'a [u8; 32], secret: &'a [u8; 32]) -> Keypair {
Keypair{ public: PublicKey::from_bytes(public),
secret: SecretKey::from_bytes(secret), }
}
/// Generate an ed25519 keypair.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::Keypair;
/// use ed25519_dalek::Signature;
///
/// let mut cspring: OsRng = OsRng::new().unwrap();
/// let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
///
/// # }
/// ```
///
/// # Input
///
/// A CSPRNG with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
/// The caller must also supply a hash function which implements the
/// `Digest` and `Default` traits, and which returns 512 bits of output.
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
#[cfg(feature = "std")]
pub fn generate<D>(csprng: &mut Rng) -> Keypair
where D: Digest<OutputSize = U64> + Default {
let sk: SecretKey = SecretKey::generate(csprng);
let pk: PublicKey = PublicKey::from_secret::<D>(&sk);
Keypair{ public: pk, secret: sk }
}
/// Sign a message with this keypair's secret key.
pub fn sign<D>(&self, message: &[u8]) -> Signature
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let mut signature_bytes: [u8; 64] = [0u8; SIGNATURE_LENGTH];
let mut expanded_key_secret: Scalar;
let mesg_digest: Scalar;
let hram_digest: Scalar;
let r: ExtendedPoint;
let s: Scalar;
let t: CompressedEdwardsY;
let secret_key: &[u8; 32] = self.secret.as_bytes();
let public_key: &[u8; 32] = self.public.as_bytes();
h.input(secret_key);
hash.copy_from_slice(h.fixed_result().as_slice());
expanded_key_secret = Scalar(*array_ref!(&hash, 0, 32));
expanded_key_secret[0] &= 248;
expanded_key_secret[31] &= 63;
expanded_key_secret[31] |= 64;
h = D::default();
h.input(&hash[32..]);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
mesg_digest = Scalar::reduce(&hash);
r = &mesg_digest * &constants::ED25519_BASEPOINT_TABLE;
h = D::default();
h.input(&r.compress().to_bytes()[..]);
h.input(public_key);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
hram_digest = Scalar::reduce(&hash);
s = Scalar::multiply_add(&hram_digest, &expanded_key_secret, &mesg_digest);
t = r.compress();
signature_bytes[..32].copy_from_slice(&t.0);
signature_bytes[32..64].copy_from_slice(&s.0);
Signature(*array_ref!(&signature_bytes, 0, 64))
}
/// Verify a signature on a message with this keypair's public key.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: FixedOutput<OutputSize = U64> + BlockInput + Default + Input {
self.public.verify::<D>(message, signature)
}
}
#[cfg(test)]
mod test {
use std::io::BufReader;
use std::io::BufRead;
use std::fs::File;
use std::string::String;
use std::vec::Vec;
use curve25519_dalek::edwards::ExtendedPoint;
use rand::OsRng;
use hex::FromHex;
use sha2::Sha512;
use super::*;
#[test]
fn unmarshal_marshal() { // TestUnmarshalMarshal
let mut cspring: OsRng;
let mut keypair: Keypair;
let mut x: Option<ExtendedPoint>;
let a: ExtendedPoint;
let public: PublicKey;
cspring = OsRng::new().unwrap();
// from_bytes() fails if vx²-u=0 and vx²+u=0
loop {
keypair = Keypair::generate::<Sha512>(&mut cspring);
x = keypair.public.decompress();
if x.is_some() {
a = x.unwrap();
break;
}
}
public = PublicKey(a.compress());
assert!(keypair.public.0 == public.0);
}
#[test]
fn sign_verify() { // TestSignVerify
let mut cspring: OsRng;
let keypair: Keypair;
let good_sig: Signature;
let bad_sig: Signature;
let good: &[u8] = "test message".as_bytes();
let bad: &[u8] = "wrong message".as_bytes();
cspring = OsRng::new().unwrap();
keypair = Keypair::generate::<Sha512>(&mut cspring);
good_sig = keypair.sign::<Sha512>(&good);
bad_sig = keypair.sign::<Sha512>(&bad);
assert!(keypair.verify::<Sha512>(&good, &good_sig) == true,
"Verification of a valid signature failed!");
assert!(keypair.verify::<Sha512>(&good, &bad_sig) == false,
"Verification of a signature on a different message passed!");
assert!(keypair.verify::<Sha512>(&bad, &good_sig) == false,
"Verification of a signature on a different message passed!");
}
// TESTVECTORS is taken from sign.input.gz in agl's ed25519 Golang
// package. It is a selection of test cases from
// http://ed25519.cr.yp.to/python/sign.input
#[cfg(test)]
#[cfg(not(release))]
#[test]
fn golden() { // TestGolden
let mut line: String;
let mut lineno: usize = 0;
let f = File::open("TESTVECTORS");
if f.is_err() {
println!("This test is only available when the code has been cloned \
from the git repository, since the TESTVECTORS file is large \
and is therefore not included within the distributed crate.");
panic!();
}
let file = BufReader::new(f.unwrap());
for l in file.lines() {
lineno += 1;
line = l.unwrap();
let parts: Vec<&str> = line.split(':').collect();
assert_eq!(parts.len(), 5, "wrong number of fields in line {}", lineno);
let sec_bytes: Vec<u8>= FromHex::from_hex(&parts[0]).unwrap();
let pub_bytes: Vec<u8> = FromHex::from_hex(&parts[1]).unwrap();
let message: Vec<u8> = FromHex::from_hex(&parts[2]).unwrap();
let sig_bytes: Vec<u8> = FromHex::from_hex(&parts[3]).unwrap();
// The signatures in the test vectors also include the message
// at the end, but we just want R and S.
let sig1: Signature = Signature::from_bytes(sig_bytes.as_ref());
let keypair: Keypair = Keypair::from_bytes(
array_ref!(*pub_bytes, 0, PUBLIC_KEY_LENGTH),
array_ref!(*sec_bytes, 0, SECRET_KEY_LENGTH));
let sig2: Signature = keypair.sign::<Sha512>(&message);
assert!(sig1 == sig2, "Signature bytes not equal on line {}", lineno);
assert!(keypair.verify::<Sha512>(&message, &sig2),
"Signature verification failed on line {}", lineno);
}
}
}
#[cfg(all(test, feature = "bench"))]
mod bench {
use test::Bencher;
use rand::OsRng;
use sha2::Sha512;
use super::*;
/// A fake RNG which simply returns zeroes.
struct ZeroRng;
impl ZeroRng {
pub fn new() -> ZeroRng {
ZeroRng
}
}
impl Rng for ZeroRng {
fn next_u32(&mut self) -> u32 { 0u32 }
fn fill_bytes(&mut self, bytes: &mut [u8]) {
for i in 0 .. bytes.len() {
bytes[i] = 0;
}
}
}
#[bench]
fn sign(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
b.iter(| | keypair.sign::<Sha512>(msg));
}
#[bench]
fn verify(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
let sig: Signature = keypair.sign::<Sha512>(msg);
b.iter(| | keypair.verify::<Sha512>(msg, &sig));
}
#[bench]
fn key_generation(b: &mut Bencher) {
let mut rng: ZeroRng = ZeroRng::new();
b.iter(| | Keypair::generate::<Sha512>(&mut rng));
}
#[bench]
fn underlying_scalar_mult_basepoint(b: &mut Bencher) {
use curve25519_dalek::constants::ED25519_BASEPOINT_TABLE;
let scalar: Scalar = Scalar([ 20, 130, 129, 196, 247, 182, 211, 102,
11, 168, 169, 131, 159, 69, 126, 35,
109, 193, 175, 54, 118, 234, 138, 81,
60, 183, 80, 186, 92, 248, 132, 13, ]);
b.iter(| | &scalar * &ED25519_BASEPOINT_TABLE);
}
}
| self.0.to_bytes()
}
| identifier_body |
ed25519.rs | // -*- mode: rust; -*-
//
// This file is part of ed25519-dalek.
// Copyright (c) 2017 Isis Lovecruft
// See LICENSE for licensing information.
//
// Authors:
// - Isis Agora Lovecruft <isis@patternsinthevoid.net>
//! A Rust implementation of ed25519 EdDSA key generation, signing, and
//! verification.
use core::fmt::Debug;
#[cfg(feature = "std")]
use rand::Rng;
use digest::BlockInput;
use digest::Digest;
use digest::Input;
use digest::FixedOutput;
use generic_array::typenum::U64;
use curve25519_dalek::constants;
use curve25519_dalek::edwards::CompressedEdwardsY;
use curve25519_dalek::edwards::ExtendedPoint;
use curve25519_dalek::scalar::Scalar;
use subtle::slices_equal;
/// The length of an ed25519 EdDSA `Signature`, in bytes.
pub const SIGNATURE_LENGTH: usize = 64;
/// The length of an ed25519 EdDSA `SecretKey`, in bytes.
pub const SECRET_KEY_LENGTH: usize = 32;
/// The length of an ed25519 EdDSA `PublicKey`, in bytes.
pub const PUBLIC_KEY_LENGTH: usize = 32;
/// An EdDSA signature.
///
/// # Note
///
/// These signatures, unlike the ed25519 signature reference implementation, are
/// "detached"—that is, they do **not** include a copy of the message which has
/// been signed.
#[derive(Copy)]
#[repr(C)]
pub struct Signature(pub [u8; SIGNATURE_LENGTH]);
impl Clone for Signature {
fn clone(&self) -> Self { *self }
}
impl Debug for Signature {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "Signature([{:?}])", &self.0[..])
}
}
impl Eq for Signature {}
impl PartialEq for Signature {
fn eq(&self, other: &Signature) -> bool {
let mut equal: u8 = 0;
for i in 0..64 {
equal |= self.0[i] ^ other.0[i];
}
if equal == 0 {
| lse {
return false;
}
}
}
impl Signature {
/// View this `Signature` as a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SIGNATURE_LENGTH] {
self.0
}
/// View this `Signature` as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SIGNATURE_LENGTH] {
&self.0
}
/// Construct a `Signature` from a slice of bytes.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> Signature {
Signature(*array_ref!(bytes, 0, SIGNATURE_LENGTH))
}
}
/// An EdDSA secret key.
#[repr(C)]
pub struct SecretKey(pub [u8; SECRET_KEY_LENGTH]);
impl Debug for SecretKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "SecretKey: {:?}", &self.0[..])
}
}
impl SecretKey {
/// Convert this secret key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; SECRET_KEY_LENGTH] {
self.0
}
/// View this secret key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; SECRET_KEY_LENGTH] {
&self.0
}
/// Construct a `SecretKey` from a slice of bytes.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::SECRET_KEY_LENGTH;
///
/// let secret_key_bytes: [u8; SECRET_KEY_LENGTH] = [
/// 157, 097, 177, 157, 239, 253, 090, 096,
/// 186, 132, 074, 244, 146, 236, 044, 196,
/// 068, 073, 197, 105, 123, 050, 105, 025,
/// 112, 059, 172, 003, 028, 174, 127, 096, ];
///
/// let secret_key: SecretKey = SecretKey::from_bytes(&secret_key_bytes[..]);
/// # }
/// ```
///
/// # Returns
///
/// An EdDSA `SecretKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> SecretKey {
SecretKey(*array_ref!(bytes, 0, SECRET_KEY_LENGTH))
}
/// Generate a `SecretKey` from a `csprng`.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::SecretKey;
/// use ed25519_dalek::Signature;
///
/// let mut csprng: OsRng = OsRng::new().unwrap();
/// let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// # }
/// ```
///
/// Afterwards, you can generate the corresponding public—provided you also
/// supply a hash function which implements the `Digest` and `Default`
/// traits, and which returns 512 bits of output—via:
///
/// ```
/// # extern crate rand;
/// # extern crate sha2;
/// # extern crate ed25519_dalek;
/// #
/// # fn main() {
/// #
/// # use rand::Rng;
/// # use rand::OsRng;
/// # use sha2::Sha512;
/// # use ed25519_dalek::PublicKey;
/// # use ed25519_dalek::SecretKey;
/// # use ed25519_dalek::Signature;
/// #
/// # let mut csprng: OsRng = OsRng::new().unwrap();
/// # let secret_key: SecretKey = SecretKey::generate(&mut csprng);
///
/// let public_key: PublicKey = PublicKey::from_secret::<Sha512>(&secret_key);
/// # }
/// ```
///
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
///
/// # Input
///
/// A CSPRING with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
#[cfg(feature = "std")]
pub fn generate(csprng: &mut Rng) -> SecretKey {
let mut sk: SecretKey = SecretKey([0u8; 32]);
csprng.fill_bytes(&mut sk.0);
sk
}
}
/// An ed25519 public key.
#[derive(Copy, Clone)]
#[repr(C)]
pub struct PublicKey(pub CompressedEdwardsY);
impl Debug for PublicKey {
fn fmt(&self, f: &mut ::core::fmt::Formatter) -> ::core::fmt::Result {
write!(f, "PublicKey( CompressedPoint( {:?} ))", self.0)
}
}
impl PublicKey {
/// Convert this public key to a byte array.
#[inline]
pub fn to_bytes(&self) -> [u8; PUBLIC_KEY_LENGTH] {
self.0.to_bytes()
}
/// View this public key as a byte array.
#[inline]
pub fn as_bytes<'a>(&'a self) -> &'a [u8; PUBLIC_KEY_LENGTH] {
&(self.0).0
}
/// Construct a `PublicKey` from a slice of bytes.
///
/// # Warning
///
/// The caller is responsible for ensuring that the bytes passed into this
/// method actually represent a `curve25519_dalek::curve::CompressedEdwardsY`
/// and that said compressed point is actually a point on the curve.
///
/// # Example
///
/// ```
/// # extern crate ed25519_dalek;
/// # fn main() {
/// use ed25519_dalek::PublicKey;
/// use ed25519_dalek::PUBLIC_KEY_LENGTH;
///
/// let public_key_bytes: [u8; PUBLIC_KEY_LENGTH] = [
/// 215, 90, 152, 1, 130, 177, 10, 183, 213, 75, 254, 211, 201, 100, 7, 58,
/// 14, 225, 114, 243, 218, 166, 35, 37, 175, 2, 26, 104, 247, 7, 81, 26];
///
/// let public_key: PublicKey = PublicKey::from_bytes(&public_key_bytes);
/// # }
/// ```
///
/// # Returns
///
/// A `PublicKey`.
#[inline]
pub fn from_bytes(bytes: &[u8]) -> PublicKey {
PublicKey(CompressedEdwardsY(*array_ref!(bytes, 0, 32)))
}
/// Convert this public key to its underlying extended twisted Edwards coordinate.
#[inline]
fn decompress(&self) -> Option<ExtendedPoint> {
self.0.decompress()
}
/// Derive this public key from its corresponding `SecretKey`.
#[cfg(feature = "std")]
#[allow(unused_assignments)]
pub fn from_secret<D>(secret_key: &SecretKey) -> PublicKey
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let pk: [u8; 32];
let mut digest: &mut [u8; 32];
h.input(secret_key.as_bytes());
hash.copy_from_slice(h.fixed_result().as_slice());
digest = array_mut_ref!(&mut hash, 0, 32);
digest[0] &= 248;
digest[31] &= 127;
digest[31] |= 64;
pk = (&Scalar(*digest) * &constants::ED25519_BASEPOINT_TABLE).compress().to_bytes();
PublicKey(CompressedEdwardsY(pk))
}
/// Verify a signature on a message with this keypair's public key.
///
/// # Return
///
/// Returns true if the signature was successfully verified, and
/// false otherwise.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: Digest<OutputSize = U64> + Default {
use curve25519_dalek::edwards::vartime;
let mut h: D = D::default();
let mut a: ExtendedPoint;
let ao: Option<ExtendedPoint>;
let r: ExtendedPoint;
let digest: [u8; 64];
let digest_reduced: Scalar;
if signature.0[63] & 224 != 0 {
return false;
}
ao = self.decompress();
if ao.is_some() {
a = ao.unwrap();
} else {
return false;
}
a = -(&a);
let top_half: &[u8; 32] = array_ref!(&signature.0, 32, 32);
let bottom_half: &[u8; 32] = array_ref!(&signature.0, 0, 32);
h.input(&bottom_half[..]);
h.input(&self.to_bytes());
h.input(&message);
let digest_bytes = h.fixed_result();
digest = *array_ref!(digest_bytes, 0, 64);
digest_reduced = Scalar::reduce(&digest);
r = vartime::double_scalar_mult_basepoint(&digest_reduced, &a, &Scalar(*top_half));
slices_equal(bottom_half, &r.compress().to_bytes()) == 1
}
}
/// An ed25519 keypair.
#[derive(Debug)]
#[repr(C)]
pub struct Keypair {
/// The public half of this keypair.
pub public: PublicKey,
/// The secret half of this keypair.
pub secret: SecretKey,
}
impl Keypair {
/// Construct a `Keypair` from the bytes of a `PublicKey` and `SecretKey`.
///
/// # Inputs
///
/// * `public`: a `[u8; 32]` representing the compressed Edwards-Y
/// coordinate of a point on curve25519.
/// * `secret`: a `[u8; 32]` representing the corresponding secret key.
///
/// # Warning
///
/// Absolutely no validation is done on the key. If you give this function
/// bytes which do not represent a valid point, or which do not represent
/// corresponding parts of the key, then your `Keypair` will be broken and
/// it will be your fault.
///
/// # Returns
///
/// A `Keypair`.
pub fn from_bytes<'a>(public: &'a [u8; 32], secret: &'a [u8; 32]) -> Keypair {
Keypair{ public: PublicKey::from_bytes(public),
secret: SecretKey::from_bytes(secret), }
}
/// Generate an ed25519 keypair.
///
/// # Example
///
/// ```
/// extern crate rand;
/// extern crate sha2;
/// extern crate ed25519_dalek;
///
/// # fn main() {
///
/// use rand::Rng;
/// use rand::OsRng;
/// use sha2::Sha512;
/// use ed25519_dalek::Keypair;
/// use ed25519_dalek::Signature;
///
/// let mut cspring: OsRng = OsRng::new().unwrap();
/// let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
///
/// # }
/// ```
///
/// # Input
///
/// A CSPRNG with a `fill_bytes()` method, e.g. the one returned
/// from `rand::OsRng::new()` (in the `rand` crate).
///
/// The caller must also supply a hash function which implements the
/// `Digest` and `Default` traits, and which returns 512 bits of output.
/// The standard hash function used for most ed25519 libraries is SHA-512,
/// which is available with `use sha2::Sha512` as in the example above.
/// Other suitable hash functions include Keccak-512 and Blake2b-512.
#[cfg(feature = "std")]
pub fn generate<D>(csprng: &mut Rng) -> Keypair
where D: Digest<OutputSize = U64> + Default {
let sk: SecretKey = SecretKey::generate(csprng);
let pk: PublicKey = PublicKey::from_secret::<D>(&sk);
Keypair{ public: pk, secret: sk }
}
/// Sign a message with this keypair's secret key.
pub fn sign<D>(&self, message: &[u8]) -> Signature
where D: Digest<OutputSize = U64> + Default {
let mut h: D = D::default();
let mut hash: [u8; 64] = [0u8; 64];
let mut signature_bytes: [u8; 64] = [0u8; SIGNATURE_LENGTH];
let mut expanded_key_secret: Scalar;
let mesg_digest: Scalar;
let hram_digest: Scalar;
let r: ExtendedPoint;
let s: Scalar;
let t: CompressedEdwardsY;
let secret_key: &[u8; 32] = self.secret.as_bytes();
let public_key: &[u8; 32] = self.public.as_bytes();
h.input(secret_key);
hash.copy_from_slice(h.fixed_result().as_slice());
expanded_key_secret = Scalar(*array_ref!(&hash, 0, 32));
expanded_key_secret[0] &= 248;
expanded_key_secret[31] &= 63;
expanded_key_secret[31] |= 64;
h = D::default();
h.input(&hash[32..]);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
mesg_digest = Scalar::reduce(&hash);
r = &mesg_digest * &constants::ED25519_BASEPOINT_TABLE;
h = D::default();
h.input(&r.compress().to_bytes()[..]);
h.input(public_key);
h.input(&message);
hash.copy_from_slice(h.fixed_result().as_slice());
hram_digest = Scalar::reduce(&hash);
s = Scalar::multiply_add(&hram_digest, &expanded_key_secret, &mesg_digest);
t = r.compress();
signature_bytes[..32].copy_from_slice(&t.0);
signature_bytes[32..64].copy_from_slice(&s.0);
Signature(*array_ref!(&signature_bytes, 0, 64))
}
/// Verify a signature on a message with this keypair's public key.
pub fn verify<D>(&self, message: &[u8], signature: &Signature) -> bool
where D: FixedOutput<OutputSize = U64> + BlockInput + Default + Input {
self.public.verify::<D>(message, signature)
}
}
#[cfg(test)]
mod test {
use std::io::BufReader;
use std::io::BufRead;
use std::fs::File;
use std::string::String;
use std::vec::Vec;
use curve25519_dalek::edwards::ExtendedPoint;
use rand::OsRng;
use hex::FromHex;
use sha2::Sha512;
use super::*;
#[test]
fn unmarshal_marshal() { // TestUnmarshalMarshal
let mut cspring: OsRng;
let mut keypair: Keypair;
let mut x: Option<ExtendedPoint>;
let a: ExtendedPoint;
let public: PublicKey;
cspring = OsRng::new().unwrap();
// from_bytes() fails if vx²-u=0 and vx²+u=0
loop {
keypair = Keypair::generate::<Sha512>(&mut cspring);
x = keypair.public.decompress();
if x.is_some() {
a = x.unwrap();
break;
}
}
public = PublicKey(a.compress());
assert!(keypair.public.0 == public.0);
}
#[test]
fn sign_verify() { // TestSignVerify
let mut cspring: OsRng;
let keypair: Keypair;
let good_sig: Signature;
let bad_sig: Signature;
let good: &[u8] = "test message".as_bytes();
let bad: &[u8] = "wrong message".as_bytes();
cspring = OsRng::new().unwrap();
keypair = Keypair::generate::<Sha512>(&mut cspring);
good_sig = keypair.sign::<Sha512>(&good);
bad_sig = keypair.sign::<Sha512>(&bad);
assert!(keypair.verify::<Sha512>(&good, &good_sig) == true,
"Verification of a valid signature failed!");
assert!(keypair.verify::<Sha512>(&good, &bad_sig) == false,
"Verification of a signature on a different message passed!");
assert!(keypair.verify::<Sha512>(&bad, &good_sig) == false,
"Verification of a signature on a different message passed!");
}
// TESTVECTORS is taken from sign.input.gz in agl's ed25519 Golang
// package. It is a selection of test cases from
// http://ed25519.cr.yp.to/python/sign.input
#[cfg(test)]
#[cfg(not(release))]
#[test]
fn golden() { // TestGolden
let mut line: String;
let mut lineno: usize = 0;
let f = File::open("TESTVECTORS");
if f.is_err() {
println!("This test is only available when the code has been cloned \
from the git repository, since the TESTVECTORS file is large \
and is therefore not included within the distributed crate.");
panic!();
}
let file = BufReader::new(f.unwrap());
for l in file.lines() {
lineno += 1;
line = l.unwrap();
let parts: Vec<&str> = line.split(':').collect();
assert_eq!(parts.len(), 5, "wrong number of fields in line {}", lineno);
let sec_bytes: Vec<u8>= FromHex::from_hex(&parts[0]).unwrap();
let pub_bytes: Vec<u8> = FromHex::from_hex(&parts[1]).unwrap();
let message: Vec<u8> = FromHex::from_hex(&parts[2]).unwrap();
let sig_bytes: Vec<u8> = FromHex::from_hex(&parts[3]).unwrap();
// The signatures in the test vectors also include the message
// at the end, but we just want R and S.
let sig1: Signature = Signature::from_bytes(sig_bytes.as_ref());
let keypair: Keypair = Keypair::from_bytes(
array_ref!(*pub_bytes, 0, PUBLIC_KEY_LENGTH),
array_ref!(*sec_bytes, 0, SECRET_KEY_LENGTH));
let sig2: Signature = keypair.sign::<Sha512>(&message);
assert!(sig1 == sig2, "Signature bytes not equal on line {}", lineno);
assert!(keypair.verify::<Sha512>(&message, &sig2),
"Signature verification failed on line {}", lineno);
}
}
}
#[cfg(all(test, feature = "bench"))]
mod bench {
use test::Bencher;
use rand::OsRng;
use sha2::Sha512;
use super::*;
/// A fake RNG which simply returns zeroes.
struct ZeroRng;
impl ZeroRng {
pub fn new() -> ZeroRng {
ZeroRng
}
}
impl Rng for ZeroRng {
fn next_u32(&mut self) -> u32 { 0u32 }
fn fill_bytes(&mut self, bytes: &mut [u8]) {
for i in 0 .. bytes.len() {
bytes[i] = 0;
}
}
}
#[bench]
fn sign(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
b.iter(| | keypair.sign::<Sha512>(msg));
}
#[bench]
fn verify(b: &mut Bencher) {
let mut cspring: OsRng = OsRng::new().unwrap();
let keypair: Keypair = Keypair::generate::<Sha512>(&mut cspring);
let msg: &[u8] = b"";
let sig: Signature = keypair.sign::<Sha512>(msg);
b.iter(| | keypair.verify::<Sha512>(msg, &sig));
}
#[bench]
fn key_generation(b: &mut Bencher) {
let mut rng: ZeroRng = ZeroRng::new();
b.iter(| | Keypair::generate::<Sha512>(&mut rng));
}
#[bench]
fn underlying_scalar_mult_basepoint(b: &mut Bencher) {
use curve25519_dalek::constants::ED25519_BASEPOINT_TABLE;
let scalar: Scalar = Scalar([ 20, 130, 129, 196, 247, 182, 211, 102,
11, 168, 169, 131, 159, 69, 126, 35,
109, 193, 175, 54, 118, 234, 138, 81,
60, 183, 80, 186, 92, 248, 132, 13, ]);
b.iter(| | &scalar * &ED25519_BASEPOINT_TABLE);
}
}
| return true;
} e | conditional_block |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one asset file
type AssetFile interface {
Name() string
ModTime() time.Time
Content() []byte
ContentGzip() []byte
}
// assetFile asset file struct
type assetFile struct {
name string
mtime time.Time
content []byte
contentGzip []byte
}
func (af *assetFile) Name() string {
return af.name
}
func (af *assetFile) ModTime() time.Time {
return af.mtime
}
func (af *assetFile) Content() []byte {
return af.content
}
func (af *assetFile) ContentGzip() []byte {
return af.contentGzip
}
var _ AssetFile = &assetFile{}
// AssetFiles asset files
type AssetFiles interface {
GetAssetFile(name string) (AssetFile, error)
GetContent(name string) []byte
GetFileNames(dir string) []string
FileHandlerFunc(name string) http.HandlerFunc
HTTPHandler(baseDir string) http.Handler
}
// assetFiles asset files
type assetFiles struct {
Files map[string]*assetFile
}
var _assetDirect bool
var _assetCwd, _ = os.Getwd()
// GetAssetFile get file by name
func (afs *assetFiles) GetAssetFile(name string) (AssetFile, error) {
name = filepath.ToSlash(name)
if name != "" && name[0] != '/' {
name = "/" + name
}
if _assetDirect {
assetFilePath := filepath.Join(_assetCwd, name)
f, err := os.Open(assetFilePath)
log.Println("[goasset] Asset Direct, name=", name, "assetPath=", assetFilePath, "err=", err)
if err != nil {
return nil, err
}
defer f.Close()
info, err := f.Stat()
if err != nil {
return nil, err
}
if info.Mode().IsRegular() {
content, err := ioutil.ReadAll(f)
if err != nil {
return nil, err
}
helper := newAssetHelper()
contentNew, errHelper := helper.Execute(assetFilePath, content, "")
if errHelper != nil {
return nil, errHelper
}
return &assetFile{
content: contentNew,
name: name,
mtime: info.ModTime(),
}, nil
}
return nil, fmt.Errorf("not file")
}
if sf, has := afs.Files[name]; has {
return sf, nil
}
return nil, fmt.Errorf("not exists")
}
// GetContent get content by name
func (afs *assetFiles) | (name string) []byte {
s, err := afs.GetAssetFile(name)
if err != nil {
return []byte("")
}
return s.Content()
}
// GetFileNames get all file names
func (afs *assetFiles) GetFileNames(dir string) []string {
if dir == "" {
dir = "/"
}
names := make([]string, 0, len(afs.Files))
dirRaw := dir
dir = path.Clean(dir)
if dir != "/" && strings.HasSuffix(dirRaw, "/") {
dir += string(filepath.Separator)
}
dir = filepath.ToSlash(dir)
for name := range afs.Files {
if strings.HasPrefix(name, dir) {
names = append(names, name)
}
}
return names
}
// FileHandlerFunc handler http files
// 若目录名称 为 *private 则不允许通过web访问
func (afs *assetFiles) FileHandlerFunc(name string) http.HandlerFunc {
if strings.Contains(name, "private/") {
return http.NotFound
}
return afs.FileHandlerFuncAll(name)
}
// FileHandlerFuncAll handler http files
// 无 private 目录规则
func (afs *assetFiles) FileHandlerFuncAll(name string) http.HandlerFunc {
name = filepath.ToSlash(name)
file, err := afs.GetAssetFile(name)
return func(writer http.ResponseWriter, req *http.Request) {
if err != nil {
http.NotFound(writer, req)
return
}
modifiedSince := req.Header.Get("If-Modified-Since")
if modifiedSince != "" {
t, err := time.Parse(http.TimeFormat, modifiedSince)
if err == nil && file.ModTime().Before(t) {
writer.Header().Del("Content-Type")
writer.Header().Del("Content-Length")
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
writer.WriteHeader(http.StatusNotModified)
return
}
}
mimeType := mime.TypeByExtension(filepath.Ext(file.Name()))
if mimeType != "" {
writer.Header().Set("Content-Type", mimeType)
}
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
gzipContent := file.ContentGzip()
var errWrote error
if len(gzipContent) > 0 && strings.Contains(req.Header.Get("Accept-Encoding"), "gzip") {
writer.Header().Set("Content-Encoding", "gzip")
_, errWrote = writer.Write(gzipContent)
} else {
_, errWrote = writer.Write(file.Content())
}
if errWrote != nil {
log.Printf("[wf] wrote %q with error:%s\n", name, errWrote)
}
}
}
// HTTPHandler handler http request
// eg:on file system is :/res/js/a.js and request is /res/js/a.js
// http.Handle("/res/",res.Asset.HttpHandler("/"))
// eg:on file system is :/res/js/a.js and request is /js/a.js
// http.Handle("/js/",res.Asset.HttpHandler("/res/"))
func (afs *assetFiles) HTTPHandler(baseDir string) http.Handler {
return &_assetFileServer{sf: afs, pdir: baseDir}
}
type _assetFileServer struct {
sf *assetFiles
pdir string
}
// ServeHTTP ServeHTTP
func (f *_assetFileServer) ServeHTTP(w http.ResponseWriter, r *http.Request) {
name := filepath.ToSlash(filepath.Join(f.pdir, r.URL.Path))
f.sf.FileHandlerFunc(name).ServeHTTP(w, r)
}
var _ AssetFiles = &assetFiles{}
var _ = flag.String
var _ = runtime.Version()
// ---------------------------helper.go--------begin--------------------------//
func newAssetHelper() *assetHelper {
helper := &assetHelper{}
helper.Regs = make(map[string]*regexp.Regexp)
helper.Regs["remove_above"] = regexp.MustCompile(`[\S\s]*?//\s*asset_remove_above\(\s*\)`)
helper.Regs["remove"] = regexp.MustCompile(`//\s*asset_remove_start\(\s*\)[\S\s]*?//\s*asset_remove_end\(\s*\)`)
helper.Regs["include"] = regexp.MustCompile(`//\s*asset_include\(([^)]+?)\)`)
helper.RegisterFn("remove_above", helper.RemoveAbove)
helper.RegisterFn("include", helper.Include)
helper.RegisterFn("remove", helper.Remove)
return helper
}
type assetHelperFn func(fileName string, content []byte) ([]byte, error)
type assetHelper struct {
Fns []map[string]assetHelperFn
Regs map[string]*regexp.Regexp
}
// RegisterFn 注册helper方法
func (h *assetHelper) RegisterFn(name string, fn assetHelperFn) {
h.Fns = append(h.Fns, map[string]assetHelperFn{name: fn})
}
// Execute 执行所有的helper方法
func (h *assetHelper) Execute(fileAbsPath string, content []byte, skipFnName string) (contentNew []byte, err error) {
contentNew = make([]byte, len(content))
copy(contentNew, content)
for _, fnInfo := range h.Fns {
for name, fn := range fnInfo {
if name == skipFnName {
continue
}
contentNew, err = fn(fileAbsPath, contentNew)
if err != nil {
return nil, fmt.Errorf("%s,current file is: %s", err.Error(), fileAbsPath)
}
}
}
return contentNew, nil
}
// RemoveAbove 删除在此标记之前的内容
// eg: \/\/ asset_remove_above()
func (h *assetHelper) RemoveAbove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove_above"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
// Remove remove 方法, 删除指定区间里的内容
// eg: \/\/asset_remove_start() 中间的内容被删除 \/\/ asset_remove_end()
func (h *assetHelper) Remove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
func (h *assetHelper) include(fileAPath string, content []byte, includeFiles map[string]map[string]bool) (contentNew []byte, err error) {
fileAPath = filepath.Clean(fileAPath)
includeFiles[fileAPath] = make(map[string]bool)
contentNew = h.Regs["include"].ReplaceAllFunc(content, func(matchData []byte) []byte {
idx := bytes.Index(matchData, []byte("("))
name := bytes.TrimSpace(matchData[idx+1 : len(matchData)-1])
if len(name) == 0 {
err = fmt.Errorf("asset_include with empty param")
return []byte(err.Error())
}
fileBPath := filepath.Join(filepath.Dir(fileAPath), string(name))
if bFiles, hasB := includeFiles[fileBPath]; hasB {
if _, hasA := bFiles[fileAPath]; hasA {
err = fmt.Errorf("asset_include error: cyclic include,%s include(%s)", fileAPath, string(name))
return []byte(err.Error())
}
}
includeFiles[fileAPath][fileBPath] = true
includeFiles[fileBPath] = make(map[string]bool)
bContent, errRead := ioutil.ReadFile(fileBPath)
if errRead != nil {
err = errRead
return []byte(err.Error())
}
b1Content, errB1 := h.Execute(fileBPath, bContent, "include")
if errB1 != nil {
err = errB1
return []byte(err.Error())
}
cContent, errInclude := h.include(fileBPath, b1Content, includeFiles)
if errInclude != nil {
err = errInclude
return []byte(err.Error())
}
return cContent
})
if err != nil {
return nil, err
}
return contentNew, nil
}
// Include 将另外一个资源文件包含到当前文件里
// eg: \/\/ asset_include(a.tpl)
func (h *assetHelper) Include(fileAPath string, content []byte) (contentNew []byte, err error) {
// 用于检查循环include
includeFiles := make(map[string]map[string]bool)
return h.include(fileAPath, content, includeFiles)
}
// ---------------------------helper.go--------finish-------------------------//
// Asset export assets
var Asset AssetFiles
func init() {
// nolint
var _assetGzipDecode = func(data []byte, fileName string) []byte {
gzipReader, errGzip := gzip.NewReader(bytes.NewBuffer(data))
if errGzip != nil {
panic(fmt.Sprintf("[goasset] gzip decode failed,file=%q, err=%s", fileName, errGzip.Error()))
}
defer gzipReader.Close()
buf, errReader := ioutil.ReadAll(gzipReader)
if errReader != nil {
panic(fmt.Sprintf("[goasset] read decode content failed, file=%q err=%s", fileName, errReader.Error()))
}
return buf
}
// nolint
var _assetBase64Decode = func(txt string, fileName string) []byte {
txt = strings.ReplaceAll(txt, "\n", "")
bf, err := base64.StdEncoding.DecodeString(txt)
if err != nil {
panic(fmt.Sprintf("[goasset](%s) base64 decode failed, err=%s", fileName, err.Error()))
}
return bf
}
asset := &assetFiles{Files: map[string]*assetFile{}}
Asset = asset
{
// 0 mtime: 2015-08-25 23:06:45 , size: 62
fileName := "/res/b.css"
contentBase64 := `
H4sIAAAAAAAA/8owrE7LzyvRLc6sSrUysSiosE7Oz8kvskovSk3Nq80wroZwi1JTajNMkDgAAAAA//8BAAD///xF3Xc4AAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 1 mtime: 2019-10-01 09:48:28 , size: 830
fileName := "/res/index.html"
contentBase64 := `
H4sIAAAAAAAA/5yTv2+7MBDFd/6Ki3fi/GD4DoeXb9u1HdKhU2XMEUOcgOxT2/z3lU0qkTRSo0xIx+fde/BsnD08/9+8vTyC5b1TGf48SNcqwz2xBmO1D8Sl
eN085f+EypBbdqQsOdeDDoEY5TjK0LWHHXhypQh8dBQsEQvg40ClYPpiaUIQYD01pZCegqzmcaIyDMa3A0/RTn/ocSogeHMSdEHqeReEQjm+vFHbRa+7dCvZ
XAhvUwbW3JpobO7Sx6+dqABneQ7FooA8vzH7oLdULIrpkost8tR01dfHmMsuT71+9t7VKO1SZTgo1L87A9Z+G8/Fe+X0YSdUGqPUCuWgsrhspbZ9OiBQ075H
aVfJYw1tXYrkE6PZtUqhYq1g+gP33kHLKeA5nVdTvrrCn+Nmips/8WaKN9dwOf4nlOmefAMAAP//AQAA//8u9YzkPgMAAA==`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1569894508, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 2 mtime: 2015-08-25 23:06:45 , size: 92
fileName := "/res/js/a.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LylTT1MvPyUos8Qnx9bCFCOol6WcUKRkrWtTqGBgYG
mtYAAAAA//8BAAD//4rtx7JYAAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 3 mtime: 2016-05-21 20:15:56 , size: 94
fileName := "/res/js/b.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOUNPUy8/JSizxCfH1sIYI6SXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//8g4AUloAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463832956, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 4 mtime: 2016-05-21 20:18:59 , size: 94
fileName := "/res/js/c.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOVNPUy8/JSizxCfH1sIYI6yXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//fIiYfFoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463833139, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 5 mtime: 2016-06-02 22:49:03 , size: 94
fileName := "/res2/f.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LyddOUNPUy8/JSizxCfH1sIYI6aXpZxQqmSta1OoYG
Bgaa1gAAAAD//wEAAP//SQFZwVoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1464878943, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
}
| GetContent | identifier_name |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one asset file
type AssetFile interface {
Name() string
ModTime() time.Time
Content() []byte
ContentGzip() []byte
}
// assetFile asset file struct
type assetFile struct {
name string
mtime time.Time
content []byte
contentGzip []byte
}
func (af *assetFile) Name() string {
return af.name
}
func (af *assetFile) ModTime() time.Time {
return af.mtime
}
func (af *assetFile) Content() []byte {
return af.content
}
func (af *assetFile) ContentGzip() []byte {
return af.contentGzip
}
var _ AssetFile = &assetFile{}
// AssetFiles asset files
type AssetFiles interface {
GetAssetFile(name string) (AssetFile, error)
GetContent(name string) []byte
GetFileNames(dir string) []string
FileHandlerFunc(name string) http.HandlerFunc
HTTPHandler(baseDir string) http.Handler
}
// assetFiles asset files
type assetFiles struct {
Files map[string]*assetFile
}
var _assetDirect bool
var _assetCwd, _ = os.Getwd()
// GetAssetFile get file by name
func (afs *assetFiles) GetAssetFile(name string) (AssetFile, error) {
name = filepath.ToSlash(name)
if name != "" && name[0] != '/' {
name = "/" + name
}
if _assetDirect {
assetFilePath := filepath.Join(_assetCwd, name)
f, err := os.Open(assetFilePath)
log.Println("[goasset] Asset Direct, name=", name, "assetPath=", assetFilePath, "err=", err)
if err != nil {
return nil, err
}
defer f.Close()
info, err := f.Stat()
if err != nil {
return nil, err
}
if info.Mode().IsRegular() {
content, err := ioutil.ReadAll(f)
if err != nil |
helper := newAssetHelper()
contentNew, errHelper := helper.Execute(assetFilePath, content, "")
if errHelper != nil {
return nil, errHelper
}
return &assetFile{
content: contentNew,
name: name,
mtime: info.ModTime(),
}, nil
}
return nil, fmt.Errorf("not file")
}
if sf, has := afs.Files[name]; has {
return sf, nil
}
return nil, fmt.Errorf("not exists")
}
// GetContent get content by name
func (afs *assetFiles) GetContent(name string) []byte {
s, err := afs.GetAssetFile(name)
if err != nil {
return []byte("")
}
return s.Content()
}
// GetFileNames get all file names
func (afs *assetFiles) GetFileNames(dir string) []string {
if dir == "" {
dir = "/"
}
names := make([]string, 0, len(afs.Files))
dirRaw := dir
dir = path.Clean(dir)
if dir != "/" && strings.HasSuffix(dirRaw, "/") {
dir += string(filepath.Separator)
}
dir = filepath.ToSlash(dir)
for name := range afs.Files {
if strings.HasPrefix(name, dir) {
names = append(names, name)
}
}
return names
}
// FileHandlerFunc handler http files
// 若目录名称 为 *private 则不允许通过web访问
func (afs *assetFiles) FileHandlerFunc(name string) http.HandlerFunc {
if strings.Contains(name, "private/") {
return http.NotFound
}
return afs.FileHandlerFuncAll(name)
}
// FileHandlerFuncAll handler http files
// 无 private 目录规则
func (afs *assetFiles) FileHandlerFuncAll(name string) http.HandlerFunc {
name = filepath.ToSlash(name)
file, err := afs.GetAssetFile(name)
return func(writer http.ResponseWriter, req *http.Request) {
if err != nil {
http.NotFound(writer, req)
return
}
modifiedSince := req.Header.Get("If-Modified-Since")
if modifiedSince != "" {
t, err := time.Parse(http.TimeFormat, modifiedSince)
if err == nil && file.ModTime().Before(t) {
writer.Header().Del("Content-Type")
writer.Header().Del("Content-Length")
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
writer.WriteHeader(http.StatusNotModified)
return
}
}
mimeType := mime.TypeByExtension(filepath.Ext(file.Name()))
if mimeType != "" {
writer.Header().Set("Content-Type", mimeType)
}
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
gzipContent := file.ContentGzip()
var errWrote error
if len(gzipContent) > 0 && strings.Contains(req.Header.Get("Accept-Encoding"), "gzip") {
writer.Header().Set("Content-Encoding", "gzip")
_, errWrote = writer.Write(gzipContent)
} else {
_, errWrote = writer.Write(file.Content())
}
if errWrote != nil {
log.Printf("[wf] wrote %q with error:%s\n", name, errWrote)
}
}
}
// HTTPHandler handler http request
// eg:on file system is :/res/js/a.js and request is /res/js/a.js
// http.Handle("/res/",res.Asset.HttpHandler("/"))
// eg:on file system is :/res/js/a.js and request is /js/a.js
// http.Handle("/js/",res.Asset.HttpHandler("/res/"))
func (afs *assetFiles) HTTPHandler(baseDir string) http.Handler {
return &_assetFileServer{sf: afs, pdir: baseDir}
}
type _assetFileServer struct {
sf *assetFiles
pdir string
}
// ServeHTTP ServeHTTP
func (f *_assetFileServer) ServeHTTP(w http.ResponseWriter, r *http.Request) {
name := filepath.ToSlash(filepath.Join(f.pdir, r.URL.Path))
f.sf.FileHandlerFunc(name).ServeHTTP(w, r)
}
var _ AssetFiles = &assetFiles{}
var _ = flag.String
var _ = runtime.Version()
// ---------------------------helper.go--------begin--------------------------//
func newAssetHelper() *assetHelper {
helper := &assetHelper{}
helper.Regs = make(map[string]*regexp.Regexp)
helper.Regs["remove_above"] = regexp.MustCompile(`[\S\s]*?//\s*asset_remove_above\(\s*\)`)
helper.Regs["remove"] = regexp.MustCompile(`//\s*asset_remove_start\(\s*\)[\S\s]*?//\s*asset_remove_end\(\s*\)`)
helper.Regs["include"] = regexp.MustCompile(`//\s*asset_include\(([^)]+?)\)`)
helper.RegisterFn("remove_above", helper.RemoveAbove)
helper.RegisterFn("include", helper.Include)
helper.RegisterFn("remove", helper.Remove)
return helper
}
type assetHelperFn func(fileName string, content []byte) ([]byte, error)
type assetHelper struct {
Fns []map[string]assetHelperFn
Regs map[string]*regexp.Regexp
}
// RegisterFn 注册helper方法
func (h *assetHelper) RegisterFn(name string, fn assetHelperFn) {
h.Fns = append(h.Fns, map[string]assetHelperFn{name: fn})
}
// Execute 执行所有的helper方法
func (h *assetHelper) Execute(fileAbsPath string, content []byte, skipFnName string) (contentNew []byte, err error) {
contentNew = make([]byte, len(content))
copy(contentNew, content)
for _, fnInfo := range h.Fns {
for name, fn := range fnInfo {
if name == skipFnName {
continue
}
contentNew, err = fn(fileAbsPath, contentNew)
if err != nil {
return nil, fmt.Errorf("%s,current file is: %s", err.Error(), fileAbsPath)
}
}
}
return contentNew, nil
}
// RemoveAbove 删除在此标记之前的内容
// eg: \/\/ asset_remove_above()
func (h *assetHelper) RemoveAbove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove_above"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
// Remove remove 方法, 删除指定区间里的内容
// eg: \/\/asset_remove_start() 中间的内容被删除 \/\/ asset_remove_end()
func (h *assetHelper) Remove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
func (h *assetHelper) include(fileAPath string, content []byte, includeFiles map[string]map[string]bool) (contentNew []byte, err error) {
fileAPath = filepath.Clean(fileAPath)
includeFiles[fileAPath] = make(map[string]bool)
contentNew = h.Regs["include"].ReplaceAllFunc(content, func(matchData []byte) []byte {
idx := bytes.Index(matchData, []byte("("))
name := bytes.TrimSpace(matchData[idx+1 : len(matchData)-1])
if len(name) == 0 {
err = fmt.Errorf("asset_include with empty param")
return []byte(err.Error())
}
fileBPath := filepath.Join(filepath.Dir(fileAPath), string(name))
if bFiles, hasB := includeFiles[fileBPath]; hasB {
if _, hasA := bFiles[fileAPath]; hasA {
err = fmt.Errorf("asset_include error: cyclic include,%s include(%s)", fileAPath, string(name))
return []byte(err.Error())
}
}
includeFiles[fileAPath][fileBPath] = true
includeFiles[fileBPath] = make(map[string]bool)
bContent, errRead := ioutil.ReadFile(fileBPath)
if errRead != nil {
err = errRead
return []byte(err.Error())
}
b1Content, errB1 := h.Execute(fileBPath, bContent, "include")
if errB1 != nil {
err = errB1
return []byte(err.Error())
}
cContent, errInclude := h.include(fileBPath, b1Content, includeFiles)
if errInclude != nil {
err = errInclude
return []byte(err.Error())
}
return cContent
})
if err != nil {
return nil, err
}
return contentNew, nil
}
// Include 将另外一个资源文件包含到当前文件里
// eg: \/\/ asset_include(a.tpl)
func (h *assetHelper) Include(fileAPath string, content []byte) (contentNew []byte, err error) {
// 用于检查循环include
includeFiles := make(map[string]map[string]bool)
return h.include(fileAPath, content, includeFiles)
}
// ---------------------------helper.go--------finish-------------------------//
// Asset export assets
var Asset AssetFiles
func init() {
// nolint
var _assetGzipDecode = func(data []byte, fileName string) []byte {
gzipReader, errGzip := gzip.NewReader(bytes.NewBuffer(data))
if errGzip != nil {
panic(fmt.Sprintf("[goasset] gzip decode failed,file=%q, err=%s", fileName, errGzip.Error()))
}
defer gzipReader.Close()
buf, errReader := ioutil.ReadAll(gzipReader)
if errReader != nil {
panic(fmt.Sprintf("[goasset] read decode content failed, file=%q err=%s", fileName, errReader.Error()))
}
return buf
}
// nolint
var _assetBase64Decode = func(txt string, fileName string) []byte {
txt = strings.ReplaceAll(txt, "\n", "")
bf, err := base64.StdEncoding.DecodeString(txt)
if err != nil {
panic(fmt.Sprintf("[goasset](%s) base64 decode failed, err=%s", fileName, err.Error()))
}
return bf
}
asset := &assetFiles{Files: map[string]*assetFile{}}
Asset = asset
{
// 0 mtime: 2015-08-25 23:06:45 , size: 62
fileName := "/res/b.css"
contentBase64 := `
H4sIAAAAAAAA/8owrE7LzyvRLc6sSrUysSiosE7Oz8kvskovSk3Nq80wroZwi1JTajNMkDgAAAAA//8BAAD///xF3Xc4AAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 1 mtime: 2019-10-01 09:48:28 , size: 830
fileName := "/res/index.html"
contentBase64 := `
H4sIAAAAAAAA/5yTv2+7MBDFd/6Ki3fi/GD4DoeXb9u1HdKhU2XMEUOcgOxT2/z3lU0qkTRSo0xIx+fde/BsnD08/9+8vTyC5b1TGf48SNcqwz2xBmO1D8Sl
eN085f+EypBbdqQsOdeDDoEY5TjK0LWHHXhypQh8dBQsEQvg40ClYPpiaUIQYD01pZCegqzmcaIyDMa3A0/RTn/ocSogeHMSdEHqeReEQjm+vFHbRa+7dCvZ
XAhvUwbW3JpobO7Sx6+dqABneQ7FooA8vzH7oLdULIrpkost8tR01dfHmMsuT71+9t7VKO1SZTgo1L87A9Z+G8/Fe+X0YSdUGqPUCuWgsrhspbZ9OiBQ075H
aVfJYw1tXYrkE6PZtUqhYq1g+gP33kHLKeA5nVdTvrrCn+Nmips/8WaKN9dwOf4nlOmefAMAAP//AQAA//8u9YzkPgMAAA==`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1569894508, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 2 mtime: 2015-08-25 23:06:45 , size: 92
fileName := "/res/js/a.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LylTT1MvPyUos8Qnx9bCFCOol6WcUKRkrWtTqGBgYG
mtYAAAAA//8BAAD//4rtx7JYAAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 3 mtime: 2016-05-21 20:15:56 , size: 94
fileName := "/res/js/b.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOUNPUy8/JSizxCfH1sIYI6SXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//8g4AUloAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463832956, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 4 mtime: 2016-05-21 20:18:59 , size: 94
fileName := "/res/js/c.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOVNPUy8/JSizxCfH1sIYI6yXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//fIiYfFoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463833139, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 5 mtime: 2016-06-02 22:49:03 , size: 94
fileName := "/res2/f.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LyddOUNPUy8/JSizxCfH1sIYI6aXpZxQqmSta1OoYG
Bgaa1gAAAAD//wEAAP//SQFZwVoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1464878943, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
}
| {
return nil, err
} | conditional_block |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one asset file
type AssetFile interface {
Name() string
ModTime() time.Time
Content() []byte
ContentGzip() []byte
}
// assetFile asset file struct
type assetFile struct {
name string
mtime time.Time
content []byte
contentGzip []byte
}
func (af *assetFile) Name() string {
return af.name
}
func (af *assetFile) ModTime() time.Time {
return af.mtime
}
func (af *assetFile) Content() []byte {
return af.content
}
func (af *assetFile) ContentGzip() []byte {
return af.contentGzip
}
var _ AssetFile = &assetFile{}
// AssetFiles asset files
type AssetFiles interface {
GetAssetFile(name string) (AssetFile, error)
GetContent(name string) []byte
GetFileNames(dir string) []string
FileHandlerFunc(name string) http.HandlerFunc
HTTPHandler(baseDir string) http.Handler
}
// assetFiles asset files
type assetFiles struct {
Files map[string]*assetFile
}
var _assetDirect bool
var _assetCwd, _ = os.Getwd()
// GetAssetFile get file by name
func (afs *assetFiles) GetAssetFile(name string) (AssetFile, error) {
name = filepath.ToSlash(name)
if name != "" && name[0] != '/' {
name = "/" + name
}
if _assetDirect {
assetFilePath := filepath.Join(_assetCwd, name)
f, err := os.Open(assetFilePath)
log.Println("[goasset] Asset Direct, name=", name, "assetPath=", assetFilePath, "err=", err)
if err != nil {
return nil, err
}
defer f.Close()
info, err := f.Stat()
if err != nil {
return nil, err
}
if info.Mode().IsRegular() {
content, err := ioutil.ReadAll(f)
if err != nil {
return nil, err
}
helper := newAssetHelper()
contentNew, errHelper := helper.Execute(assetFilePath, content, "")
if errHelper != nil {
return nil, errHelper
}
return &assetFile{
content: contentNew,
name: name,
mtime: info.ModTime(),
}, nil
}
return nil, fmt.Errorf("not file")
}
if sf, has := afs.Files[name]; has {
return sf, nil
}
return nil, fmt.Errorf("not exists")
}
// GetContent get content by name
func (afs *assetFiles) GetContent(name string) []byte {
s, err := afs.GetAssetFile(name)
if err != nil {
return []byte("")
}
return s.Content()
}
// GetFileNames get all file names
func (afs *assetFiles) GetFileNames(dir string) []string {
if dir == "" {
dir = "/"
}
names := make([]string, 0, len(afs.Files))
dirRaw := dir
dir = path.Clean(dir)
if dir != "/" && strings.HasSuffix(dirRaw, "/") {
dir += string(filepath.Separator)
}
dir = filepath.ToSlash(dir)
for name := range afs.Files {
if strings.HasPrefix(name, dir) {
names = append(names, name)
}
}
return names
}
// FileHandlerFunc handler http files
// 若目录名称 为 *private 则不允许通过web访问
func (afs *assetFiles) FileHandlerFunc(name string) http.HandlerFunc {
if strings.Contains(name, "private/") {
return http.NotFound
}
return afs.FileHandlerFuncAll(name)
}
// FileHandlerFuncAll handler http files
// 无 private 目录规则
func (afs *assetFiles) FileHandlerFuncAll(name string) http.HandlerFunc {
name = filepath.ToSlash(name)
file, err := afs.GetAssetFile(name)
return func(writer http.ResponseWriter, req *http.Request) {
if err != nil {
http.NotFound(writer, req)
return
}
modifiedSince := req.Header.Get("If-Modified-Since")
if modifiedSince != "" {
t, err := time.Parse(http.TimeFormat, modifiedSince)
if err == nil && file.ModTime().Before(t) {
writer.Header().Del("Content-Type")
writer.Header().Del("Content-Length")
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
writer.WriteHeader(http.StatusNotModified)
return
}
}
mimeType := mime.TypeByExtension(filepath.Ext(file.Name()))
if mimeType != "" {
writer.Header().Set("Content-Type", mimeType)
}
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
gzipContent := file.ContentGzip()
var errWrote error
if len(gzipContent) > 0 && strings.Contains(req.Header.Get("Accept-Encoding"), "gzip") {
writer.Header().Set("Content-Encoding", "gzip")
_, errWrote = writer.Write(gzipContent)
} else {
_, errWrote = writer.Write(file.Content())
}
if errWrote != nil {
log.Printf("[wf] wrote %q with error:%s\n", name, errWrote)
}
}
}
// HTTPHandler handler http request
// eg:on file system is :/res/js/a.js and request is /res/js/a.js
// http.Handle("/res/",res.Asset.HttpHandler("/"))
// eg:on file system is :/res/js/a.js and request is /js/a.js
// http.Handle("/js/",res.Asset.HttpHandler("/res/"))
func (afs *assetFiles) HTTPHandler(baseDir string) http.Handler {
return &_assetFileServer{sf: afs, pdir: baseDir}
}
type _assetFileServer struct {
sf *assetFiles
pdir string
}
// ServeHTTP ServeHTTP
func (f *_assetFileServer) ServeHTTP(w http.ResponseWriter, r *http.Request) {
name := filepath.ToSlash(filepath.J | r _ = flag.String
var _ = runtime.Version()
// ---------------------------helper.go--------begin--------------------------//
func newAssetHelper() *assetHelper {
helper := &assetHelper{}
helper.Regs = make(map[string]*regexp.Regexp)
helper.Regs["remove_above"] = regexp.MustCompile(`[\S\s]*?//\s*asset_remove_above\(\s*\)`)
helper.Regs["remove"] = regexp.MustCompile(`//\s*asset_remove_start\(\s*\)[\S\s]*?//\s*asset_remove_end\(\s*\)`)
helper.Regs["include"] = regexp.MustCompile(`//\s*asset_include\(([^)]+?)\)`)
helper.RegisterFn("remove_above", helper.RemoveAbove)
helper.RegisterFn("include", helper.Include)
helper.RegisterFn("remove", helper.Remove)
return helper
}
type assetHelperFn func(fileName string, content []byte) ([]byte, error)
type assetHelper struct {
Fns []map[string]assetHelperFn
Regs map[string]*regexp.Regexp
}
// RegisterFn 注册helper方法
func (h *assetHelper) RegisterFn(name string, fn assetHelperFn) {
h.Fns = append(h.Fns, map[string]assetHelperFn{name: fn})
}
// Execute 执行所有的helper方法
func (h *assetHelper) Execute(fileAbsPath string, content []byte, skipFnName string) (contentNew []byte, err error) {
contentNew = make([]byte, len(content))
copy(contentNew, content)
for _, fnInfo := range h.Fns {
for name, fn := range fnInfo {
if name == skipFnName {
continue
}
contentNew, err = fn(fileAbsPath, contentNew)
if err != nil {
return nil, fmt.Errorf("%s,current file is: %s", err.Error(), fileAbsPath)
}
}
}
return contentNew, nil
}
// RemoveAbove 删除在此标记之前的内容
// eg: \/\/ asset_remove_above()
func (h *assetHelper) RemoveAbove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove_above"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
// Remove remove 方法, 删除指定区间里的内容
// eg: \/\/asset_remove_start() 中间的内容被删除 \/\/ asset_remove_end()
func (h *assetHelper) Remove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
func (h *assetHelper) include(fileAPath string, content []byte, includeFiles map[string]map[string]bool) (contentNew []byte, err error) {
fileAPath = filepath.Clean(fileAPath)
includeFiles[fileAPath] = make(map[string]bool)
contentNew = h.Regs["include"].ReplaceAllFunc(content, func(matchData []byte) []byte {
idx := bytes.Index(matchData, []byte("("))
name := bytes.TrimSpace(matchData[idx+1 : len(matchData)-1])
if len(name) == 0 {
err = fmt.Errorf("asset_include with empty param")
return []byte(err.Error())
}
fileBPath := filepath.Join(filepath.Dir(fileAPath), string(name))
if bFiles, hasB := includeFiles[fileBPath]; hasB {
if _, hasA := bFiles[fileAPath]; hasA {
err = fmt.Errorf("asset_include error: cyclic include,%s include(%s)", fileAPath, string(name))
return []byte(err.Error())
}
}
includeFiles[fileAPath][fileBPath] = true
includeFiles[fileBPath] = make(map[string]bool)
bContent, errRead := ioutil.ReadFile(fileBPath)
if errRead != nil {
err = errRead
return []byte(err.Error())
}
b1Content, errB1 := h.Execute(fileBPath, bContent, "include")
if errB1 != nil {
err = errB1
return []byte(err.Error())
}
cContent, errInclude := h.include(fileBPath, b1Content, includeFiles)
if errInclude != nil {
err = errInclude
return []byte(err.Error())
}
return cContent
})
if err != nil {
return nil, err
}
return contentNew, nil
}
// Include 将另外一个资源文件包含到当前文件里
// eg: \/\/ asset_include(a.tpl)
func (h *assetHelper) Include(fileAPath string, content []byte) (contentNew []byte, err error) {
// 用于检查循环include
includeFiles := make(map[string]map[string]bool)
return h.include(fileAPath, content, includeFiles)
}
// ---------------------------helper.go--------finish-------------------------//
// Asset export assets
var Asset AssetFiles
func init() {
// nolint
var _assetGzipDecode = func(data []byte, fileName string) []byte {
gzipReader, errGzip := gzip.NewReader(bytes.NewBuffer(data))
if errGzip != nil {
panic(fmt.Sprintf("[goasset] gzip decode failed,file=%q, err=%s", fileName, errGzip.Error()))
}
defer gzipReader.Close()
buf, errReader := ioutil.ReadAll(gzipReader)
if errReader != nil {
panic(fmt.Sprintf("[goasset] read decode content failed, file=%q err=%s", fileName, errReader.Error()))
}
return buf
}
// nolint
var _assetBase64Decode = func(txt string, fileName string) []byte {
txt = strings.ReplaceAll(txt, "\n", "")
bf, err := base64.StdEncoding.DecodeString(txt)
if err != nil {
panic(fmt.Sprintf("[goasset](%s) base64 decode failed, err=%s", fileName, err.Error()))
}
return bf
}
asset := &assetFiles{Files: map[string]*assetFile{}}
Asset = asset
{
// 0 mtime: 2015-08-25 23:06:45 , size: 62
fileName := "/res/b.css"
contentBase64 := `
H4sIAAAAAAAA/8owrE7LzyvRLc6sSrUysSiosE7Oz8kvskovSk3Nq80wroZwi1JTajNMkDgAAAAA//8BAAD///xF3Xc4AAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 1 mtime: 2019-10-01 09:48:28 , size: 830
fileName := "/res/index.html"
contentBase64 := `
H4sIAAAAAAAA/5yTv2+7MBDFd/6Ki3fi/GD4DoeXb9u1HdKhU2XMEUOcgOxT2/z3lU0qkTRSo0xIx+fde/BsnD08/9+8vTyC5b1TGf48SNcqwz2xBmO1D8Sl
eN085f+EypBbdqQsOdeDDoEY5TjK0LWHHXhypQh8dBQsEQvg40ClYPpiaUIQYD01pZCegqzmcaIyDMa3A0/RTn/ocSogeHMSdEHqeReEQjm+vFHbRa+7dCvZ
XAhvUwbW3JpobO7Sx6+dqABneQ7FooA8vzH7oLdULIrpkost8tR01dfHmMsuT71+9t7VKO1SZTgo1L87A9Z+G8/Fe+X0YSdUGqPUCuWgsrhspbZ9OiBQ075H
aVfJYw1tXYrkE6PZtUqhYq1g+gP33kHLKeA5nVdTvrrCn+Nmips/8WaKN9dwOf4nlOmefAMAAP//AQAA//8u9YzkPgMAAA==`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1569894508, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 2 mtime: 2015-08-25 23:06:45 , size: 92
fileName := "/res/js/a.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LylTT1MvPyUos8Qnx9bCFCOol6WcUKRkrWtTqGBgYG
mtYAAAAA//8BAAD//4rtx7JYAAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 3 mtime: 2016-05-21 20:15:56 , size: 94
fileName := "/res/js/b.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOUNPUy8/JSizxCfH1sIYI6SXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//8g4AUloAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463832956, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 4 mtime: 2016-05-21 20:18:59 , size: 94
fileName := "/res/js/c.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOVNPUy8/JSizxCfH1sIYI6yXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//fIiYfFoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463833139, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 5 mtime: 2016-06-02 22:49:03 , size: 94
fileName := "/res2/f.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LyddOUNPUy8/JSizxCfH1sIYI6aXpZxQqmSta1OoYG
Bgaa1gAAAAD//wEAAP//SQFZwVoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1464878943, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
}
| oin(f.pdir, r.URL.Path))
f.sf.FileHandlerFunc(name).ServeHTTP(w, r)
}
var _ AssetFiles = &assetFiles{}
va | identifier_body |
asset.go | // Generated by goasset(1.0 20200404) or "go generate" . DO NOT EDIT.
// https://github.com/hidu/goasset/
package res
import (
"bytes"
"compress/gzip"
"encoding/base64"
"flag"
"fmt"
"io/ioutil"
"log"
"mime"
"net/http"
"os"
"path"
"path/filepath"
"regexp"
"runtime"
"strings"
"time"
)
// AssetFile one asset file
type AssetFile interface {
Name() string
ModTime() time.Time
Content() []byte
ContentGzip() []byte
}
// assetFile asset file struct
type assetFile struct {
name string
mtime time.Time
content []byte
contentGzip []byte
}
func (af *assetFile) Name() string {
return af.name
}
func (af *assetFile) ModTime() time.Time {
return af.mtime
}
func (af *assetFile) Content() []byte {
return af.content
}
func (af *assetFile) ContentGzip() []byte {
return af.contentGzip
}
var _ AssetFile = &assetFile{}
// AssetFiles asset files
type AssetFiles interface {
GetAssetFile(name string) (AssetFile, error)
GetContent(name string) []byte
GetFileNames(dir string) []string
FileHandlerFunc(name string) http.HandlerFunc
HTTPHandler(baseDir string) http.Handler
} |
// assetFiles asset files
type assetFiles struct {
Files map[string]*assetFile
}
var _assetDirect bool
var _assetCwd, _ = os.Getwd()
// GetAssetFile get file by name
func (afs *assetFiles) GetAssetFile(name string) (AssetFile, error) {
name = filepath.ToSlash(name)
if name != "" && name[0] != '/' {
name = "/" + name
}
if _assetDirect {
assetFilePath := filepath.Join(_assetCwd, name)
f, err := os.Open(assetFilePath)
log.Println("[goasset] Asset Direct, name=", name, "assetPath=", assetFilePath, "err=", err)
if err != nil {
return nil, err
}
defer f.Close()
info, err := f.Stat()
if err != nil {
return nil, err
}
if info.Mode().IsRegular() {
content, err := ioutil.ReadAll(f)
if err != nil {
return nil, err
}
helper := newAssetHelper()
contentNew, errHelper := helper.Execute(assetFilePath, content, "")
if errHelper != nil {
return nil, errHelper
}
return &assetFile{
content: contentNew,
name: name,
mtime: info.ModTime(),
}, nil
}
return nil, fmt.Errorf("not file")
}
if sf, has := afs.Files[name]; has {
return sf, nil
}
return nil, fmt.Errorf("not exists")
}
// GetContent get content by name
func (afs *assetFiles) GetContent(name string) []byte {
s, err := afs.GetAssetFile(name)
if err != nil {
return []byte("")
}
return s.Content()
}
// GetFileNames get all file names
func (afs *assetFiles) GetFileNames(dir string) []string {
if dir == "" {
dir = "/"
}
names := make([]string, 0, len(afs.Files))
dirRaw := dir
dir = path.Clean(dir)
if dir != "/" && strings.HasSuffix(dirRaw, "/") {
dir += string(filepath.Separator)
}
dir = filepath.ToSlash(dir)
for name := range afs.Files {
if strings.HasPrefix(name, dir) {
names = append(names, name)
}
}
return names
}
// FileHandlerFunc handler http files
// 若目录名称 为 *private 则不允许通过web访问
func (afs *assetFiles) FileHandlerFunc(name string) http.HandlerFunc {
if strings.Contains(name, "private/") {
return http.NotFound
}
return afs.FileHandlerFuncAll(name)
}
// FileHandlerFuncAll handler http files
// 无 private 目录规则
func (afs *assetFiles) FileHandlerFuncAll(name string) http.HandlerFunc {
name = filepath.ToSlash(name)
file, err := afs.GetAssetFile(name)
return func(writer http.ResponseWriter, req *http.Request) {
if err != nil {
http.NotFound(writer, req)
return
}
modifiedSince := req.Header.Get("If-Modified-Since")
if modifiedSince != "" {
t, err := time.Parse(http.TimeFormat, modifiedSince)
if err == nil && file.ModTime().Before(t) {
writer.Header().Del("Content-Type")
writer.Header().Del("Content-Length")
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
writer.WriteHeader(http.StatusNotModified)
return
}
}
mimeType := mime.TypeByExtension(filepath.Ext(file.Name()))
if mimeType != "" {
writer.Header().Set("Content-Type", mimeType)
}
writer.Header().Set("Last-Modified", file.ModTime().UTC().Format(http.TimeFormat))
gzipContent := file.ContentGzip()
var errWrote error
if len(gzipContent) > 0 && strings.Contains(req.Header.Get("Accept-Encoding"), "gzip") {
writer.Header().Set("Content-Encoding", "gzip")
_, errWrote = writer.Write(gzipContent)
} else {
_, errWrote = writer.Write(file.Content())
}
if errWrote != nil {
log.Printf("[wf] wrote %q with error:%s\n", name, errWrote)
}
}
}
// HTTPHandler handler http request
// eg:on file system is :/res/js/a.js and request is /res/js/a.js
// http.Handle("/res/",res.Asset.HttpHandler("/"))
// eg:on file system is :/res/js/a.js and request is /js/a.js
// http.Handle("/js/",res.Asset.HttpHandler("/res/"))
func (afs *assetFiles) HTTPHandler(baseDir string) http.Handler {
return &_assetFileServer{sf: afs, pdir: baseDir}
}
type _assetFileServer struct {
sf *assetFiles
pdir string
}
// ServeHTTP ServeHTTP
func (f *_assetFileServer) ServeHTTP(w http.ResponseWriter, r *http.Request) {
name := filepath.ToSlash(filepath.Join(f.pdir, r.URL.Path))
f.sf.FileHandlerFunc(name).ServeHTTP(w, r)
}
var _ AssetFiles = &assetFiles{}
var _ = flag.String
var _ = runtime.Version()
// ---------------------------helper.go--------begin--------------------------//
func newAssetHelper() *assetHelper {
helper := &assetHelper{}
helper.Regs = make(map[string]*regexp.Regexp)
helper.Regs["remove_above"] = regexp.MustCompile(`[\S\s]*?//\s*asset_remove_above\(\s*\)`)
helper.Regs["remove"] = regexp.MustCompile(`//\s*asset_remove_start\(\s*\)[\S\s]*?//\s*asset_remove_end\(\s*\)`)
helper.Regs["include"] = regexp.MustCompile(`//\s*asset_include\(([^)]+?)\)`)
helper.RegisterFn("remove_above", helper.RemoveAbove)
helper.RegisterFn("include", helper.Include)
helper.RegisterFn("remove", helper.Remove)
return helper
}
type assetHelperFn func(fileName string, content []byte) ([]byte, error)
type assetHelper struct {
Fns []map[string]assetHelperFn
Regs map[string]*regexp.Regexp
}
// RegisterFn 注册helper方法
func (h *assetHelper) RegisterFn(name string, fn assetHelperFn) {
h.Fns = append(h.Fns, map[string]assetHelperFn{name: fn})
}
// Execute 执行所有的helper方法
func (h *assetHelper) Execute(fileAbsPath string, content []byte, skipFnName string) (contentNew []byte, err error) {
contentNew = make([]byte, len(content))
copy(contentNew, content)
for _, fnInfo := range h.Fns {
for name, fn := range fnInfo {
if name == skipFnName {
continue
}
contentNew, err = fn(fileAbsPath, contentNew)
if err != nil {
return nil, fmt.Errorf("%s,current file is: %s", err.Error(), fileAbsPath)
}
}
}
return contentNew, nil
}
// RemoveAbove 删除在此标记之前的内容
// eg: \/\/ asset_remove_above()
func (h *assetHelper) RemoveAbove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove_above"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
// Remove remove 方法, 删除指定区间里的内容
// eg: \/\/asset_remove_start() 中间的内容被删除 \/\/ asset_remove_end()
func (h *assetHelper) Remove(fileAbsPath string, content []byte) (contentNew []byte, err error) {
contentNew = h.Regs["remove"].ReplaceAll(content, []byte(""))
return contentNew, nil
}
func (h *assetHelper) include(fileAPath string, content []byte, includeFiles map[string]map[string]bool) (contentNew []byte, err error) {
fileAPath = filepath.Clean(fileAPath)
includeFiles[fileAPath] = make(map[string]bool)
contentNew = h.Regs["include"].ReplaceAllFunc(content, func(matchData []byte) []byte {
idx := bytes.Index(matchData, []byte("("))
name := bytes.TrimSpace(matchData[idx+1 : len(matchData)-1])
if len(name) == 0 {
err = fmt.Errorf("asset_include with empty param")
return []byte(err.Error())
}
fileBPath := filepath.Join(filepath.Dir(fileAPath), string(name))
if bFiles, hasB := includeFiles[fileBPath]; hasB {
if _, hasA := bFiles[fileAPath]; hasA {
err = fmt.Errorf("asset_include error: cyclic include,%s include(%s)", fileAPath, string(name))
return []byte(err.Error())
}
}
includeFiles[fileAPath][fileBPath] = true
includeFiles[fileBPath] = make(map[string]bool)
bContent, errRead := ioutil.ReadFile(fileBPath)
if errRead != nil {
err = errRead
return []byte(err.Error())
}
b1Content, errB1 := h.Execute(fileBPath, bContent, "include")
if errB1 != nil {
err = errB1
return []byte(err.Error())
}
cContent, errInclude := h.include(fileBPath, b1Content, includeFiles)
if errInclude != nil {
err = errInclude
return []byte(err.Error())
}
return cContent
})
if err != nil {
return nil, err
}
return contentNew, nil
}
// Include 将另外一个资源文件包含到当前文件里
// eg: \/\/ asset_include(a.tpl)
func (h *assetHelper) Include(fileAPath string, content []byte) (contentNew []byte, err error) {
// 用于检查循环include
includeFiles := make(map[string]map[string]bool)
return h.include(fileAPath, content, includeFiles)
}
// ---------------------------helper.go--------finish-------------------------//
// Asset export assets
var Asset AssetFiles
func init() {
// nolint
var _assetGzipDecode = func(data []byte, fileName string) []byte {
gzipReader, errGzip := gzip.NewReader(bytes.NewBuffer(data))
if errGzip != nil {
panic(fmt.Sprintf("[goasset] gzip decode failed,file=%q, err=%s", fileName, errGzip.Error()))
}
defer gzipReader.Close()
buf, errReader := ioutil.ReadAll(gzipReader)
if errReader != nil {
panic(fmt.Sprintf("[goasset] read decode content failed, file=%q err=%s", fileName, errReader.Error()))
}
return buf
}
// nolint
var _assetBase64Decode = func(txt string, fileName string) []byte {
txt = strings.ReplaceAll(txt, "\n", "")
bf, err := base64.StdEncoding.DecodeString(txt)
if err != nil {
panic(fmt.Sprintf("[goasset](%s) base64 decode failed, err=%s", fileName, err.Error()))
}
return bf
}
asset := &assetFiles{Files: map[string]*assetFile{}}
Asset = asset
{
// 0 mtime: 2015-08-25 23:06:45 , size: 62
fileName := "/res/b.css"
contentBase64 := `
H4sIAAAAAAAA/8owrE7LzyvRLc6sSrUysSiosE7Oz8kvskovSk3Nq80wroZwi1JTajNMkDgAAAAA//8BAAD///xF3Xc4AAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 1 mtime: 2019-10-01 09:48:28 , size: 830
fileName := "/res/index.html"
contentBase64 := `
H4sIAAAAAAAA/5yTv2+7MBDFd/6Ki3fi/GD4DoeXb9u1HdKhU2XMEUOcgOxT2/z3lU0qkTRSo0xIx+fde/BsnD08/9+8vTyC5b1TGf48SNcqwz2xBmO1D8Sl
eN085f+EypBbdqQsOdeDDoEY5TjK0LWHHXhypQh8dBQsEQvg40ClYPpiaUIQYD01pZCegqzmcaIyDMa3A0/RTn/ocSogeHMSdEHqeReEQjm+vFHbRa+7dCvZ
XAhvUwbW3JpobO7Sx6+dqABneQ7FooA8vzH7oLdULIrpkost8tR01dfHmMsuT71+9t7VKO1SZTgo1L87A9Z+G8/Fe+X0YSdUGqPUCuWgsrhspbZ9OiBQ075H
aVfJYw1tXYrkE6PZtUqhYq1g+gP33kHLKeA5nVdTvrrCn+Nmips/8WaKN9dwOf4nlOmefAMAAP//AQAA//8u9YzkPgMAAA==`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1569894508, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 2 mtime: 2015-08-25 23:06:45 , size: 92
fileName := "/res/js/a.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LylTT1MvPyUos8Qnx9bCFCOol6WcUKRkrWtTqGBgYG
mtYAAAAA//8BAAD//4rtx7JYAAAA`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1440515205, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 3 mtime: 2016-05-21 20:15:56 , size: 94
fileName := "/res/js/b.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOUNPUy8/JSizxCfH1sIYI6SXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//8g4AUloAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463832956, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 4 mtime: 2016-05-21 20:18:59 , size: 94
fileName := "/res/js/c.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LydZOVNPUy8/JSizxCfH1sIYI6yXpZxQpGSta1OoYG
Bgaa1gAAAAD//wEAAP//fIiYfFoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1463833139, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
{
// 5 mtime: 2016-06-02 22:49:03 , size: 94
fileName := "/res2/f.js"
contentBase64 := `
H4sIAAAAAAAA/ypOLQnJzE3NLy3RSCvNSy7JzM/T0KxOyU8uzU3NK9FLTy1xzUkFMZ0qPVM0lDJSc3LyddOUNPUy8/JSizxCfH1sIYI6aXpZxQqmSta1OoYG
Bgaa1gAAAAD//wEAAP//SQFZwVoAAAA=`
contentGz := _assetBase64Decode(contentBase64, fileName)
oneFile := &assetFile{
name: fileName,
mtime: time.Unix(1464878943, 0),
content: _assetGzipDecode(contentGz, fileName),
contentGzip: contentGz,
}
asset.Files[fileName] = oneFile
}
} | random_line_split | |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import networkx as nx
import os
import codecs
from pycorenlp import StanfordCoreNLP
import matplotlib.pyplot as plt
import re
import operator
import json
from collections import OrderedDict
import logging
# custom
from classes import Stats, Annotations
from grobid_quantities.quantities import QuantitiesClient
##################################################################################
# Globals
##################################################################################
basedir = os.path.abspath(os.path.dirname(__file__))
stats = Stats()
A = None # global annotations object
Num = None # global sentence object
G = None # global dependency tree object
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)-8s %(message)s',
datefmt='%a, %d %b %Y %H:%M:%S',
filename=os.path.join(basedir, 'measurement.log'))
##################################################################################
def _build_graph(show=False):
"""Load word dependencies into graph using networkx. Enables easy traversal of dependencies for parsing particular patterns.
One graph is created for each sentence.
Args:
show (bool): If set to True, labeled visualization of network will be opened via matplotlib for each sentence
Returns:
None: Global variable G is set from within function
"""
global G
G = nx.Graph()
node_labels, edge_labels = {}, {}
for idx, dep in enumerate(A.deps):
types = ["dependent", "governor"]
# nodes, labels
for x in types:
G.add_node(str(dep[x]), word=dep[x + "Gloss"], pos=A.lookup[dep[x]]["pos"])
node_labels[str(dep[x])] = dep[x + "Gloss"] + " : " + A.lookup[dep[x]]["pos"]
# edges, labels
G.add_edge(str(dep[types[0]]), str(dep[types[1]]), dep=dep["dep"])
edge_labels[(str(dep[types[0]]), str(dep[types[1]]))] = dep["dep"]
if show == True:
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos=pos, labels=node_labels, node_color="white", alpha=.5)
nx.draw_networkx_edge_labels(G, pos=pos, edge_labels=edge_labels)
plt.show()
#########################################
# Dependency / POS parsing functions
#########################################
def _get_connected(edge, idx):
"""If an edge connects to a node (word), return the index of the node
Args:
edge (tuple): Contains token indices of two connect words and the dependency type between them - e.g. ('11', '14', {'dep': 'nmod:at'})
idx (int): Token index of word
Returns:
str or None: str if connected word is found in provided edge, None if not
"""
if str(edge[0]) == str(idx) and A.lookup[int(edge[1])]["word"] != Num:
return edge[1]
elif str(edge[1]) == str(idx) and A.lookup[int(edge[0])]["word"] != Num:
return edge[0]
def _get_cousin(sibling_idx, dep_type_list, visited_nodes={}):
"""Find a second degree relation within the dependency graph.
Used to find subject in a sentence when the measurement unit is a direct object, for example.
Args:
sibling_idx (str): Token index of the sibling node through which to find the cousin
dep_type_list (list): Allowable dependency types connecting sibling to cousin
Returns:
list: cousin words meeting POS and dependency criteria
"""
words = [] # Visited nodes prevent recursion from bouncing between two "VB" nodes
for dep_type in dep_type_list:
for edge in G.edges(data=True):
cousin_idx = _get_connected(edge, sibling_idx)
allowed_pos = ["NN", "PR"]
if cousin_idx and dep_type in edge[2]['dep'] and any(
x in A.lookup[int(cousin_idx)]['pos'] for x in allowed_pos):
words.append(G.nodes[cousin_idx]['word'])
# Go to second cousin if cousin is a verb
elif cousin_idx and dep_type in edge[2]['dep'] and "VB" in A.lookup[int(cousin_idx)]['pos'] and (
not cousin_idx in visited_nodes or visited_nodes[cousin_idx] < 2):
words.extend(_get_cousin(cousin_idx, ["nsubj", "nsubjpass", "acl"], visited_nodes=visited_nodes))
if cousin_idx:
if cousin_idx in visited_nodes:
visited_nodes[cousin_idx] += 1
else:
visited_nodes[cousin_idx] = 1
return set(words)
def _add_related(related, dep, all_related, index, connector=None):
"""Adds a word (and its metadata) related to a measurement to the list of all related words for that measurement
Args:
related (str): related token/word
dep (str): the dependency type connecting the unit to the related word
all_related (list): existing list of "related" objects to be augmented
index (str): token index of related word
connector (str): if related word is cousin of unit (not sibling) then connecter is word between
Returns:
list: all related words for a given measurement (augmented with new 'related' passed in)
"""
doc = {}
doc["relationForm"] = dep
doc["rawName"] = related
doc["tokenIndex"] = int(index)
doc["offsetStart"] = A.lookup[int(index)]["start"]
doc["offsetEnd"] = A.lookup[int(index)]["end"]
doc["connector"] = "" if connector is None else connector
if not doc in all_related:
all_related.append(doc)
return all_related
def | (related):
"""For related words found for a measurement (usually nouns), add any connected adjectives, compounds, or modifiers.
Args:
related (list): objects containing related words and their metadata
Returns:
list: original list of related objects augmented with additional descriptor words
"""
for r in related:
r["descriptors"] = []
for edge in G.edges(data=True):
sibling_idx = _get_connected(edge, r["tokenIndex"])
if sibling_idx and (A.lookup[int(sibling_idx)]["pos"] == "JJ" or edge[2]["dep"] in ["amod", "compound"]):
r["descriptors"].append(
{
"tokenIndex": sibling_idx,
"rawName": A.lookup[int(sibling_idx)]["word"]
}
)
if sibling_idx and "NN" in A.lookup[int(sibling_idx)]["pos"] and "amod" in edge[2]["dep"]:
additional_related = _get_cousin(sibling_idx, ["nmod"])
for add in set(additional_related):
related = _add_related(add, "nmod", related, A.index_lookup[add],
connector=G.nodes[sibling_idx]['word'])
return related
def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):
""" If measurement is found, runs processed sentence through valid dependency patterns
(from JSON file) to find additional words related to measurements
Args:
dep (str): dependency type present in dependency patterns JSON
dep_obj (dict): object containing accepted POS types and measurement formats for a given dependency type
all_related (list): contains words related to a measurement to be augmented if valid pattern is found
edge (list): Connected node (word) indices and dependency type between
sibling_idx (str): token index of word connected to unit
Returns:
list: related words and metadata
"""
# Check for a matching dependency type
related = []
if edge[2]["dep"] == dep:
# Check for matching POS type(s)
for pos_logic in dep_obj.keys():
connector = None
if isinstance(dep_obj[pos_logic], dict):
for pos in dep_obj[pos_logic].keys():
# Check for allowed part of speech tags in matched dependency patterns
if (pos_logic == "pos_in" and pos in G.nodes[sibling_idx]["pos"]) or (
pos_logic == "pos_equals" and pos == G.nodes[sibling_idx]["pos"]):
pass
elif pos_logic == "pos_not":
if not [False if not_pos == G.nodes[sibling_idx]["pos"] else True for not_pos in
dep_obj.keys()]: continue
else:
continue
# if no additional checks, have a match
if dep_obj[pos_logic][pos] == None or any(
y in dep_obj[pos_logic][pos] for y in [None, "add_sibling"]):
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']])
# if additional checks are required, process further
if dep_obj[pos_logic][pos]:
if "get_cousin" in dep_obj[pos_logic][pos]:
related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos]["get_cousin"]))
connector = G.nodes[sibling_idx]['word']
if "special" in dep_obj[pos_logic][pos]:
if dep == "compound" and pos == "NN":
related = [G.nodes[sibling_idx]['word']]
if None in related:
related.remove(None)
# Allows for getting cousin and returning sibling
if "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == "always":
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
if len(related) > 0 and isinstance(related, list):
for x in related:
if x != None:
all_related = _add_related(x, dep, all_related, A.index_lookup[x],
connector=connector)
elif "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == True:
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
return all_related
def _parse_patterns(unit_idx, measurement_format, patterns_file):
""" Loads depedency patters JSON file and uses "_check_criteria" to look for words related to measurement (connected via unit token)
Args:
unit_idx (list): index or indices of measurement unit token(s)
measurement_format (str): indicates form of measurement value + unit (attached: 10m, space between: 10 m, hyphenated: 10-m)
Returns:
list: related words and metadata
"""
all_related = []
for edge in G.edges(data=True):
for idx in unit_idx:
sibling_idx = _get_connected(edge, idx)
if sibling_idx:
with open(os.path.join(basedir, patterns_file), "r") as tree:
tree = json.load(tree)
for dep in tree["dep"].keys():
if tree["dep"][dep]["enhanced"] == True:
for inner_dep in tree["dep"][dep].keys():
if isinstance(tree["dep"][dep][inner_dep], dict) and measurement_format in \
tree["dep"][dep][inner_dep]["measurement_types"]:
full_dep = dep + ":" + inner_dep
full_dep_obj = tree["dep"][dep][inner_dep]
all_related = _check_criteria(full_dep, full_dep_obj, all_related, edge,
sibling_idx)
elif measurement_format in tree["dep"][dep]["measurement_types"]:
all_related = _check_criteria(dep, tree["dep"][dep], all_related, edge, sibling_idx)
for x in range(0, len(tree["word"]["or"])):
if G.nodes[sibling_idx]["word"] == tree["word"]["or"][x]:
related = _get_cousin(sibling_idx, ["nsubj"])
for r in related:
all_related = _add_related(r, "operator", all_related, A.index_lookup[r])
all_related = _add_descriptors(all_related)
return all_related
def _get_related(stats, match, patterns_file):
""" Calls _parse_patterns() to get words related to a measurement and provides de-duplication between related words and grobid response
Args:
stats (Stats object): Global object used to track parsing behaviors
match (dict): information on measurements and units extracted by Grobid
Returns:
list: related words and metadata
"""
all_related = None
measurement_formats = ["space_between", "attached", "hyphenated"]
all_related = _parse_patterns(match["unit_idx"], match["measurement_format"], patterns_file)
if all_related == None:
all_related = _parse_patterns(match["unit_idx"], ["uncertain"], patterns_file)
# get words like approximately
num_adverbs = _parse_patterns([match["num_idx"]], match["measurement_format"], patterns_file)
unit_adverbs = _parse_patterns([match["unit_idx"]], match["measurement_format"], patterns_file)
adverbs = num_adverbs + unit_adverbs
for_removal = []
for a in adverbs:
if a["relationForm"] != "advmod":
for_removal.append(a)
else:
[a.pop(key, None) for key in ["descriptors", "connector"]] # not relevant for adverbs
[adverbs.remove(a) for a in for_removal]
if adverbs:
match["grobid"]["adverbs"] = adverbs
# Check to make sure related isn't already a number, unit, or quantified thing identified by Grobid
potential_keys = ["quantity", "quantityLeast", "quantityMost", "quantified"]
if all_related:
for key in potential_keys:
for related in all_related:
if key in match["grobid"]:
num, unit, quantified = "", "", ""
if "rawValue" in match["grobid"][key]: num = match["grobid"][key]["rawValue"]
if "rawUnit" in match["grobid"][key]: unit = match["grobid"][key]["rawUnit"]["name"]
if "normalizedName" in match["grobid"][key]: quantified = match["grobid"][key]["normalizedName"]
if related["rawName"] in [num, unit, quantified] or related["rawName"] == num + unit or (
quantified in related["rawName"] and not quantified == ""):
all_related.remove(related)
if related["rawName"] == unit:
for k in related.keys():
if not k in match["grobid"][key]["rawUnit"]:
match["grobid"][key]["rawUnit"][k] = related[k]
elif related["rawName"] == quantified:
for k in related.keys():
if not k in match["grobid"][key]:
match["grobid"][key][k] = related[k]
return all_related
def _simplify_results(match):
"""WORK IN PROGRESS: Prune metadata from extracted measurements and related words for more readable output
Args:
match (dict): Object contatining all metadata about extraction types, locations, relationships within sentence
Returns:
list: contains 4 items, extracted numeric value or range (list), unit(s) (list), qunatified words identified by Grobid (str), related words (str)
"""
keys = []
simplified = {}
simplified["value"] = []
if match["type"] == "value":
keys = ["quantity"]
elif match["type"] == "interval":
keys = ["quantityLeast", "quantityMost"]
for key in keys:
if key in match:
if "parsedValue" in match[key]:
simplified["value"].append(match[key]["parsedValue"])
elif "rawValue" in match[key]:
simplified["value"].append(match[key]["rawValue"])
else:
return None
simplified["unit"] = match[key]["rawUnit"]["name"] if "rawUnit" in match[key] else ""
if len(simplified["value"]) == 1:
simplified["value"] = simplified["value"][0]
simplified["quantified"] = {}
simplified["related"] = {}
if "quantified" in match:
if simplified["unit"] == "":
simplified["unit"] = match["quantified"]["normalizedName"]
simplified["quantified"][match["quantified"]["normalizedName"]] = []
if "descriptors" in match["quantified"]:
match["quantified"]["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for x in match["quantified"]["descriptors"]:
simplified["quantified"][match["quantified"]["normalizedName"]].append(x["rawName"])
if match["related"]:
for r in match["related"]:
simplified["related"][r["rawName"]] = []
if "descriptors" in r:
r["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for z in r["descriptors"]:
simplified["related"][r["rawName"]].append(z["rawName"])
return simplified
def _reconstruct_sent(parsed_sentence):
"""Reconstruct sentence from CoreNLP tokens - raw sentence text isn't retained by CoreNLP after sentence splitting and processing
Args:
parsed_sentence (dict): Object containing CoreNLP output
Returns:
str: original sentence
"""
sent = ""
for x in range(0, len(parsed_sentence["tokens"])):
sent += parsed_sentence["tokens"][x]['originalText']
if x + 1 != len(parsed_sentence["tokens"]):
# Use character indices from tokens to ensure correct spacing when reconstructing
num_spaces = parsed_sentence["tokens"][x + 1]["characterOffsetBegin"] - parsed_sentence["tokens"][x][
"characterOffsetEnd"]
for y in range(0, num_spaces):
sent += " "
return sent
def _sorted_dictionary(orig_dict, sort_list):
od = OrderedDict()
for item in sort_list:
if item in orig_dict:
od[item] = orig_dict[item]
return od
#########################################
# Top-Level function
#########################################
def extract(content, corenlp_endpoint, grobid_endpoint, dependency_patterns_file, output_file=None, show_graph=False,
pretty=False, simplify=False):
""" Top-level user interface to parsing measurements and related words
Args:
content (str): sentence or paragraph to be parsed (shouldn't be much larger)
corenlp_endpoint (str): host + port of CoreNLP service (e.g. "http://localhost:9000")
grobid_endpoint (str): host + port of grobid service (e.g. "http://localhost:8080")
dependency_patterns (str): filepath to dependency patterns JSON file
output_file (optional: str): file to write output to
show_graph (bool): Will show network visualization of sentence dependencies if True
pretty (bool): JSON output will be pretty printed if True, else one JSON doc per line (JSONL)
simplify (bool): If True provides bare bones output with only extractions and not metadata about indices, types, etc.
Returns:
List of objects: containing parsed measurement info
(optionally write to file)
"""
all_extractions = []
out = None
if output_file:
out = codecs.open(output_file, "a", encoding="utf-8")
if len(content) < 5:
return None
nlp = StanfordCoreNLP(corenlp_endpoint)
output = nlp.annotate(content, properties={'outputFormat': 'json', 'timeout': '9999'})
if isinstance(output, str): # str supports both python 2 and 3
output = json.loads(output.encode("latin-1"), strict=False)
if "sentences" in output and isinstance(output["sentences"], list):
for i in range(0, len(output["sentences"])):
s_str = _reconstruct_sent(output["sentences"][i])
# Enhanced dependencies have different key names in JSON depending on version of CoreNLP
possible_keys = [
"enhanced-plus-plus-dependencies-annotation",
"enhancedPlusPlusDependencies"
]
dep_key = "collapsed-ccprocessed-dependencies" # default key
if "collapsed-ccprocessed-dependencies" not in output["sentences"][i]:
for k in possible_keys:
if k in output["sentences"][i]:
dep_key = k
global A
A = Annotations(output["sentences"][i]["tokens"], output["sentences"][i][dep_key])
if A.check_output(output["sentences"][i], stats) is True:
stats.total_sentences += 1
G = _build_graph(show=show_graph)
grobid_response = grobid_quantities(s_str, A, grobid_endpoint)
if isinstance(grobid_response, dict) and "measurements" in grobid_response:
for quantity in grobid_response["measurements"]:
A.augment_match(quantity)
stats.total_measurements += len(A.matches)
for idx, match in enumerate(A.matches):
global Num
Num = match["num"]
match["sentence"] = i + 1
match["grobid"]["related"] = _get_related(stats, match, dependency_patterns_file)
# Remove fields used for processing but not to be shown to user
remove = ["adverbs", "num", "unit", "connector", "form", "sentence", "num_idx", "unit_idx",
"measurement_format"]
[match.pop(x, None) for x in remove]
sort_order = ['adverbs', 'type', 'quantity', 'quantityLeast', 'quantityMost', 'quantified',
'related']
match_ordered = _sorted_dictionary(match["grobid"], sort_order)
if simplify:
simplified_sort_order = ['value', 'unit', 'quantified', 'related']
simplified = _simplify_results(match_ordered)
if simplified:
match_ordered = _sorted_dictionary(match["grobid"], simplified_sort_order)
if pretty and not simplify:
if out:
out.write(json.dumps(match_ordered, ensure_ascii=False, indent=4))
if idx != len(A.matches) - 1 and out:
out.write(",\n")
elif out:
out.write(json.dumps(match_ordered, ensure_ascii=False) + "\n")
all_extractions.extend(A.matches)
else:
logging.warning("CoreNLP parsing failed for sentence: %s" % (s_str))
else:
logging.warning("CoreNLP parsing failed for content: %s" % (content))
if out:
out.close()
logging.info("Total sentences parsed: %s" % (str(stats.total_sentences)))
logging.info("Total measurements found: %s" % (str(stats.total_measurements)))
stats.print_summary()
return all_extractions
def grobid_quantities(sentence, a, endpoint):
"""
a = annotations
"""
"""Pass sentence text to Grobid server on port 8080 for measurement parsing
Args:
sentence (str): Sentence to be parsed
a (Annotations object): object containing relevant CoreNLP output
Returns:
dict: object containing Grobid output
"""
# $ needs to be escaped when passed via subprocess
sentence = re.sub("\$", "\\$", sentence)
sentence = re.sub("\"", '\\"', sentence)
sentence = re.sub("%", '%25', sentence)
sentence = re.sub("`", "'", sentence)
sentence = re.sub("'", '\\"', sentence)
if endpoint[len(endpoint) - 1:] == "/":
endpoint = endpoint[:len(endpoint) - 1]
response = None
# try:
response = QuantitiesClient(endpoint).process_text(sentence)
if response[0] != 200:
print('No Grobid response for: %s' % sentence)
logging.warning('No Grobid response for: %s' % sentence)
return ""
quantities = response[1]
# Add token index for num, unit, quantified if available
if isinstance(quantities, dict):
if "measurements" in quantities.keys():
for q in quantities["measurements"]:
key = ""
if q["type"] == "value":
key = "quantity"
# if Grobid doesn't parse interval correctly, sometimes only 'QuantityLeast' or 'QuantityMost' is available
if q["type"] == "interval":
if "quantityLeast" in q:
key = "quantityLeast"
elif "QuantityMost" in q:
key = "quantityMost"
else:
return {}
if q["type"] == "listc":
return {}
if key == "":
logging.error('Unknown Grobid key resulting from parse of: %s' % sentence)
print("Unknown Grobid key resulting from parse of: %s" % sentence)
# Grobid doesn't pick up negatives
if sentence[sentence.find(q[key]["rawValue"]) - 1] == "-":
q[key]["parsedValue"] = float("-" + str(q[key]["parsedValue"]))
q[key]["rawValue"] = "-" + str(q[key]["rawValue"])
q[key]["offsetStart"] -= 1
if q[key]["offsetStart"] in a.tok_start:
q[key]["tokenIndex"] = a.tok_start[q[key]["offsetStart"]]
else:
print("Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
logging.error(
"Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
return {}
if "rawUnit" in q[key]:
q[key]["rawUnit"]["after"] = a.lookup[q[key]["tokenIndex"]]["after"]
q[key]["rawUnit"]["tokenIndices"] = []
if q[key]["rawUnit"]["offsetStart"] in a.tok_start:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_start[q[key]["rawUnit"]["offsetStart"]]))
if q[key]["rawUnit"]["offsetEnd"] in a.tok_end:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_end[q[key]["rawUnit"]["offsetEnd"]]))
if q[key]["rawUnit"]["offsetStart"] == q[key]["offsetEnd"]:
q[key]["rawUnit"]["tokenIndices"].append(str(q[key]["tokenIndex"]))
q[key]["rawUnit"]["tokenIndices"] = list(set(q[key]["rawUnit"]["tokenIndices"]))
if "quantified" in q:
# often times Grobid with return a phrase where normalized name is in middle. In this case, "offsetStart" identifies the wrong token
add_to_offset = 0
normalized_idx, words = None, None
if " " in q["quantified"]["rawName"]:
words = q["quantified"]["rawName"].split(" ")
for i, w in enumerate(words):
if not q["quantified"]["normalizedName"] in w:
add_to_offset += (len(w) + 1) # +1 for space that was split on
else:
break
q["quantified"]["offsetStart"] += add_to_offset
if q["quantified"]["offsetStart"] in a.tok_start:
q["quantified"]["tokenIndex"] = a.tok_start[q["quantified"]["offsetStart"]]
else:
logging.warning(
"Not finding token index for Grobid quantified word in CoreNLP output. Sentence: %s" % (
sentence))
# hyphen causing issue - Grobid doesn't treat hyphenated clause as one word
# example error sentence: "Macroscopic examination of the CNS revealed micrencephaly with a whole-brain weight of 84 grams."
return quantities
| _add_descriptors | identifier_name |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import networkx as nx
import os
import codecs
from pycorenlp import StanfordCoreNLP
import matplotlib.pyplot as plt
import re
import operator
import json
from collections import OrderedDict
import logging
# custom
from classes import Stats, Annotations
from grobid_quantities.quantities import QuantitiesClient
##################################################################################
# Globals
##################################################################################
basedir = os.path.abspath(os.path.dirname(__file__))
stats = Stats()
A = None # global annotations object
Num = None # global sentence object
G = None # global dependency tree object
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)-8s %(message)s',
datefmt='%a, %d %b %Y %H:%M:%S',
filename=os.path.join(basedir, 'measurement.log'))
##################################################################################
def _build_graph(show=False):
"""Load word dependencies into graph using networkx. Enables easy traversal of dependencies for parsing particular patterns.
One graph is created for each sentence.
Args:
show (bool): If set to True, labeled visualization of network will be opened via matplotlib for each sentence
Returns:
None: Global variable G is set from within function
"""
global G
G = nx.Graph()
node_labels, edge_labels = {}, {}
for idx, dep in enumerate(A.deps):
types = ["dependent", "governor"]
# nodes, labels
for x in types:
G.add_node(str(dep[x]), word=dep[x + "Gloss"], pos=A.lookup[dep[x]]["pos"])
node_labels[str(dep[x])] = dep[x + "Gloss"] + " : " + A.lookup[dep[x]]["pos"]
# edges, labels
G.add_edge(str(dep[types[0]]), str(dep[types[1]]), dep=dep["dep"])
edge_labels[(str(dep[types[0]]), str(dep[types[1]]))] = dep["dep"]
if show == True:
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos=pos, labels=node_labels, node_color="white", alpha=.5)
nx.draw_networkx_edge_labels(G, pos=pos, edge_labels=edge_labels)
plt.show()
#########################################
# Dependency / POS parsing functions
#########################################
def _get_connected(edge, idx):
|
def _get_cousin(sibling_idx, dep_type_list, visited_nodes={}):
"""Find a second degree relation within the dependency graph.
Used to find subject in a sentence when the measurement unit is a direct object, for example.
Args:
sibling_idx (str): Token index of the sibling node through which to find the cousin
dep_type_list (list): Allowable dependency types connecting sibling to cousin
Returns:
list: cousin words meeting POS and dependency criteria
"""
words = [] # Visited nodes prevent recursion from bouncing between two "VB" nodes
for dep_type in dep_type_list:
for edge in G.edges(data=True):
cousin_idx = _get_connected(edge, sibling_idx)
allowed_pos = ["NN", "PR"]
if cousin_idx and dep_type in edge[2]['dep'] and any(
x in A.lookup[int(cousin_idx)]['pos'] for x in allowed_pos):
words.append(G.nodes[cousin_idx]['word'])
# Go to second cousin if cousin is a verb
elif cousin_idx and dep_type in edge[2]['dep'] and "VB" in A.lookup[int(cousin_idx)]['pos'] and (
not cousin_idx in visited_nodes or visited_nodes[cousin_idx] < 2):
words.extend(_get_cousin(cousin_idx, ["nsubj", "nsubjpass", "acl"], visited_nodes=visited_nodes))
if cousin_idx:
if cousin_idx in visited_nodes:
visited_nodes[cousin_idx] += 1
else:
visited_nodes[cousin_idx] = 1
return set(words)
def _add_related(related, dep, all_related, index, connector=None):
"""Adds a word (and its metadata) related to a measurement to the list of all related words for that measurement
Args:
related (str): related token/word
dep (str): the dependency type connecting the unit to the related word
all_related (list): existing list of "related" objects to be augmented
index (str): token index of related word
connector (str): if related word is cousin of unit (not sibling) then connecter is word between
Returns:
list: all related words for a given measurement (augmented with new 'related' passed in)
"""
doc = {}
doc["relationForm"] = dep
doc["rawName"] = related
doc["tokenIndex"] = int(index)
doc["offsetStart"] = A.lookup[int(index)]["start"]
doc["offsetEnd"] = A.lookup[int(index)]["end"]
doc["connector"] = "" if connector is None else connector
if not doc in all_related:
all_related.append(doc)
return all_related
def _add_descriptors(related):
"""For related words found for a measurement (usually nouns), add any connected adjectives, compounds, or modifiers.
Args:
related (list): objects containing related words and their metadata
Returns:
list: original list of related objects augmented with additional descriptor words
"""
for r in related:
r["descriptors"] = []
for edge in G.edges(data=True):
sibling_idx = _get_connected(edge, r["tokenIndex"])
if sibling_idx and (A.lookup[int(sibling_idx)]["pos"] == "JJ" or edge[2]["dep"] in ["amod", "compound"]):
r["descriptors"].append(
{
"tokenIndex": sibling_idx,
"rawName": A.lookup[int(sibling_idx)]["word"]
}
)
if sibling_idx and "NN" in A.lookup[int(sibling_idx)]["pos"] and "amod" in edge[2]["dep"]:
additional_related = _get_cousin(sibling_idx, ["nmod"])
for add in set(additional_related):
related = _add_related(add, "nmod", related, A.index_lookup[add],
connector=G.nodes[sibling_idx]['word'])
return related
def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):
""" If measurement is found, runs processed sentence through valid dependency patterns
(from JSON file) to find additional words related to measurements
Args:
dep (str): dependency type present in dependency patterns JSON
dep_obj (dict): object containing accepted POS types and measurement formats for a given dependency type
all_related (list): contains words related to a measurement to be augmented if valid pattern is found
edge (list): Connected node (word) indices and dependency type between
sibling_idx (str): token index of word connected to unit
Returns:
list: related words and metadata
"""
# Check for a matching dependency type
related = []
if edge[2]["dep"] == dep:
# Check for matching POS type(s)
for pos_logic in dep_obj.keys():
connector = None
if isinstance(dep_obj[pos_logic], dict):
for pos in dep_obj[pos_logic].keys():
# Check for allowed part of speech tags in matched dependency patterns
if (pos_logic == "pos_in" and pos in G.nodes[sibling_idx]["pos"]) or (
pos_logic == "pos_equals" and pos == G.nodes[sibling_idx]["pos"]):
pass
elif pos_logic == "pos_not":
if not [False if not_pos == G.nodes[sibling_idx]["pos"] else True for not_pos in
dep_obj.keys()]: continue
else:
continue
# if no additional checks, have a match
if dep_obj[pos_logic][pos] == None or any(
y in dep_obj[pos_logic][pos] for y in [None, "add_sibling"]):
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']])
# if additional checks are required, process further
if dep_obj[pos_logic][pos]:
if "get_cousin" in dep_obj[pos_logic][pos]:
related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos]["get_cousin"]))
connector = G.nodes[sibling_idx]['word']
if "special" in dep_obj[pos_logic][pos]:
if dep == "compound" and pos == "NN":
related = [G.nodes[sibling_idx]['word']]
if None in related:
related.remove(None)
# Allows for getting cousin and returning sibling
if "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == "always":
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
if len(related) > 0 and isinstance(related, list):
for x in related:
if x != None:
all_related = _add_related(x, dep, all_related, A.index_lookup[x],
connector=connector)
elif "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == True:
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
return all_related
def _parse_patterns(unit_idx, measurement_format, patterns_file):
""" Loads depedency patters JSON file and uses "_check_criteria" to look for words related to measurement (connected via unit token)
Args:
unit_idx (list): index or indices of measurement unit token(s)
measurement_format (str): indicates form of measurement value + unit (attached: 10m, space between: 10 m, hyphenated: 10-m)
Returns:
list: related words and metadata
"""
all_related = []
for edge in G.edges(data=True):
for idx in unit_idx:
sibling_idx = _get_connected(edge, idx)
if sibling_idx:
with open(os.path.join(basedir, patterns_file), "r") as tree:
tree = json.load(tree)
for dep in tree["dep"].keys():
if tree["dep"][dep]["enhanced"] == True:
for inner_dep in tree["dep"][dep].keys():
if isinstance(tree["dep"][dep][inner_dep], dict) and measurement_format in \
tree["dep"][dep][inner_dep]["measurement_types"]:
full_dep = dep + ":" + inner_dep
full_dep_obj = tree["dep"][dep][inner_dep]
all_related = _check_criteria(full_dep, full_dep_obj, all_related, edge,
sibling_idx)
elif measurement_format in tree["dep"][dep]["measurement_types"]:
all_related = _check_criteria(dep, tree["dep"][dep], all_related, edge, sibling_idx)
for x in range(0, len(tree["word"]["or"])):
if G.nodes[sibling_idx]["word"] == tree["word"]["or"][x]:
related = _get_cousin(sibling_idx, ["nsubj"])
for r in related:
all_related = _add_related(r, "operator", all_related, A.index_lookup[r])
all_related = _add_descriptors(all_related)
return all_related
def _get_related(stats, match, patterns_file):
""" Calls _parse_patterns() to get words related to a measurement and provides de-duplication between related words and grobid response
Args:
stats (Stats object): Global object used to track parsing behaviors
match (dict): information on measurements and units extracted by Grobid
Returns:
list: related words and metadata
"""
all_related = None
measurement_formats = ["space_between", "attached", "hyphenated"]
all_related = _parse_patterns(match["unit_idx"], match["measurement_format"], patterns_file)
if all_related == None:
all_related = _parse_patterns(match["unit_idx"], ["uncertain"], patterns_file)
# get words like approximately
num_adverbs = _parse_patterns([match["num_idx"]], match["measurement_format"], patterns_file)
unit_adverbs = _parse_patterns([match["unit_idx"]], match["measurement_format"], patterns_file)
adverbs = num_adverbs + unit_adverbs
for_removal = []
for a in adverbs:
if a["relationForm"] != "advmod":
for_removal.append(a)
else:
[a.pop(key, None) for key in ["descriptors", "connector"]] # not relevant for adverbs
[adverbs.remove(a) for a in for_removal]
if adverbs:
match["grobid"]["adverbs"] = adverbs
# Check to make sure related isn't already a number, unit, or quantified thing identified by Grobid
potential_keys = ["quantity", "quantityLeast", "quantityMost", "quantified"]
if all_related:
for key in potential_keys:
for related in all_related:
if key in match["grobid"]:
num, unit, quantified = "", "", ""
if "rawValue" in match["grobid"][key]: num = match["grobid"][key]["rawValue"]
if "rawUnit" in match["grobid"][key]: unit = match["grobid"][key]["rawUnit"]["name"]
if "normalizedName" in match["grobid"][key]: quantified = match["grobid"][key]["normalizedName"]
if related["rawName"] in [num, unit, quantified] or related["rawName"] == num + unit or (
quantified in related["rawName"] and not quantified == ""):
all_related.remove(related)
if related["rawName"] == unit:
for k in related.keys():
if not k in match["grobid"][key]["rawUnit"]:
match["grobid"][key]["rawUnit"][k] = related[k]
elif related["rawName"] == quantified:
for k in related.keys():
if not k in match["grobid"][key]:
match["grobid"][key][k] = related[k]
return all_related
def _simplify_results(match):
"""WORK IN PROGRESS: Prune metadata from extracted measurements and related words for more readable output
Args:
match (dict): Object contatining all metadata about extraction types, locations, relationships within sentence
Returns:
list: contains 4 items, extracted numeric value or range (list), unit(s) (list), qunatified words identified by Grobid (str), related words (str)
"""
keys = []
simplified = {}
simplified["value"] = []
if match["type"] == "value":
keys = ["quantity"]
elif match["type"] == "interval":
keys = ["quantityLeast", "quantityMost"]
for key in keys:
if key in match:
if "parsedValue" in match[key]:
simplified["value"].append(match[key]["parsedValue"])
elif "rawValue" in match[key]:
simplified["value"].append(match[key]["rawValue"])
else:
return None
simplified["unit"] = match[key]["rawUnit"]["name"] if "rawUnit" in match[key] else ""
if len(simplified["value"]) == 1:
simplified["value"] = simplified["value"][0]
simplified["quantified"] = {}
simplified["related"] = {}
if "quantified" in match:
if simplified["unit"] == "":
simplified["unit"] = match["quantified"]["normalizedName"]
simplified["quantified"][match["quantified"]["normalizedName"]] = []
if "descriptors" in match["quantified"]:
match["quantified"]["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for x in match["quantified"]["descriptors"]:
simplified["quantified"][match["quantified"]["normalizedName"]].append(x["rawName"])
if match["related"]:
for r in match["related"]:
simplified["related"][r["rawName"]] = []
if "descriptors" in r:
r["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for z in r["descriptors"]:
simplified["related"][r["rawName"]].append(z["rawName"])
return simplified
def _reconstruct_sent(parsed_sentence):
"""Reconstruct sentence from CoreNLP tokens - raw sentence text isn't retained by CoreNLP after sentence splitting and processing
Args:
parsed_sentence (dict): Object containing CoreNLP output
Returns:
str: original sentence
"""
sent = ""
for x in range(0, len(parsed_sentence["tokens"])):
sent += parsed_sentence["tokens"][x]['originalText']
if x + 1 != len(parsed_sentence["tokens"]):
# Use character indices from tokens to ensure correct spacing when reconstructing
num_spaces = parsed_sentence["tokens"][x + 1]["characterOffsetBegin"] - parsed_sentence["tokens"][x][
"characterOffsetEnd"]
for y in range(0, num_spaces):
sent += " "
return sent
def _sorted_dictionary(orig_dict, sort_list):
od = OrderedDict()
for item in sort_list:
if item in orig_dict:
od[item] = orig_dict[item]
return od
#########################################
# Top-Level function
#########################################
def extract(content, corenlp_endpoint, grobid_endpoint, dependency_patterns_file, output_file=None, show_graph=False,
pretty=False, simplify=False):
""" Top-level user interface to parsing measurements and related words
Args:
content (str): sentence or paragraph to be parsed (shouldn't be much larger)
corenlp_endpoint (str): host + port of CoreNLP service (e.g. "http://localhost:9000")
grobid_endpoint (str): host + port of grobid service (e.g. "http://localhost:8080")
dependency_patterns (str): filepath to dependency patterns JSON file
output_file (optional: str): file to write output to
show_graph (bool): Will show network visualization of sentence dependencies if True
pretty (bool): JSON output will be pretty printed if True, else one JSON doc per line (JSONL)
simplify (bool): If True provides bare bones output with only extractions and not metadata about indices, types, etc.
Returns:
List of objects: containing parsed measurement info
(optionally write to file)
"""
all_extractions = []
out = None
if output_file:
out = codecs.open(output_file, "a", encoding="utf-8")
if len(content) < 5:
return None
nlp = StanfordCoreNLP(corenlp_endpoint)
output = nlp.annotate(content, properties={'outputFormat': 'json', 'timeout': '9999'})
if isinstance(output, str): # str supports both python 2 and 3
output = json.loads(output.encode("latin-1"), strict=False)
if "sentences" in output and isinstance(output["sentences"], list):
for i in range(0, len(output["sentences"])):
s_str = _reconstruct_sent(output["sentences"][i])
# Enhanced dependencies have different key names in JSON depending on version of CoreNLP
possible_keys = [
"enhanced-plus-plus-dependencies-annotation",
"enhancedPlusPlusDependencies"
]
dep_key = "collapsed-ccprocessed-dependencies" # default key
if "collapsed-ccprocessed-dependencies" not in output["sentences"][i]:
for k in possible_keys:
if k in output["sentences"][i]:
dep_key = k
global A
A = Annotations(output["sentences"][i]["tokens"], output["sentences"][i][dep_key])
if A.check_output(output["sentences"][i], stats) is True:
stats.total_sentences += 1
G = _build_graph(show=show_graph)
grobid_response = grobid_quantities(s_str, A, grobid_endpoint)
if isinstance(grobid_response, dict) and "measurements" in grobid_response:
for quantity in grobid_response["measurements"]:
A.augment_match(quantity)
stats.total_measurements += len(A.matches)
for idx, match in enumerate(A.matches):
global Num
Num = match["num"]
match["sentence"] = i + 1
match["grobid"]["related"] = _get_related(stats, match, dependency_patterns_file)
# Remove fields used for processing but not to be shown to user
remove = ["adverbs", "num", "unit", "connector", "form", "sentence", "num_idx", "unit_idx",
"measurement_format"]
[match.pop(x, None) for x in remove]
sort_order = ['adverbs', 'type', 'quantity', 'quantityLeast', 'quantityMost', 'quantified',
'related']
match_ordered = _sorted_dictionary(match["grobid"], sort_order)
if simplify:
simplified_sort_order = ['value', 'unit', 'quantified', 'related']
simplified = _simplify_results(match_ordered)
if simplified:
match_ordered = _sorted_dictionary(match["grobid"], simplified_sort_order)
if pretty and not simplify:
if out:
out.write(json.dumps(match_ordered, ensure_ascii=False, indent=4))
if idx != len(A.matches) - 1 and out:
out.write(",\n")
elif out:
out.write(json.dumps(match_ordered, ensure_ascii=False) + "\n")
all_extractions.extend(A.matches)
else:
logging.warning("CoreNLP parsing failed for sentence: %s" % (s_str))
else:
logging.warning("CoreNLP parsing failed for content: %s" % (content))
if out:
out.close()
logging.info("Total sentences parsed: %s" % (str(stats.total_sentences)))
logging.info("Total measurements found: %s" % (str(stats.total_measurements)))
stats.print_summary()
return all_extractions
def grobid_quantities(sentence, a, endpoint):
"""
a = annotations
"""
"""Pass sentence text to Grobid server on port 8080 for measurement parsing
Args:
sentence (str): Sentence to be parsed
a (Annotations object): object containing relevant CoreNLP output
Returns:
dict: object containing Grobid output
"""
# $ needs to be escaped when passed via subprocess
sentence = re.sub("\$", "\\$", sentence)
sentence = re.sub("\"", '\\"', sentence)
sentence = re.sub("%", '%25', sentence)
sentence = re.sub("`", "'", sentence)
sentence = re.sub("'", '\\"', sentence)
if endpoint[len(endpoint) - 1:] == "/":
endpoint = endpoint[:len(endpoint) - 1]
response = None
# try:
response = QuantitiesClient(endpoint).process_text(sentence)
if response[0] != 200:
print('No Grobid response for: %s' % sentence)
logging.warning('No Grobid response for: %s' % sentence)
return ""
quantities = response[1]
# Add token index for num, unit, quantified if available
if isinstance(quantities, dict):
if "measurements" in quantities.keys():
for q in quantities["measurements"]:
key = ""
if q["type"] == "value":
key = "quantity"
# if Grobid doesn't parse interval correctly, sometimes only 'QuantityLeast' or 'QuantityMost' is available
if q["type"] == "interval":
if "quantityLeast" in q:
key = "quantityLeast"
elif "QuantityMost" in q:
key = "quantityMost"
else:
return {}
if q["type"] == "listc":
return {}
if key == "":
logging.error('Unknown Grobid key resulting from parse of: %s' % sentence)
print("Unknown Grobid key resulting from parse of: %s" % sentence)
# Grobid doesn't pick up negatives
if sentence[sentence.find(q[key]["rawValue"]) - 1] == "-":
q[key]["parsedValue"] = float("-" + str(q[key]["parsedValue"]))
q[key]["rawValue"] = "-" + str(q[key]["rawValue"])
q[key]["offsetStart"] -= 1
if q[key]["offsetStart"] in a.tok_start:
q[key]["tokenIndex"] = a.tok_start[q[key]["offsetStart"]]
else:
print("Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
logging.error(
"Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
return {}
if "rawUnit" in q[key]:
q[key]["rawUnit"]["after"] = a.lookup[q[key]["tokenIndex"]]["after"]
q[key]["rawUnit"]["tokenIndices"] = []
if q[key]["rawUnit"]["offsetStart"] in a.tok_start:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_start[q[key]["rawUnit"]["offsetStart"]]))
if q[key]["rawUnit"]["offsetEnd"] in a.tok_end:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_end[q[key]["rawUnit"]["offsetEnd"]]))
if q[key]["rawUnit"]["offsetStart"] == q[key]["offsetEnd"]:
q[key]["rawUnit"]["tokenIndices"].append(str(q[key]["tokenIndex"]))
q[key]["rawUnit"]["tokenIndices"] = list(set(q[key]["rawUnit"]["tokenIndices"]))
if "quantified" in q:
# often times Grobid with return a phrase where normalized name is in middle. In this case, "offsetStart" identifies the wrong token
add_to_offset = 0
normalized_idx, words = None, None
if " " in q["quantified"]["rawName"]:
words = q["quantified"]["rawName"].split(" ")
for i, w in enumerate(words):
if not q["quantified"]["normalizedName"] in w:
add_to_offset += (len(w) + 1) # +1 for space that was split on
else:
break
q["quantified"]["offsetStart"] += add_to_offset
if q["quantified"]["offsetStart"] in a.tok_start:
q["quantified"]["tokenIndex"] = a.tok_start[q["quantified"]["offsetStart"]]
else:
logging.warning(
"Not finding token index for Grobid quantified word in CoreNLP output. Sentence: %s" % (
sentence))
# hyphen causing issue - Grobid doesn't treat hyphenated clause as one word
# example error sentence: "Macroscopic examination of the CNS revealed micrencephaly with a whole-brain weight of 84 grams."
return quantities
| """If an edge connects to a node (word), return the index of the node
Args:
edge (tuple): Contains token indices of two connect words and the dependency type between them - e.g. ('11', '14', {'dep': 'nmod:at'})
idx (int): Token index of word
Returns:
str or None: str if connected word is found in provided edge, None if not
"""
if str(edge[0]) == str(idx) and A.lookup[int(edge[1])]["word"] != Num:
return edge[1]
elif str(edge[1]) == str(idx) and A.lookup[int(edge[0])]["word"] != Num:
return edge[0] | identifier_body |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import networkx as nx
import os
import codecs
from pycorenlp import StanfordCoreNLP
import matplotlib.pyplot as plt
import re
import operator
import json
from collections import OrderedDict
import logging
# custom
from classes import Stats, Annotations
from grobid_quantities.quantities import QuantitiesClient
##################################################################################
# Globals
##################################################################################
basedir = os.path.abspath(os.path.dirname(__file__))
stats = Stats()
A = None # global annotations object
Num = None # global sentence object
G = None # global dependency tree object
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)-8s %(message)s',
datefmt='%a, %d %b %Y %H:%M:%S',
filename=os.path.join(basedir, 'measurement.log'))
##################################################################################
def _build_graph(show=False):
"""Load word dependencies into graph using networkx. Enables easy traversal of dependencies for parsing particular patterns.
One graph is created for each sentence.
Args:
show (bool): If set to True, labeled visualization of network will be opened via matplotlib for each sentence
Returns:
None: Global variable G is set from within function
"""
global G
G = nx.Graph()
node_labels, edge_labels = {}, {}
for idx, dep in enumerate(A.deps):
types = ["dependent", "governor"]
# nodes, labels
for x in types:
G.add_node(str(dep[x]), word=dep[x + "Gloss"], pos=A.lookup[dep[x]]["pos"])
node_labels[str(dep[x])] = dep[x + "Gloss"] + " : " + A.lookup[dep[x]]["pos"]
# edges, labels
G.add_edge(str(dep[types[0]]), str(dep[types[1]]), dep=dep["dep"])
edge_labels[(str(dep[types[0]]), str(dep[types[1]]))] = dep["dep"]
if show == True:
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos=pos, labels=node_labels, node_color="white", alpha=.5)
nx.draw_networkx_edge_labels(G, pos=pos, edge_labels=edge_labels)
plt.show()
#########################################
# Dependency / POS parsing functions
#########################################
def _get_connected(edge, idx):
"""If an edge connects to a node (word), return the index of the node
Args:
edge (tuple): Contains token indices of two connect words and the dependency type between them - e.g. ('11', '14', {'dep': 'nmod:at'})
idx (int): Token index of word
Returns:
str or None: str if connected word is found in provided edge, None if not
"""
if str(edge[0]) == str(idx) and A.lookup[int(edge[1])]["word"] != Num:
return edge[1]
elif str(edge[1]) == str(idx) and A.lookup[int(edge[0])]["word"] != Num:
return edge[0]
def _get_cousin(sibling_idx, dep_type_list, visited_nodes={}):
"""Find a second degree relation within the dependency graph.
Used to find subject in a sentence when the measurement unit is a direct object, for example.
Args:
sibling_idx (str): Token index of the sibling node through which to find the cousin
dep_type_list (list): Allowable dependency types connecting sibling to cousin
Returns:
list: cousin words meeting POS and dependency criteria
"""
words = [] # Visited nodes prevent recursion from bouncing between two "VB" nodes
for dep_type in dep_type_list:
for edge in G.edges(data=True):
cousin_idx = _get_connected(edge, sibling_idx)
allowed_pos = ["NN", "PR"]
if cousin_idx and dep_type in edge[2]['dep'] and any(
x in A.lookup[int(cousin_idx)]['pos'] for x in allowed_pos):
words.append(G.nodes[cousin_idx]['word'])
# Go to second cousin if cousin is a verb
elif cousin_idx and dep_type in edge[2]['dep'] and "VB" in A.lookup[int(cousin_idx)]['pos'] and (
not cousin_idx in visited_nodes or visited_nodes[cousin_idx] < 2):
words.extend(_get_cousin(cousin_idx, ["nsubj", "nsubjpass", "acl"], visited_nodes=visited_nodes))
if cousin_idx:
if cousin_idx in visited_nodes:
visited_nodes[cousin_idx] += 1
else:
visited_nodes[cousin_idx] = 1
return set(words)
def _add_related(related, dep, all_related, index, connector=None):
"""Adds a word (and its metadata) related to a measurement to the list of all related words for that measurement
Args:
related (str): related token/word
dep (str): the dependency type connecting the unit to the related word
all_related (list): existing list of "related" objects to be augmented
index (str): token index of related word
connector (str): if related word is cousin of unit (not sibling) then connecter is word between
Returns:
list: all related words for a given measurement (augmented with new 'related' passed in)
"""
doc = {}
doc["relationForm"] = dep
doc["rawName"] = related
doc["tokenIndex"] = int(index)
doc["offsetStart"] = A.lookup[int(index)]["start"]
doc["offsetEnd"] = A.lookup[int(index)]["end"]
doc["connector"] = "" if connector is None else connector
if not doc in all_related:
all_related.append(doc)
return all_related
def _add_descriptors(related):
"""For related words found for a measurement (usually nouns), add any connected adjectives, compounds, or modifiers.
Args:
related (list): objects containing related words and their metadata
Returns:
list: original list of related objects augmented with additional descriptor words
"""
for r in related:
r["descriptors"] = []
for edge in G.edges(data=True):
sibling_idx = _get_connected(edge, r["tokenIndex"])
if sibling_idx and (A.lookup[int(sibling_idx)]["pos"] == "JJ" or edge[2]["dep"] in ["amod", "compound"]):
r["descriptors"].append(
{
"tokenIndex": sibling_idx,
"rawName": A.lookup[int(sibling_idx)]["word"]
}
)
if sibling_idx and "NN" in A.lookup[int(sibling_idx)]["pos"] and "amod" in edge[2]["dep"]:
additional_related = _get_cousin(sibling_idx, ["nmod"])
for add in set(additional_related):
related = _add_related(add, "nmod", related, A.index_lookup[add],
connector=G.nodes[sibling_idx]['word'])
return related
def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):
""" If measurement is found, runs processed sentence through valid dependency patterns
(from JSON file) to find additional words related to measurements
Args:
dep (str): dependency type present in dependency patterns JSON
dep_obj (dict): object containing accepted POS types and measurement formats for a given dependency type
all_related (list): contains words related to a measurement to be augmented if valid pattern is found
edge (list): Connected node (word) indices and dependency type between
sibling_idx (str): token index of word connected to unit
Returns:
list: related words and metadata
"""
# Check for a matching dependency type
related = []
if edge[2]["dep"] == dep:
# Check for matching POS type(s)
for pos_logic in dep_obj.keys():
connector = None
if isinstance(dep_obj[pos_logic], dict):
for pos in dep_obj[pos_logic].keys():
# Check for allowed part of speech tags in matched dependency patterns
if (pos_logic == "pos_in" and pos in G.nodes[sibling_idx]["pos"]) or (
pos_logic == "pos_equals" and pos == G.nodes[sibling_idx]["pos"]):
pass
elif pos_logic == "pos_not":
if not [False if not_pos == G.nodes[sibling_idx]["pos"] else True for not_pos in
dep_obj.keys()]: continue
else:
continue
# if no additional checks, have a match
if dep_obj[pos_logic][pos] == None or any(
y in dep_obj[pos_logic][pos] for y in [None, "add_sibling"]):
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']])
# if additional checks are required, process further
if dep_obj[pos_logic][pos]:
if "get_cousin" in dep_obj[pos_logic][pos]:
related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos]["get_cousin"]))
connector = G.nodes[sibling_idx]['word']
if "special" in dep_obj[pos_logic][pos]:
if dep == "compound" and pos == "NN":
related = [G.nodes[sibling_idx]['word']]
if None in related:
related.remove(None)
# Allows for getting cousin and returning sibling
if "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == "always":
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
if len(related) > 0 and isinstance(related, list):
for x in related:
if x != None:
all_related = _add_related(x, dep, all_related, A.index_lookup[x],
connector=connector)
elif "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == True:
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
return all_related
def _parse_patterns(unit_idx, measurement_format, patterns_file):
""" Loads depedency patters JSON file and uses "_check_criteria" to look for words related to measurement (connected via unit token)
Args:
unit_idx (list): index or indices of measurement unit token(s)
measurement_format (str): indicates form of measurement value + unit (attached: 10m, space between: 10 m, hyphenated: 10-m)
Returns:
list: related words and metadata
"""
all_related = []
for edge in G.edges(data=True):
for idx in unit_idx:
sibling_idx = _get_connected(edge, idx)
if sibling_idx:
with open(os.path.join(basedir, patterns_file), "r") as tree:
tree = json.load(tree)
for dep in tree["dep"].keys():
if tree["dep"][dep]["enhanced"] == True:
for inner_dep in tree["dep"][dep].keys():
if isinstance(tree["dep"][dep][inner_dep], dict) and measurement_format in \
tree["dep"][dep][inner_dep]["measurement_types"]:
full_dep = dep + ":" + inner_dep
full_dep_obj = tree["dep"][dep][inner_dep]
all_related = _check_criteria(full_dep, full_dep_obj, all_related, edge,
sibling_idx)
elif measurement_format in tree["dep"][dep]["measurement_types"]:
all_related = _check_criteria(dep, tree["dep"][dep], all_related, edge, sibling_idx)
for x in range(0, len(tree["word"]["or"])):
if G.nodes[sibling_idx]["word"] == tree["word"]["or"][x]:
related = _get_cousin(sibling_idx, ["nsubj"])
for r in related:
all_related = _add_related(r, "operator", all_related, A.index_lookup[r])
all_related = _add_descriptors(all_related)
return all_related
def _get_related(stats, match, patterns_file):
""" Calls _parse_patterns() to get words related to a measurement and provides de-duplication between related words and grobid response
Args:
stats (Stats object): Global object used to track parsing behaviors
match (dict): information on measurements and units extracted by Grobid
Returns:
list: related words and metadata
"""
all_related = None
measurement_formats = ["space_between", "attached", "hyphenated"]
all_related = _parse_patterns(match["unit_idx"], match["measurement_format"], patterns_file)
if all_related == None:
all_related = _parse_patterns(match["unit_idx"], ["uncertain"], patterns_file)
# get words like approximately
num_adverbs = _parse_patterns([match["num_idx"]], match["measurement_format"], patterns_file)
unit_adverbs = _parse_patterns([match["unit_idx"]], match["measurement_format"], patterns_file)
adverbs = num_adverbs + unit_adverbs
for_removal = []
for a in adverbs:
if a["relationForm"] != "advmod":
for_removal.append(a)
else:
[a.pop(key, None) for key in ["descriptors", "connector"]] # not relevant for adverbs
[adverbs.remove(a) for a in for_removal]
if adverbs:
match["grobid"]["adverbs"] = adverbs
# Check to make sure related isn't already a number, unit, or quantified thing identified by Grobid
potential_keys = ["quantity", "quantityLeast", "quantityMost", "quantified"]
if all_related:
for key in potential_keys:
for related in all_related:
if key in match["grobid"]:
num, unit, quantified = "", "", ""
if "rawValue" in match["grobid"][key]: num = match["grobid"][key]["rawValue"]
if "rawUnit" in match["grobid"][key]: unit = match["grobid"][key]["rawUnit"]["name"]
if "normalizedName" in match["grobid"][key]: quantified = match["grobid"][key]["normalizedName"]
if related["rawName"] in [num, unit, quantified] or related["rawName"] == num + unit or (
quantified in related["rawName"] and not quantified == ""):
all_related.remove(related)
if related["rawName"] == unit:
for k in related.keys():
if not k in match["grobid"][key]["rawUnit"]:
match["grobid"][key]["rawUnit"][k] = related[k]
elif related["rawName"] == quantified:
for k in related.keys():
if not k in match["grobid"][key]:
match["grobid"][key][k] = related[k]
return all_related
def _simplify_results(match):
"""WORK IN PROGRESS: Prune metadata from extracted measurements and related words for more readable output
Args:
match (dict): Object contatining all metadata about extraction types, locations, relationships within sentence
Returns:
list: contains 4 items, extracted numeric value or range (list), unit(s) (list), qunatified words identified by Grobid (str), related words (str)
"""
keys = []
simplified = {}
simplified["value"] = []
if match["type"] == "value":
keys = ["quantity"]
elif match["type"] == "interval":
keys = ["quantityLeast", "quantityMost"]
for key in keys:
if key in match:
if "parsedValue" in match[key]:
simplified["value"].append(match[key]["parsedValue"])
elif "rawValue" in match[key]:
simplified["value"].append(match[key]["rawValue"])
else:
return None
simplified["unit"] = match[key]["rawUnit"]["name"] if "rawUnit" in match[key] else ""
if len(simplified["value"]) == 1:
simplified["value"] = simplified["value"][0]
simplified["quantified"] = {}
simplified["related"] = {}
if "quantified" in match:
if simplified["unit"] == "":
simplified["unit"] = match["quantified"]["normalizedName"]
simplified["quantified"][match["quantified"]["normalizedName"]] = []
if "descriptors" in match["quantified"]:
match["quantified"]["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for x in match["quantified"]["descriptors"]:
simplified["quantified"][match["quantified"]["normalizedName"]].append(x["rawName"])
if match["related"]:
for r in match["related"]:
simplified["related"][r["rawName"]] = []
if "descriptors" in r:
r["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for z in r["descriptors"]:
simplified["related"][r["rawName"]].append(z["rawName"])
return simplified
def _reconstruct_sent(parsed_sentence):
"""Reconstruct sentence from CoreNLP tokens - raw sentence text isn't retained by CoreNLP after sentence splitting and processing
Args:
parsed_sentence (dict): Object containing CoreNLP output
Returns:
str: original sentence
"""
sent = ""
for x in range(0, len(parsed_sentence["tokens"])):
sent += parsed_sentence["tokens"][x]['originalText']
if x + 1 != len(parsed_sentence["tokens"]):
# Use character indices from tokens to ensure correct spacing when reconstructing
num_spaces = parsed_sentence["tokens"][x + 1]["characterOffsetBegin"] - parsed_sentence["tokens"][x][
"characterOffsetEnd"]
for y in range(0, num_spaces):
sent += " "
return sent
def _sorted_dictionary(orig_dict, sort_list):
od = OrderedDict()
for item in sort_list:
if item in orig_dict:
od[item] = orig_dict[item]
return od
#########################################
# Top-Level function
#########################################
def extract(content, corenlp_endpoint, grobid_endpoint, dependency_patterns_file, output_file=None, show_graph=False,
pretty=False, simplify=False):
""" Top-level user interface to parsing measurements and related words
Args:
content (str): sentence or paragraph to be parsed (shouldn't be much larger)
corenlp_endpoint (str): host + port of CoreNLP service (e.g. "http://localhost:9000")
grobid_endpoint (str): host + port of grobid service (e.g. "http://localhost:8080")
dependency_patterns (str): filepath to dependency patterns JSON file
output_file (optional: str): file to write output to
show_graph (bool): Will show network visualization of sentence dependencies if True
pretty (bool): JSON output will be pretty printed if True, else one JSON doc per line (JSONL)
simplify (bool): If True provides bare bones output with only extractions and not metadata about indices, types, etc.
Returns:
List of objects: containing parsed measurement info
(optionally write to file)
"""
all_extractions = []
out = None
if output_file:
out = codecs.open(output_file, "a", encoding="utf-8")
if len(content) < 5:
return None
nlp = StanfordCoreNLP(corenlp_endpoint)
output = nlp.annotate(content, properties={'outputFormat': 'json', 'timeout': '9999'})
if isinstance(output, str): # str supports both python 2 and 3
output = json.loads(output.encode("latin-1"), strict=False)
if "sentences" in output and isinstance(output["sentences"], list):
for i in range(0, len(output["sentences"])):
s_str = _reconstruct_sent(output["sentences"][i])
# Enhanced dependencies have different key names in JSON depending on version of CoreNLP
possible_keys = [
"enhanced-plus-plus-dependencies-annotation",
"enhancedPlusPlusDependencies"
]
dep_key = "collapsed-ccprocessed-dependencies" # default key
if "collapsed-ccprocessed-dependencies" not in output["sentences"][i]:
for k in possible_keys:
if k in output["sentences"][i]:
dep_key = k
global A
A = Annotations(output["sentences"][i]["tokens"], output["sentences"][i][dep_key])
if A.check_output(output["sentences"][i], stats) is True:
stats.total_sentences += 1
G = _build_graph(show=show_graph)
grobid_response = grobid_quantities(s_str, A, grobid_endpoint)
if isinstance(grobid_response, dict) and "measurements" in grobid_response:
for quantity in grobid_response["measurements"]:
A.augment_match(quantity)
stats.total_measurements += len(A.matches)
for idx, match in enumerate(A.matches):
global Num
Num = match["num"]
match["sentence"] = i + 1
match["grobid"]["related"] = _get_related(stats, match, dependency_patterns_file)
# Remove fields used for processing but not to be shown to user
remove = ["adverbs", "num", "unit", "connector", "form", "sentence", "num_idx", "unit_idx",
"measurement_format"]
[match.pop(x, None) for x in remove]
sort_order = ['adverbs', 'type', 'quantity', 'quantityLeast', 'quantityMost', 'quantified',
'related']
match_ordered = _sorted_dictionary(match["grobid"], sort_order)
if simplify:
simplified_sort_order = ['value', 'unit', 'quantified', 'related']
simplified = _simplify_results(match_ordered)
if simplified:
match_ordered = _sorted_dictionary(match["grobid"], simplified_sort_order)
if pretty and not simplify:
if out:
out.write(json.dumps(match_ordered, ensure_ascii=False, indent=4))
if idx != len(A.matches) - 1 and out:
out.write(",\n")
elif out:
out.write(json.dumps(match_ordered, ensure_ascii=False) + "\n")
all_extractions.extend(A.matches)
else:
logging.warning("CoreNLP parsing failed for sentence: %s" % (s_str))
else:
logging.warning("CoreNLP parsing failed for content: %s" % (content))
if out:
out.close()
logging.info("Total sentences parsed: %s" % (str(stats.total_sentences)))
logging.info("Total measurements found: %s" % (str(stats.total_measurements)))
stats.print_summary()
return all_extractions
def grobid_quantities(sentence, a, endpoint):
"""
a = annotations
"""
"""Pass sentence text to Grobid server on port 8080 for measurement parsing
Args:
sentence (str): Sentence to be parsed
a (Annotations object): object containing relevant CoreNLP output
Returns:
dict: object containing Grobid output
"""
# $ needs to be escaped when passed via subprocess
sentence = re.sub("\$", "\\$", sentence)
sentence = re.sub("\"", '\\"', sentence)
sentence = re.sub("%", '%25', sentence)
sentence = re.sub("`", "'", sentence)
sentence = re.sub("'", '\\"', sentence)
if endpoint[len(endpoint) - 1:] == "/":
endpoint = endpoint[:len(endpoint) - 1]
response = None
# try:
response = QuantitiesClient(endpoint).process_text(sentence)
if response[0] != 200:
print('No Grobid response for: %s' % sentence)
logging.warning('No Grobid response for: %s' % sentence)
return ""
quantities = response[1]
# Add token index for num, unit, quantified if available
if isinstance(quantities, dict):
if "measurements" in quantities.keys():
for q in quantities["measurements"]:
key = ""
if q["type"] == "value":
key = "quantity"
# if Grobid doesn't parse interval correctly, sometimes only 'QuantityLeast' or 'QuantityMost' is available
if q["type"] == "interval":
if "quantityLeast" in q:
key = "quantityLeast"
elif "QuantityMost" in q:
key = "quantityMost"
else:
return {}
if q["type"] == "listc":
return {}
if key == "":
logging.error('Unknown Grobid key resulting from parse of: %s' % sentence)
print("Unknown Grobid key resulting from parse of: %s" % sentence)
# Grobid doesn't pick up negatives
if sentence[sentence.find(q[key]["rawValue"]) - 1] == "-":
q[key]["parsedValue"] = float("-" + str(q[key]["parsedValue"]))
q[key]["rawValue"] = "-" + str(q[key]["rawValue"])
q[key]["offsetStart"] -= 1
if q[key]["offsetStart"] in a.tok_start:
q[key]["tokenIndex"] = a.tok_start[q[key]["offsetStart"]]
else:
print("Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
logging.error( | "Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
return {}
if "rawUnit" in q[key]:
q[key]["rawUnit"]["after"] = a.lookup[q[key]["tokenIndex"]]["after"]
q[key]["rawUnit"]["tokenIndices"] = []
if q[key]["rawUnit"]["offsetStart"] in a.tok_start:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_start[q[key]["rawUnit"]["offsetStart"]]))
if q[key]["rawUnit"]["offsetEnd"] in a.tok_end:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_end[q[key]["rawUnit"]["offsetEnd"]]))
if q[key]["rawUnit"]["offsetStart"] == q[key]["offsetEnd"]:
q[key]["rawUnit"]["tokenIndices"].append(str(q[key]["tokenIndex"]))
q[key]["rawUnit"]["tokenIndices"] = list(set(q[key]["rawUnit"]["tokenIndices"]))
if "quantified" in q:
# often times Grobid with return a phrase where normalized name is in middle. In this case, "offsetStart" identifies the wrong token
add_to_offset = 0
normalized_idx, words = None, None
if " " in q["quantified"]["rawName"]:
words = q["quantified"]["rawName"].split(" ")
for i, w in enumerate(words):
if not q["quantified"]["normalizedName"] in w:
add_to_offset += (len(w) + 1) # +1 for space that was split on
else:
break
q["quantified"]["offsetStart"] += add_to_offset
if q["quantified"]["offsetStart"] in a.tok_start:
q["quantified"]["tokenIndex"] = a.tok_start[q["quantified"]["offsetStart"]]
else:
logging.warning(
"Not finding token index for Grobid quantified word in CoreNLP output. Sentence: %s" % (
sentence))
# hyphen causing issue - Grobid doesn't treat hyphenated clause as one word
# example error sentence: "Macroscopic examination of the CNS revealed micrencephaly with a whole-brain weight of 84 grams."
return quantities | random_line_split | |
Measurements.py | #!/usr/bin/env python
# encoding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import networkx as nx
import os
import codecs
from pycorenlp import StanfordCoreNLP
import matplotlib.pyplot as plt
import re
import operator
import json
from collections import OrderedDict
import logging
# custom
from classes import Stats, Annotations
from grobid_quantities.quantities import QuantitiesClient
##################################################################################
# Globals
##################################################################################
basedir = os.path.abspath(os.path.dirname(__file__))
stats = Stats()
A = None # global annotations object
Num = None # global sentence object
G = None # global dependency tree object
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)-8s %(message)s',
datefmt='%a, %d %b %Y %H:%M:%S',
filename=os.path.join(basedir, 'measurement.log'))
##################################################################################
def _build_graph(show=False):
"""Load word dependencies into graph using networkx. Enables easy traversal of dependencies for parsing particular patterns.
One graph is created for each sentence.
Args:
show (bool): If set to True, labeled visualization of network will be opened via matplotlib for each sentence
Returns:
None: Global variable G is set from within function
"""
global G
G = nx.Graph()
node_labels, edge_labels = {}, {}
for idx, dep in enumerate(A.deps):
types = ["dependent", "governor"]
# nodes, labels
for x in types:
G.add_node(str(dep[x]), word=dep[x + "Gloss"], pos=A.lookup[dep[x]]["pos"])
node_labels[str(dep[x])] = dep[x + "Gloss"] + " : " + A.lookup[dep[x]]["pos"]
# edges, labels
G.add_edge(str(dep[types[0]]), str(dep[types[1]]), dep=dep["dep"])
edge_labels[(str(dep[types[0]]), str(dep[types[1]]))] = dep["dep"]
if show == True:
pos = nx.spring_layout(G)
nx.draw_networkx(G, pos=pos, labels=node_labels, node_color="white", alpha=.5)
nx.draw_networkx_edge_labels(G, pos=pos, edge_labels=edge_labels)
plt.show()
#########################################
# Dependency / POS parsing functions
#########################################
def _get_connected(edge, idx):
"""If an edge connects to a node (word), return the index of the node
Args:
edge (tuple): Contains token indices of two connect words and the dependency type between them - e.g. ('11', '14', {'dep': 'nmod:at'})
idx (int): Token index of word
Returns:
str or None: str if connected word is found in provided edge, None if not
"""
if str(edge[0]) == str(idx) and A.lookup[int(edge[1])]["word"] != Num:
return edge[1]
elif str(edge[1]) == str(idx) and A.lookup[int(edge[0])]["word"] != Num:
return edge[0]
def _get_cousin(sibling_idx, dep_type_list, visited_nodes={}):
"""Find a second degree relation within the dependency graph.
Used to find subject in a sentence when the measurement unit is a direct object, for example.
Args:
sibling_idx (str): Token index of the sibling node through which to find the cousin
dep_type_list (list): Allowable dependency types connecting sibling to cousin
Returns:
list: cousin words meeting POS and dependency criteria
"""
words = [] # Visited nodes prevent recursion from bouncing between two "VB" nodes
for dep_type in dep_type_list:
for edge in G.edges(data=True):
cousin_idx = _get_connected(edge, sibling_idx)
allowed_pos = ["NN", "PR"]
if cousin_idx and dep_type in edge[2]['dep'] and any(
x in A.lookup[int(cousin_idx)]['pos'] for x in allowed_pos):
words.append(G.nodes[cousin_idx]['word'])
# Go to second cousin if cousin is a verb
elif cousin_idx and dep_type in edge[2]['dep'] and "VB" in A.lookup[int(cousin_idx)]['pos'] and (
not cousin_idx in visited_nodes or visited_nodes[cousin_idx] < 2):
words.extend(_get_cousin(cousin_idx, ["nsubj", "nsubjpass", "acl"], visited_nodes=visited_nodes))
if cousin_idx:
if cousin_idx in visited_nodes:
visited_nodes[cousin_idx] += 1
else:
visited_nodes[cousin_idx] = 1
return set(words)
def _add_related(related, dep, all_related, index, connector=None):
"""Adds a word (and its metadata) related to a measurement to the list of all related words for that measurement
Args:
related (str): related token/word
dep (str): the dependency type connecting the unit to the related word
all_related (list): existing list of "related" objects to be augmented
index (str): token index of related word
connector (str): if related word is cousin of unit (not sibling) then connecter is word between
Returns:
list: all related words for a given measurement (augmented with new 'related' passed in)
"""
doc = {}
doc["relationForm"] = dep
doc["rawName"] = related
doc["tokenIndex"] = int(index)
doc["offsetStart"] = A.lookup[int(index)]["start"]
doc["offsetEnd"] = A.lookup[int(index)]["end"]
doc["connector"] = "" if connector is None else connector
if not doc in all_related:
all_related.append(doc)
return all_related
def _add_descriptors(related):
"""For related words found for a measurement (usually nouns), add any connected adjectives, compounds, or modifiers.
Args:
related (list): objects containing related words and their metadata
Returns:
list: original list of related objects augmented with additional descriptor words
"""
for r in related:
r["descriptors"] = []
for edge in G.edges(data=True):
sibling_idx = _get_connected(edge, r["tokenIndex"])
if sibling_idx and (A.lookup[int(sibling_idx)]["pos"] == "JJ" or edge[2]["dep"] in ["amod", "compound"]):
r["descriptors"].append(
{
"tokenIndex": sibling_idx,
"rawName": A.lookup[int(sibling_idx)]["word"]
}
)
if sibling_idx and "NN" in A.lookup[int(sibling_idx)]["pos"] and "amod" in edge[2]["dep"]:
additional_related = _get_cousin(sibling_idx, ["nmod"])
for add in set(additional_related):
related = _add_related(add, "nmod", related, A.index_lookup[add],
connector=G.nodes[sibling_idx]['word'])
return related
def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):
""" If measurement is found, runs processed sentence through valid dependency patterns
(from JSON file) to find additional words related to measurements
Args:
dep (str): dependency type present in dependency patterns JSON
dep_obj (dict): object containing accepted POS types and measurement formats for a given dependency type
all_related (list): contains words related to a measurement to be augmented if valid pattern is found
edge (list): Connected node (word) indices and dependency type between
sibling_idx (str): token index of word connected to unit
Returns:
list: related words and metadata
"""
# Check for a matching dependency type
related = []
if edge[2]["dep"] == dep:
# Check for matching POS type(s)
for pos_logic in dep_obj.keys():
connector = None
if isinstance(dep_obj[pos_logic], dict):
for pos in dep_obj[pos_logic].keys():
# Check for allowed part of speech tags in matched dependency patterns
if (pos_logic == "pos_in" and pos in G.nodes[sibling_idx]["pos"]) or (
pos_logic == "pos_equals" and pos == G.nodes[sibling_idx]["pos"]):
pass
elif pos_logic == "pos_not":
if not [False if not_pos == G.nodes[sibling_idx]["pos"] else True for not_pos in
dep_obj.keys()]: continue
else:
continue
# if no additional checks, have a match
if dep_obj[pos_logic][pos] == None or any(
y in dep_obj[pos_logic][pos] for y in [None, "add_sibling"]):
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']])
# if additional checks are required, process further
if dep_obj[pos_logic][pos]:
if "get_cousin" in dep_obj[pos_logic][pos]:
related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos]["get_cousin"]))
connector = G.nodes[sibling_idx]['word']
if "special" in dep_obj[pos_logic][pos]:
if dep == "compound" and pos == "NN":
related = [G.nodes[sibling_idx]['word']]
if None in related:
related.remove(None)
# Allows for getting cousin and returning sibling
if "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == "always":
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
if len(related) > 0 and isinstance(related, list):
for x in related:
if x != None:
all_related = _add_related(x, dep, all_related, A.index_lookup[x],
connector=connector)
elif "else" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos]["else"] == True:
all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,
A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)
return all_related
def _parse_patterns(unit_idx, measurement_format, patterns_file):
""" Loads depedency patters JSON file and uses "_check_criteria" to look for words related to measurement (connected via unit token)
Args:
unit_idx (list): index or indices of measurement unit token(s)
measurement_format (str): indicates form of measurement value + unit (attached: 10m, space between: 10 m, hyphenated: 10-m)
Returns:
list: related words and metadata
"""
all_related = []
for edge in G.edges(data=True):
for idx in unit_idx:
sibling_idx = _get_connected(edge, idx)
if sibling_idx:
with open(os.path.join(basedir, patterns_file), "r") as tree:
tree = json.load(tree)
for dep in tree["dep"].keys():
if tree["dep"][dep]["enhanced"] == True:
for inner_dep in tree["dep"][dep].keys():
if isinstance(tree["dep"][dep][inner_dep], dict) and measurement_format in \
tree["dep"][dep][inner_dep]["measurement_types"]:
full_dep = dep + ":" + inner_dep
full_dep_obj = tree["dep"][dep][inner_dep]
all_related = _check_criteria(full_dep, full_dep_obj, all_related, edge,
sibling_idx)
elif measurement_format in tree["dep"][dep]["measurement_types"]:
all_related = _check_criteria(dep, tree["dep"][dep], all_related, edge, sibling_idx)
for x in range(0, len(tree["word"]["or"])):
if G.nodes[sibling_idx]["word"] == tree["word"]["or"][x]:
related = _get_cousin(sibling_idx, ["nsubj"])
for r in related:
all_related = _add_related(r, "operator", all_related, A.index_lookup[r])
all_related = _add_descriptors(all_related)
return all_related
def _get_related(stats, match, patterns_file):
""" Calls _parse_patterns() to get words related to a measurement and provides de-duplication between related words and grobid response
Args:
stats (Stats object): Global object used to track parsing behaviors
match (dict): information on measurements and units extracted by Grobid
Returns:
list: related words and metadata
"""
all_related = None
measurement_formats = ["space_between", "attached", "hyphenated"]
all_related = _parse_patterns(match["unit_idx"], match["measurement_format"], patterns_file)
if all_related == None:
all_related = _parse_patterns(match["unit_idx"], ["uncertain"], patterns_file)
# get words like approximately
num_adverbs = _parse_patterns([match["num_idx"]], match["measurement_format"], patterns_file)
unit_adverbs = _parse_patterns([match["unit_idx"]], match["measurement_format"], patterns_file)
adverbs = num_adverbs + unit_adverbs
for_removal = []
for a in adverbs:
if a["relationForm"] != "advmod":
for_removal.append(a)
else:
[a.pop(key, None) for key in ["descriptors", "connector"]] # not relevant for adverbs
[adverbs.remove(a) for a in for_removal]
if adverbs:
match["grobid"]["adverbs"] = adverbs
# Check to make sure related isn't already a number, unit, or quantified thing identified by Grobid
potential_keys = ["quantity", "quantityLeast", "quantityMost", "quantified"]
if all_related:
for key in potential_keys:
for related in all_related:
if key in match["grobid"]:
num, unit, quantified = "", "", ""
if "rawValue" in match["grobid"][key]: num = match["grobid"][key]["rawValue"]
if "rawUnit" in match["grobid"][key]: unit = match["grobid"][key]["rawUnit"]["name"]
if "normalizedName" in match["grobid"][key]: quantified = match["grobid"][key]["normalizedName"]
if related["rawName"] in [num, unit, quantified] or related["rawName"] == num + unit or (
quantified in related["rawName"] and not quantified == ""):
all_related.remove(related)
if related["rawName"] == unit:
for k in related.keys():
if not k in match["grobid"][key]["rawUnit"]:
match["grobid"][key]["rawUnit"][k] = related[k]
elif related["rawName"] == quantified:
for k in related.keys():
if not k in match["grobid"][key]:
match["grobid"][key][k] = related[k]
return all_related
def _simplify_results(match):
"""WORK IN PROGRESS: Prune metadata from extracted measurements and related words for more readable output
Args:
match (dict): Object contatining all metadata about extraction types, locations, relationships within sentence
Returns:
list: contains 4 items, extracted numeric value or range (list), unit(s) (list), qunatified words identified by Grobid (str), related words (str)
"""
keys = []
simplified = {}
simplified["value"] = []
if match["type"] == "value":
keys = ["quantity"]
elif match["type"] == "interval":
keys = ["quantityLeast", "quantityMost"]
for key in keys:
if key in match:
if "parsedValue" in match[key]:
simplified["value"].append(match[key]["parsedValue"])
elif "rawValue" in match[key]:
simplified["value"].append(match[key]["rawValue"])
else:
return None
simplified["unit"] = match[key]["rawUnit"]["name"] if "rawUnit" in match[key] else ""
if len(simplified["value"]) == 1:
simplified["value"] = simplified["value"][0]
simplified["quantified"] = {}
simplified["related"] = {}
if "quantified" in match:
if simplified["unit"] == "":
simplified["unit"] = match["quantified"]["normalizedName"]
simplified["quantified"][match["quantified"]["normalizedName"]] = []
if "descriptors" in match["quantified"]:
match["quantified"]["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for x in match["quantified"]["descriptors"]:
simplified["quantified"][match["quantified"]["normalizedName"]].append(x["rawName"])
if match["related"]:
for r in match["related"]:
simplified["related"][r["rawName"]] = []
if "descriptors" in r:
|
return simplified
def _reconstruct_sent(parsed_sentence):
"""Reconstruct sentence from CoreNLP tokens - raw sentence text isn't retained by CoreNLP after sentence splitting and processing
Args:
parsed_sentence (dict): Object containing CoreNLP output
Returns:
str: original sentence
"""
sent = ""
for x in range(0, len(parsed_sentence["tokens"])):
sent += parsed_sentence["tokens"][x]['originalText']
if x + 1 != len(parsed_sentence["tokens"]):
# Use character indices from tokens to ensure correct spacing when reconstructing
num_spaces = parsed_sentence["tokens"][x + 1]["characterOffsetBegin"] - parsed_sentence["tokens"][x][
"characterOffsetEnd"]
for y in range(0, num_spaces):
sent += " "
return sent
def _sorted_dictionary(orig_dict, sort_list):
od = OrderedDict()
for item in sort_list:
if item in orig_dict:
od[item] = orig_dict[item]
return od
#########################################
# Top-Level function
#########################################
def extract(content, corenlp_endpoint, grobid_endpoint, dependency_patterns_file, output_file=None, show_graph=False,
pretty=False, simplify=False):
""" Top-level user interface to parsing measurements and related words
Args:
content (str): sentence or paragraph to be parsed (shouldn't be much larger)
corenlp_endpoint (str): host + port of CoreNLP service (e.g. "http://localhost:9000")
grobid_endpoint (str): host + port of grobid service (e.g. "http://localhost:8080")
dependency_patterns (str): filepath to dependency patterns JSON file
output_file (optional: str): file to write output to
show_graph (bool): Will show network visualization of sentence dependencies if True
pretty (bool): JSON output will be pretty printed if True, else one JSON doc per line (JSONL)
simplify (bool): If True provides bare bones output with only extractions and not metadata about indices, types, etc.
Returns:
List of objects: containing parsed measurement info
(optionally write to file)
"""
all_extractions = []
out = None
if output_file:
out = codecs.open(output_file, "a", encoding="utf-8")
if len(content) < 5:
return None
nlp = StanfordCoreNLP(corenlp_endpoint)
output = nlp.annotate(content, properties={'outputFormat': 'json', 'timeout': '9999'})
if isinstance(output, str): # str supports both python 2 and 3
output = json.loads(output.encode("latin-1"), strict=False)
if "sentences" in output and isinstance(output["sentences"], list):
for i in range(0, len(output["sentences"])):
s_str = _reconstruct_sent(output["sentences"][i])
# Enhanced dependencies have different key names in JSON depending on version of CoreNLP
possible_keys = [
"enhanced-plus-plus-dependencies-annotation",
"enhancedPlusPlusDependencies"
]
dep_key = "collapsed-ccprocessed-dependencies" # default key
if "collapsed-ccprocessed-dependencies" not in output["sentences"][i]:
for k in possible_keys:
if k in output["sentences"][i]:
dep_key = k
global A
A = Annotations(output["sentences"][i]["tokens"], output["sentences"][i][dep_key])
if A.check_output(output["sentences"][i], stats) is True:
stats.total_sentences += 1
G = _build_graph(show=show_graph)
grobid_response = grobid_quantities(s_str, A, grobid_endpoint)
if isinstance(grobid_response, dict) and "measurements" in grobid_response:
for quantity in grobid_response["measurements"]:
A.augment_match(quantity)
stats.total_measurements += len(A.matches)
for idx, match in enumerate(A.matches):
global Num
Num = match["num"]
match["sentence"] = i + 1
match["grobid"]["related"] = _get_related(stats, match, dependency_patterns_file)
# Remove fields used for processing but not to be shown to user
remove = ["adverbs", "num", "unit", "connector", "form", "sentence", "num_idx", "unit_idx",
"measurement_format"]
[match.pop(x, None) for x in remove]
sort_order = ['adverbs', 'type', 'quantity', 'quantityLeast', 'quantityMost', 'quantified',
'related']
match_ordered = _sorted_dictionary(match["grobid"], sort_order)
if simplify:
simplified_sort_order = ['value', 'unit', 'quantified', 'related']
simplified = _simplify_results(match_ordered)
if simplified:
match_ordered = _sorted_dictionary(match["grobid"], simplified_sort_order)
if pretty and not simplify:
if out:
out.write(json.dumps(match_ordered, ensure_ascii=False, indent=4))
if idx != len(A.matches) - 1 and out:
out.write(",\n")
elif out:
out.write(json.dumps(match_ordered, ensure_ascii=False) + "\n")
all_extractions.extend(A.matches)
else:
logging.warning("CoreNLP parsing failed for sentence: %s" % (s_str))
else:
logging.warning("CoreNLP parsing failed for content: %s" % (content))
if out:
out.close()
logging.info("Total sentences parsed: %s" % (str(stats.total_sentences)))
logging.info("Total measurements found: %s" % (str(stats.total_measurements)))
stats.print_summary()
return all_extractions
def grobid_quantities(sentence, a, endpoint):
"""
a = annotations
"""
"""Pass sentence text to Grobid server on port 8080 for measurement parsing
Args:
sentence (str): Sentence to be parsed
a (Annotations object): object containing relevant CoreNLP output
Returns:
dict: object containing Grobid output
"""
# $ needs to be escaped when passed via subprocess
sentence = re.sub("\$", "\\$", sentence)
sentence = re.sub("\"", '\\"', sentence)
sentence = re.sub("%", '%25', sentence)
sentence = re.sub("`", "'", sentence)
sentence = re.sub("'", '\\"', sentence)
if endpoint[len(endpoint) - 1:] == "/":
endpoint = endpoint[:len(endpoint) - 1]
response = None
# try:
response = QuantitiesClient(endpoint).process_text(sentence)
if response[0] != 200:
print('No Grobid response for: %s' % sentence)
logging.warning('No Grobid response for: %s' % sentence)
return ""
quantities = response[1]
# Add token index for num, unit, quantified if available
if isinstance(quantities, dict):
if "measurements" in quantities.keys():
for q in quantities["measurements"]:
key = ""
if q["type"] == "value":
key = "quantity"
# if Grobid doesn't parse interval correctly, sometimes only 'QuantityLeast' or 'QuantityMost' is available
if q["type"] == "interval":
if "quantityLeast" in q:
key = "quantityLeast"
elif "QuantityMost" in q:
key = "quantityMost"
else:
return {}
if q["type"] == "listc":
return {}
if key == "":
logging.error('Unknown Grobid key resulting from parse of: %s' % sentence)
print("Unknown Grobid key resulting from parse of: %s" % sentence)
# Grobid doesn't pick up negatives
if sentence[sentence.find(q[key]["rawValue"]) - 1] == "-":
q[key]["parsedValue"] = float("-" + str(q[key]["parsedValue"]))
q[key]["rawValue"] = "-" + str(q[key]["rawValue"])
q[key]["offsetStart"] -= 1
if q[key]["offsetStart"] in a.tok_start:
q[key]["tokenIndex"] = a.tok_start[q[key]["offsetStart"]]
else:
print("Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
logging.error(
"Not finding token index for Grobid Quantity value in CoreNLP output. Sentence: %s" % sentence)
return {}
if "rawUnit" in q[key]:
q[key]["rawUnit"]["after"] = a.lookup[q[key]["tokenIndex"]]["after"]
q[key]["rawUnit"]["tokenIndices"] = []
if q[key]["rawUnit"]["offsetStart"] in a.tok_start:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_start[q[key]["rawUnit"]["offsetStart"]]))
if q[key]["rawUnit"]["offsetEnd"] in a.tok_end:
q[key]["rawUnit"]["tokenIndices"].append(str(a.tok_end[q[key]["rawUnit"]["offsetEnd"]]))
if q[key]["rawUnit"]["offsetStart"] == q[key]["offsetEnd"]:
q[key]["rawUnit"]["tokenIndices"].append(str(q[key]["tokenIndex"]))
q[key]["rawUnit"]["tokenIndices"] = list(set(q[key]["rawUnit"]["tokenIndices"]))
if "quantified" in q:
# often times Grobid with return a phrase where normalized name is in middle. In this case, "offsetStart" identifies the wrong token
add_to_offset = 0
normalized_idx, words = None, None
if " " in q["quantified"]["rawName"]:
words = q["quantified"]["rawName"].split(" ")
for i, w in enumerate(words):
if not q["quantified"]["normalizedName"] in w:
add_to_offset += (len(w) + 1) # +1 for space that was split on
else:
break
q["quantified"]["offsetStart"] += add_to_offset
if q["quantified"]["offsetStart"] in a.tok_start:
q["quantified"]["tokenIndex"] = a.tok_start[q["quantified"]["offsetStart"]]
else:
logging.warning(
"Not finding token index for Grobid quantified word in CoreNLP output. Sentence: %s" % (
sentence))
# hyphen causing issue - Grobid doesn't treat hyphenated clause as one word
# example error sentence: "Macroscopic examination of the CNS revealed micrencephaly with a whole-brain weight of 84 grams."
return quantities
| r["descriptors"].sort(key=lambda x: int(x["tokenIndex"]), reverse=False)
for z in r["descriptors"]:
simplified["related"][r["rawName"]].append(z["rawName"]) | conditional_block |
nsis.rs | // Copyright 2019-2023 Tauri Programme within The Commons Conservancy
// SPDX-License-Identifier: Apache-2.0
// SPDX-License-Identifier: MIT
#[cfg(target_os = "windows")]
use crate::bundle::windows::util::try_sign;
use crate::{
bundle::{
common::CommandExt,
windows::util::{
download, download_and_verify, extract_zip, HashAlgorithm, NSIS_OUTPUT_FOLDER_NAME,
NSIS_UPDATER_OUTPUT_FOLDER_NAME, WEBVIEW2_BOOTSTRAPPER_URL, WEBVIEW2_X64_INSTALLER_GUID,
WEBVIEW2_X86_INSTALLER_GUID,
},
},
Settings,
};
use tauri_utils::display_path;
use anyhow::Context;
use handlebars::{to_json, Handlebars};
use log::{info, warn};
use tauri_utils::{
config::{NSISInstallerMode, WebviewInstallMode},
resources::resource_relpath,
};
use std::{
collections::{BTreeMap, HashMap},
fs::{copy, create_dir_all, remove_dir_all, rename, write},
path::{Path, PathBuf},
process::Command,
};
// URLS for the NSIS toolchain.
#[cfg(target_os = "windows")]
const NSIS_URL: &str =
"https://github.com/tauri-apps/binary-releases/releases/download/nsis-3/nsis-3.zip";
#[cfg(target_os = "windows")]
const NSIS_SHA1: &str = "057e83c7d82462ec394af76c87d06733605543d4";
const NSIS_APPLICATIONID_URL: &str = "https://github.com/tauri-apps/binary-releases/releases/download/nsis-plugins-v0/NSIS-ApplicationID.zip";
const NSIS_TAURI_UTILS: &str =
"https://github.com/tauri-apps/nsis-tauri-utils/releases/download/nsis_tauri_utils-v0.1.1/nsis_tauri_utils.dll";
const NSIS_TAURI_UTILS_SHA1: &str = "A21C67CF5AB6D4274AFFF0D68CFCE680D213DDC7";
#[cfg(target_os = "windows")]
const NSIS_REQUIRED_FILES: &[&str] = &[
"makensis.exe",
"Bin/makensis.exe",
"Stubs/lzma-x86-unicode",
"Stubs/lzma_solid-x86-unicode",
"Plugins/x86-unicode/ApplicationID.dll",
"Plugins/x86-unicode/nsis_tauri_utils.dll",
"Include/MUI2.nsh",
"Include/FileFunc.nsh",
"Include/x64.nsh",
"Include/nsDialogs.nsh",
"Include/WinMessages.nsh",
];
#[cfg(not(target_os = "windows"))]
const NSIS_REQUIRED_FILES: &[&str] = &[
"Plugins/x86-unicode/ApplicationID.dll",
"Plugins/x86-unicode/nsis_tauri_utils.dll",
];
/// Runs all of the commands to build the NSIS installer.
/// Returns a vector of PathBuf that shows where the NSIS installer was created.
pub fn | (settings: &Settings, updater: bool) -> crate::Result<Vec<PathBuf>> {
let tauri_tools_path = dirs_next::cache_dir().unwrap().join("tauri");
let nsis_toolset_path = tauri_tools_path.join("NSIS");
if !nsis_toolset_path.exists() {
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
} else if NSIS_REQUIRED_FILES
.iter()
.any(|p| !nsis_toolset_path.join(p).exists())
{
warn!("NSIS directory is missing some files. Recreating it.");
std::fs::remove_dir_all(&nsis_toolset_path)?;
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
}
build_nsis_app_installer(settings, &nsis_toolset_path, &tauri_tools_path, updater)
}
// Gets NSIS and verifies the download via Sha1
fn get_and_extract_nsis(nsis_toolset_path: &Path, _tauri_tools_path: &Path) -> crate::Result<()> {
info!("Verifying NSIS package");
#[cfg(target_os = "windows")]
{
let data = download_and_verify(NSIS_URL, NSIS_SHA1, HashAlgorithm::Sha1)?;
info!("extracting NSIS");
extract_zip(&data, _tauri_tools_path)?;
rename(_tauri_tools_path.join("nsis-3.08"), nsis_toolset_path)?;
}
let nsis_plugins = nsis_toolset_path.join("Plugins");
let data = download(NSIS_APPLICATIONID_URL)?;
info!("extracting NSIS ApplicationID plugin");
extract_zip(&data, &nsis_plugins)?;
create_dir_all(nsis_plugins.join("x86-unicode"))?;
copy(
nsis_plugins
.join("ReleaseUnicode")
.join("ApplicationID.dll"),
nsis_plugins.join("x86-unicode").join("ApplicationID.dll"),
)?;
let data = download_and_verify(NSIS_TAURI_UTILS, NSIS_TAURI_UTILS_SHA1, HashAlgorithm::Sha1)?;
write(
nsis_plugins
.join("x86-unicode")
.join("nsis_tauri_utils.dll"),
data,
)?;
Ok(())
}
fn add_build_number_if_needed(version_str: &str) -> anyhow::Result<String> {
let version = semver::Version::parse(version_str).context("invalid app version")?;
if !version.build.is_empty() {
let build = version.build.parse::<u64>();
if build.is_ok() {
return Ok(format!(
"{}.{}.{}.{}",
version.major, version.minor, version.patch, version.build
));
} else {
anyhow::bail!("optional build metadata in app version must be numeric-only");
}
}
Ok(format!(
"{}.{}.{}.0",
version.major, version.minor, version.patch,
))
}
fn build_nsis_app_installer(
settings: &Settings,
_nsis_toolset_path: &Path,
tauri_tools_path: &Path,
updater: bool,
) -> crate::Result<Vec<PathBuf>> {
let arch = match settings.binary_arch() {
"x86_64" => "x64",
"x86" => "x86",
"aarch64" => "arm64",
target => {
return Err(crate::Error::ArchError(format!(
"unsupported target: {}",
target
)))
}
};
info!("Target: {}", arch);
#[cfg(target_os = "windows")]
{
let main_binary = settings
.binaries()
.iter()
.find(|bin| bin.main())
.ok_or_else(|| anyhow::anyhow!("Failed to get main binary"))?;
let app_exe_source = settings.binary_path(main_binary);
try_sign(&app_exe_source, settings)?;
}
#[cfg(not(target_os = "windows"))]
info!("Code signing is currently only supported on Windows hosts, skipping...");
let output_path = settings.project_out_directory().join("nsis").join(arch);
if output_path.exists() {
remove_dir_all(&output_path)?;
}
create_dir_all(&output_path)?;
let mut data = BTreeMap::new();
let bundle_id = settings.bundle_identifier();
let manufacturer = settings
.publisher()
.unwrap_or_else(|| bundle_id.split('.').nth(1).unwrap_or(bundle_id));
#[cfg(not(target_os = "windows"))]
{
let mut dir = dirs_next::cache_dir().unwrap();
dir.extend(["tauri", "NSIS", "Plugins", "x86-unicode"]);
data.insert("additional_plugins_path", to_json(dir));
}
data.insert("arch", to_json(arch));
data.insert("bundle_id", to_json(bundle_id));
data.insert("manufacturer", to_json(manufacturer));
data.insert("product_name", to_json(settings.product_name()));
data.insert("short_description", to_json(settings.short_description()));
data.insert("copyright", to_json(settings.copyright_string()));
let version = settings.version_string();
data.insert("version", to_json(version));
data.insert(
"version_with_build",
to_json(add_build_number_if_needed(version)?),
);
data.insert(
"allow_downgrades",
to_json(settings.windows().allow_downgrades),
);
let mut install_mode = NSISInstallerMode::CurrentUser;
let mut languages = vec!["English".into()];
let mut custom_template_path = None;
let mut custom_language_files = None;
if let Some(nsis) = &settings.windows().nsis {
custom_template_path = nsis.template.clone();
custom_language_files = nsis.custom_language_files.clone();
install_mode = nsis.install_mode;
if let Some(langs) = &nsis.languages {
languages.clear();
languages.extend_from_slice(langs);
}
if let Some(license) = &nsis.license {
data.insert("license", to_json(dunce::canonicalize(license)?));
}
if let Some(installer_icon) = &nsis.installer_icon {
data.insert(
"installer_icon",
to_json(dunce::canonicalize(installer_icon)?),
);
}
if let Some(header_image) = &nsis.header_image {
data.insert("header_image", to_json(dunce::canonicalize(header_image)?));
}
if let Some(sidebar_image) = &nsis.sidebar_image {
data.insert(
"sidebar_image",
to_json(dunce::canonicalize(sidebar_image)?),
);
}
data.insert(
"display_language_selector",
to_json(nsis.display_language_selector && languages.len() > 1),
);
}
data.insert(
"install_mode",
to_json(match install_mode {
NSISInstallerMode::CurrentUser => "currentUser",
NSISInstallerMode::PerMachine => "perMachine",
NSISInstallerMode::Both => "both",
}),
);
let mut languages_data = Vec::new();
for lang in &languages {
if let Some(data) = get_lang_data(lang, custom_language_files.as_ref())? {
languages_data.push(data);
} else {
log::warn!("Custom tauri messages for {lang} are not translated.\nIf it is a valid language listed on <https://github.com/kichik/nsis/tree/9465c08046f00ccb6eda985abbdbf52c275c6c4d/Contrib/Language%20files>, please open a Tauri feature request\n or you can provide a custom language file for it in `tauri.conf.json > tauri > bundle > windows > nsis > custom_language_files`");
}
}
data.insert("languages", to_json(languages.clone()));
data.insert(
"language_files",
to_json(
languages_data
.iter()
.map(|d| d.0.clone())
.collect::<Vec<_>>(),
),
);
let main_binary = settings
.binaries()
.iter()
.find(|bin| bin.main())
.ok_or_else(|| anyhow::anyhow!("Failed to get main binary"))?;
data.insert(
"main_binary_name",
to_json(main_binary.name().replace(".exe", "")),
);
data.insert(
"main_binary_path",
to_json(settings.binary_path(main_binary).with_extension("exe")),
);
let out_file = "nsis-output.exe";
data.insert("out_file", to_json(out_file));
let resources = generate_resource_data(settings)?;
data.insert("resources", to_json(resources));
let binaries = generate_binaries_data(settings)?;
data.insert("binaries", to_json(binaries));
if let Some(file_associations) = &settings.file_associations() {
data.insert("file_associations", to_json(file_associations));
}
let silent_webview2_install = if let WebviewInstallMode::DownloadBootstrapper { silent }
| WebviewInstallMode::EmbedBootstrapper { silent }
| WebviewInstallMode::OfflineInstaller { silent } =
settings.windows().webview_install_mode
{
silent
} else {
true
};
let webview2_install_mode = if updater {
WebviewInstallMode::DownloadBootstrapper {
silent: silent_webview2_install,
}
} else {
let mut webview_install_mode = settings.windows().webview_install_mode.clone();
if let Some(fixed_runtime_path) = settings.windows().webview_fixed_runtime_path.clone() {
webview_install_mode = WebviewInstallMode::FixedRuntime {
path: fixed_runtime_path,
};
} else if let Some(wix) = &settings.windows().wix {
if wix.skip_webview_install {
webview_install_mode = WebviewInstallMode::Skip;
}
}
webview_install_mode
};
let webview2_installer_args = to_json(if silent_webview2_install {
"/silent"
} else {
""
});
data.insert("webview2_installer_args", to_json(webview2_installer_args));
data.insert(
"install_webview2_mode",
to_json(match webview2_install_mode {
WebviewInstallMode::DownloadBootstrapper { silent: _ } => "downloadBootstrapper",
WebviewInstallMode::EmbedBootstrapper { silent: _ } => "embedBootstrapper",
WebviewInstallMode::OfflineInstaller { silent: _ } => "offlineInstaller",
_ => "",
}),
);
match webview2_install_mode {
WebviewInstallMode::EmbedBootstrapper { silent: _ } => {
let webview2_bootstrapper_path = tauri_tools_path.join("MicrosoftEdgeWebview2Setup.exe");
std::fs::write(
&webview2_bootstrapper_path,
download(WEBVIEW2_BOOTSTRAPPER_URL)?,
)?;
data.insert(
"webview2_bootstrapper_path",
to_json(webview2_bootstrapper_path),
);
}
WebviewInstallMode::OfflineInstaller { silent: _ } => {
let guid = if arch == "x64" {
WEBVIEW2_X64_INSTALLER_GUID
} else {
WEBVIEW2_X86_INSTALLER_GUID
};
let offline_installer_path = tauri_tools_path
.join("Webview2OfflineInstaller")
.join(guid)
.join(arch);
create_dir_all(&offline_installer_path)?;
let webview2_installer_path =
offline_installer_path.join("MicrosoftEdgeWebView2RuntimeInstaller.exe");
if !webview2_installer_path.exists() {
std::fs::write(
&webview2_installer_path,
download(
&format!("https://msedge.sf.dl.delivery.mp.microsoft.com/filestreamingservice/files/{}/MicrosoftEdgeWebView2RuntimeInstaller{}.exe",
guid,
arch.to_uppercase(),
),
)?,
)?;
}
data.insert("webview2_installer_path", to_json(webview2_installer_path));
}
_ => {}
}
let mut handlebars = Handlebars::new();
handlebars.register_helper("or", Box::new(handlebars_or));
handlebars.register_helper("association-description", Box::new(association_description));
handlebars.register_escape_fn(|s| {
let mut output = String::new();
for c in s.chars() {
match c {
'\"' => output.push_str("$\\\""),
'$' => output.push_str("$$"),
'`' => output.push_str("$\\`"),
'\n' => output.push_str("$\\n"),
'\t' => output.push_str("$\\t"),
'\r' => output.push_str("$\\r"),
_ => output.push(c),
}
}
output
});
if let Some(path) = custom_template_path {
handlebars
.register_template_string("installer.nsi", std::fs::read_to_string(path)?)
.map_err(|e| e.to_string())
.expect("Failed to setup custom handlebar template");
} else {
handlebars
.register_template_string("installer.nsi", include_str!("./templates/installer.nsi"))
.map_err(|e| e.to_string())
.expect("Failed to setup handlebar template");
}
write_ut16_le_with_bom(
&output_path.join("FileAssociation.nsh"),
include_str!("./templates/FileAssociation.nsh"),
)?;
let installer_nsi_path = output_path.join("installer.nsi");
write_ut16_le_with_bom(
&installer_nsi_path,
handlebars.render("installer.nsi", &data)?.as_str(),
)?;
for (lang, data) in languages_data.iter() {
if let Some(content) = data {
write_ut16_le_with_bom(output_path.join(lang).with_extension("nsh"), content)?;
}
}
let package_base_name = format!(
"{}_{}_{}-setup",
main_binary.name().replace(".exe", ""),
settings.version_string(),
arch,
);
let nsis_output_path = output_path.join(out_file);
let nsis_installer_path = settings.project_out_directory().to_path_buf().join(format!(
"bundle/{}/{}.exe",
if updater {
NSIS_UPDATER_OUTPUT_FOLDER_NAME
} else {
NSIS_OUTPUT_FOLDER_NAME
},
package_base_name
));
create_dir_all(nsis_installer_path.parent().unwrap())?;
info!(action = "Running"; "makensis.exe to produce {}", display_path(&nsis_installer_path));
#[cfg(target_os = "windows")]
let mut nsis_cmd = Command::new(_nsis_toolset_path.join("makensis.exe"));
#[cfg(not(target_os = "windows"))]
let mut nsis_cmd = Command::new("makensis");
nsis_cmd
.arg(match settings.log_level() {
log::Level::Error => "-V1",
log::Level::Warn => "-V2",
log::Level::Info => "-V3",
_ => "-V4",
})
.arg(installer_nsi_path)
.current_dir(output_path)
.piped()
.context("error running makensis.exe")?;
rename(nsis_output_path, &nsis_installer_path)?;
// Code signing is currently only supported on Windows hosts
#[cfg(target_os = "windows")]
try_sign(&nsis_installer_path, settings)?;
Ok(vec![nsis_installer_path])
}
fn handlebars_or(
h: &handlebars::Helper<'_, '_>,
_: &Handlebars<'_>,
_: &handlebars::Context,
_: &mut handlebars::RenderContext<'_, '_>,
out: &mut dyn handlebars::Output,
) -> handlebars::HelperResult {
let param1 = h.param(0).unwrap().render();
let param2 = h.param(1).unwrap();
out.write(&if param1.is_empty() {
param2.render()
} else {
param1
})?;
Ok(())
}
fn association_description(
h: &handlebars::Helper<'_, '_>,
_: &Handlebars<'_>,
_: &handlebars::Context,
_: &mut handlebars::RenderContext<'_, '_>,
out: &mut dyn handlebars::Output,
) -> handlebars::HelperResult {
let description = h.param(0).unwrap().render();
let ext = h.param(1).unwrap();
out.write(&if description.is_empty() {
format!("{} File", ext.render().to_uppercase())
} else {
description
})?;
Ok(())
}
/// BTreeMap<OriginalPath, (ParentOfTargetPath, TargetPath)>
type ResourcesMap = BTreeMap<PathBuf, (String, PathBuf)>;
fn generate_resource_data(settings: &Settings) -> crate::Result<ResourcesMap> {
let mut resources = ResourcesMap::new();
let cwd = std::env::current_dir()?;
let mut added_resources = Vec::new();
for src in settings.resource_files() {
let src = src?;
let resource_path = dunce::canonicalize(cwd.join(&src))?;
// In some glob resource paths like `assets/**/*` a file might appear twice
// because the `tauri_utils::resources::ResourcePaths` iterator also reads a directory
// when it finds one. So we must check it before processing the file.
if added_resources.contains(&resource_path) {
continue;
}
added_resources.push(resource_path.clone());
let target_path = resource_relpath(&src);
resources.insert(
resource_path,
(
target_path
.parent()
.map(|p| p.to_string_lossy().to_string())
.unwrap_or_default(),
target_path,
),
);
}
Ok(resources)
}
/// BTreeMap<OriginalPath, TargetFileName>
type BinariesMap = BTreeMap<PathBuf, String>;
fn generate_binaries_data(settings: &Settings) -> crate::Result<BinariesMap> {
let mut binaries = BinariesMap::new();
let cwd = std::env::current_dir()?;
for src in settings.external_binaries() {
let src = src?;
let binary_path = dunce::canonicalize(cwd.join(&src))?;
let dest_filename = src
.file_name()
.expect("failed to extract external binary filename")
.to_string_lossy()
.replace(&format!("-{}", settings.target()), "");
binaries.insert(binary_path, dest_filename);
}
for bin in settings.binaries() {
if !bin.main() {
let bin_path = settings.binary_path(bin);
binaries.insert(
bin_path.clone(),
bin_path
.file_name()
.expect("failed to extract external binary filename")
.to_string_lossy()
.to_string(),
);
}
}
Ok(binaries)
}
fn get_lang_data(
lang: &str,
custom_lang_files: Option<&HashMap<String, PathBuf>>,
) -> crate::Result<Option<(PathBuf, Option<&'static str>)>> {
if let Some(path) = custom_lang_files.and_then(|h| h.get(lang)) {
return Ok(Some((dunce::canonicalize(path)?, None)));
}
let lang_path = PathBuf::from(format!("{lang}.nsh"));
let lang_content = match lang.to_lowercase().as_str() {
"arabic" => Some(include_str!("./templates/nsis-languages/Arabic.nsh")),
"bulgarian" => Some(include_str!("./templates/nsis-languages/Bulgarian.nsh")),
"dutch" => Some(include_str!("./templates/nsis-languages/Dutch.nsh")),
"english" => Some(include_str!("./templates/nsis-languages/English.nsh")),
"japanese" => Some(include_str!("./templates/nsis-languages/Japanese.nsh")),
"korean" => Some(include_str!("./templates/nsis-languages/Korean.nsh")),
"portuguesebr" => Some(include_str!("./templates/nsis-languages/PortugueseBR.nsh")),
"tradchinese" => Some(include_str!("./templates/nsis-languages/TradChinese.nsh")),
"simpchinese" => Some(include_str!("./templates/nsis-languages/SimpChinese.nsh")),
"french" => Some(include_str!("./templates/nsis-languages/French.nsh")),
"spanish" => Some(include_str!("./templates/nsis-languages/Spanish.nsh")),
"spanishinternational" => Some(include_str!(
"./templates/nsis-languages/SpanishInternational.nsh"
)),
"persian" => Some(include_str!("./templates/nsis-languages/Persian.nsh")),
"turkish" => Some(include_str!("./templates/nsis-languages/Turkish.nsh")),
"swedish" => Some(include_str!("./templates/nsis-languages/Swedish.nsh")),
_ => return Ok(None),
};
Ok(Some((lang_path, lang_content)))
}
fn write_ut16_le_with_bom<P: AsRef<Path>>(path: P, content: &str) -> crate::Result<()> {
use std::fs::File;
use std::io::{BufWriter, Write};
let file = File::create(path)?;
let mut output = BufWriter::new(file);
output.write_all(&[0xFF, 0xFE])?; // the BOM part
for utf16 in content.encode_utf16() {
output.write_all(&utf16.to_le_bytes())?;
}
Ok(())
}
| bundle_project | identifier_name |
nsis.rs | // Copyright 2019-2023 Tauri Programme within The Commons Conservancy
// SPDX-License-Identifier: Apache-2.0
// SPDX-License-Identifier: MIT
#[cfg(target_os = "windows")]
use crate::bundle::windows::util::try_sign;
use crate::{
bundle::{
common::CommandExt,
windows::util::{
download, download_and_verify, extract_zip, HashAlgorithm, NSIS_OUTPUT_FOLDER_NAME,
NSIS_UPDATER_OUTPUT_FOLDER_NAME, WEBVIEW2_BOOTSTRAPPER_URL, WEBVIEW2_X64_INSTALLER_GUID,
WEBVIEW2_X86_INSTALLER_GUID,
},
},
Settings,
};
use tauri_utils::display_path;
use anyhow::Context;
use handlebars::{to_json, Handlebars};
use log::{info, warn};
use tauri_utils::{
config::{NSISInstallerMode, WebviewInstallMode},
resources::resource_relpath,
};
use std::{
collections::{BTreeMap, HashMap},
fs::{copy, create_dir_all, remove_dir_all, rename, write},
path::{Path, PathBuf},
process::Command,
};
// URLS for the NSIS toolchain.
#[cfg(target_os = "windows")]
const NSIS_URL: &str =
"https://github.com/tauri-apps/binary-releases/releases/download/nsis-3/nsis-3.zip";
#[cfg(target_os = "windows")]
const NSIS_SHA1: &str = "057e83c7d82462ec394af76c87d06733605543d4";
const NSIS_APPLICATIONID_URL: &str = "https://github.com/tauri-apps/binary-releases/releases/download/nsis-plugins-v0/NSIS-ApplicationID.zip";
const NSIS_TAURI_UTILS: &str =
"https://github.com/tauri-apps/nsis-tauri-utils/releases/download/nsis_tauri_utils-v0.1.1/nsis_tauri_utils.dll";
const NSIS_TAURI_UTILS_SHA1: &str = "A21C67CF5AB6D4274AFFF0D68CFCE680D213DDC7";
#[cfg(target_os = "windows")]
const NSIS_REQUIRED_FILES: &[&str] = &[
"makensis.exe",
"Bin/makensis.exe",
"Stubs/lzma-x86-unicode",
"Stubs/lzma_solid-x86-unicode",
"Plugins/x86-unicode/ApplicationID.dll",
"Plugins/x86-unicode/nsis_tauri_utils.dll",
"Include/MUI2.nsh",
"Include/FileFunc.nsh",
"Include/x64.nsh",
"Include/nsDialogs.nsh",
"Include/WinMessages.nsh",
];
#[cfg(not(target_os = "windows"))]
const NSIS_REQUIRED_FILES: &[&str] = &[
"Plugins/x86-unicode/ApplicationID.dll",
"Plugins/x86-unicode/nsis_tauri_utils.dll",
];
/// Runs all of the commands to build the NSIS installer.
/// Returns a vector of PathBuf that shows where the NSIS installer was created.
pub fn bundle_project(settings: &Settings, updater: bool) -> crate::Result<Vec<PathBuf>> {
let tauri_tools_path = dirs_next::cache_dir().unwrap().join("tauri");
let nsis_toolset_path = tauri_tools_path.join("NSIS");
if !nsis_toolset_path.exists() {
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
} else if NSIS_REQUIRED_FILES
.iter()
.any(|p| !nsis_toolset_path.join(p).exists())
{
warn!("NSIS directory is missing some files. Recreating it.");
std::fs::remove_dir_all(&nsis_toolset_path)?;
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
}
build_nsis_app_installer(settings, &nsis_toolset_path, &tauri_tools_path, updater)
}
// Gets NSIS and verifies the download via Sha1
fn get_and_extract_nsis(nsis_toolset_path: &Path, _tauri_tools_path: &Path) -> crate::Result<()> {
info!("Verifying NSIS package");
#[cfg(target_os = "windows")]
{
let data = download_and_verify(NSIS_URL, NSIS_SHA1, HashAlgorithm::Sha1)?; | rename(_tauri_tools_path.join("nsis-3.08"), nsis_toolset_path)?;
}
let nsis_plugins = nsis_toolset_path.join("Plugins");
let data = download(NSIS_APPLICATIONID_URL)?;
info!("extracting NSIS ApplicationID plugin");
extract_zip(&data, &nsis_plugins)?;
create_dir_all(nsis_plugins.join("x86-unicode"))?;
copy(
nsis_plugins
.join("ReleaseUnicode")
.join("ApplicationID.dll"),
nsis_plugins.join("x86-unicode").join("ApplicationID.dll"),
)?;
let data = download_and_verify(NSIS_TAURI_UTILS, NSIS_TAURI_UTILS_SHA1, HashAlgorithm::Sha1)?;
write(
nsis_plugins
.join("x86-unicode")
.join("nsis_tauri_utils.dll"),
data,
)?;
Ok(())
}
fn add_build_number_if_needed(version_str: &str) -> anyhow::Result<String> {
let version = semver::Version::parse(version_str).context("invalid app version")?;
if !version.build.is_empty() {
let build = version.build.parse::<u64>();
if build.is_ok() {
return Ok(format!(
"{}.{}.{}.{}",
version.major, version.minor, version.patch, version.build
));
} else {
anyhow::bail!("optional build metadata in app version must be numeric-only");
}
}
Ok(format!(
"{}.{}.{}.0",
version.major, version.minor, version.patch,
))
}
fn build_nsis_app_installer(
settings: &Settings,
_nsis_toolset_path: &Path,
tauri_tools_path: &Path,
updater: bool,
) -> crate::Result<Vec<PathBuf>> {
let arch = match settings.binary_arch() {
"x86_64" => "x64",
"x86" => "x86",
"aarch64" => "arm64",
target => {
return Err(crate::Error::ArchError(format!(
"unsupported target: {}",
target
)))
}
};
info!("Target: {}", arch);
#[cfg(target_os = "windows")]
{
let main_binary = settings
.binaries()
.iter()
.find(|bin| bin.main())
.ok_or_else(|| anyhow::anyhow!("Failed to get main binary"))?;
let app_exe_source = settings.binary_path(main_binary);
try_sign(&app_exe_source, settings)?;
}
#[cfg(not(target_os = "windows"))]
info!("Code signing is currently only supported on Windows hosts, skipping...");
let output_path = settings.project_out_directory().join("nsis").join(arch);
if output_path.exists() {
remove_dir_all(&output_path)?;
}
create_dir_all(&output_path)?;
let mut data = BTreeMap::new();
let bundle_id = settings.bundle_identifier();
let manufacturer = settings
.publisher()
.unwrap_or_else(|| bundle_id.split('.').nth(1).unwrap_or(bundle_id));
#[cfg(not(target_os = "windows"))]
{
let mut dir = dirs_next::cache_dir().unwrap();
dir.extend(["tauri", "NSIS", "Plugins", "x86-unicode"]);
data.insert("additional_plugins_path", to_json(dir));
}
data.insert("arch", to_json(arch));
data.insert("bundle_id", to_json(bundle_id));
data.insert("manufacturer", to_json(manufacturer));
data.insert("product_name", to_json(settings.product_name()));
data.insert("short_description", to_json(settings.short_description()));
data.insert("copyright", to_json(settings.copyright_string()));
let version = settings.version_string();
data.insert("version", to_json(version));
data.insert(
"version_with_build",
to_json(add_build_number_if_needed(version)?),
);
data.insert(
"allow_downgrades",
to_json(settings.windows().allow_downgrades),
);
let mut install_mode = NSISInstallerMode::CurrentUser;
let mut languages = vec!["English".into()];
let mut custom_template_path = None;
let mut custom_language_files = None;
if let Some(nsis) = &settings.windows().nsis {
custom_template_path = nsis.template.clone();
custom_language_files = nsis.custom_language_files.clone();
install_mode = nsis.install_mode;
if let Some(langs) = &nsis.languages {
languages.clear();
languages.extend_from_slice(langs);
}
if let Some(license) = &nsis.license {
data.insert("license", to_json(dunce::canonicalize(license)?));
}
if let Some(installer_icon) = &nsis.installer_icon {
data.insert(
"installer_icon",
to_json(dunce::canonicalize(installer_icon)?),
);
}
if let Some(header_image) = &nsis.header_image {
data.insert("header_image", to_json(dunce::canonicalize(header_image)?));
}
if let Some(sidebar_image) = &nsis.sidebar_image {
data.insert(
"sidebar_image",
to_json(dunce::canonicalize(sidebar_image)?),
);
}
data.insert(
"display_language_selector",
to_json(nsis.display_language_selector && languages.len() > 1),
);
}
data.insert(
"install_mode",
to_json(match install_mode {
NSISInstallerMode::CurrentUser => "currentUser",
NSISInstallerMode::PerMachine => "perMachine",
NSISInstallerMode::Both => "both",
}),
);
let mut languages_data = Vec::new();
for lang in &languages {
if let Some(data) = get_lang_data(lang, custom_language_files.as_ref())? {
languages_data.push(data);
} else {
log::warn!("Custom tauri messages for {lang} are not translated.\nIf it is a valid language listed on <https://github.com/kichik/nsis/tree/9465c08046f00ccb6eda985abbdbf52c275c6c4d/Contrib/Language%20files>, please open a Tauri feature request\n or you can provide a custom language file for it in `tauri.conf.json > tauri > bundle > windows > nsis > custom_language_files`");
}
}
data.insert("languages", to_json(languages.clone()));
data.insert(
"language_files",
to_json(
languages_data
.iter()
.map(|d| d.0.clone())
.collect::<Vec<_>>(),
),
);
let main_binary = settings
.binaries()
.iter()
.find(|bin| bin.main())
.ok_or_else(|| anyhow::anyhow!("Failed to get main binary"))?;
data.insert(
"main_binary_name",
to_json(main_binary.name().replace(".exe", "")),
);
data.insert(
"main_binary_path",
to_json(settings.binary_path(main_binary).with_extension("exe")),
);
let out_file = "nsis-output.exe";
data.insert("out_file", to_json(out_file));
let resources = generate_resource_data(settings)?;
data.insert("resources", to_json(resources));
let binaries = generate_binaries_data(settings)?;
data.insert("binaries", to_json(binaries));
if let Some(file_associations) = &settings.file_associations() {
data.insert("file_associations", to_json(file_associations));
}
let silent_webview2_install = if let WebviewInstallMode::DownloadBootstrapper { silent }
| WebviewInstallMode::EmbedBootstrapper { silent }
| WebviewInstallMode::OfflineInstaller { silent } =
settings.windows().webview_install_mode
{
silent
} else {
true
};
let webview2_install_mode = if updater {
WebviewInstallMode::DownloadBootstrapper {
silent: silent_webview2_install,
}
} else {
let mut webview_install_mode = settings.windows().webview_install_mode.clone();
if let Some(fixed_runtime_path) = settings.windows().webview_fixed_runtime_path.clone() {
webview_install_mode = WebviewInstallMode::FixedRuntime {
path: fixed_runtime_path,
};
} else if let Some(wix) = &settings.windows().wix {
if wix.skip_webview_install {
webview_install_mode = WebviewInstallMode::Skip;
}
}
webview_install_mode
};
let webview2_installer_args = to_json(if silent_webview2_install {
"/silent"
} else {
""
});
data.insert("webview2_installer_args", to_json(webview2_installer_args));
data.insert(
"install_webview2_mode",
to_json(match webview2_install_mode {
WebviewInstallMode::DownloadBootstrapper { silent: _ } => "downloadBootstrapper",
WebviewInstallMode::EmbedBootstrapper { silent: _ } => "embedBootstrapper",
WebviewInstallMode::OfflineInstaller { silent: _ } => "offlineInstaller",
_ => "",
}),
);
match webview2_install_mode {
WebviewInstallMode::EmbedBootstrapper { silent: _ } => {
let webview2_bootstrapper_path = tauri_tools_path.join("MicrosoftEdgeWebview2Setup.exe");
std::fs::write(
&webview2_bootstrapper_path,
download(WEBVIEW2_BOOTSTRAPPER_URL)?,
)?;
data.insert(
"webview2_bootstrapper_path",
to_json(webview2_bootstrapper_path),
);
}
WebviewInstallMode::OfflineInstaller { silent: _ } => {
let guid = if arch == "x64" {
WEBVIEW2_X64_INSTALLER_GUID
} else {
WEBVIEW2_X86_INSTALLER_GUID
};
let offline_installer_path = tauri_tools_path
.join("Webview2OfflineInstaller")
.join(guid)
.join(arch);
create_dir_all(&offline_installer_path)?;
let webview2_installer_path =
offline_installer_path.join("MicrosoftEdgeWebView2RuntimeInstaller.exe");
if !webview2_installer_path.exists() {
std::fs::write(
&webview2_installer_path,
download(
&format!("https://msedge.sf.dl.delivery.mp.microsoft.com/filestreamingservice/files/{}/MicrosoftEdgeWebView2RuntimeInstaller{}.exe",
guid,
arch.to_uppercase(),
),
)?,
)?;
}
data.insert("webview2_installer_path", to_json(webview2_installer_path));
}
_ => {}
}
let mut handlebars = Handlebars::new();
handlebars.register_helper("or", Box::new(handlebars_or));
handlebars.register_helper("association-description", Box::new(association_description));
handlebars.register_escape_fn(|s| {
let mut output = String::new();
for c in s.chars() {
match c {
'\"' => output.push_str("$\\\""),
'$' => output.push_str("$$"),
'`' => output.push_str("$\\`"),
'\n' => output.push_str("$\\n"),
'\t' => output.push_str("$\\t"),
'\r' => output.push_str("$\\r"),
_ => output.push(c),
}
}
output
});
if let Some(path) = custom_template_path {
handlebars
.register_template_string("installer.nsi", std::fs::read_to_string(path)?)
.map_err(|e| e.to_string())
.expect("Failed to setup custom handlebar template");
} else {
handlebars
.register_template_string("installer.nsi", include_str!("./templates/installer.nsi"))
.map_err(|e| e.to_string())
.expect("Failed to setup handlebar template");
}
write_ut16_le_with_bom(
&output_path.join("FileAssociation.nsh"),
include_str!("./templates/FileAssociation.nsh"),
)?;
let installer_nsi_path = output_path.join("installer.nsi");
write_ut16_le_with_bom(
&installer_nsi_path,
handlebars.render("installer.nsi", &data)?.as_str(),
)?;
for (lang, data) in languages_data.iter() {
if let Some(content) = data {
write_ut16_le_with_bom(output_path.join(lang).with_extension("nsh"), content)?;
}
}
let package_base_name = format!(
"{}_{}_{}-setup",
main_binary.name().replace(".exe", ""),
settings.version_string(),
arch,
);
let nsis_output_path = output_path.join(out_file);
let nsis_installer_path = settings.project_out_directory().to_path_buf().join(format!(
"bundle/{}/{}.exe",
if updater {
NSIS_UPDATER_OUTPUT_FOLDER_NAME
} else {
NSIS_OUTPUT_FOLDER_NAME
},
package_base_name
));
create_dir_all(nsis_installer_path.parent().unwrap())?;
info!(action = "Running"; "makensis.exe to produce {}", display_path(&nsis_installer_path));
#[cfg(target_os = "windows")]
let mut nsis_cmd = Command::new(_nsis_toolset_path.join("makensis.exe"));
#[cfg(not(target_os = "windows"))]
let mut nsis_cmd = Command::new("makensis");
nsis_cmd
.arg(match settings.log_level() {
log::Level::Error => "-V1",
log::Level::Warn => "-V2",
log::Level::Info => "-V3",
_ => "-V4",
})
.arg(installer_nsi_path)
.current_dir(output_path)
.piped()
.context("error running makensis.exe")?;
rename(nsis_output_path, &nsis_installer_path)?;
// Code signing is currently only supported on Windows hosts
#[cfg(target_os = "windows")]
try_sign(&nsis_installer_path, settings)?;
Ok(vec![nsis_installer_path])
}
fn handlebars_or(
h: &handlebars::Helper<'_, '_>,
_: &Handlebars<'_>,
_: &handlebars::Context,
_: &mut handlebars::RenderContext<'_, '_>,
out: &mut dyn handlebars::Output,
) -> handlebars::HelperResult {
let param1 = h.param(0).unwrap().render();
let param2 = h.param(1).unwrap();
out.write(&if param1.is_empty() {
param2.render()
} else {
param1
})?;
Ok(())
}
fn association_description(
h: &handlebars::Helper<'_, '_>,
_: &Handlebars<'_>,
_: &handlebars::Context,
_: &mut handlebars::RenderContext<'_, '_>,
out: &mut dyn handlebars::Output,
) -> handlebars::HelperResult {
let description = h.param(0).unwrap().render();
let ext = h.param(1).unwrap();
out.write(&if description.is_empty() {
format!("{} File", ext.render().to_uppercase())
} else {
description
})?;
Ok(())
}
/// BTreeMap<OriginalPath, (ParentOfTargetPath, TargetPath)>
type ResourcesMap = BTreeMap<PathBuf, (String, PathBuf)>;
fn generate_resource_data(settings: &Settings) -> crate::Result<ResourcesMap> {
let mut resources = ResourcesMap::new();
let cwd = std::env::current_dir()?;
let mut added_resources = Vec::new();
for src in settings.resource_files() {
let src = src?;
let resource_path = dunce::canonicalize(cwd.join(&src))?;
// In some glob resource paths like `assets/**/*` a file might appear twice
// because the `tauri_utils::resources::ResourcePaths` iterator also reads a directory
// when it finds one. So we must check it before processing the file.
if added_resources.contains(&resource_path) {
continue;
}
added_resources.push(resource_path.clone());
let target_path = resource_relpath(&src);
resources.insert(
resource_path,
(
target_path
.parent()
.map(|p| p.to_string_lossy().to_string())
.unwrap_or_default(),
target_path,
),
);
}
Ok(resources)
}
/// BTreeMap<OriginalPath, TargetFileName>
type BinariesMap = BTreeMap<PathBuf, String>;
fn generate_binaries_data(settings: &Settings) -> crate::Result<BinariesMap> {
let mut binaries = BinariesMap::new();
let cwd = std::env::current_dir()?;
for src in settings.external_binaries() {
let src = src?;
let binary_path = dunce::canonicalize(cwd.join(&src))?;
let dest_filename = src
.file_name()
.expect("failed to extract external binary filename")
.to_string_lossy()
.replace(&format!("-{}", settings.target()), "");
binaries.insert(binary_path, dest_filename);
}
for bin in settings.binaries() {
if !bin.main() {
let bin_path = settings.binary_path(bin);
binaries.insert(
bin_path.clone(),
bin_path
.file_name()
.expect("failed to extract external binary filename")
.to_string_lossy()
.to_string(),
);
}
}
Ok(binaries)
}
fn get_lang_data(
lang: &str,
custom_lang_files: Option<&HashMap<String, PathBuf>>,
) -> crate::Result<Option<(PathBuf, Option<&'static str>)>> {
if let Some(path) = custom_lang_files.and_then(|h| h.get(lang)) {
return Ok(Some((dunce::canonicalize(path)?, None)));
}
let lang_path = PathBuf::from(format!("{lang}.nsh"));
let lang_content = match lang.to_lowercase().as_str() {
"arabic" => Some(include_str!("./templates/nsis-languages/Arabic.nsh")),
"bulgarian" => Some(include_str!("./templates/nsis-languages/Bulgarian.nsh")),
"dutch" => Some(include_str!("./templates/nsis-languages/Dutch.nsh")),
"english" => Some(include_str!("./templates/nsis-languages/English.nsh")),
"japanese" => Some(include_str!("./templates/nsis-languages/Japanese.nsh")),
"korean" => Some(include_str!("./templates/nsis-languages/Korean.nsh")),
"portuguesebr" => Some(include_str!("./templates/nsis-languages/PortugueseBR.nsh")),
"tradchinese" => Some(include_str!("./templates/nsis-languages/TradChinese.nsh")),
"simpchinese" => Some(include_str!("./templates/nsis-languages/SimpChinese.nsh")),
"french" => Some(include_str!("./templates/nsis-languages/French.nsh")),
"spanish" => Some(include_str!("./templates/nsis-languages/Spanish.nsh")),
"spanishinternational" => Some(include_str!(
"./templates/nsis-languages/SpanishInternational.nsh"
)),
"persian" => Some(include_str!("./templates/nsis-languages/Persian.nsh")),
"turkish" => Some(include_str!("./templates/nsis-languages/Turkish.nsh")),
"swedish" => Some(include_str!("./templates/nsis-languages/Swedish.nsh")),
_ => return Ok(None),
};
Ok(Some((lang_path, lang_content)))
}
fn write_ut16_le_with_bom<P: AsRef<Path>>(path: P, content: &str) -> crate::Result<()> {
use std::fs::File;
use std::io::{BufWriter, Write};
let file = File::create(path)?;
let mut output = BufWriter::new(file);
output.write_all(&[0xFF, 0xFE])?; // the BOM part
for utf16 in content.encode_utf16() {
output.write_all(&utf16.to_le_bytes())?;
}
Ok(())
} | info!("extracting NSIS");
extract_zip(&data, _tauri_tools_path)?; | random_line_split |
nsis.rs | // Copyright 2019-2023 Tauri Programme within The Commons Conservancy
// SPDX-License-Identifier: Apache-2.0
// SPDX-License-Identifier: MIT
#[cfg(target_os = "windows")]
use crate::bundle::windows::util::try_sign;
use crate::{
bundle::{
common::CommandExt,
windows::util::{
download, download_and_verify, extract_zip, HashAlgorithm, NSIS_OUTPUT_FOLDER_NAME,
NSIS_UPDATER_OUTPUT_FOLDER_NAME, WEBVIEW2_BOOTSTRAPPER_URL, WEBVIEW2_X64_INSTALLER_GUID,
WEBVIEW2_X86_INSTALLER_GUID,
},
},
Settings,
};
use tauri_utils::display_path;
use anyhow::Context;
use handlebars::{to_json, Handlebars};
use log::{info, warn};
use tauri_utils::{
config::{NSISInstallerMode, WebviewInstallMode},
resources::resource_relpath,
};
use std::{
collections::{BTreeMap, HashMap},
fs::{copy, create_dir_all, remove_dir_all, rename, write},
path::{Path, PathBuf},
process::Command,
};
// URLS for the NSIS toolchain.
#[cfg(target_os = "windows")]
const NSIS_URL: &str =
"https://github.com/tauri-apps/binary-releases/releases/download/nsis-3/nsis-3.zip";
#[cfg(target_os = "windows")]
const NSIS_SHA1: &str = "057e83c7d82462ec394af76c87d06733605543d4";
const NSIS_APPLICATIONID_URL: &str = "https://github.com/tauri-apps/binary-releases/releases/download/nsis-plugins-v0/NSIS-ApplicationID.zip";
const NSIS_TAURI_UTILS: &str =
"https://github.com/tauri-apps/nsis-tauri-utils/releases/download/nsis_tauri_utils-v0.1.1/nsis_tauri_utils.dll";
const NSIS_TAURI_UTILS_SHA1: &str = "A21C67CF5AB6D4274AFFF0D68CFCE680D213DDC7";
#[cfg(target_os = "windows")]
const NSIS_REQUIRED_FILES: &[&str] = &[
"makensis.exe",
"Bin/makensis.exe",
"Stubs/lzma-x86-unicode",
"Stubs/lzma_solid-x86-unicode",
"Plugins/x86-unicode/ApplicationID.dll",
"Plugins/x86-unicode/nsis_tauri_utils.dll",
"Include/MUI2.nsh",
"Include/FileFunc.nsh",
"Include/x64.nsh",
"Include/nsDialogs.nsh",
"Include/WinMessages.nsh",
];
#[cfg(not(target_os = "windows"))]
const NSIS_REQUIRED_FILES: &[&str] = &[
"Plugins/x86-unicode/ApplicationID.dll",
"Plugins/x86-unicode/nsis_tauri_utils.dll",
];
/// Runs all of the commands to build the NSIS installer.
/// Returns a vector of PathBuf that shows where the NSIS installer was created.
pub fn bundle_project(settings: &Settings, updater: bool) -> crate::Result<Vec<PathBuf>> {
let tauri_tools_path = dirs_next::cache_dir().unwrap().join("tauri");
let nsis_toolset_path = tauri_tools_path.join("NSIS");
if !nsis_toolset_path.exists() {
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
} else if NSIS_REQUIRED_FILES
.iter()
.any(|p| !nsis_toolset_path.join(p).exists())
{
warn!("NSIS directory is missing some files. Recreating it.");
std::fs::remove_dir_all(&nsis_toolset_path)?;
get_and_extract_nsis(&nsis_toolset_path, &tauri_tools_path)?;
}
build_nsis_app_installer(settings, &nsis_toolset_path, &tauri_tools_path, updater)
}
// Gets NSIS and verifies the download via Sha1
fn get_and_extract_nsis(nsis_toolset_path: &Path, _tauri_tools_path: &Path) -> crate::Result<()> {
info!("Verifying NSIS package");
#[cfg(target_os = "windows")]
{
let data = download_and_verify(NSIS_URL, NSIS_SHA1, HashAlgorithm::Sha1)?;
info!("extracting NSIS");
extract_zip(&data, _tauri_tools_path)?;
rename(_tauri_tools_path.join("nsis-3.08"), nsis_toolset_path)?;
}
let nsis_plugins = nsis_toolset_path.join("Plugins");
let data = download(NSIS_APPLICATIONID_URL)?;
info!("extracting NSIS ApplicationID plugin");
extract_zip(&data, &nsis_plugins)?;
create_dir_all(nsis_plugins.join("x86-unicode"))?;
copy(
nsis_plugins
.join("ReleaseUnicode")
.join("ApplicationID.dll"),
nsis_plugins.join("x86-unicode").join("ApplicationID.dll"),
)?;
let data = download_and_verify(NSIS_TAURI_UTILS, NSIS_TAURI_UTILS_SHA1, HashAlgorithm::Sha1)?;
write(
nsis_plugins
.join("x86-unicode")
.join("nsis_tauri_utils.dll"),
data,
)?;
Ok(())
}
fn add_build_number_if_needed(version_str: &str) -> anyhow::Result<String> {
let version = semver::Version::parse(version_str).context("invalid app version")?;
if !version.build.is_empty() {
let build = version.build.parse::<u64>();
if build.is_ok() {
return Ok(format!(
"{}.{}.{}.{}",
version.major, version.minor, version.patch, version.build
));
} else {
anyhow::bail!("optional build metadata in app version must be numeric-only");
}
}
Ok(format!(
"{}.{}.{}.0",
version.major, version.minor, version.patch,
))
}
fn build_nsis_app_installer(
settings: &Settings,
_nsis_toolset_path: &Path,
tauri_tools_path: &Path,
updater: bool,
) -> crate::Result<Vec<PathBuf>> {
let arch = match settings.binary_arch() {
"x86_64" => "x64",
"x86" => "x86",
"aarch64" => "arm64",
target => {
return Err(crate::Error::ArchError(format!(
"unsupported target: {}",
target
)))
}
};
info!("Target: {}", arch);
#[cfg(target_os = "windows")]
{
let main_binary = settings
.binaries()
.iter()
.find(|bin| bin.main())
.ok_or_else(|| anyhow::anyhow!("Failed to get main binary"))?;
let app_exe_source = settings.binary_path(main_binary);
try_sign(&app_exe_source, settings)?;
}
#[cfg(not(target_os = "windows"))]
info!("Code signing is currently only supported on Windows hosts, skipping...");
let output_path = settings.project_out_directory().join("nsis").join(arch);
if output_path.exists() {
remove_dir_all(&output_path)?;
}
create_dir_all(&output_path)?;
let mut data = BTreeMap::new();
let bundle_id = settings.bundle_identifier();
let manufacturer = settings
.publisher()
.unwrap_or_else(|| bundle_id.split('.').nth(1).unwrap_or(bundle_id));
#[cfg(not(target_os = "windows"))]
{
let mut dir = dirs_next::cache_dir().unwrap();
dir.extend(["tauri", "NSIS", "Plugins", "x86-unicode"]);
data.insert("additional_plugins_path", to_json(dir));
}
data.insert("arch", to_json(arch));
data.insert("bundle_id", to_json(bundle_id));
data.insert("manufacturer", to_json(manufacturer));
data.insert("product_name", to_json(settings.product_name()));
data.insert("short_description", to_json(settings.short_description()));
data.insert("copyright", to_json(settings.copyright_string()));
let version = settings.version_string();
data.insert("version", to_json(version));
data.insert(
"version_with_build",
to_json(add_build_number_if_needed(version)?),
);
data.insert(
"allow_downgrades",
to_json(settings.windows().allow_downgrades),
);
let mut install_mode = NSISInstallerMode::CurrentUser;
let mut languages = vec!["English".into()];
let mut custom_template_path = None;
let mut custom_language_files = None;
if let Some(nsis) = &settings.windows().nsis {
custom_template_path = nsis.template.clone();
custom_language_files = nsis.custom_language_files.clone();
install_mode = nsis.install_mode;
if let Some(langs) = &nsis.languages {
languages.clear();
languages.extend_from_slice(langs);
}
if let Some(license) = &nsis.license {
data.insert("license", to_json(dunce::canonicalize(license)?));
}
if let Some(installer_icon) = &nsis.installer_icon {
data.insert(
"installer_icon",
to_json(dunce::canonicalize(installer_icon)?),
);
}
if let Some(header_image) = &nsis.header_image {
data.insert("header_image", to_json(dunce::canonicalize(header_image)?));
}
if let Some(sidebar_image) = &nsis.sidebar_image {
data.insert(
"sidebar_image",
to_json(dunce::canonicalize(sidebar_image)?),
);
}
data.insert(
"display_language_selector",
to_json(nsis.display_language_selector && languages.len() > 1),
);
}
data.insert(
"install_mode",
to_json(match install_mode {
NSISInstallerMode::CurrentUser => "currentUser",
NSISInstallerMode::PerMachine => "perMachine",
NSISInstallerMode::Both => "both",
}),
);
let mut languages_data = Vec::new();
for lang in &languages {
if let Some(data) = get_lang_data(lang, custom_language_files.as_ref())? {
languages_data.push(data);
} else {
log::warn!("Custom tauri messages for {lang} are not translated.\nIf it is a valid language listed on <https://github.com/kichik/nsis/tree/9465c08046f00ccb6eda985abbdbf52c275c6c4d/Contrib/Language%20files>, please open a Tauri feature request\n or you can provide a custom language file for it in `tauri.conf.json > tauri > bundle > windows > nsis > custom_language_files`");
}
}
data.insert("languages", to_json(languages.clone()));
data.insert(
"language_files",
to_json(
languages_data
.iter()
.map(|d| d.0.clone())
.collect::<Vec<_>>(),
),
);
let main_binary = settings
.binaries()
.iter()
.find(|bin| bin.main())
.ok_or_else(|| anyhow::anyhow!("Failed to get main binary"))?;
data.insert(
"main_binary_name",
to_json(main_binary.name().replace(".exe", "")),
);
data.insert(
"main_binary_path",
to_json(settings.binary_path(main_binary).with_extension("exe")),
);
let out_file = "nsis-output.exe";
data.insert("out_file", to_json(out_file));
let resources = generate_resource_data(settings)?;
data.insert("resources", to_json(resources));
let binaries = generate_binaries_data(settings)?;
data.insert("binaries", to_json(binaries));
if let Some(file_associations) = &settings.file_associations() {
data.insert("file_associations", to_json(file_associations));
}
let silent_webview2_install = if let WebviewInstallMode::DownloadBootstrapper { silent }
| WebviewInstallMode::EmbedBootstrapper { silent }
| WebviewInstallMode::OfflineInstaller { silent } =
settings.windows().webview_install_mode
{
silent
} else {
true
};
let webview2_install_mode = if updater {
WebviewInstallMode::DownloadBootstrapper {
silent: silent_webview2_install,
}
} else {
let mut webview_install_mode = settings.windows().webview_install_mode.clone();
if let Some(fixed_runtime_path) = settings.windows().webview_fixed_runtime_path.clone() {
webview_install_mode = WebviewInstallMode::FixedRuntime {
path: fixed_runtime_path,
};
} else if let Some(wix) = &settings.windows().wix {
if wix.skip_webview_install {
webview_install_mode = WebviewInstallMode::Skip;
}
}
webview_install_mode
};
let webview2_installer_args = to_json(if silent_webview2_install {
"/silent"
} else {
""
});
data.insert("webview2_installer_args", to_json(webview2_installer_args));
data.insert(
"install_webview2_mode",
to_json(match webview2_install_mode {
WebviewInstallMode::DownloadBootstrapper { silent: _ } => "downloadBootstrapper",
WebviewInstallMode::EmbedBootstrapper { silent: _ } => "embedBootstrapper",
WebviewInstallMode::OfflineInstaller { silent: _ } => "offlineInstaller",
_ => "",
}),
);
match webview2_install_mode {
WebviewInstallMode::EmbedBootstrapper { silent: _ } => {
let webview2_bootstrapper_path = tauri_tools_path.join("MicrosoftEdgeWebview2Setup.exe");
std::fs::write(
&webview2_bootstrapper_path,
download(WEBVIEW2_BOOTSTRAPPER_URL)?,
)?;
data.insert(
"webview2_bootstrapper_path",
to_json(webview2_bootstrapper_path),
);
}
WebviewInstallMode::OfflineInstaller { silent: _ } => {
let guid = if arch == "x64" {
WEBVIEW2_X64_INSTALLER_GUID
} else {
WEBVIEW2_X86_INSTALLER_GUID
};
let offline_installer_path = tauri_tools_path
.join("Webview2OfflineInstaller")
.join(guid)
.join(arch);
create_dir_all(&offline_installer_path)?;
let webview2_installer_path =
offline_installer_path.join("MicrosoftEdgeWebView2RuntimeInstaller.exe");
if !webview2_installer_path.exists() {
std::fs::write(
&webview2_installer_path,
download(
&format!("https://msedge.sf.dl.delivery.mp.microsoft.com/filestreamingservice/files/{}/MicrosoftEdgeWebView2RuntimeInstaller{}.exe",
guid,
arch.to_uppercase(),
),
)?,
)?;
}
data.insert("webview2_installer_path", to_json(webview2_installer_path));
}
_ => {}
}
let mut handlebars = Handlebars::new();
handlebars.register_helper("or", Box::new(handlebars_or));
handlebars.register_helper("association-description", Box::new(association_description));
handlebars.register_escape_fn(|s| {
let mut output = String::new();
for c in s.chars() {
match c {
'\"' => output.push_str("$\\\""),
'$' => output.push_str("$$"),
'`' => output.push_str("$\\`"),
'\n' => output.push_str("$\\n"),
'\t' => output.push_str("$\\t"),
'\r' => output.push_str("$\\r"),
_ => output.push(c),
}
}
output
});
if let Some(path) = custom_template_path {
handlebars
.register_template_string("installer.nsi", std::fs::read_to_string(path)?)
.map_err(|e| e.to_string())
.expect("Failed to setup custom handlebar template");
} else {
handlebars
.register_template_string("installer.nsi", include_str!("./templates/installer.nsi"))
.map_err(|e| e.to_string())
.expect("Failed to setup handlebar template");
}
write_ut16_le_with_bom(
&output_path.join("FileAssociation.nsh"),
include_str!("./templates/FileAssociation.nsh"),
)?;
let installer_nsi_path = output_path.join("installer.nsi");
write_ut16_le_with_bom(
&installer_nsi_path,
handlebars.render("installer.nsi", &data)?.as_str(),
)?;
for (lang, data) in languages_data.iter() {
if let Some(content) = data {
write_ut16_le_with_bom(output_path.join(lang).with_extension("nsh"), content)?;
}
}
let package_base_name = format!(
"{}_{}_{}-setup",
main_binary.name().replace(".exe", ""),
settings.version_string(),
arch,
);
let nsis_output_path = output_path.join(out_file);
let nsis_installer_path = settings.project_out_directory().to_path_buf().join(format!(
"bundle/{}/{}.exe",
if updater {
NSIS_UPDATER_OUTPUT_FOLDER_NAME
} else {
NSIS_OUTPUT_FOLDER_NAME
},
package_base_name
));
create_dir_all(nsis_installer_path.parent().unwrap())?;
info!(action = "Running"; "makensis.exe to produce {}", display_path(&nsis_installer_path));
#[cfg(target_os = "windows")]
let mut nsis_cmd = Command::new(_nsis_toolset_path.join("makensis.exe"));
#[cfg(not(target_os = "windows"))]
let mut nsis_cmd = Command::new("makensis");
nsis_cmd
.arg(match settings.log_level() {
log::Level::Error => "-V1",
log::Level::Warn => "-V2",
log::Level::Info => "-V3",
_ => "-V4",
})
.arg(installer_nsi_path)
.current_dir(output_path)
.piped()
.context("error running makensis.exe")?;
rename(nsis_output_path, &nsis_installer_path)?;
// Code signing is currently only supported on Windows hosts
#[cfg(target_os = "windows")]
try_sign(&nsis_installer_path, settings)?;
Ok(vec![nsis_installer_path])
}
fn handlebars_or(
h: &handlebars::Helper<'_, '_>,
_: &Handlebars<'_>,
_: &handlebars::Context,
_: &mut handlebars::RenderContext<'_, '_>,
out: &mut dyn handlebars::Output,
) -> handlebars::HelperResult {
let param1 = h.param(0).unwrap().render();
let param2 = h.param(1).unwrap();
out.write(&if param1.is_empty() {
param2.render()
} else {
param1
})?;
Ok(())
}
fn association_description(
h: &handlebars::Helper<'_, '_>,
_: &Handlebars<'_>,
_: &handlebars::Context,
_: &mut handlebars::RenderContext<'_, '_>,
out: &mut dyn handlebars::Output,
) -> handlebars::HelperResult {
let description = h.param(0).unwrap().render();
let ext = h.param(1).unwrap();
out.write(&if description.is_empty() {
format!("{} File", ext.render().to_uppercase())
} else {
description
})?;
Ok(())
}
/// BTreeMap<OriginalPath, (ParentOfTargetPath, TargetPath)>
type ResourcesMap = BTreeMap<PathBuf, (String, PathBuf)>;
fn generate_resource_data(settings: &Settings) -> crate::Result<ResourcesMap> {
let mut resources = ResourcesMap::new();
let cwd = std::env::current_dir()?;
let mut added_resources = Vec::new();
for src in settings.resource_files() {
let src = src?;
let resource_path = dunce::canonicalize(cwd.join(&src))?;
// In some glob resource paths like `assets/**/*` a file might appear twice
// because the `tauri_utils::resources::ResourcePaths` iterator also reads a directory
// when it finds one. So we must check it before processing the file.
if added_resources.contains(&resource_path) {
continue;
}
added_resources.push(resource_path.clone());
let target_path = resource_relpath(&src);
resources.insert(
resource_path,
(
target_path
.parent()
.map(|p| p.to_string_lossy().to_string())
.unwrap_or_default(),
target_path,
),
);
}
Ok(resources)
}
/// BTreeMap<OriginalPath, TargetFileName>
type BinariesMap = BTreeMap<PathBuf, String>;
fn generate_binaries_data(settings: &Settings) -> crate::Result<BinariesMap> {
let mut binaries = BinariesMap::new();
let cwd = std::env::current_dir()?;
for src in settings.external_binaries() {
let src = src?;
let binary_path = dunce::canonicalize(cwd.join(&src))?;
let dest_filename = src
.file_name()
.expect("failed to extract external binary filename")
.to_string_lossy()
.replace(&format!("-{}", settings.target()), "");
binaries.insert(binary_path, dest_filename);
}
for bin in settings.binaries() {
if !bin.main() {
let bin_path = settings.binary_path(bin);
binaries.insert(
bin_path.clone(),
bin_path
.file_name()
.expect("failed to extract external binary filename")
.to_string_lossy()
.to_string(),
);
}
}
Ok(binaries)
}
fn get_lang_data(
lang: &str,
custom_lang_files: Option<&HashMap<String, PathBuf>>,
) -> crate::Result<Option<(PathBuf, Option<&'static str>)>> |
fn write_ut16_le_with_bom<P: AsRef<Path>>(path: P, content: &str) -> crate::Result<()> {
use std::fs::File;
use std::io::{BufWriter, Write};
let file = File::create(path)?;
let mut output = BufWriter::new(file);
output.write_all(&[0xFF, 0xFE])?; // the BOM part
for utf16 in content.encode_utf16() {
output.write_all(&utf16.to_le_bytes())?;
}
Ok(())
}
| {
if let Some(path) = custom_lang_files.and_then(|h| h.get(lang)) {
return Ok(Some((dunce::canonicalize(path)?, None)));
}
let lang_path = PathBuf::from(format!("{lang}.nsh"));
let lang_content = match lang.to_lowercase().as_str() {
"arabic" => Some(include_str!("./templates/nsis-languages/Arabic.nsh")),
"bulgarian" => Some(include_str!("./templates/nsis-languages/Bulgarian.nsh")),
"dutch" => Some(include_str!("./templates/nsis-languages/Dutch.nsh")),
"english" => Some(include_str!("./templates/nsis-languages/English.nsh")),
"japanese" => Some(include_str!("./templates/nsis-languages/Japanese.nsh")),
"korean" => Some(include_str!("./templates/nsis-languages/Korean.nsh")),
"portuguesebr" => Some(include_str!("./templates/nsis-languages/PortugueseBR.nsh")),
"tradchinese" => Some(include_str!("./templates/nsis-languages/TradChinese.nsh")),
"simpchinese" => Some(include_str!("./templates/nsis-languages/SimpChinese.nsh")),
"french" => Some(include_str!("./templates/nsis-languages/French.nsh")),
"spanish" => Some(include_str!("./templates/nsis-languages/Spanish.nsh")),
"spanishinternational" => Some(include_str!(
"./templates/nsis-languages/SpanishInternational.nsh"
)),
"persian" => Some(include_str!("./templates/nsis-languages/Persian.nsh")),
"turkish" => Some(include_str!("./templates/nsis-languages/Turkish.nsh")),
"swedish" => Some(include_str!("./templates/nsis-languages/Swedish.nsh")),
_ => return Ok(None),
};
Ok(Some((lang_path, lang_content)))
} | identifier_body |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
Package automation contains code to execute high-level cluster operations
(e.g. resharding) as a series of low-level operations
(e.g. vtctl, shell commands, ...).
*/
package automation
import (
"errors"
"fmt"
"sync"
"vitess.io/vitess/go/vt/proto/automationservice"
"context"
"vitess.io/vitess/go/vt/log"
automationpb "vitess.io/vitess/go/vt/proto/automation"
"vitess.io/vitess/go/vt/vterrors"
)
type schedulerState int32
const (
stateNotRunning schedulerState = iota
stateRunning
stateShuttingDown
stateShutdown
)
type taskCreator func(string) Task
// Scheduler executes automation tasks and maintains the execution state.
type Scheduler struct {
automationservice.UnimplementedAutomationServer
idGenerator IDGenerator
mu sync.Mutex
// Guarded by "mu".
registeredClusterOperations map[string]bool
// Guarded by "mu".
toBeScheduledClusterOperations chan ClusterOperationInstance
// Guarded by "mu".
state schedulerState
// Guarded by "taskCreatorMu". May be overridden by testing code.
taskCreator taskCreator
taskCreatorMu sync.Mutex
pendingOpsWg *sync.WaitGroup
muOpList sync.Mutex
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
// This map contains a copy of the ClusterOperationInstance which is currently processed.
// The scheduler may update the copy with the latest status.
activeClusterOperations map[string]ClusterOperationInstance
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
finishedClusterOperations map[string]ClusterOperationInstance
}
// NewScheduler creates a new instance.
func NewScheduler() (*Scheduler, error) {
defaultClusterOperations := map[string]bool{
"HorizontalReshardingTask": true,
"VerticalSplitTask": true,
}
s := &Scheduler{
registeredClusterOperations: defaultClusterOperations,
idGenerator: IDGenerator{},
toBeScheduledClusterOperations: make(chan ClusterOperationInstance, 10),
state: stateNotRunning,
taskCreator: defaultTaskCreator,
pendingOpsWg: &sync.WaitGroup{},
activeClusterOperations: make(map[string]ClusterOperationInstance),
finishedClusterOperations: make(map[string]ClusterOperationInstance),
}
return s, nil
}
func (s *Scheduler) registerClusterOperation(clusterOperationName string) {
s.mu.Lock()
defer s.mu.Unlock()
s.registeredClusterOperations[clusterOperationName] = true
}
// Run processes queued cluster operations.
func (s *Scheduler) Run() {
s.mu.Lock()
s.state = stateRunning
s.mu.Unlock()
s.startProcessRequestsLoop()
}
func (s *Scheduler) startProcessRequestsLoop() {
// Use a WaitGroup instead of just a done channel, because we want
// to be able to shut down the scheduler even if Run() was never executed.
s.pendingOpsWg.Add(1)
go s.processRequestsLoop()
}
func (s *Scheduler) processRequestsLoop() {
defer s.pendingOpsWg.Done()
for op := range s.toBeScheduledClusterOperations {
s.processClusterOperation(op)
}
log.Infof("Stopped processing loop for ClusterOperations.")
}
func (s *Scheduler) processClusterOperation(clusterOp ClusterOperationInstance) {
if clusterOp.State == automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE {
log.Infof("ClusterOperation: %v skipping because it is already done. Details: %v", clusterOp.Id, clusterOp)
return
}
log.Infof("ClusterOperation: %v running. Details: %v", clusterOp.Id, clusterOp)
clusterOpLoop:
for i := 0; i < len(clusterOp.SerialTasks); i++ {
taskContainer := clusterOp.SerialTasks[i]
for _, taskProto := range taskContainer.ParallelTasks {
newTaskContainers, output, err := s.runTask(taskProto, clusterOp.Id)
if err != nil {
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
} else {
MarkTaskSucceeded(taskProto, output)
}
if newTaskContainers != nil {
// Make sure all new tasks do not miss any required parameters.
err := s.validateTaskContainers(newTaskContainers)
if err != nil {
err = vterrors.Wrapf(err, "task: %v (%v/%v) emitted a new task which is not valid. Error: %v", taskProto.Name, clusterOp.Id, taskProto.Id, err)
log.Error(err)
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
}
clusterOp.InsertTaskContainers(newTaskContainers, i+1)
log.Infof("ClusterOperation: %v %d new task containers added by %v (%v/%v). Updated ClusterOperation: %v",
clusterOp.Id, len(newTaskContainers), taskProto.Name, clusterOp.Id, taskProto.Id, clusterOp)
}
s.Checkpoint(clusterOp)
}
}
clusterOp.State = automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE
log.Infof("ClusterOperation: %v finished. Details: %v", clusterOp.Id, clusterOp)
s.Checkpoint(clusterOp)
// Move operation from active to finished.
s.muOpList.Lock()
defer s.muOpList.Unlock()
if _, ok := s.activeClusterOperations[clusterOp.Id]; !ok |
delete(s.activeClusterOperations, clusterOp.Id)
s.finishedClusterOperations[clusterOp.Id] = clusterOp
}
func (s *Scheduler) runTask(taskProto *automationpb.Task, clusterOpID string) ([]*automationpb.TaskContainer, string, error) {
if taskProto.State == automationpb.TaskState_DONE {
// Task is already done (e.g. because we resume from a checkpoint).
if taskProto.Error != "" {
log.Errorf("Task: %v (%v/%v) failed before. Aborting the ClusterOperation. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto.Error, taskProto)
return nil, "", errors.New(taskProto.Error)
}
log.Infof("Task: %v (%v/%v) skipped because it is already done. Full Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
return nil, taskProto.Output, nil
}
task, err := s.createTaskInstance(taskProto.Name)
if err != nil {
log.Errorf("Task: %v (%v/%v) could not be instantiated. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, err, taskProto)
return nil, "", err
}
taskProto.State = automationpb.TaskState_RUNNING
log.Infof("Task: %v (%v/%v) running. Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
newTaskContainers, output, err := task.Run(taskProto.Parameters)
log.Infof("Task: %v (%v/%v) finished. newTaskContainers: %v, output: %v, error: %v", taskProto.Name, clusterOpID, taskProto.Id, newTaskContainers, output, err)
return newTaskContainers, output, err
}
func (s *Scheduler) validateTaskContainers(newTaskContainers []*automationpb.TaskContainer) error {
for _, newTaskContainer := range newTaskContainers {
for _, newTaskProto := range newTaskContainer.ParallelTasks {
err := s.validateTaskSpecification(newTaskProto.Name, newTaskProto.Parameters)
if err != nil {
return fmt.Errorf("error: %v task: %v", err, newTaskProto)
}
}
}
return nil
}
func defaultTaskCreator(taskName string) Task {
switch taskName {
case "HorizontalReshardingTask":
return &HorizontalReshardingTask{}
case "VerticalSplitTask":
return &VerticalSplitTask{}
case "CopySchemaShardTask":
return &CopySchemaShardTask{}
case "MigrateServedFromTask":
return &MigrateServedFromTask{}
case "MigrateServedTypesTask":
return &MigrateServedTypesTask{}
case "RebuildKeyspaceGraph":
return &RebuildKeyspaceGraphTask{}
case "SplitCloneTask":
return &SplitCloneTask{}
case "SplitDiffTask":
return &SplitDiffTask{}
case "VerticalSplitCloneTask":
return &VerticalSplitCloneTask{}
case "VerticalSplitDiffTask":
return &VerticalSplitDiffTask{}
case "WaitForFilteredReplicationTask":
return &WaitForFilteredReplicationTask{}
default:
return nil
}
}
func (s *Scheduler) setTaskCreator(creator taskCreator) {
s.taskCreatorMu.Lock()
defer s.taskCreatorMu.Unlock()
s.taskCreator = creator
}
func (s *Scheduler) validateTaskSpecification(taskName string, parameters map[string]string) error {
taskInstanceForParametersCheck, err := s.createTaskInstance(taskName)
if err != nil {
return err
}
errParameters := validateParameters(taskInstanceForParametersCheck, parameters)
if errParameters != nil {
return errParameters
}
return nil
}
func (s *Scheduler) createTaskInstance(taskName string) (Task, error) {
s.taskCreatorMu.Lock()
taskCreator := s.taskCreator
s.taskCreatorMu.Unlock()
task := taskCreator(taskName)
if task == nil {
return nil, fmt.Errorf("no implementation found for: %v", taskName)
}
return task, nil
}
// validateParameters returns an error if not all required parameters are provided in "parameters".
// Unknown parameters (neither required nor optional) result in an error.
func validateParameters(task Task, parameters map[string]string) error {
validParams := make(map[string]bool)
var missingParams []string
for _, reqParam := range task.RequiredParameters() {
if _, ok := parameters[reqParam]; ok {
validParams[reqParam] = true
} else {
missingParams = append(missingParams, reqParam)
}
}
if len(missingParams) > 0 {
return fmt.Errorf("required parameters are missing: %v", missingParams)
}
for _, optParam := range task.OptionalParameters() {
validParams[optParam] = true
}
for param := range parameters {
if !validParams[param] {
return fmt.Errorf("parameter %v is not allowed. Allowed required parameters: %v optional parameters: %v",
param, task.RequiredParameters(), task.OptionalParameters())
}
}
return nil
}
// EnqueueClusterOperation can be used to start a new cluster operation.
func (s *Scheduler) EnqueueClusterOperation(ctx context.Context, req *automationpb.EnqueueClusterOperationRequest) (*automationpb.EnqueueClusterOperationResponse, error) {
s.mu.Lock()
defer s.mu.Unlock()
if s.state != stateRunning {
return nil, fmt.Errorf("scheduler is not running. State: %v", s.state)
}
if !s.registeredClusterOperations[req.Name] {
return nil, fmt.Errorf("no ClusterOperation with name: %v is registered", req.Name)
}
err := s.validateTaskSpecification(req.Name, req.Parameters)
if err != nil {
return nil, err
}
clusterOpID := s.idGenerator.GetNextID()
taskIDGenerator := IDGenerator{}
initialTask := NewTaskContainerWithSingleTask(req.Name, req.Parameters)
clusterOp := NewClusterOperationInstance(clusterOpID, initialTask, &taskIDGenerator)
s.muOpList.Lock()
s.activeClusterOperations[clusterOpID] = clusterOp.Clone()
s.muOpList.Unlock()
s.toBeScheduledClusterOperations <- clusterOp
return &automationpb.EnqueueClusterOperationResponse{
Id: clusterOp.Id,
}, nil
}
// findClusterOp checks for a given ClusterOperation ID if it's in the list of active or finished operations.
func (s *Scheduler) findClusterOp(id string) (ClusterOperationInstance, error) {
var ok bool
var clusterOp ClusterOperationInstance
s.muOpList.Lock()
defer s.muOpList.Unlock()
clusterOp, ok = s.activeClusterOperations[id]
if !ok {
clusterOp, ok = s.finishedClusterOperations[id]
}
if !ok {
return clusterOp, fmt.Errorf("ClusterOperation with id: %v not found", id)
}
return clusterOp.Clone(), nil
}
// Checkpoint should be called every time the state of the cluster op changes.
// It is used to update the copy of the state in activeClusterOperations.
func (s *Scheduler) Checkpoint(clusterOp ClusterOperationInstance) {
// TODO(mberlin): Add here support for persistent checkpoints.
s.muOpList.Lock()
defer s.muOpList.Unlock()
s.activeClusterOperations[clusterOp.Id] = clusterOp.Clone()
}
// GetClusterOperationDetails can be used to query the full details of active or finished operations.
func (s *Scheduler) GetClusterOperationDetails(ctx context.Context, req *automationpb.GetClusterOperationDetailsRequest) (*automationpb.GetClusterOperationDetailsResponse, error) {
clusterOp, err := s.findClusterOp(req.Id)
if err != nil {
return nil, err
}
return &automationpb.GetClusterOperationDetailsResponse{
ClusterOp: clusterOp.ClusterOperation,
}, nil
}
// ShutdownAndWait shuts down the scheduler and waits infinitely until all pending cluster operations have finished.
func (s *Scheduler) ShutdownAndWait() {
s.mu.Lock()
if s.state != stateShuttingDown {
s.state = stateShuttingDown
close(s.toBeScheduledClusterOperations)
}
s.mu.Unlock()
log.Infof("Scheduler was shut down. Waiting for pending ClusterOperations to finish.")
s.pendingOpsWg.Wait()
s.mu.Lock()
s.state = stateShutdown
s.mu.Unlock()
log.Infof("All pending ClusterOperations finished.")
}
| {
panic("Pending ClusterOperation was not recorded as active, but should have.")
} | conditional_block |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
Package automation contains code to execute high-level cluster operations
(e.g. resharding) as a series of low-level operations
(e.g. vtctl, shell commands, ...).
*/
package automation
import (
"errors"
"fmt"
"sync"
"vitess.io/vitess/go/vt/proto/automationservice"
"context"
"vitess.io/vitess/go/vt/log"
automationpb "vitess.io/vitess/go/vt/proto/automation"
"vitess.io/vitess/go/vt/vterrors"
)
type schedulerState int32
const (
stateNotRunning schedulerState = iota
stateRunning
stateShuttingDown
stateShutdown
)
type taskCreator func(string) Task
// Scheduler executes automation tasks and maintains the execution state.
type Scheduler struct {
automationservice.UnimplementedAutomationServer
idGenerator IDGenerator
mu sync.Mutex
// Guarded by "mu".
registeredClusterOperations map[string]bool
// Guarded by "mu".
toBeScheduledClusterOperations chan ClusterOperationInstance
// Guarded by "mu".
state schedulerState
// Guarded by "taskCreatorMu". May be overridden by testing code.
taskCreator taskCreator
taskCreatorMu sync.Mutex
pendingOpsWg *sync.WaitGroup
muOpList sync.Mutex
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
// This map contains a copy of the ClusterOperationInstance which is currently processed.
// The scheduler may update the copy with the latest status.
activeClusterOperations map[string]ClusterOperationInstance
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
finishedClusterOperations map[string]ClusterOperationInstance
}
// NewScheduler creates a new instance.
func NewScheduler() (*Scheduler, error) {
defaultClusterOperations := map[string]bool{
"HorizontalReshardingTask": true,
"VerticalSplitTask": true,
}
s := &Scheduler{
registeredClusterOperations: defaultClusterOperations,
idGenerator: IDGenerator{},
toBeScheduledClusterOperations: make(chan ClusterOperationInstance, 10),
state: stateNotRunning,
taskCreator: defaultTaskCreator,
pendingOpsWg: &sync.WaitGroup{},
activeClusterOperations: make(map[string]ClusterOperationInstance),
finishedClusterOperations: make(map[string]ClusterOperationInstance),
}
return s, nil
}
func (s *Scheduler) registerClusterOperation(clusterOperationName string) {
s.mu.Lock()
defer s.mu.Unlock()
s.registeredClusterOperations[clusterOperationName] = true
}
// Run processes queued cluster operations.
func (s *Scheduler) Run() {
s.mu.Lock()
s.state = stateRunning
s.mu.Unlock()
s.startProcessRequestsLoop()
}
func (s *Scheduler) startProcessRequestsLoop() {
// Use a WaitGroup instead of just a done channel, because we want
// to be able to shut down the scheduler even if Run() was never executed.
s.pendingOpsWg.Add(1)
go s.processRequestsLoop()
}
func (s *Scheduler) processRequestsLoop() {
defer s.pendingOpsWg.Done()
for op := range s.toBeScheduledClusterOperations {
s.processClusterOperation(op)
}
log.Infof("Stopped processing loop for ClusterOperations.")
}
func (s *Scheduler) processClusterOperation(clusterOp ClusterOperationInstance) {
if clusterOp.State == automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE {
log.Infof("ClusterOperation: %v skipping because it is already done. Details: %v", clusterOp.Id, clusterOp)
return
}
log.Infof("ClusterOperation: %v running. Details: %v", clusterOp.Id, clusterOp)
clusterOpLoop:
for i := 0; i < len(clusterOp.SerialTasks); i++ {
taskContainer := clusterOp.SerialTasks[i]
for _, taskProto := range taskContainer.ParallelTasks {
newTaskContainers, output, err := s.runTask(taskProto, clusterOp.Id)
if err != nil {
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
} else {
MarkTaskSucceeded(taskProto, output)
}
if newTaskContainers != nil {
// Make sure all new tasks do not miss any required parameters.
err := s.validateTaskContainers(newTaskContainers)
if err != nil {
err = vterrors.Wrapf(err, "task: %v (%v/%v) emitted a new task which is not valid. Error: %v", taskProto.Name, clusterOp.Id, taskProto.Id, err)
log.Error(err)
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
}
clusterOp.InsertTaskContainers(newTaskContainers, i+1)
log.Infof("ClusterOperation: %v %d new task containers added by %v (%v/%v). Updated ClusterOperation: %v",
clusterOp.Id, len(newTaskContainers), taskProto.Name, clusterOp.Id, taskProto.Id, clusterOp)
}
s.Checkpoint(clusterOp)
}
}
clusterOp.State = automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE
log.Infof("ClusterOperation: %v finished. Details: %v", clusterOp.Id, clusterOp)
s.Checkpoint(clusterOp)
// Move operation from active to finished.
s.muOpList.Lock()
defer s.muOpList.Unlock()
if _, ok := s.activeClusterOperations[clusterOp.Id]; !ok {
panic("Pending ClusterOperation was not recorded as active, but should have.")
}
delete(s.activeClusterOperations, clusterOp.Id)
s.finishedClusterOperations[clusterOp.Id] = clusterOp
}
func (s *Scheduler) runTask(taskProto *automationpb.Task, clusterOpID string) ([]*automationpb.TaskContainer, string, error) {
if taskProto.State == automationpb.TaskState_DONE {
// Task is already done (e.g. because we resume from a checkpoint).
if taskProto.Error != "" {
log.Errorf("Task: %v (%v/%v) failed before. Aborting the ClusterOperation. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto.Error, taskProto)
return nil, "", errors.New(taskProto.Error)
}
log.Infof("Task: %v (%v/%v) skipped because it is already done. Full Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
return nil, taskProto.Output, nil
}
task, err := s.createTaskInstance(taskProto.Name)
if err != nil {
log.Errorf("Task: %v (%v/%v) could not be instantiated. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, err, taskProto)
return nil, "", err
}
taskProto.State = automationpb.TaskState_RUNNING
log.Infof("Task: %v (%v/%v) running. Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
newTaskContainers, output, err := task.Run(taskProto.Parameters)
log.Infof("Task: %v (%v/%v) finished. newTaskContainers: %v, output: %v, error: %v", taskProto.Name, clusterOpID, taskProto.Id, newTaskContainers, output, err)
return newTaskContainers, output, err
}
func (s *Scheduler) validateTaskContainers(newTaskContainers []*automationpb.TaskContainer) error {
for _, newTaskContainer := range newTaskContainers {
for _, newTaskProto := range newTaskContainer.ParallelTasks {
err := s.validateTaskSpecification(newTaskProto.Name, newTaskProto.Parameters)
if err != nil {
return fmt.Errorf("error: %v task: %v", err, newTaskProto)
}
}
}
return nil
}
func defaultTaskCreator(taskName string) Task {
switch taskName {
case "HorizontalReshardingTask":
return &HorizontalReshardingTask{}
case "VerticalSplitTask":
return &VerticalSplitTask{}
case "CopySchemaShardTask":
return &CopySchemaShardTask{}
case "MigrateServedFromTask":
return &MigrateServedFromTask{}
case "MigrateServedTypesTask":
return &MigrateServedTypesTask{}
case "RebuildKeyspaceGraph":
return &RebuildKeyspaceGraphTask{}
case "SplitCloneTask":
return &SplitCloneTask{}
case "SplitDiffTask":
return &SplitDiffTask{}
case "VerticalSplitCloneTask":
return &VerticalSplitCloneTask{}
case "VerticalSplitDiffTask":
return &VerticalSplitDiffTask{}
case "WaitForFilteredReplicationTask":
return &WaitForFilteredReplicationTask{}
default:
return nil
}
}
func (s *Scheduler) setTaskCreator(creator taskCreator) {
s.taskCreatorMu.Lock()
defer s.taskCreatorMu.Unlock()
s.taskCreator = creator
}
func (s *Scheduler) validateTaskSpecification(taskName string, parameters map[string]string) error |
func (s *Scheduler) createTaskInstance(taskName string) (Task, error) {
s.taskCreatorMu.Lock()
taskCreator := s.taskCreator
s.taskCreatorMu.Unlock()
task := taskCreator(taskName)
if task == nil {
return nil, fmt.Errorf("no implementation found for: %v", taskName)
}
return task, nil
}
// validateParameters returns an error if not all required parameters are provided in "parameters".
// Unknown parameters (neither required nor optional) result in an error.
func validateParameters(task Task, parameters map[string]string) error {
validParams := make(map[string]bool)
var missingParams []string
for _, reqParam := range task.RequiredParameters() {
if _, ok := parameters[reqParam]; ok {
validParams[reqParam] = true
} else {
missingParams = append(missingParams, reqParam)
}
}
if len(missingParams) > 0 {
return fmt.Errorf("required parameters are missing: %v", missingParams)
}
for _, optParam := range task.OptionalParameters() {
validParams[optParam] = true
}
for param := range parameters {
if !validParams[param] {
return fmt.Errorf("parameter %v is not allowed. Allowed required parameters: %v optional parameters: %v",
param, task.RequiredParameters(), task.OptionalParameters())
}
}
return nil
}
// EnqueueClusterOperation can be used to start a new cluster operation.
func (s *Scheduler) EnqueueClusterOperation(ctx context.Context, req *automationpb.EnqueueClusterOperationRequest) (*automationpb.EnqueueClusterOperationResponse, error) {
s.mu.Lock()
defer s.mu.Unlock()
if s.state != stateRunning {
return nil, fmt.Errorf("scheduler is not running. State: %v", s.state)
}
if !s.registeredClusterOperations[req.Name] {
return nil, fmt.Errorf("no ClusterOperation with name: %v is registered", req.Name)
}
err := s.validateTaskSpecification(req.Name, req.Parameters)
if err != nil {
return nil, err
}
clusterOpID := s.idGenerator.GetNextID()
taskIDGenerator := IDGenerator{}
initialTask := NewTaskContainerWithSingleTask(req.Name, req.Parameters)
clusterOp := NewClusterOperationInstance(clusterOpID, initialTask, &taskIDGenerator)
s.muOpList.Lock()
s.activeClusterOperations[clusterOpID] = clusterOp.Clone()
s.muOpList.Unlock()
s.toBeScheduledClusterOperations <- clusterOp
return &automationpb.EnqueueClusterOperationResponse{
Id: clusterOp.Id,
}, nil
}
// findClusterOp checks for a given ClusterOperation ID if it's in the list of active or finished operations.
func (s *Scheduler) findClusterOp(id string) (ClusterOperationInstance, error) {
var ok bool
var clusterOp ClusterOperationInstance
s.muOpList.Lock()
defer s.muOpList.Unlock()
clusterOp, ok = s.activeClusterOperations[id]
if !ok {
clusterOp, ok = s.finishedClusterOperations[id]
}
if !ok {
return clusterOp, fmt.Errorf("ClusterOperation with id: %v not found", id)
}
return clusterOp.Clone(), nil
}
// Checkpoint should be called every time the state of the cluster op changes.
// It is used to update the copy of the state in activeClusterOperations.
func (s *Scheduler) Checkpoint(clusterOp ClusterOperationInstance) {
// TODO(mberlin): Add here support for persistent checkpoints.
s.muOpList.Lock()
defer s.muOpList.Unlock()
s.activeClusterOperations[clusterOp.Id] = clusterOp.Clone()
}
// GetClusterOperationDetails can be used to query the full details of active or finished operations.
func (s *Scheduler) GetClusterOperationDetails(ctx context.Context, req *automationpb.GetClusterOperationDetailsRequest) (*automationpb.GetClusterOperationDetailsResponse, error) {
clusterOp, err := s.findClusterOp(req.Id)
if err != nil {
return nil, err
}
return &automationpb.GetClusterOperationDetailsResponse{
ClusterOp: clusterOp.ClusterOperation,
}, nil
}
// ShutdownAndWait shuts down the scheduler and waits infinitely until all pending cluster operations have finished.
func (s *Scheduler) ShutdownAndWait() {
s.mu.Lock()
if s.state != stateShuttingDown {
s.state = stateShuttingDown
close(s.toBeScheduledClusterOperations)
}
s.mu.Unlock()
log.Infof("Scheduler was shut down. Waiting for pending ClusterOperations to finish.")
s.pendingOpsWg.Wait()
s.mu.Lock()
s.state = stateShutdown
s.mu.Unlock()
log.Infof("All pending ClusterOperations finished.")
}
| {
taskInstanceForParametersCheck, err := s.createTaskInstance(taskName)
if err != nil {
return err
}
errParameters := validateParameters(taskInstanceForParametersCheck, parameters)
if errParameters != nil {
return errParameters
}
return nil
} | identifier_body |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
Package automation contains code to execute high-level cluster operations
(e.g. resharding) as a series of low-level operations
(e.g. vtctl, shell commands, ...).
*/
package automation
import (
"errors"
"fmt"
"sync"
"vitess.io/vitess/go/vt/proto/automationservice"
"context"
"vitess.io/vitess/go/vt/log"
automationpb "vitess.io/vitess/go/vt/proto/automation"
"vitess.io/vitess/go/vt/vterrors"
)
type schedulerState int32
const (
stateNotRunning schedulerState = iota
stateRunning
stateShuttingDown
stateShutdown
)
type taskCreator func(string) Task
// Scheduler executes automation tasks and maintains the execution state.
type Scheduler struct {
automationservice.UnimplementedAutomationServer
idGenerator IDGenerator
mu sync.Mutex
// Guarded by "mu".
registeredClusterOperations map[string]bool
// Guarded by "mu".
toBeScheduledClusterOperations chan ClusterOperationInstance
// Guarded by "mu".
state schedulerState
// Guarded by "taskCreatorMu". May be overridden by testing code.
taskCreator taskCreator
taskCreatorMu sync.Mutex
pendingOpsWg *sync.WaitGroup
muOpList sync.Mutex
// Guarded by "muOpList". | // The scheduler may update the copy with the latest status.
activeClusterOperations map[string]ClusterOperationInstance
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
finishedClusterOperations map[string]ClusterOperationInstance
}
// NewScheduler creates a new instance.
func NewScheduler() (*Scheduler, error) {
defaultClusterOperations := map[string]bool{
"HorizontalReshardingTask": true,
"VerticalSplitTask": true,
}
s := &Scheduler{
registeredClusterOperations: defaultClusterOperations,
idGenerator: IDGenerator{},
toBeScheduledClusterOperations: make(chan ClusterOperationInstance, 10),
state: stateNotRunning,
taskCreator: defaultTaskCreator,
pendingOpsWg: &sync.WaitGroup{},
activeClusterOperations: make(map[string]ClusterOperationInstance),
finishedClusterOperations: make(map[string]ClusterOperationInstance),
}
return s, nil
}
func (s *Scheduler) registerClusterOperation(clusterOperationName string) {
s.mu.Lock()
defer s.mu.Unlock()
s.registeredClusterOperations[clusterOperationName] = true
}
// Run processes queued cluster operations.
func (s *Scheduler) Run() {
s.mu.Lock()
s.state = stateRunning
s.mu.Unlock()
s.startProcessRequestsLoop()
}
func (s *Scheduler) startProcessRequestsLoop() {
// Use a WaitGroup instead of just a done channel, because we want
// to be able to shut down the scheduler even if Run() was never executed.
s.pendingOpsWg.Add(1)
go s.processRequestsLoop()
}
func (s *Scheduler) processRequestsLoop() {
defer s.pendingOpsWg.Done()
for op := range s.toBeScheduledClusterOperations {
s.processClusterOperation(op)
}
log.Infof("Stopped processing loop for ClusterOperations.")
}
func (s *Scheduler) processClusterOperation(clusterOp ClusterOperationInstance) {
if clusterOp.State == automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE {
log.Infof("ClusterOperation: %v skipping because it is already done. Details: %v", clusterOp.Id, clusterOp)
return
}
log.Infof("ClusterOperation: %v running. Details: %v", clusterOp.Id, clusterOp)
clusterOpLoop:
for i := 0; i < len(clusterOp.SerialTasks); i++ {
taskContainer := clusterOp.SerialTasks[i]
for _, taskProto := range taskContainer.ParallelTasks {
newTaskContainers, output, err := s.runTask(taskProto, clusterOp.Id)
if err != nil {
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
} else {
MarkTaskSucceeded(taskProto, output)
}
if newTaskContainers != nil {
// Make sure all new tasks do not miss any required parameters.
err := s.validateTaskContainers(newTaskContainers)
if err != nil {
err = vterrors.Wrapf(err, "task: %v (%v/%v) emitted a new task which is not valid. Error: %v", taskProto.Name, clusterOp.Id, taskProto.Id, err)
log.Error(err)
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
}
clusterOp.InsertTaskContainers(newTaskContainers, i+1)
log.Infof("ClusterOperation: %v %d new task containers added by %v (%v/%v). Updated ClusterOperation: %v",
clusterOp.Id, len(newTaskContainers), taskProto.Name, clusterOp.Id, taskProto.Id, clusterOp)
}
s.Checkpoint(clusterOp)
}
}
clusterOp.State = automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE
log.Infof("ClusterOperation: %v finished. Details: %v", clusterOp.Id, clusterOp)
s.Checkpoint(clusterOp)
// Move operation from active to finished.
s.muOpList.Lock()
defer s.muOpList.Unlock()
if _, ok := s.activeClusterOperations[clusterOp.Id]; !ok {
panic("Pending ClusterOperation was not recorded as active, but should have.")
}
delete(s.activeClusterOperations, clusterOp.Id)
s.finishedClusterOperations[clusterOp.Id] = clusterOp
}
func (s *Scheduler) runTask(taskProto *automationpb.Task, clusterOpID string) ([]*automationpb.TaskContainer, string, error) {
if taskProto.State == automationpb.TaskState_DONE {
// Task is already done (e.g. because we resume from a checkpoint).
if taskProto.Error != "" {
log.Errorf("Task: %v (%v/%v) failed before. Aborting the ClusterOperation. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto.Error, taskProto)
return nil, "", errors.New(taskProto.Error)
}
log.Infof("Task: %v (%v/%v) skipped because it is already done. Full Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
return nil, taskProto.Output, nil
}
task, err := s.createTaskInstance(taskProto.Name)
if err != nil {
log.Errorf("Task: %v (%v/%v) could not be instantiated. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, err, taskProto)
return nil, "", err
}
taskProto.State = automationpb.TaskState_RUNNING
log.Infof("Task: %v (%v/%v) running. Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
newTaskContainers, output, err := task.Run(taskProto.Parameters)
log.Infof("Task: %v (%v/%v) finished. newTaskContainers: %v, output: %v, error: %v", taskProto.Name, clusterOpID, taskProto.Id, newTaskContainers, output, err)
return newTaskContainers, output, err
}
func (s *Scheduler) validateTaskContainers(newTaskContainers []*automationpb.TaskContainer) error {
for _, newTaskContainer := range newTaskContainers {
for _, newTaskProto := range newTaskContainer.ParallelTasks {
err := s.validateTaskSpecification(newTaskProto.Name, newTaskProto.Parameters)
if err != nil {
return fmt.Errorf("error: %v task: %v", err, newTaskProto)
}
}
}
return nil
}
func defaultTaskCreator(taskName string) Task {
switch taskName {
case "HorizontalReshardingTask":
return &HorizontalReshardingTask{}
case "VerticalSplitTask":
return &VerticalSplitTask{}
case "CopySchemaShardTask":
return &CopySchemaShardTask{}
case "MigrateServedFromTask":
return &MigrateServedFromTask{}
case "MigrateServedTypesTask":
return &MigrateServedTypesTask{}
case "RebuildKeyspaceGraph":
return &RebuildKeyspaceGraphTask{}
case "SplitCloneTask":
return &SplitCloneTask{}
case "SplitDiffTask":
return &SplitDiffTask{}
case "VerticalSplitCloneTask":
return &VerticalSplitCloneTask{}
case "VerticalSplitDiffTask":
return &VerticalSplitDiffTask{}
case "WaitForFilteredReplicationTask":
return &WaitForFilteredReplicationTask{}
default:
return nil
}
}
func (s *Scheduler) setTaskCreator(creator taskCreator) {
s.taskCreatorMu.Lock()
defer s.taskCreatorMu.Unlock()
s.taskCreator = creator
}
func (s *Scheduler) validateTaskSpecification(taskName string, parameters map[string]string) error {
taskInstanceForParametersCheck, err := s.createTaskInstance(taskName)
if err != nil {
return err
}
errParameters := validateParameters(taskInstanceForParametersCheck, parameters)
if errParameters != nil {
return errParameters
}
return nil
}
func (s *Scheduler) createTaskInstance(taskName string) (Task, error) {
s.taskCreatorMu.Lock()
taskCreator := s.taskCreator
s.taskCreatorMu.Unlock()
task := taskCreator(taskName)
if task == nil {
return nil, fmt.Errorf("no implementation found for: %v", taskName)
}
return task, nil
}
// validateParameters returns an error if not all required parameters are provided in "parameters".
// Unknown parameters (neither required nor optional) result in an error.
func validateParameters(task Task, parameters map[string]string) error {
validParams := make(map[string]bool)
var missingParams []string
for _, reqParam := range task.RequiredParameters() {
if _, ok := parameters[reqParam]; ok {
validParams[reqParam] = true
} else {
missingParams = append(missingParams, reqParam)
}
}
if len(missingParams) > 0 {
return fmt.Errorf("required parameters are missing: %v", missingParams)
}
for _, optParam := range task.OptionalParameters() {
validParams[optParam] = true
}
for param := range parameters {
if !validParams[param] {
return fmt.Errorf("parameter %v is not allowed. Allowed required parameters: %v optional parameters: %v",
param, task.RequiredParameters(), task.OptionalParameters())
}
}
return nil
}
// EnqueueClusterOperation can be used to start a new cluster operation.
func (s *Scheduler) EnqueueClusterOperation(ctx context.Context, req *automationpb.EnqueueClusterOperationRequest) (*automationpb.EnqueueClusterOperationResponse, error) {
s.mu.Lock()
defer s.mu.Unlock()
if s.state != stateRunning {
return nil, fmt.Errorf("scheduler is not running. State: %v", s.state)
}
if !s.registeredClusterOperations[req.Name] {
return nil, fmt.Errorf("no ClusterOperation with name: %v is registered", req.Name)
}
err := s.validateTaskSpecification(req.Name, req.Parameters)
if err != nil {
return nil, err
}
clusterOpID := s.idGenerator.GetNextID()
taskIDGenerator := IDGenerator{}
initialTask := NewTaskContainerWithSingleTask(req.Name, req.Parameters)
clusterOp := NewClusterOperationInstance(clusterOpID, initialTask, &taskIDGenerator)
s.muOpList.Lock()
s.activeClusterOperations[clusterOpID] = clusterOp.Clone()
s.muOpList.Unlock()
s.toBeScheduledClusterOperations <- clusterOp
return &automationpb.EnqueueClusterOperationResponse{
Id: clusterOp.Id,
}, nil
}
// findClusterOp checks for a given ClusterOperation ID if it's in the list of active or finished operations.
func (s *Scheduler) findClusterOp(id string) (ClusterOperationInstance, error) {
var ok bool
var clusterOp ClusterOperationInstance
s.muOpList.Lock()
defer s.muOpList.Unlock()
clusterOp, ok = s.activeClusterOperations[id]
if !ok {
clusterOp, ok = s.finishedClusterOperations[id]
}
if !ok {
return clusterOp, fmt.Errorf("ClusterOperation with id: %v not found", id)
}
return clusterOp.Clone(), nil
}
// Checkpoint should be called every time the state of the cluster op changes.
// It is used to update the copy of the state in activeClusterOperations.
func (s *Scheduler) Checkpoint(clusterOp ClusterOperationInstance) {
// TODO(mberlin): Add here support for persistent checkpoints.
s.muOpList.Lock()
defer s.muOpList.Unlock()
s.activeClusterOperations[clusterOp.Id] = clusterOp.Clone()
}
// GetClusterOperationDetails can be used to query the full details of active or finished operations.
func (s *Scheduler) GetClusterOperationDetails(ctx context.Context, req *automationpb.GetClusterOperationDetailsRequest) (*automationpb.GetClusterOperationDetailsResponse, error) {
clusterOp, err := s.findClusterOp(req.Id)
if err != nil {
return nil, err
}
return &automationpb.GetClusterOperationDetailsResponse{
ClusterOp: clusterOp.ClusterOperation,
}, nil
}
// ShutdownAndWait shuts down the scheduler and waits infinitely until all pending cluster operations have finished.
func (s *Scheduler) ShutdownAndWait() {
s.mu.Lock()
if s.state != stateShuttingDown {
s.state = stateShuttingDown
close(s.toBeScheduledClusterOperations)
}
s.mu.Unlock()
log.Infof("Scheduler was shut down. Waiting for pending ClusterOperations to finish.")
s.pendingOpsWg.Wait()
s.mu.Lock()
s.state = stateShutdown
s.mu.Unlock()
log.Infof("All pending ClusterOperations finished.")
} | // The key of the map is ClusterOperationInstance.ID.
// This map contains a copy of the ClusterOperationInstance which is currently processed. | random_line_split |
scheduler.go | /*
Copyright 2019 The Vitess Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
/*
Package automation contains code to execute high-level cluster operations
(e.g. resharding) as a series of low-level operations
(e.g. vtctl, shell commands, ...).
*/
package automation
import (
"errors"
"fmt"
"sync"
"vitess.io/vitess/go/vt/proto/automationservice"
"context"
"vitess.io/vitess/go/vt/log"
automationpb "vitess.io/vitess/go/vt/proto/automation"
"vitess.io/vitess/go/vt/vterrors"
)
type schedulerState int32
const (
stateNotRunning schedulerState = iota
stateRunning
stateShuttingDown
stateShutdown
)
type taskCreator func(string) Task
// Scheduler executes automation tasks and maintains the execution state.
type Scheduler struct {
automationservice.UnimplementedAutomationServer
idGenerator IDGenerator
mu sync.Mutex
// Guarded by "mu".
registeredClusterOperations map[string]bool
// Guarded by "mu".
toBeScheduledClusterOperations chan ClusterOperationInstance
// Guarded by "mu".
state schedulerState
// Guarded by "taskCreatorMu". May be overridden by testing code.
taskCreator taskCreator
taskCreatorMu sync.Mutex
pendingOpsWg *sync.WaitGroup
muOpList sync.Mutex
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
// This map contains a copy of the ClusterOperationInstance which is currently processed.
// The scheduler may update the copy with the latest status.
activeClusterOperations map[string]ClusterOperationInstance
// Guarded by "muOpList".
// The key of the map is ClusterOperationInstance.ID.
finishedClusterOperations map[string]ClusterOperationInstance
}
// NewScheduler creates a new instance.
func NewScheduler() (*Scheduler, error) {
defaultClusterOperations := map[string]bool{
"HorizontalReshardingTask": true,
"VerticalSplitTask": true,
}
s := &Scheduler{
registeredClusterOperations: defaultClusterOperations,
idGenerator: IDGenerator{},
toBeScheduledClusterOperations: make(chan ClusterOperationInstance, 10),
state: stateNotRunning,
taskCreator: defaultTaskCreator,
pendingOpsWg: &sync.WaitGroup{},
activeClusterOperations: make(map[string]ClusterOperationInstance),
finishedClusterOperations: make(map[string]ClusterOperationInstance),
}
return s, nil
}
func (s *Scheduler) registerClusterOperation(clusterOperationName string) {
s.mu.Lock()
defer s.mu.Unlock()
s.registeredClusterOperations[clusterOperationName] = true
}
// Run processes queued cluster operations.
func (s *Scheduler) Run() {
s.mu.Lock()
s.state = stateRunning
s.mu.Unlock()
s.startProcessRequestsLoop()
}
func (s *Scheduler) startProcessRequestsLoop() {
// Use a WaitGroup instead of just a done channel, because we want
// to be able to shut down the scheduler even if Run() was never executed.
s.pendingOpsWg.Add(1)
go s.processRequestsLoop()
}
func (s *Scheduler) processRequestsLoop() {
defer s.pendingOpsWg.Done()
for op := range s.toBeScheduledClusterOperations {
s.processClusterOperation(op)
}
log.Infof("Stopped processing loop for ClusterOperations.")
}
func (s *Scheduler) processClusterOperation(clusterOp ClusterOperationInstance) {
if clusterOp.State == automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE {
log.Infof("ClusterOperation: %v skipping because it is already done. Details: %v", clusterOp.Id, clusterOp)
return
}
log.Infof("ClusterOperation: %v running. Details: %v", clusterOp.Id, clusterOp)
clusterOpLoop:
for i := 0; i < len(clusterOp.SerialTasks); i++ {
taskContainer := clusterOp.SerialTasks[i]
for _, taskProto := range taskContainer.ParallelTasks {
newTaskContainers, output, err := s.runTask(taskProto, clusterOp.Id)
if err != nil {
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
} else {
MarkTaskSucceeded(taskProto, output)
}
if newTaskContainers != nil {
// Make sure all new tasks do not miss any required parameters.
err := s.validateTaskContainers(newTaskContainers)
if err != nil {
err = vterrors.Wrapf(err, "task: %v (%v/%v) emitted a new task which is not valid. Error: %v", taskProto.Name, clusterOp.Id, taskProto.Id, err)
log.Error(err)
MarkTaskFailed(taskProto, output, err)
clusterOp.Error = err.Error()
break clusterOpLoop
}
clusterOp.InsertTaskContainers(newTaskContainers, i+1)
log.Infof("ClusterOperation: %v %d new task containers added by %v (%v/%v). Updated ClusterOperation: %v",
clusterOp.Id, len(newTaskContainers), taskProto.Name, clusterOp.Id, taskProto.Id, clusterOp)
}
s.Checkpoint(clusterOp)
}
}
clusterOp.State = automationpb.ClusterOperationState_CLUSTER_OPERATION_DONE
log.Infof("ClusterOperation: %v finished. Details: %v", clusterOp.Id, clusterOp)
s.Checkpoint(clusterOp)
// Move operation from active to finished.
s.muOpList.Lock()
defer s.muOpList.Unlock()
if _, ok := s.activeClusterOperations[clusterOp.Id]; !ok {
panic("Pending ClusterOperation was not recorded as active, but should have.")
}
delete(s.activeClusterOperations, clusterOp.Id)
s.finishedClusterOperations[clusterOp.Id] = clusterOp
}
func (s *Scheduler) runTask(taskProto *automationpb.Task, clusterOpID string) ([]*automationpb.TaskContainer, string, error) {
if taskProto.State == automationpb.TaskState_DONE {
// Task is already done (e.g. because we resume from a checkpoint).
if taskProto.Error != "" {
log.Errorf("Task: %v (%v/%v) failed before. Aborting the ClusterOperation. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto.Error, taskProto)
return nil, "", errors.New(taskProto.Error)
}
log.Infof("Task: %v (%v/%v) skipped because it is already done. Full Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
return nil, taskProto.Output, nil
}
task, err := s.createTaskInstance(taskProto.Name)
if err != nil {
log.Errorf("Task: %v (%v/%v) could not be instantiated. Error: %v Details: %v", taskProto.Name, clusterOpID, taskProto.Id, err, taskProto)
return nil, "", err
}
taskProto.State = automationpb.TaskState_RUNNING
log.Infof("Task: %v (%v/%v) running. Details: %v", taskProto.Name, clusterOpID, taskProto.Id, taskProto)
newTaskContainers, output, err := task.Run(taskProto.Parameters)
log.Infof("Task: %v (%v/%v) finished. newTaskContainers: %v, output: %v, error: %v", taskProto.Name, clusterOpID, taskProto.Id, newTaskContainers, output, err)
return newTaskContainers, output, err
}
func (s *Scheduler) validateTaskContainers(newTaskContainers []*automationpb.TaskContainer) error {
for _, newTaskContainer := range newTaskContainers {
for _, newTaskProto := range newTaskContainer.ParallelTasks {
err := s.validateTaskSpecification(newTaskProto.Name, newTaskProto.Parameters)
if err != nil {
return fmt.Errorf("error: %v task: %v", err, newTaskProto)
}
}
}
return nil
}
func defaultTaskCreator(taskName string) Task {
switch taskName {
case "HorizontalReshardingTask":
return &HorizontalReshardingTask{}
case "VerticalSplitTask":
return &VerticalSplitTask{}
case "CopySchemaShardTask":
return &CopySchemaShardTask{}
case "MigrateServedFromTask":
return &MigrateServedFromTask{}
case "MigrateServedTypesTask":
return &MigrateServedTypesTask{}
case "RebuildKeyspaceGraph":
return &RebuildKeyspaceGraphTask{}
case "SplitCloneTask":
return &SplitCloneTask{}
case "SplitDiffTask":
return &SplitDiffTask{}
case "VerticalSplitCloneTask":
return &VerticalSplitCloneTask{}
case "VerticalSplitDiffTask":
return &VerticalSplitDiffTask{}
case "WaitForFilteredReplicationTask":
return &WaitForFilteredReplicationTask{}
default:
return nil
}
}
func (s *Scheduler) setTaskCreator(creator taskCreator) {
s.taskCreatorMu.Lock()
defer s.taskCreatorMu.Unlock()
s.taskCreator = creator
}
func (s *Scheduler) validateTaskSpecification(taskName string, parameters map[string]string) error {
taskInstanceForParametersCheck, err := s.createTaskInstance(taskName)
if err != nil {
return err
}
errParameters := validateParameters(taskInstanceForParametersCheck, parameters)
if errParameters != nil {
return errParameters
}
return nil
}
func (s *Scheduler) createTaskInstance(taskName string) (Task, error) {
s.taskCreatorMu.Lock()
taskCreator := s.taskCreator
s.taskCreatorMu.Unlock()
task := taskCreator(taskName)
if task == nil {
return nil, fmt.Errorf("no implementation found for: %v", taskName)
}
return task, nil
}
// validateParameters returns an error if not all required parameters are provided in "parameters".
// Unknown parameters (neither required nor optional) result in an error.
func validateParameters(task Task, parameters map[string]string) error {
validParams := make(map[string]bool)
var missingParams []string
for _, reqParam := range task.RequiredParameters() {
if _, ok := parameters[reqParam]; ok {
validParams[reqParam] = true
} else {
missingParams = append(missingParams, reqParam)
}
}
if len(missingParams) > 0 {
return fmt.Errorf("required parameters are missing: %v", missingParams)
}
for _, optParam := range task.OptionalParameters() {
validParams[optParam] = true
}
for param := range parameters {
if !validParams[param] {
return fmt.Errorf("parameter %v is not allowed. Allowed required parameters: %v optional parameters: %v",
param, task.RequiredParameters(), task.OptionalParameters())
}
}
return nil
}
// EnqueueClusterOperation can be used to start a new cluster operation.
func (s *Scheduler) EnqueueClusterOperation(ctx context.Context, req *automationpb.EnqueueClusterOperationRequest) (*automationpb.EnqueueClusterOperationResponse, error) {
s.mu.Lock()
defer s.mu.Unlock()
if s.state != stateRunning {
return nil, fmt.Errorf("scheduler is not running. State: %v", s.state)
}
if !s.registeredClusterOperations[req.Name] {
return nil, fmt.Errorf("no ClusterOperation with name: %v is registered", req.Name)
}
err := s.validateTaskSpecification(req.Name, req.Parameters)
if err != nil {
return nil, err
}
clusterOpID := s.idGenerator.GetNextID()
taskIDGenerator := IDGenerator{}
initialTask := NewTaskContainerWithSingleTask(req.Name, req.Parameters)
clusterOp := NewClusterOperationInstance(clusterOpID, initialTask, &taskIDGenerator)
s.muOpList.Lock()
s.activeClusterOperations[clusterOpID] = clusterOp.Clone()
s.muOpList.Unlock()
s.toBeScheduledClusterOperations <- clusterOp
return &automationpb.EnqueueClusterOperationResponse{
Id: clusterOp.Id,
}, nil
}
// findClusterOp checks for a given ClusterOperation ID if it's in the list of active or finished operations.
func (s *Scheduler) findClusterOp(id string) (ClusterOperationInstance, error) {
var ok bool
var clusterOp ClusterOperationInstance
s.muOpList.Lock()
defer s.muOpList.Unlock()
clusterOp, ok = s.activeClusterOperations[id]
if !ok {
clusterOp, ok = s.finishedClusterOperations[id]
}
if !ok {
return clusterOp, fmt.Errorf("ClusterOperation with id: %v not found", id)
}
return clusterOp.Clone(), nil
}
// Checkpoint should be called every time the state of the cluster op changes.
// It is used to update the copy of the state in activeClusterOperations.
func (s *Scheduler) Checkpoint(clusterOp ClusterOperationInstance) {
// TODO(mberlin): Add here support for persistent checkpoints.
s.muOpList.Lock()
defer s.muOpList.Unlock()
s.activeClusterOperations[clusterOp.Id] = clusterOp.Clone()
}
// GetClusterOperationDetails can be used to query the full details of active or finished operations.
func (s *Scheduler) GetClusterOperationDetails(ctx context.Context, req *automationpb.GetClusterOperationDetailsRequest) (*automationpb.GetClusterOperationDetailsResponse, error) {
clusterOp, err := s.findClusterOp(req.Id)
if err != nil {
return nil, err
}
return &automationpb.GetClusterOperationDetailsResponse{
ClusterOp: clusterOp.ClusterOperation,
}, nil
}
// ShutdownAndWait shuts down the scheduler and waits infinitely until all pending cluster operations have finished.
func (s *Scheduler) | () {
s.mu.Lock()
if s.state != stateShuttingDown {
s.state = stateShuttingDown
close(s.toBeScheduledClusterOperations)
}
s.mu.Unlock()
log.Infof("Scheduler was shut down. Waiting for pending ClusterOperations to finish.")
s.pendingOpsWg.Wait()
s.mu.Lock()
s.state = stateShutdown
s.mu.Unlock()
log.Infof("All pending ClusterOperations finished.")
}
| ShutdownAndWait | identifier_name |
index.js | import { defineHidden, FluidType, is, each, isFluidValue, createInterpolator, toArray, isEqual, Globals, needsInterpolation, useForceUpdate, useIsomorphicLayoutEffect } from '@react-spring/shared';
import _extends from '@babel/runtime/helpers/esm/extends';
import { deprecateInterpolate } from '@react-spring/shared/deprecations';
import { to, createAnimatedTransform, createAnimatedStyle, frameLoop, applyAnimatedValues, getComponentProps } from '@react-spring/shared/globals';
import { createInterpolator as createInterpolator$1, is as is$1 } from '@react-spring/shared';
import React, { forwardRef, useRef } from 'react';
const AnimatedType = '__$AnimatedType';
/** Returns true for `Animated` nodes. Returns false for `SpringValue` objects. */
const isAnimated = value => !!(value && value[AnimatedType]);
class Animated {
constructor() {
defineHidden(this, AnimatedType, 1);
}
/** Returns every animated number used by this node. */
getPayload() {
return this.payload || [];
}
}
/** The `AnimatedProps` class sets this before initializing */
Animated.context = null;
const isAnimationValue = value => (value && value[FluidType]) == 2;
let nextId = 1;
/**
* A kind of `FluidValue` that manages an `AnimatedValue` node.
*
* Its underlying value can be accessed and even observed.
*/
class AnimationValue {
constructor(key) {
this.key = key;
this.id = nextId++;
this._priority = 0;
this._children = new Set();
defineHidden(this, FluidType, 2);
}
/** @internal Controls the order in which animations are updated */
get priority() {
return this._priority;
}
set priority(priority) {
if (this._priority != priority) {
this._priority = priority;
this._onPriorityChange(priority);
}
}
/** Get the current value */
get() {
// The node doesn't exist until the first update, which normally isn't an
// issue but it can be for tests.
return this.node && this.node.getValue();
}
/** Create a spring that maps our value to another value */
to() {
for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {
args[_key] = arguments[_key];
}
return to(this, args);
}
/** @deprecated Use the `to` method instead. */
interpolate() {
deprecateInterpolate();
for (var _len2 = arguments.length, args = new Array(_len2), _key2 = 0; _key2 < _len2; _key2++) {
args[_key2] = arguments[_key2];
}
return to(this, args);
}
/** @internal */
addChild(child) {
if (!this._children.size) this._attach();
this._children.add(child);
}
/** @internal */
removeChild(child) {
this._children.delete(child);
if (!this._children.size) this._detach();
}
/** @internal */
onParentPriorityChange(priority, _parent) {
// Assume we only have one parent.
this.priority = priority + 1;
}
_attach() {}
_detach() {}
/** Notify observers of a change to our value */
_onChange(value, idle) {
if (idle === void 0) {
idle = false;
}
// Clone "_children" so it can be safely mutated by the loop.
for (const observer of Array.from(this._children)) {
if (is.fun(observer)) {
observer(value, this);
} else {
observer.onParentChange(value, idle, this);
}
}
}
/** Notify observers of a change to our priority */
_onPriorityChange(priority) {
each(this._children, observer => {
if (!is.fun(observer)) {
observer.onParentPriorityChange(priority, this);
}
});
}
/** Reset our node and the nodes of every descendant */
_reset(goal) {
this.node.reset(!this.idle, goal);
each(this._children, observer => {
if (isAnimationValue(observer)) {
observer._reset(goal);
}
});
}
}
/** An object containing `Animated` nodes */
class AnimatedObject extends Animated {
constructor(source) {
if (source === void 0) {
source = null;
}
super();
this.setValue(source);
}
getValue(animated) {
if (!this.source) return null;
const values = {};
each(this.source, (source, key) => {
if (isAnimated(source)) {
values[key] = source.getValue(animated);
} else if (isFluidValue(source)) {
values[key] = source.get();
} else if (!animated) {
values[key] = source;
}
});
return values;
}
/** Replace the raw object data */
setValue(source) {
this.source = source;
this.payload = this._makePayload(source);
}
reset(isActive, _goal) {
if (this.payload) {
each(this.payload, node => node.reset(isActive));
}
}
/** Create a payload set. */
_makePayload(source) {
if (source) {
const payload = new Set();
each(source, this._addToPayload, payload);
return Array.from(payload);
}
}
/** Add to a payload set. */
_addToPayload(source) {
if (isFluidValue(source)) {
if (Animated.context) {
Animated.context.dependencies.add(source);
}
if (isAnimationValue(source)) {
source = source.node;
}
}
if (isAnimated(source)) {
each(source.getPayload(), node => this.add(node));
}
}
}
class AnimatedStyle extends AnimatedObject {
constructor(style) {
super(style || null);
}
setValue(style) {
super.setValue(style && style.transform && createAnimatedTransform ? _extends({}, style, {
transform: createAnimatedTransform(style.transform)
}) : style);
}
}
/** An animated number or a native attribute value */
class AnimatedValue extends Animated {
constructor(_value) {
super();
this._value = _value;
this.done = true;
if (is.num(this._value)) {
this.lastPosition = this._value;
}
}
static create(from, _to) {
return new AnimatedValue(from);
}
getPayload() {
return [this];
}
getValue() {
return this._value;
}
/**
* Set the current value and optionally round it.
*
* The `step` argument does nothing whenever it equals `undefined` or `0`.
* It works with fractions and whole numbers. The best use case is (probably)
* rounding to the pixel grid with a step of:
*
* 1 / window.devicePixelRatio
*/
setValue(value, step) {
if (is.num(value)) {
this.lastPosition = value;
if (step) {
value = Math.round(value / step) * step;
if (this.done) {
this.lastPosition = value;
}
}
}
if (this._value === value) {
return false;
}
this._value = value;
return true;
}
reset(isActive, _goal) {
this.done = false;
if (is.num(this._value)) {
this.elapsedTime = 0;
this.lastPosition = this._value;
if (!isActive) this.lastVelocity = null;
this.v0 = null;
}
}
}
/**
* `Into` springs are memoized interpolators that react to their dependencies.
* The memoized result is updated whenever a dependency changes.
*/
class Into extends AnimationValue {
constructor(
/** The source of input values */
source, args) {
super();
this.source = source;
this.calc = createInterpolator(...args);
this.node = new AnimatedValue(this._compute());
}
get idle() {
return this.node.done;
}
_compute() {
const inputs = is.arr(this.source) ? this.source.map(node => node.get()) : toArray(this.source.get());
return this.calc(...inputs);
}
_attach() {
// Start observing our "source" once we have an observer.
let priority = 0;
each(toArray(this.source), source => {
priority = Math.max(priority, (source.priority || 0) + 1);
source.addChild(this);
});
this.priority = priority;
}
_detach() {
// Stop observing our "source" once we have no observers.
each(toArray(this.source), source => {
source.removeChild(this);
});
}
/** @internal */
onParentChange(_value, idle) {
const node = this.node;
if (idle && !node.done) {
// We're not idle until every source is idle.
node.done = toArray(this.source).every(source => !isAnimationValue(source) || source.idle);
} // TODO: only compute once per frame (note: we'll need to call "onParentChange")
const value = this._compute();
if (!isEqual(value, this.get())) {
node.setValue(value);
this._onChange(value, node.done);
}
}
/** @internal */
onParentPriorityChange(_priority) {
// Set our priority to 1 + the highest parent.
this.priority = toArray(this.source).reduce((max, source) => Math.max(max, (source.priority || 0) + 1), 0);
}
}
Globals.assign({
to: (source, args) => new Into(source, args),
createAnimatedStyle: style => new AnimatedStyle(style)
});
class AnimatedString extends AnimatedValue {
constructor(from, to) {
super(0);
this._string = null;
this._toString = createInterpolator$1({
output: [from, to]
});
}
static create(from, to) {
if (to === void 0) {
to = from;
}
if (is$1.str(from) && is$1.str(to)) {
return new AnimatedString(from, to);
}
throw TypeError('Expected "from" and "to" to be strings');
}
getValue() {
let value = this._string;
return value == null ? this._string = this._toString(this._value) : value;
}
setValue(value) {
if (!is$1.num(value)) {
this._string = value;
this._value = 1;
} else if (super.setValue(value)) {
this._string = null;
} else {
return false;
}
return true;
}
reset(isActive, goal) {
if (goal) {
this._toString = createInterpolator$1({
output: [this.getValue(), goal]
});
}
this._value = 0;
super.reset(isActive);
}
}
/** An array of animated nodes */
class AnimatedArray extends AnimatedObject {
constructor(from, to) {
super(null);
super.setValue(this._makeAnimated(from, to));
}
static create(from, to) {
return new AnimatedArray(from, to);
}
getValue() {
return this.source.map(node => node.getValue());
}
setValue(newValue) {
const payload = this.getPayload(); // Reuse the payload when lengths are equal.
if (newValue && newValue.length == payload.length) {
each(payload, (node, i) => node.setValue(newValue[i]));
} else {
// Remake the payload when length changes.
this.source = this._makeAnimated(newValue);
this.payload = this._makePayload(this.source);
}
}
/** Convert the `from` and `to` values to an array of `Animated` nodes */
_makeAnimated(from, to) {
if (to === void 0) {
to = from;
}
return from ? from.map((from, i) => (needsInterpolation(from) ? AnimatedString : AnimatedValue).create(from, to[i])) : [];
}
}
class AnimatedProps extends AnimatedObject {
constructor(update) {
super(null);
this.update = update;
/** Equals true when a re-render is scheduled for "end of frame" */
this.dirty = false;
}
setValue(props, context) {
if (!props) return; // The constructor passes null.
|
super.setValue(props.style && createAnimatedStyle ? _extends({}, props, {
style: createAnimatedStyle(props.style)
}) : props);
Animated.context = null;
}
/** @internal */
onParentChange() {
if (!this.dirty) {
this.dirty = true;
frameLoop.onFrame(() => {
this.dirty = false;
this.update();
});
}
}
/** @internal */
onParentPriorityChange() {}
}
const cacheKey = Symbol.for('AnimatedComponent');
const withAnimated = Component => is.str(Component) ? createAnimatedComponent(Component) : Component[cacheKey] || (Component[cacheKey] = createAnimatedComponent(Component));
const createAnimatedComponent = Component => forwardRef((rawProps, ref) => {
const instanceRef = useRef(null);
const hasInstance = // Function components must use "forwardRef" to avoid being
// re-rendered on every animation frame.
!is.fun(Component) || Component.prototype.isReactComponent;
const forceUpdate = useForceUpdate();
const props = new AnimatedProps(() => {
const instance = instanceRef.current;
if (hasInstance && !instance) {
return; // The wrapped component forgot to forward its ref.
}
const didUpdate = instance ? applyAnimatedValues(instance, props.getValue(true)) : false; // Re-render the component when native updates fail.
if (didUpdate === false) {
forceUpdate();
}
});
const dependencies = new Set();
props.setValue(rawProps, {
dependencies
});
useIsomorphicLayoutEffect(() => {
each(dependencies, dep => dep.addChild(props));
return () => each(dependencies, dep => dep.removeChild(props));
});
return React.createElement(Component, Object.assign({}, getComponentProps(props.getValue()), {
ref: hasInstance && (value => {
instanceRef.current = updateRef(ref, value);
})
}));
});
function updateRef(ref, value) {
if (ref) {
if (is.fun(ref)) ref(value);else ref.current = value;
}
return value;
}
/**
* Pass the given components to `withAnimated` and add the newly animated
* components to `withAnimated` as properties.
*/
const extendAnimated = (withAnimated, components, lowercase) => {
components.forEach(Component => {
let key = getDisplayName(Component);
if (lowercase) {
key = key[0].toLowerCase() + key.slice(1);
}
withAnimated[key] = withAnimated(Component);
});
return withAnimated;
};
const getDisplayName = arg => is.str(arg) ? arg : arg && is.str(arg.displayName) ? arg.displayName : is.fun(arg) && arg.name || null;
export { Animated, AnimatedArray, AnimatedObject, AnimatedProps, AnimatedString, AnimatedStyle, AnimatedType, AnimatedValue, AnimationValue, Into, extendAnimated, isAnimated, isAnimationValue, withAnimated };
//# sourceMappingURL=index.js.map | if (context) {
Animated.context = context;
}
| random_line_split |
index.js | import { defineHidden, FluidType, is, each, isFluidValue, createInterpolator, toArray, isEqual, Globals, needsInterpolation, useForceUpdate, useIsomorphicLayoutEffect } from '@react-spring/shared';
import _extends from '@babel/runtime/helpers/esm/extends';
import { deprecateInterpolate } from '@react-spring/shared/deprecations';
import { to, createAnimatedTransform, createAnimatedStyle, frameLoop, applyAnimatedValues, getComponentProps } from '@react-spring/shared/globals';
import { createInterpolator as createInterpolator$1, is as is$1 } from '@react-spring/shared';
import React, { forwardRef, useRef } from 'react';
const AnimatedType = '__$AnimatedType';
/** Returns true for `Animated` nodes. Returns false for `SpringValue` objects. */
const isAnimated = value => !!(value && value[AnimatedType]);
class Animated {
constructor() {
defineHidden(this, AnimatedType, 1);
}
/** Returns every animated number used by this node. */
getPayload() {
return this.payload || [];
}
}
/** The `AnimatedProps` class sets this before initializing */
Animated.context = null;
const isAnimationValue = value => (value && value[FluidType]) == 2;
let nextId = 1;
/**
* A kind of `FluidValue` that manages an `AnimatedValue` node.
*
* Its underlying value can be accessed and even observed.
*/
class AnimationValue {
constructor(key) {
this.key = key;
this.id = nextId++;
this._priority = 0;
this._children = new Set();
defineHidden(this, FluidType, 2);
}
/** @internal Controls the order in which animations are updated */
get priority() {
return this._priority;
}
set priority(priority) {
if (this._priority != priority) {
this._priority = priority;
this._onPriorityChange(priority);
}
}
/** Get the current value */
get() {
// The node doesn't exist until the first update, which normally isn't an
// issue but it can be for tests.
return this.node && this.node.getValue();
}
/** Create a spring that maps our value to another value */
to() {
for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {
args[_key] = arguments[_key];
}
return to(this, args);
}
/** @deprecated Use the `to` method instead. */
interpolate() {
deprecateInterpolate();
for (var _len2 = arguments.length, args = new Array(_len2), _key2 = 0; _key2 < _len2; _key2++) {
args[_key2] = arguments[_key2];
}
return to(this, args);
}
/** @internal */
addChild(child) {
if (!this._children.size) this._attach();
this._children.add(child);
}
/** @internal */
removeChild(child) {
this._children.delete(child);
if (!this._children.size) this._detach();
}
/** @internal */
onParentPriorityChange(priority, _parent) {
// Assume we only have one parent.
this.priority = priority + 1;
}
_attach() {}
_detach() {}
/** Notify observers of a change to our value */
_onChange(value, idle) {
if (idle === void 0) {
idle = false;
}
// Clone "_children" so it can be safely mutated by the loop.
for (const observer of Array.from(this._children)) {
if (is.fun(observer)) {
observer(value, this);
} else {
observer.onParentChange(value, idle, this);
}
}
}
/** Notify observers of a change to our priority */
_onPriorityChange(priority) {
each(this._children, observer => {
if (!is.fun(observer)) {
observer.onParentPriorityChange(priority, this);
}
});
}
/** Reset our node and the nodes of every descendant */
_reset(goal) {
this.node.reset(!this.idle, goal);
each(this._children, observer => {
if (isAnimationValue(observer)) {
observer._reset(goal);
}
});
}
}
/** An object containing `Animated` nodes */
class AnimatedObject extends Animated {
constructor(source) {
if (source === void 0) {
source = null;
}
super();
this.setValue(source);
}
getValue(animated) {
if (!this.source) return null;
const values = {};
each(this.source, (source, key) => {
if (isAnimated(source)) {
values[key] = source.getValue(animated);
} else if (isFluidValue(source)) {
values[key] = source.get();
} else if (!animated) {
values[key] = source;
}
});
return values;
}
/** Replace the raw object data */
setValue(source) {
this.source = source;
this.payload = this._makePayload(source);
}
reset(isActive, _goal) {
if (this.payload) {
each(this.payload, node => node.reset(isActive));
}
}
/** Create a payload set. */
_makePayload(source) {
if (source) {
const payload = new Set();
each(source, this._addToPayload, payload);
return Array.from(payload);
}
}
/** Add to a payload set. */
_addToPayload(source) {
if (isFluidValue(source)) {
if (Animated.context) {
Animated.context.dependencies.add(source);
}
if (isAnimationValue(source)) {
source = source.node;
}
}
if (isAnimated(source)) {
each(source.getPayload(), node => this.add(node));
}
}
}
class AnimatedStyle extends AnimatedObject {
constructor(style) {
super(style || null);
}
setValue(style) {
super.setValue(style && style.transform && createAnimatedTransform ? _extends({}, style, {
transform: createAnimatedTransform(style.transform)
}) : style);
}
}
/** An animated number or a native attribute value */
class AnimatedValue extends Animated {
constructor(_value) {
super();
this._value = _value;
this.done = true;
if (is.num(this._value)) {
this.lastPosition = this._value;
}
}
static create(from, _to) {
return new AnimatedValue(from);
}
getPayload() {
return [this];
}
getValue() {
return this._value;
}
/**
* Set the current value and optionally round it.
*
* The `step` argument does nothing whenever it equals `undefined` or `0`.
* It works with fractions and whole numbers. The best use case is (probably)
* rounding to the pixel grid with a step of:
*
* 1 / window.devicePixelRatio
*/
setValue(value, step) {
if (is.num(value)) {
this.lastPosition = value;
if (step) {
value = Math.round(value / step) * step;
if (this.done) {
this.lastPosition = value;
}
}
}
if (this._value === value) {
return false;
}
this._value = value;
return true;
}
reset(isActive, _goal) {
this.done = false;
if (is.num(this._value)) {
this.elapsedTime = 0;
this.lastPosition = this._value;
if (!isActive) this.lastVelocity = null;
this.v0 = null;
}
}
}
/**
* `Into` springs are memoized interpolators that react to their dependencies.
* The memoized result is updated whenever a dependency changes.
*/
class Into extends AnimationValue {
constructor(
/** The source of input values */
source, args) {
super();
this.source = source;
this.calc = createInterpolator(...args);
this.node = new AnimatedValue(this._compute());
}
get idle() {
return this.node.done;
}
_compute() {
const inputs = is.arr(this.source) ? this.source.map(node => node.get()) : toArray(this.source.get());
return this.calc(...inputs);
}
_attach() {
// Start observing our "source" once we have an observer.
let priority = 0;
each(toArray(this.source), source => {
priority = Math.max(priority, (source.priority || 0) + 1);
source.addChild(this);
});
this.priority = priority;
}
_detach() {
// Stop observing our "source" once we have no observers.
each(toArray(this.source), source => {
source.removeChild(this);
});
}
/** @internal */
onParentChange(_value, idle) {
const node = this.node;
if (idle && !node.done) {
// We're not idle until every source is idle.
node.done = toArray(this.source).every(source => !isAnimationValue(source) || source.idle);
} // TODO: only compute once per frame (note: we'll need to call "onParentChange")
const value = this._compute();
if (!isEqual(value, this.get())) {
node.setValue(value);
this._onChange(value, node.done);
}
}
/** @internal */
onParentPriorityChange(_priority) {
// Set our priority to 1 + the highest parent.
this.priority = toArray(this.source).reduce((max, source) => Math.max(max, (source.priority || 0) + 1), 0);
}
}
Globals.assign({
to: (source, args) => new Into(source, args),
createAnimatedStyle: style => new AnimatedStyle(style)
});
class AnimatedString extends AnimatedValue {
constructor(from, to) {
super(0);
this._string = null;
this._toString = createInterpolator$1({
output: [from, to]
});
}
static create(from, to) {
if (to === void 0) {
to = from;
}
if (is$1.str(from) && is$1.str(to)) {
return new AnimatedString(from, to);
}
throw TypeError('Expected "from" and "to" to be strings');
}
| () {
let value = this._string;
return value == null ? this._string = this._toString(this._value) : value;
}
setValue(value) {
if (!is$1.num(value)) {
this._string = value;
this._value = 1;
} else if (super.setValue(value)) {
this._string = null;
} else {
return false;
}
return true;
}
reset(isActive, goal) {
if (goal) {
this._toString = createInterpolator$1({
output: [this.getValue(), goal]
});
}
this._value = 0;
super.reset(isActive);
}
}
/** An array of animated nodes */
class AnimatedArray extends AnimatedObject {
constructor(from, to) {
super(null);
super.setValue(this._makeAnimated(from, to));
}
static create(from, to) {
return new AnimatedArray(from, to);
}
getValue() {
return this.source.map(node => node.getValue());
}
setValue(newValue) {
const payload = this.getPayload(); // Reuse the payload when lengths are equal.
if (newValue && newValue.length == payload.length) {
each(payload, (node, i) => node.setValue(newValue[i]));
} else {
// Remake the payload when length changes.
this.source = this._makeAnimated(newValue);
this.payload = this._makePayload(this.source);
}
}
/** Convert the `from` and `to` values to an array of `Animated` nodes */
_makeAnimated(from, to) {
if (to === void 0) {
to = from;
}
return from ? from.map((from, i) => (needsInterpolation(from) ? AnimatedString : AnimatedValue).create(from, to[i])) : [];
}
}
class AnimatedProps extends AnimatedObject {
constructor(update) {
super(null);
this.update = update;
/** Equals true when a re-render is scheduled for "end of frame" */
this.dirty = false;
}
setValue(props, context) {
if (!props) return; // The constructor passes null.
if (context) {
Animated.context = context;
}
super.setValue(props.style && createAnimatedStyle ? _extends({}, props, {
style: createAnimatedStyle(props.style)
}) : props);
Animated.context = null;
}
/** @internal */
onParentChange() {
if (!this.dirty) {
this.dirty = true;
frameLoop.onFrame(() => {
this.dirty = false;
this.update();
});
}
}
/** @internal */
onParentPriorityChange() {}
}
const cacheKey = Symbol.for('AnimatedComponent');
const withAnimated = Component => is.str(Component) ? createAnimatedComponent(Component) : Component[cacheKey] || (Component[cacheKey] = createAnimatedComponent(Component));
const createAnimatedComponent = Component => forwardRef((rawProps, ref) => {
const instanceRef = useRef(null);
const hasInstance = // Function components must use "forwardRef" to avoid being
// re-rendered on every animation frame.
!is.fun(Component) || Component.prototype.isReactComponent;
const forceUpdate = useForceUpdate();
const props = new AnimatedProps(() => {
const instance = instanceRef.current;
if (hasInstance && !instance) {
return; // The wrapped component forgot to forward its ref.
}
const didUpdate = instance ? applyAnimatedValues(instance, props.getValue(true)) : false; // Re-render the component when native updates fail.
if (didUpdate === false) {
forceUpdate();
}
});
const dependencies = new Set();
props.setValue(rawProps, {
dependencies
});
useIsomorphicLayoutEffect(() => {
each(dependencies, dep => dep.addChild(props));
return () => each(dependencies, dep => dep.removeChild(props));
});
return React.createElement(Component, Object.assign({}, getComponentProps(props.getValue()), {
ref: hasInstance && (value => {
instanceRef.current = updateRef(ref, value);
})
}));
});
function updateRef(ref, value) {
if (ref) {
if (is.fun(ref)) ref(value);else ref.current = value;
}
return value;
}
/**
* Pass the given components to `withAnimated` and add the newly animated
* components to `withAnimated` as properties.
*/
const extendAnimated = (withAnimated, components, lowercase) => {
components.forEach(Component => {
let key = getDisplayName(Component);
if (lowercase) {
key = key[0].toLowerCase() + key.slice(1);
}
withAnimated[key] = withAnimated(Component);
});
return withAnimated;
};
const getDisplayName = arg => is.str(arg) ? arg : arg && is.str(arg.displayName) ? arg.displayName : is.fun(arg) && arg.name || null;
export { Animated, AnimatedArray, AnimatedObject, AnimatedProps, AnimatedString, AnimatedStyle, AnimatedType, AnimatedValue, AnimationValue, Into, extendAnimated, isAnimated, isAnimationValue, withAnimated };
//# sourceMappingURL=index.js.map
| getValue | identifier_name |
index.js | import { defineHidden, FluidType, is, each, isFluidValue, createInterpolator, toArray, isEqual, Globals, needsInterpolation, useForceUpdate, useIsomorphicLayoutEffect } from '@react-spring/shared';
import _extends from '@babel/runtime/helpers/esm/extends';
import { deprecateInterpolate } from '@react-spring/shared/deprecations';
import { to, createAnimatedTransform, createAnimatedStyle, frameLoop, applyAnimatedValues, getComponentProps } from '@react-spring/shared/globals';
import { createInterpolator as createInterpolator$1, is as is$1 } from '@react-spring/shared';
import React, { forwardRef, useRef } from 'react';
const AnimatedType = '__$AnimatedType';
/** Returns true for `Animated` nodes. Returns false for `SpringValue` objects. */
const isAnimated = value => !!(value && value[AnimatedType]);
class Animated {
constructor() {
defineHidden(this, AnimatedType, 1);
}
/** Returns every animated number used by this node. */
getPayload() {
return this.payload || [];
}
}
/** The `AnimatedProps` class sets this before initializing */
Animated.context = null;
const isAnimationValue = value => (value && value[FluidType]) == 2;
let nextId = 1;
/**
* A kind of `FluidValue` that manages an `AnimatedValue` node.
*
* Its underlying value can be accessed and even observed.
*/
class AnimationValue {
constructor(key) {
this.key = key;
this.id = nextId++;
this._priority = 0;
this._children = new Set();
defineHidden(this, FluidType, 2);
}
/** @internal Controls the order in which animations are updated */
get priority() {
return this._priority;
}
set priority(priority) {
if (this._priority != priority) {
this._priority = priority;
this._onPriorityChange(priority);
}
}
/** Get the current value */
get() {
// The node doesn't exist until the first update, which normally isn't an
// issue but it can be for tests.
return this.node && this.node.getValue();
}
/** Create a spring that maps our value to another value */
to() {
for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {
args[_key] = arguments[_key];
}
return to(this, args);
}
/** @deprecated Use the `to` method instead. */
interpolate() {
deprecateInterpolate();
for (var _len2 = arguments.length, args = new Array(_len2), _key2 = 0; _key2 < _len2; _key2++) {
args[_key2] = arguments[_key2];
}
return to(this, args);
}
/** @internal */
addChild(child) {
if (!this._children.size) this._attach();
this._children.add(child);
}
/** @internal */
removeChild(child) {
this._children.delete(child);
if (!this._children.size) this._detach();
}
/** @internal */
onParentPriorityChange(priority, _parent) {
// Assume we only have one parent.
this.priority = priority + 1;
}
_attach() {}
_detach() {}
/** Notify observers of a change to our value */
_onChange(value, idle) {
if (idle === void 0) {
idle = false;
}
// Clone "_children" so it can be safely mutated by the loop.
for (const observer of Array.from(this._children)) {
if (is.fun(observer)) {
observer(value, this);
} else {
observer.onParentChange(value, idle, this);
}
}
}
/** Notify observers of a change to our priority */
_onPriorityChange(priority) {
each(this._children, observer => {
if (!is.fun(observer)) |
});
}
/** Reset our node and the nodes of every descendant */
_reset(goal) {
this.node.reset(!this.idle, goal);
each(this._children, observer => {
if (isAnimationValue(observer)) {
observer._reset(goal);
}
});
}
}
/** An object containing `Animated` nodes */
class AnimatedObject extends Animated {
constructor(source) {
if (source === void 0) {
source = null;
}
super();
this.setValue(source);
}
getValue(animated) {
if (!this.source) return null;
const values = {};
each(this.source, (source, key) => {
if (isAnimated(source)) {
values[key] = source.getValue(animated);
} else if (isFluidValue(source)) {
values[key] = source.get();
} else if (!animated) {
values[key] = source;
}
});
return values;
}
/** Replace the raw object data */
setValue(source) {
this.source = source;
this.payload = this._makePayload(source);
}
reset(isActive, _goal) {
if (this.payload) {
each(this.payload, node => node.reset(isActive));
}
}
/** Create a payload set. */
_makePayload(source) {
if (source) {
const payload = new Set();
each(source, this._addToPayload, payload);
return Array.from(payload);
}
}
/** Add to a payload set. */
_addToPayload(source) {
if (isFluidValue(source)) {
if (Animated.context) {
Animated.context.dependencies.add(source);
}
if (isAnimationValue(source)) {
source = source.node;
}
}
if (isAnimated(source)) {
each(source.getPayload(), node => this.add(node));
}
}
}
class AnimatedStyle extends AnimatedObject {
constructor(style) {
super(style || null);
}
setValue(style) {
super.setValue(style && style.transform && createAnimatedTransform ? _extends({}, style, {
transform: createAnimatedTransform(style.transform)
}) : style);
}
}
/** An animated number or a native attribute value */
class AnimatedValue extends Animated {
constructor(_value) {
super();
this._value = _value;
this.done = true;
if (is.num(this._value)) {
this.lastPosition = this._value;
}
}
static create(from, _to) {
return new AnimatedValue(from);
}
getPayload() {
return [this];
}
getValue() {
return this._value;
}
/**
* Set the current value and optionally round it.
*
* The `step` argument does nothing whenever it equals `undefined` or `0`.
* It works with fractions and whole numbers. The best use case is (probably)
* rounding to the pixel grid with a step of:
*
* 1 / window.devicePixelRatio
*/
setValue(value, step) {
if (is.num(value)) {
this.lastPosition = value;
if (step) {
value = Math.round(value / step) * step;
if (this.done) {
this.lastPosition = value;
}
}
}
if (this._value === value) {
return false;
}
this._value = value;
return true;
}
reset(isActive, _goal) {
this.done = false;
if (is.num(this._value)) {
this.elapsedTime = 0;
this.lastPosition = this._value;
if (!isActive) this.lastVelocity = null;
this.v0 = null;
}
}
}
/**
* `Into` springs are memoized interpolators that react to their dependencies.
* The memoized result is updated whenever a dependency changes.
*/
class Into extends AnimationValue {
constructor(
/** The source of input values */
source, args) {
super();
this.source = source;
this.calc = createInterpolator(...args);
this.node = new AnimatedValue(this._compute());
}
get idle() {
return this.node.done;
}
_compute() {
const inputs = is.arr(this.source) ? this.source.map(node => node.get()) : toArray(this.source.get());
return this.calc(...inputs);
}
_attach() {
// Start observing our "source" once we have an observer.
let priority = 0;
each(toArray(this.source), source => {
priority = Math.max(priority, (source.priority || 0) + 1);
source.addChild(this);
});
this.priority = priority;
}
_detach() {
// Stop observing our "source" once we have no observers.
each(toArray(this.source), source => {
source.removeChild(this);
});
}
/** @internal */
onParentChange(_value, idle) {
const node = this.node;
if (idle && !node.done) {
// We're not idle until every source is idle.
node.done = toArray(this.source).every(source => !isAnimationValue(source) || source.idle);
} // TODO: only compute once per frame (note: we'll need to call "onParentChange")
const value = this._compute();
if (!isEqual(value, this.get())) {
node.setValue(value);
this._onChange(value, node.done);
}
}
/** @internal */
onParentPriorityChange(_priority) {
// Set our priority to 1 + the highest parent.
this.priority = toArray(this.source).reduce((max, source) => Math.max(max, (source.priority || 0) + 1), 0);
}
}
Globals.assign({
to: (source, args) => new Into(source, args),
createAnimatedStyle: style => new AnimatedStyle(style)
});
class AnimatedString extends AnimatedValue {
constructor(from, to) {
super(0);
this._string = null;
this._toString = createInterpolator$1({
output: [from, to]
});
}
static create(from, to) {
if (to === void 0) {
to = from;
}
if (is$1.str(from) && is$1.str(to)) {
return new AnimatedString(from, to);
}
throw TypeError('Expected "from" and "to" to be strings');
}
getValue() {
let value = this._string;
return value == null ? this._string = this._toString(this._value) : value;
}
setValue(value) {
if (!is$1.num(value)) {
this._string = value;
this._value = 1;
} else if (super.setValue(value)) {
this._string = null;
} else {
return false;
}
return true;
}
reset(isActive, goal) {
if (goal) {
this._toString = createInterpolator$1({
output: [this.getValue(), goal]
});
}
this._value = 0;
super.reset(isActive);
}
}
/** An array of animated nodes */
class AnimatedArray extends AnimatedObject {
constructor(from, to) {
super(null);
super.setValue(this._makeAnimated(from, to));
}
static create(from, to) {
return new AnimatedArray(from, to);
}
getValue() {
return this.source.map(node => node.getValue());
}
setValue(newValue) {
const payload = this.getPayload(); // Reuse the payload when lengths are equal.
if (newValue && newValue.length == payload.length) {
each(payload, (node, i) => node.setValue(newValue[i]));
} else {
// Remake the payload when length changes.
this.source = this._makeAnimated(newValue);
this.payload = this._makePayload(this.source);
}
}
/** Convert the `from` and `to` values to an array of `Animated` nodes */
_makeAnimated(from, to) {
if (to === void 0) {
to = from;
}
return from ? from.map((from, i) => (needsInterpolation(from) ? AnimatedString : AnimatedValue).create(from, to[i])) : [];
}
}
class AnimatedProps extends AnimatedObject {
constructor(update) {
super(null);
this.update = update;
/** Equals true when a re-render is scheduled for "end of frame" */
this.dirty = false;
}
setValue(props, context) {
if (!props) return; // The constructor passes null.
if (context) {
Animated.context = context;
}
super.setValue(props.style && createAnimatedStyle ? _extends({}, props, {
style: createAnimatedStyle(props.style)
}) : props);
Animated.context = null;
}
/** @internal */
onParentChange() {
if (!this.dirty) {
this.dirty = true;
frameLoop.onFrame(() => {
this.dirty = false;
this.update();
});
}
}
/** @internal */
onParentPriorityChange() {}
}
const cacheKey = Symbol.for('AnimatedComponent');
const withAnimated = Component => is.str(Component) ? createAnimatedComponent(Component) : Component[cacheKey] || (Component[cacheKey] = createAnimatedComponent(Component));
const createAnimatedComponent = Component => forwardRef((rawProps, ref) => {
const instanceRef = useRef(null);
const hasInstance = // Function components must use "forwardRef" to avoid being
// re-rendered on every animation frame.
!is.fun(Component) || Component.prototype.isReactComponent;
const forceUpdate = useForceUpdate();
const props = new AnimatedProps(() => {
const instance = instanceRef.current;
if (hasInstance && !instance) {
return; // The wrapped component forgot to forward its ref.
}
const didUpdate = instance ? applyAnimatedValues(instance, props.getValue(true)) : false; // Re-render the component when native updates fail.
if (didUpdate === false) {
forceUpdate();
}
});
const dependencies = new Set();
props.setValue(rawProps, {
dependencies
});
useIsomorphicLayoutEffect(() => {
each(dependencies, dep => dep.addChild(props));
return () => each(dependencies, dep => dep.removeChild(props));
});
return React.createElement(Component, Object.assign({}, getComponentProps(props.getValue()), {
ref: hasInstance && (value => {
instanceRef.current = updateRef(ref, value);
})
}));
});
function updateRef(ref, value) {
if (ref) {
if (is.fun(ref)) ref(value);else ref.current = value;
}
return value;
}
/**
* Pass the given components to `withAnimated` and add the newly animated
* components to `withAnimated` as properties.
*/
const extendAnimated = (withAnimated, components, lowercase) => {
components.forEach(Component => {
let key = getDisplayName(Component);
if (lowercase) {
key = key[0].toLowerCase() + key.slice(1);
}
withAnimated[key] = withAnimated(Component);
});
return withAnimated;
};
const getDisplayName = arg => is.str(arg) ? arg : arg && is.str(arg.displayName) ? arg.displayName : is.fun(arg) && arg.name || null;
export { Animated, AnimatedArray, AnimatedObject, AnimatedProps, AnimatedString, AnimatedStyle, AnimatedType, AnimatedValue, AnimationValue, Into, extendAnimated, isAnimated, isAnimationValue, withAnimated };
//# sourceMappingURL=index.js.map
| {
observer.onParentPriorityChange(priority, this);
} | conditional_block |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence
from torchvision import transforms
def to_var(x, volatile=False):
|
def main(args):
# Create model directory
if not os.path.exists(args.model_path):
os.makedirs(args.model_path)
# Image preprocessing
# For normalization, see https://github.com/pytorch/vision#models
transform = transforms.Compose([
transforms.RandomCrop(args.crop_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.485, 0.456, 0.406),
(0.229, 0.224, 0.225))])
# Load vocabulary wrapper.
with open(args.vocab_path, 'rb') as f:
vocab = pickle.load(f)
#read rationalization data
rationalizations = []
max_length = 0
lengths = []
bad_worker_ids = ['A2CNSIECB9UP05','A23782O23HSPLA','A2F9ZBSR6AXXND','A3GI86L18Z71XY','AIXTI8PKSX1D2','A2QWHXMFQI18GQ','A3SB7QYI84HYJT',
'A2Q2A7AB6MMFLI','A2P1KI42CJVNIA','A1IJXPKZTJV809','A2WZ0RZMKQ2WGJ','A3EKETMVGU2PM9','A1OCEC1TBE3CWA','AE1RYK54MH11G','A2ADEPVGNNXNPA',
'A15QGLWS8CNJFU','A18O3DEA5Z4MJD','AAAL4RENVAPML','A3TZBZ92CQKQLG','ABO9F0JD9NN54','A8F6JFG0WSELT','ARN9ET3E608LJ','A2TCYNRAZWK8CC',
'A32BK0E1IPDUAF','ANNV3E6CIVCW4']
with open('./Log/Rationalizations.txt') as f:
for line in f:
line = line.lower()
line = re.sub('[^a-z\ \']+', " ", line)
words = line.split()
length = len(words)
lengths.append(length)
if length>max_length:
max_length = length
for index,word in enumerate(words):
words[index] = vocab.word2idx[word]
rationalizations.append(words)
# max_length = max(rationalizations,key=len
rationalizations=[np.array(xi) for xi in rationalizations]
# for index,r in enumerate(rationalizations):
# # print(max_length)
# r = np.lib.pad(r,(0,max_length - len(r)),'constant')
# rationalizations[index] = r
# rationalizations = np.vstack(rationalizations)
# print(rationalizations)
# print(rationalizations.shape)
# print(torch.from_numpy(rationalizations))
# rationalizations = torch.from_numpy(rationalizations)
# print(np.asarray(rationalizations).reshape(rationalizations.shape,rationalizations.shape))
# Build data loader
data_loader = get_loader(args.image_dir, args.caption_path, vocab,
transform, args.batch_size,
shuffle=True, num_workers=args.num_workers)
# Build the models
encoder = EncoderCNN(args.embed_size)
decoder = DecoderRNN(args.embed_size, args.hidden_size,
len(vocab), args.num_layers)
if torch.cuda.is_available():
encoder.cuda()
decoder.cuda()
# Loss and Optimizer
criterion = nn.CrossEntropyLoss()
params = list(decoder.parameters()) + list(encoder.linear.parameters()) + list(encoder.bn.parameters())
optimizer = torch.optim.Adam(params, lr=args.learning_rate)
frogger_data_loader = get_images('./data/FroggerDataset/',args.batch_size,transform)
# exit(0)
# Train the Models
# data = iter(frogger_data_loader)
# imgs = data.next()[0]
# print(imgs)
# print(frogger_data_loader[0])
# exit(0)
# for i,(images) in enumerate(frogger_data_loader):
# print(images)
total_step = len(frogger_data_loader)
for epoch in range(args.num_epochs):
for i,x in enumerate(frogger_data_loader):
# print(x)
# print(x[0])
# exit(0)
# print(x[0])
# exit(0)
images = to_var(x[0], volatile=True)
print(images[0][1])
exit(0)
captions = []
max_length = max(lengths[i:i+2])
rats = rationalizations[i:i+2]
rats.sort(key = lambda s: len(s))
rats.reverse()
# print(rats)
# exit(0)
for index,r in enumerate(rats):
# print(max_length)
r = np.lib.pad(r,(0,max_length - len(r)),'constant')
captions.append(r)
# rationalizations = np.vstack(rationalizations)
# captions.sort(key = lambda s: len(s))
captions = to_var(torch.from_numpy(np.asarray(captions)))
# lengths.append(len(rationalizations[i]))
new_lengths = []
# new_lengths.append(lengths[i])
new_lengths = lengths[i:i+2]
new_lengths.sort()
new_lengths.reverse()
captions = captions
# print(captions)
# print(new_lengths)
targets = pack_padded_sequence(captions, new_lengths, batch_first=True)[0]
decoder.zero_grad()
encoder.zero_grad()
# print(images)
features = encoder(images)
# print(features)
# print(rats)
# print(len(lengths))
outputs = decoder(features, captions, new_lengths)
loss = criterion(outputs, targets)
loss.backward()
optimizer.step()
# Print log info
if i % args.log_step == 0:
print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
%(epoch, args.num_epochs, i, total_step,
loss.data[0], np.exp(loss.data[0])))
# Save the models
if (i+1) % args.save_step == 0:
torch.save(decoder.state_dict(),
os.path.join(args.model_path,
'decoder-%d-%d.pkl' %(epoch+1, i+1)))
torch.save(encoder.state_dict(),
os.path.join(args.model_path,
'encoder-%d-%d.pkl' %(epoch+1, i+1)))
# exit(0)
# total_step = len(data_loader)
# for epoch in range(args.num_epochs):
# for i, (images, captions, lengths) in enumerate(data_loader):
# # print(captions)
# # print(images)
# # print(lengths)
# # print(captions)
# # # print(images)
# # exit(0)
# # Set mini-batch dataset
# images = to_var(images, volatile=True)
# print(captions)
# captions = to_var(captions)
# print(captions)
# print(lengths)
# targets = pack_padded_sequence(captions, lengths, batch_first=True)[0]
# # Forward, Backward and Optimize
# decoder.zero_grad()
# encoder.zero_grad()
# print(images)
# features = encoder(images)
# print(features)
# exit(0)
# outputs = decoder(features, captions, lengths)
# loss = criterion(outputs, targets)
# loss.backward()
# optimizer.step()
# # Print log info
# if i % args.log_step == 0:
# print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
# %(epoch, args.num_epochs, i, total_step,
# loss.data[0], np.exp(loss.data[0])))
# # Save the models
# if (i+1) % args.save_step == 0:
# torch.save(decoder.state_dict(),
# os.path.join(args.model_path,
# 'decoder-%d-%d.pkl' %(epoch+1, i+1)))
# torch.save(encoder.state_dict(),
# os.path.join(args.model_path,
# 'encoder-%d-%d.pkl' %(epoch+1, i+1)))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', type=str, default='./models/' ,
help='path for saving trained models')
parser.add_argument('--crop_size', type=int, default=224 ,
help='size for randomly cropping images')
parser.add_argument('--vocab_path', type=str, default='./data/vocab_frogger.pkl',
help='path for vocabulary wrapper')
parser.add_argument('--image_dir', type=str, default='./data/resized2014' ,
help='directory for resized images')
parser.add_argument('--caption_path', type=str,
default='./data/annotations/captions_train2014.json',
help='path for train annotation json file')
parser.add_argument('--log_step', type=int , default=10,
help='step size for prining log info')
parser.add_argument('--save_step', type=int , default=20,
help='step size for saving trained models')
# Model parameters
parser.add_argument('--embed_size', type=int , default=256 ,
help='dimension of word embedding vectors')
parser.add_argument('--hidden_size', type=int , default=512 ,
help='dimension of lstm hidden states')
parser.add_argument('--num_layers', type=int , default=1 ,
help='number of layers in lstm')
parser.add_argument('--num_epochs', type=int, default=10)
parser.add_argument('--batch_size', type=int, default=2)
parser.add_argument('--num_workers', type=int, default=2)
parser.add_argument('--learning_rate', type=float, default=0.001)
args = parser.parse_args()
print(args)
main(args) | if torch.cuda.is_available():
x = x.cuda()
return Variable(x, volatile=volatile) | identifier_body |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence
from torchvision import transforms
def to_var(x, volatile=False):
if torch.cuda.is_available():
x = x.cuda()
return Variable(x, volatile=volatile)
def main(args):
# Create model directory
if not os.path.exists(args.model_path):
os.makedirs(args.model_path)
# Image preprocessing
# For normalization, see https://github.com/pytorch/vision#models
transform = transforms.Compose([
transforms.RandomCrop(args.crop_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.485, 0.456, 0.406),
(0.229, 0.224, 0.225))])
# Load vocabulary wrapper.
with open(args.vocab_path, 'rb') as f:
vocab = pickle.load(f)
#read rationalization data
rationalizations = []
max_length = 0
lengths = []
bad_worker_ids = ['A2CNSIECB9UP05','A23782O23HSPLA','A2F9ZBSR6AXXND','A3GI86L18Z71XY','AIXTI8PKSX1D2','A2QWHXMFQI18GQ','A3SB7QYI84HYJT',
'A2Q2A7AB6MMFLI','A2P1KI42CJVNIA','A1IJXPKZTJV809','A2WZ0RZMKQ2WGJ','A3EKETMVGU2PM9','A1OCEC1TBE3CWA','AE1RYK54MH11G','A2ADEPVGNNXNPA',
'A15QGLWS8CNJFU','A18O3DEA5Z4MJD','AAAL4RENVAPML','A3TZBZ92CQKQLG','ABO9F0JD9NN54','A8F6JFG0WSELT','ARN9ET3E608LJ','A2TCYNRAZWK8CC',
'A32BK0E1IPDUAF','ANNV3E6CIVCW4']
with open('./Log/Rationalizations.txt') as f:
for line in f:
line = line.lower()
line = re.sub('[^a-z\ \']+', " ", line)
words = line.split()
length = len(words)
lengths.append(length)
if length>max_length:
|
for index,word in enumerate(words):
words[index] = vocab.word2idx[word]
rationalizations.append(words)
# max_length = max(rationalizations,key=len
rationalizations=[np.array(xi) for xi in rationalizations]
# for index,r in enumerate(rationalizations):
# # print(max_length)
# r = np.lib.pad(r,(0,max_length - len(r)),'constant')
# rationalizations[index] = r
# rationalizations = np.vstack(rationalizations)
# print(rationalizations)
# print(rationalizations.shape)
# print(torch.from_numpy(rationalizations))
# rationalizations = torch.from_numpy(rationalizations)
# print(np.asarray(rationalizations).reshape(rationalizations.shape,rationalizations.shape))
# Build data loader
data_loader = get_loader(args.image_dir, args.caption_path, vocab,
transform, args.batch_size,
shuffle=True, num_workers=args.num_workers)
# Build the models
encoder = EncoderCNN(args.embed_size)
decoder = DecoderRNN(args.embed_size, args.hidden_size,
len(vocab), args.num_layers)
if torch.cuda.is_available():
encoder.cuda()
decoder.cuda()
# Loss and Optimizer
criterion = nn.CrossEntropyLoss()
params = list(decoder.parameters()) + list(encoder.linear.parameters()) + list(encoder.bn.parameters())
optimizer = torch.optim.Adam(params, lr=args.learning_rate)
frogger_data_loader = get_images('./data/FroggerDataset/',args.batch_size,transform)
# exit(0)
# Train the Models
# data = iter(frogger_data_loader)
# imgs = data.next()[0]
# print(imgs)
# print(frogger_data_loader[0])
# exit(0)
# for i,(images) in enumerate(frogger_data_loader):
# print(images)
total_step = len(frogger_data_loader)
for epoch in range(args.num_epochs):
for i,x in enumerate(frogger_data_loader):
# print(x)
# print(x[0])
# exit(0)
# print(x[0])
# exit(0)
images = to_var(x[0], volatile=True)
print(images[0][1])
exit(0)
captions = []
max_length = max(lengths[i:i+2])
rats = rationalizations[i:i+2]
rats.sort(key = lambda s: len(s))
rats.reverse()
# print(rats)
# exit(0)
for index,r in enumerate(rats):
# print(max_length)
r = np.lib.pad(r,(0,max_length - len(r)),'constant')
captions.append(r)
# rationalizations = np.vstack(rationalizations)
# captions.sort(key = lambda s: len(s))
captions = to_var(torch.from_numpy(np.asarray(captions)))
# lengths.append(len(rationalizations[i]))
new_lengths = []
# new_lengths.append(lengths[i])
new_lengths = lengths[i:i+2]
new_lengths.sort()
new_lengths.reverse()
captions = captions
# print(captions)
# print(new_lengths)
targets = pack_padded_sequence(captions, new_lengths, batch_first=True)[0]
decoder.zero_grad()
encoder.zero_grad()
# print(images)
features = encoder(images)
# print(features)
# print(rats)
# print(len(lengths))
outputs = decoder(features, captions, new_lengths)
loss = criterion(outputs, targets)
loss.backward()
optimizer.step()
# Print log info
if i % args.log_step == 0:
print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
%(epoch, args.num_epochs, i, total_step,
loss.data[0], np.exp(loss.data[0])))
# Save the models
if (i+1) % args.save_step == 0:
torch.save(decoder.state_dict(),
os.path.join(args.model_path,
'decoder-%d-%d.pkl' %(epoch+1, i+1)))
torch.save(encoder.state_dict(),
os.path.join(args.model_path,
'encoder-%d-%d.pkl' %(epoch+1, i+1)))
# exit(0)
# total_step = len(data_loader)
# for epoch in range(args.num_epochs):
# for i, (images, captions, lengths) in enumerate(data_loader):
# # print(captions)
# # print(images)
# # print(lengths)
# # print(captions)
# # # print(images)
# # exit(0)
# # Set mini-batch dataset
# images = to_var(images, volatile=True)
# print(captions)
# captions = to_var(captions)
# print(captions)
# print(lengths)
# targets = pack_padded_sequence(captions, lengths, batch_first=True)[0]
# # Forward, Backward and Optimize
# decoder.zero_grad()
# encoder.zero_grad()
# print(images)
# features = encoder(images)
# print(features)
# exit(0)
# outputs = decoder(features, captions, lengths)
# loss = criterion(outputs, targets)
# loss.backward()
# optimizer.step()
# # Print log info
# if i % args.log_step == 0:
# print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
# %(epoch, args.num_epochs, i, total_step,
# loss.data[0], np.exp(loss.data[0])))
# # Save the models
# if (i+1) % args.save_step == 0:
# torch.save(decoder.state_dict(),
# os.path.join(args.model_path,
# 'decoder-%d-%d.pkl' %(epoch+1, i+1)))
# torch.save(encoder.state_dict(),
# os.path.join(args.model_path,
# 'encoder-%d-%d.pkl' %(epoch+1, i+1)))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', type=str, default='./models/' ,
help='path for saving trained models')
parser.add_argument('--crop_size', type=int, default=224 ,
help='size for randomly cropping images')
parser.add_argument('--vocab_path', type=str, default='./data/vocab_frogger.pkl',
help='path for vocabulary wrapper')
parser.add_argument('--image_dir', type=str, default='./data/resized2014' ,
help='directory for resized images')
parser.add_argument('--caption_path', type=str,
default='./data/annotations/captions_train2014.json',
help='path for train annotation json file')
parser.add_argument('--log_step', type=int , default=10,
help='step size for prining log info')
parser.add_argument('--save_step', type=int , default=20,
help='step size for saving trained models')
# Model parameters
parser.add_argument('--embed_size', type=int , default=256 ,
help='dimension of word embedding vectors')
parser.add_argument('--hidden_size', type=int , default=512 ,
help='dimension of lstm hidden states')
parser.add_argument('--num_layers', type=int , default=1 ,
help='number of layers in lstm')
parser.add_argument('--num_epochs', type=int, default=10)
parser.add_argument('--batch_size', type=int, default=2)
parser.add_argument('--num_workers', type=int, default=2)
parser.add_argument('--learning_rate', type=float, default=0.001)
args = parser.parse_args()
print(args)
main(args) | max_length = length | conditional_block |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence
from torchvision import transforms
def to_var(x, volatile=False):
if torch.cuda.is_available():
x = x.cuda()
return Variable(x, volatile=volatile)
def main(args):
# Create model directory
if not os.path.exists(args.model_path):
os.makedirs(args.model_path)
# Image preprocessing
# For normalization, see https://github.com/pytorch/vision#models
transform = transforms.Compose([
transforms.RandomCrop(args.crop_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.485, 0.456, 0.406),
(0.229, 0.224, 0.225))])
# Load vocabulary wrapper.
with open(args.vocab_path, 'rb') as f:
vocab = pickle.load(f)
#read rationalization data
rationalizations = []
max_length = 0
lengths = []
bad_worker_ids = ['A2CNSIECB9UP05','A23782O23HSPLA','A2F9ZBSR6AXXND','A3GI86L18Z71XY','AIXTI8PKSX1D2','A2QWHXMFQI18GQ','A3SB7QYI84HYJT',
'A2Q2A7AB6MMFLI','A2P1KI42CJVNIA','A1IJXPKZTJV809','A2WZ0RZMKQ2WGJ','A3EKETMVGU2PM9','A1OCEC1TBE3CWA','AE1RYK54MH11G','A2ADEPVGNNXNPA',
'A15QGLWS8CNJFU','A18O3DEA5Z4MJD','AAAL4RENVAPML','A3TZBZ92CQKQLG','ABO9F0JD9NN54','A8F6JFG0WSELT','ARN9ET3E608LJ','A2TCYNRAZWK8CC',
'A32BK0E1IPDUAF','ANNV3E6CIVCW4']
with open('./Log/Rationalizations.txt') as f:
for line in f:
line = line.lower()
line = re.sub('[^a-z\ \']+', " ", line)
words = line.split()
length = len(words)
lengths.append(length)
if length>max_length:
max_length = length
for index,word in enumerate(words):
words[index] = vocab.word2idx[word]
rationalizations.append(words)
# max_length = max(rationalizations,key=len
rationalizations=[np.array(xi) for xi in rationalizations]
# for index,r in enumerate(rationalizations):
# # print(max_length)
# r = np.lib.pad(r,(0,max_length - len(r)),'constant')
# rationalizations[index] = r
# rationalizations = np.vstack(rationalizations)
# print(rationalizations)
# print(rationalizations.shape)
# print(torch.from_numpy(rationalizations))
# rationalizations = torch.from_numpy(rationalizations)
# print(np.asarray(rationalizations).reshape(rationalizations.shape,rationalizations.shape))
# Build data loader
data_loader = get_loader(args.image_dir, args.caption_path, vocab,
transform, args.batch_size,
shuffle=True, num_workers=args.num_workers)
# Build the models
encoder = EncoderCNN(args.embed_size)
decoder = DecoderRNN(args.embed_size, args.hidden_size,
len(vocab), args.num_layers)
if torch.cuda.is_available():
encoder.cuda()
decoder.cuda()
# Loss and Optimizer
criterion = nn.CrossEntropyLoss()
params = list(decoder.parameters()) + list(encoder.linear.parameters()) + list(encoder.bn.parameters())
optimizer = torch.optim.Adam(params, lr=args.learning_rate)
frogger_data_loader = get_images('./data/FroggerDataset/',args.batch_size,transform)
# exit(0)
# Train the Models
# data = iter(frogger_data_loader)
# imgs = data.next()[0]
# print(imgs)
# print(frogger_data_loader[0])
# exit(0)
# for i,(images) in enumerate(frogger_data_loader):
# print(images)
total_step = len(frogger_data_loader)
for epoch in range(args.num_epochs):
for i,x in enumerate(frogger_data_loader):
# print(x)
# print(x[0])
# exit(0)
# print(x[0])
# exit(0)
images = to_var(x[0], volatile=True)
print(images[0][1])
exit(0)
captions = []
max_length = max(lengths[i:i+2])
rats = rationalizations[i:i+2]
rats.sort(key = lambda s: len(s))
rats.reverse()
# print(rats)
# exit(0)
for index,r in enumerate(rats):
# print(max_length)
r = np.lib.pad(r,(0,max_length - len(r)),'constant')
captions.append(r)
# rationalizations = np.vstack(rationalizations)
# captions.sort(key = lambda s: len(s))
captions = to_var(torch.from_numpy(np.asarray(captions)))
# lengths.append(len(rationalizations[i]))
new_lengths = []
# new_lengths.append(lengths[i])
new_lengths = lengths[i:i+2]
new_lengths.sort() | new_lengths.reverse()
captions = captions
# print(captions)
# print(new_lengths)
targets = pack_padded_sequence(captions, new_lengths, batch_first=True)[0]
decoder.zero_grad()
encoder.zero_grad()
# print(images)
features = encoder(images)
# print(features)
# print(rats)
# print(len(lengths))
outputs = decoder(features, captions, new_lengths)
loss = criterion(outputs, targets)
loss.backward()
optimizer.step()
# Print log info
if i % args.log_step == 0:
print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
%(epoch, args.num_epochs, i, total_step,
loss.data[0], np.exp(loss.data[0])))
# Save the models
if (i+1) % args.save_step == 0:
torch.save(decoder.state_dict(),
os.path.join(args.model_path,
'decoder-%d-%d.pkl' %(epoch+1, i+1)))
torch.save(encoder.state_dict(),
os.path.join(args.model_path,
'encoder-%d-%d.pkl' %(epoch+1, i+1)))
# exit(0)
# total_step = len(data_loader)
# for epoch in range(args.num_epochs):
# for i, (images, captions, lengths) in enumerate(data_loader):
# # print(captions)
# # print(images)
# # print(lengths)
# # print(captions)
# # # print(images)
# # exit(0)
# # Set mini-batch dataset
# images = to_var(images, volatile=True)
# print(captions)
# captions = to_var(captions)
# print(captions)
# print(lengths)
# targets = pack_padded_sequence(captions, lengths, batch_first=True)[0]
# # Forward, Backward and Optimize
# decoder.zero_grad()
# encoder.zero_grad()
# print(images)
# features = encoder(images)
# print(features)
# exit(0)
# outputs = decoder(features, captions, lengths)
# loss = criterion(outputs, targets)
# loss.backward()
# optimizer.step()
# # Print log info
# if i % args.log_step == 0:
# print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
# %(epoch, args.num_epochs, i, total_step,
# loss.data[0], np.exp(loss.data[0])))
# # Save the models
# if (i+1) % args.save_step == 0:
# torch.save(decoder.state_dict(),
# os.path.join(args.model_path,
# 'decoder-%d-%d.pkl' %(epoch+1, i+1)))
# torch.save(encoder.state_dict(),
# os.path.join(args.model_path,
# 'encoder-%d-%d.pkl' %(epoch+1, i+1)))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', type=str, default='./models/' ,
help='path for saving trained models')
parser.add_argument('--crop_size', type=int, default=224 ,
help='size for randomly cropping images')
parser.add_argument('--vocab_path', type=str, default='./data/vocab_frogger.pkl',
help='path for vocabulary wrapper')
parser.add_argument('--image_dir', type=str, default='./data/resized2014' ,
help='directory for resized images')
parser.add_argument('--caption_path', type=str,
default='./data/annotations/captions_train2014.json',
help='path for train annotation json file')
parser.add_argument('--log_step', type=int , default=10,
help='step size for prining log info')
parser.add_argument('--save_step', type=int , default=20,
help='step size for saving trained models')
# Model parameters
parser.add_argument('--embed_size', type=int , default=256 ,
help='dimension of word embedding vectors')
parser.add_argument('--hidden_size', type=int , default=512 ,
help='dimension of lstm hidden states')
parser.add_argument('--num_layers', type=int , default=1 ,
help='number of layers in lstm')
parser.add_argument('--num_epochs', type=int, default=10)
parser.add_argument('--batch_size', type=int, default=2)
parser.add_argument('--num_workers', type=int, default=2)
parser.add_argument('--learning_rate', type=float, default=0.001)
args = parser.parse_args()
print(args)
main(args) | random_line_split | |
train.py | import argparse
import torch
import torch.nn as nn
import re
import numpy as np
import os
import pickle
from data_loader import get_loader
from data_loader import get_images
from build_vocab import Vocabulary
from model import EncoderCNN, DecoderRNN
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence
from torchvision import transforms
def | (x, volatile=False):
if torch.cuda.is_available():
x = x.cuda()
return Variable(x, volatile=volatile)
def main(args):
# Create model directory
if not os.path.exists(args.model_path):
os.makedirs(args.model_path)
# Image preprocessing
# For normalization, see https://github.com/pytorch/vision#models
transform = transforms.Compose([
transforms.RandomCrop(args.crop_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.485, 0.456, 0.406),
(0.229, 0.224, 0.225))])
# Load vocabulary wrapper.
with open(args.vocab_path, 'rb') as f:
vocab = pickle.load(f)
#read rationalization data
rationalizations = []
max_length = 0
lengths = []
bad_worker_ids = ['A2CNSIECB9UP05','A23782O23HSPLA','A2F9ZBSR6AXXND','A3GI86L18Z71XY','AIXTI8PKSX1D2','A2QWHXMFQI18GQ','A3SB7QYI84HYJT',
'A2Q2A7AB6MMFLI','A2P1KI42CJVNIA','A1IJXPKZTJV809','A2WZ0RZMKQ2WGJ','A3EKETMVGU2PM9','A1OCEC1TBE3CWA','AE1RYK54MH11G','A2ADEPVGNNXNPA',
'A15QGLWS8CNJFU','A18O3DEA5Z4MJD','AAAL4RENVAPML','A3TZBZ92CQKQLG','ABO9F0JD9NN54','A8F6JFG0WSELT','ARN9ET3E608LJ','A2TCYNRAZWK8CC',
'A32BK0E1IPDUAF','ANNV3E6CIVCW4']
with open('./Log/Rationalizations.txt') as f:
for line in f:
line = line.lower()
line = re.sub('[^a-z\ \']+', " ", line)
words = line.split()
length = len(words)
lengths.append(length)
if length>max_length:
max_length = length
for index,word in enumerate(words):
words[index] = vocab.word2idx[word]
rationalizations.append(words)
# max_length = max(rationalizations,key=len
rationalizations=[np.array(xi) for xi in rationalizations]
# for index,r in enumerate(rationalizations):
# # print(max_length)
# r = np.lib.pad(r,(0,max_length - len(r)),'constant')
# rationalizations[index] = r
# rationalizations = np.vstack(rationalizations)
# print(rationalizations)
# print(rationalizations.shape)
# print(torch.from_numpy(rationalizations))
# rationalizations = torch.from_numpy(rationalizations)
# print(np.asarray(rationalizations).reshape(rationalizations.shape,rationalizations.shape))
# Build data loader
data_loader = get_loader(args.image_dir, args.caption_path, vocab,
transform, args.batch_size,
shuffle=True, num_workers=args.num_workers)
# Build the models
encoder = EncoderCNN(args.embed_size)
decoder = DecoderRNN(args.embed_size, args.hidden_size,
len(vocab), args.num_layers)
if torch.cuda.is_available():
encoder.cuda()
decoder.cuda()
# Loss and Optimizer
criterion = nn.CrossEntropyLoss()
params = list(decoder.parameters()) + list(encoder.linear.parameters()) + list(encoder.bn.parameters())
optimizer = torch.optim.Adam(params, lr=args.learning_rate)
frogger_data_loader = get_images('./data/FroggerDataset/',args.batch_size,transform)
# exit(0)
# Train the Models
# data = iter(frogger_data_loader)
# imgs = data.next()[0]
# print(imgs)
# print(frogger_data_loader[0])
# exit(0)
# for i,(images) in enumerate(frogger_data_loader):
# print(images)
total_step = len(frogger_data_loader)
for epoch in range(args.num_epochs):
for i,x in enumerate(frogger_data_loader):
# print(x)
# print(x[0])
# exit(0)
# print(x[0])
# exit(0)
images = to_var(x[0], volatile=True)
print(images[0][1])
exit(0)
captions = []
max_length = max(lengths[i:i+2])
rats = rationalizations[i:i+2]
rats.sort(key = lambda s: len(s))
rats.reverse()
# print(rats)
# exit(0)
for index,r in enumerate(rats):
# print(max_length)
r = np.lib.pad(r,(0,max_length - len(r)),'constant')
captions.append(r)
# rationalizations = np.vstack(rationalizations)
# captions.sort(key = lambda s: len(s))
captions = to_var(torch.from_numpy(np.asarray(captions)))
# lengths.append(len(rationalizations[i]))
new_lengths = []
# new_lengths.append(lengths[i])
new_lengths = lengths[i:i+2]
new_lengths.sort()
new_lengths.reverse()
captions = captions
# print(captions)
# print(new_lengths)
targets = pack_padded_sequence(captions, new_lengths, batch_first=True)[0]
decoder.zero_grad()
encoder.zero_grad()
# print(images)
features = encoder(images)
# print(features)
# print(rats)
# print(len(lengths))
outputs = decoder(features, captions, new_lengths)
loss = criterion(outputs, targets)
loss.backward()
optimizer.step()
# Print log info
if i % args.log_step == 0:
print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
%(epoch, args.num_epochs, i, total_step,
loss.data[0], np.exp(loss.data[0])))
# Save the models
if (i+1) % args.save_step == 0:
torch.save(decoder.state_dict(),
os.path.join(args.model_path,
'decoder-%d-%d.pkl' %(epoch+1, i+1)))
torch.save(encoder.state_dict(),
os.path.join(args.model_path,
'encoder-%d-%d.pkl' %(epoch+1, i+1)))
# exit(0)
# total_step = len(data_loader)
# for epoch in range(args.num_epochs):
# for i, (images, captions, lengths) in enumerate(data_loader):
# # print(captions)
# # print(images)
# # print(lengths)
# # print(captions)
# # # print(images)
# # exit(0)
# # Set mini-batch dataset
# images = to_var(images, volatile=True)
# print(captions)
# captions = to_var(captions)
# print(captions)
# print(lengths)
# targets = pack_padded_sequence(captions, lengths, batch_first=True)[0]
# # Forward, Backward and Optimize
# decoder.zero_grad()
# encoder.zero_grad()
# print(images)
# features = encoder(images)
# print(features)
# exit(0)
# outputs = decoder(features, captions, lengths)
# loss = criterion(outputs, targets)
# loss.backward()
# optimizer.step()
# # Print log info
# if i % args.log_step == 0:
# print('Epoch [%d/%d], Step [%d/%d], Loss: %.4f, Perplexity: %5.4f'
# %(epoch, args.num_epochs, i, total_step,
# loss.data[0], np.exp(loss.data[0])))
# # Save the models
# if (i+1) % args.save_step == 0:
# torch.save(decoder.state_dict(),
# os.path.join(args.model_path,
# 'decoder-%d-%d.pkl' %(epoch+1, i+1)))
# torch.save(encoder.state_dict(),
# os.path.join(args.model_path,
# 'encoder-%d-%d.pkl' %(epoch+1, i+1)))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_path', type=str, default='./models/' ,
help='path for saving trained models')
parser.add_argument('--crop_size', type=int, default=224 ,
help='size for randomly cropping images')
parser.add_argument('--vocab_path', type=str, default='./data/vocab_frogger.pkl',
help='path for vocabulary wrapper')
parser.add_argument('--image_dir', type=str, default='./data/resized2014' ,
help='directory for resized images')
parser.add_argument('--caption_path', type=str,
default='./data/annotations/captions_train2014.json',
help='path for train annotation json file')
parser.add_argument('--log_step', type=int , default=10,
help='step size for prining log info')
parser.add_argument('--save_step', type=int , default=20,
help='step size for saving trained models')
# Model parameters
parser.add_argument('--embed_size', type=int , default=256 ,
help='dimension of word embedding vectors')
parser.add_argument('--hidden_size', type=int , default=512 ,
help='dimension of lstm hidden states')
parser.add_argument('--num_layers', type=int , default=1 ,
help='number of layers in lstm')
parser.add_argument('--num_epochs', type=int, default=10)
parser.add_argument('--batch_size', type=int, default=2)
parser.add_argument('--num_workers', type=int, default=2)
parser.add_argument('--learning_rate', type=float, default=0.001)
args = parser.parse_args()
print(args)
main(args) | to_var | identifier_name |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celery.schedules import crontab
from celery.task import periodic_task
from django.conf import settings
from django.core.mail import send_mail
from rest_framework import status
from hs_core.hydroshare import utils
from hs_core.hydroshare.hs_bagit import create_bag_files
from hs_core.hydroshare.resource import get_activated_doi, get_resource_doi, \
get_crossref_url, deposit_res_metadata_with_crossref
from django_irods.storage import IrodsStorage
from theme.models import UserQuota, QuotaMessage, UserProfile, User
from django_irods.icommands import SessionException
from hs_core.models import BaseResource
from theme.utils import get_quota_message
# Pass 'django' into getLogger instead of __name__
# for celery tasks (as this seems to be the
# only way to successfully log in code executed
# by celery, despite our catch-all handler).
logger = logging.getLogger('django')
# Currently there are two different cleanups scheduled.
# One is 20 minutes after creation, the other is nightly.
# TODO Clean up zipfiles in remote federated storage as well.
@periodic_task(ignore_result=True, run_every=crontab(minute=30, hour=23))
def nightly_zips_cleanup():
# delete 2 days ago
date_folder = (date.today() - timedelta(2)).strftime('%Y-%m-%d')
zips_daily_date = "zips/{daily_date}".format(daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage()
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
federated_prefixes = BaseResource.objects.all().values_list('resource_federation_path')\
.distinct()
for p in federated_prefixes:
prefix = p[0] # strip tuple
if prefix != "":
zips_daily_date = "{prefix}/zips/{daily_date}"\
.format(prefix=prefix, daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage("federated")
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def sync_email_subscriptions():
sixty_days = datetime.today() - timedelta(days=60)
active_subscribed = UserProfile.objects.filter(email_opt_out=False,
user__last_login__gte=sixty_days,
user__is_active=True)
sync_mailchimp(active_subscribed, settings.MAILCHIMP_ACTIVE_SUBSCRIBERS)
subscribed = UserProfile.objects.filter(email_opt_out=False, user__is_active=True)
sync_mailchimp(subscribed, settings.MAILCHIMP_SUBSCRIBERS)
def sync_mailchimp(active_subscribed, list_id):
session = requests.Session()
url = "https://us3.api.mailchimp.com/3.0/lists/{list_id}/members"
# get total members
response = session.get(url.format(list_id=list_id), auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
total_items = json.loads(response.content)["total_items"]
# get list of all member ids
response = session.get((url + "?offset=0&count={total_items}").format(list_id=list_id,
total_items=total_items),
auth=requests.auth.HTTPBasicAuth('hs-celery',
settings.MAILCHIMP_PASSWORD))
# clear the email list
delete_count = 0
for member in json.loads(response.content)["members"]:
if member["status"] == "subscribed":
session_response = session.delete(
(url + "/{id}").format(list_id=list_id, id=member["id"]),
auth=requests.auth.HTTPBasicAuth('hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 204:
logger.info("Expected 204 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
delete_count += 1
# add active subscribed users to mailchimp
add_count = 0
for subscriber in active_subscribed:
json_data = {"email_address": subscriber.user.email, "status": "subscribed",
"merge_fields": {"FNAME": subscriber.user.first_name,
"LNAME": subscriber.user.last_name}}
session_response = session.post(
url.format(list_id=list_id), json=json_data, auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 200:
logger.info("Expected 200 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
add_count += 1
if delete_count == active_subscribed.count():
logger.info("successfully cleared mailchimp for list id " + list_id)
else:
logger.info(
"cleared " + str(delete_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
if active_subscribed.count() == add_count:
logger.info("successfully synced all subscriptions for list id " + list_id)
else:
|
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def manage_task_nightly():
# The nightly running task do DOI activation check
# Check DOI activation on failed and pending resources and send email.
msg_lst = []
# retrieve all published resources with failed metadata deposition with CrossRef if any and
# retry metadata deposition
failed_resources = BaseResource.objects.filter(raccess__published=True, doi__contains='failure')
for res in failed_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
response = deposit_res_metadata_with_crossref(res)
if response.status_code == status.HTTP_200_OK:
# retry of metadata deposition succeeds, change resource flag from failure
# to pending
res.doi = get_resource_doi(act_doi, 'pending')
res.save()
else:
# retry of metadata deposition failed again, notify admin
msg_lst.append("Metadata deposition with CrossRef for the published resource "
"DOI {res_doi} failed again after retry with first metadata "
"deposition requested since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
pending_resources = BaseResource.objects.filter(raccess__published=True,
doi__contains='pending')
for res in pending_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
main_url = get_crossref_url()
req_str = '{MAIN_URL}servlet/submissionDownload?usr={USERNAME}&pwd=' \
'{PASSWORD}&doi_batch_id={DOI_BATCH_ID}&type={TYPE}'
response = requests.get(req_str.format(MAIN_URL=main_url,
USERNAME=settings.CROSSREF_LOGIN_ID,
PASSWORD=settings.CROSSREF_LOGIN_PWD,
DOI_BATCH_ID=res.short_id,
TYPE='result'))
root = ElementTree.fromstring(response.content)
rec_cnt_elem = root.find('.//record_count')
failure_cnt_elem = root.find('.//failure_count')
success = False
if rec_cnt_elem is not None and failure_cnt_elem is not None:
rec_cnt = int(rec_cnt_elem.text)
failure_cnt = int(failure_cnt_elem.text)
if rec_cnt > 0 and failure_cnt == 0:
res.doi = act_doi
res.save()
success = True
if not success:
msg_lst.append("Published resource DOI {res_doi} is not yet activated with request "
"data deposited since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
if msg_lst:
email_msg = '\n'.join(msg_lst)
subject = 'Notification of pending DOI deposition/activation of published resources'
# send email for people monitoring and follow-up as needed
send_mail(subject, email_msg, settings.DEFAULT_FROM_EMAIL, [settings.DEFAULT_SUPPORT_EMAIL])
@periodic_task(ignore_result=True, run_every=crontab(minute=15, hour=0, day_of_week=1,
day_of_month='1-7'))
def send_over_quota_emails():
# check over quota cases and send quota warning emails as needed
hs_internal_zone = "hydroshare"
if not QuotaMessage.objects.exists():
QuotaMessage.objects.create()
qmsg = QuotaMessage.objects.first()
users = User.objects.filter(is_active=True).filter(is_superuser=False).all()
for u in users:
uq = UserQuota.objects.filter(user__username=u.username, zone=hs_internal_zone).first()
if uq:
used_percent = uq.used_percent
if used_percent >= qmsg.soft_limit_percent:
if used_percent >= 100 and used_percent < qmsg.hard_limit_percent:
if uq.remaining_grace_period < 0:
# triggers grace period counting
uq.remaining_grace_period = qmsg.grace_period
elif uq.remaining_grace_period > 0:
# reduce remaining_grace_period by one day
uq.remaining_grace_period -= 1
elif used_percent >= qmsg.hard_limit_percent:
# set grace period to 0 when user quota exceeds hard limit
uq.remaining_grace_period = 0
uq.save()
if u.first_name and u.last_name:
sal_name = '{} {}'.format(u.first_name, u.last_name)
elif u.first_name:
sal_name = u.first_name
elif u.last_name:
sal_name = u.last_name
else:
sal_name = u.username
msg_str = 'Dear ' + sal_name + ':\n\n'
ori_qm = get_quota_message(u)
# make embedded settings.DEFAULT_SUPPORT_EMAIL clickable with subject auto-filled
replace_substr = "<a href='mailto:{0}?subject=Request more quota'>{0}</a>".format(
settings.DEFAULT_SUPPORT_EMAIL)
new_qm = ori_qm.replace(settings.DEFAULT_SUPPORT_EMAIL, replace_substr)
msg_str += new_qm
msg_str += '\n\nHydroShare Support'
subject = 'Quota warning'
try:
# send email for people monitoring and follow-up as needed
send_mail(subject, '', settings.DEFAULT_FROM_EMAIL,
[u.email, settings.DEFAULT_SUPPORT_EMAIL],
html_message=msg_str)
except Exception as ex:
logger.debug("Failed to send quota warning email: " + ex.message)
else:
if uq.remaining_grace_period >= 0:
# turn grace period off now that the user is below quota soft limit
uq.remaining_grace_period = -1
uq.save()
else:
logger.debug('user ' + u.username + ' does not have UserQuota foreign key relation')
@shared_task
def add_zip_file_contents_to_resource(pk, zip_file_path):
"""Add zip file to existing resource and remove tmp zip file."""
zfile = None
resource = None
try:
resource = utils.get_resource_by_shortkey(pk, or_404=False)
zfile = zipfile.ZipFile(zip_file_path)
num_files = len(zfile.infolist())
zcontents = utils.ZipContents(zfile)
files = zcontents.get_files()
resource.file_unpack_status = 'Running'
resource.save()
for i, f in enumerate(files):
logger.debug("Adding file {0} to resource {1}".format(f.name, pk))
utils.add_file_to_resource(resource, f)
resource.file_unpack_message = "Imported {0} of about {1} file(s) ...".format(
i, num_files)
resource.save()
# This might make the resource unsuitable for public consumption
resource.update_public_and_discoverable()
# TODO: this is a bit of a lie because a different user requested the bag overwrite
utils.resource_modified(resource, resource.creator, overwrite_bag=False)
# Call success callback
resource.file_unpack_message = None
resource.file_unpack_status = 'Done'
resource.save()
except BaseResource.DoesNotExist:
msg = "Unable to add zip file contents to non-existent resource {pk}."
msg = msg.format(pk=pk)
logger.error(msg)
except:
exc_info = "".join(traceback.format_exception(*sys.exc_info()))
if resource:
resource.file_unpack_status = 'Error'
resource.file_unpack_message = exc_info
resource.save()
if zfile:
zfile.close()
logger.error(exc_info)
finally:
# Delete upload file
os.unlink(zip_file_path)
@shared_task
def delete_zip(zip_path):
istorage = IrodsStorage()
if istorage.exists(zip_path):
istorage.delete(zip_path)
@shared_task
def create_temp_zip(resource_id, input_path, output_path, sf_aggregation, sf_zip=False):
""" Create temporary zip file from input_path and store in output_path
:param input_path: full irods path of input starting with federation path
:param output_path: full irods path of output starting with federation path
:param sf_aggregation: if True, include logical metadata files
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage() # invoke federated storage as necessary
if res.resource_type == "CompositeResource":
if '/data/contents/' in input_path:
short_path = input_path.split('/data/contents/')[1] # strip /data/contents/
res.create_aggregation_xml_documents(aggregation_name=short_path)
else: # all metadata included, e.g., /data/*
res.create_aggregation_xml_documents()
try:
if sf_zip:
# input path points to single file aggregation
# ensure that foo.zip contains aggregation metadata
# by copying these into a temp subdirectory foo/foo parallel to where foo.zip is stored
temp_folder_name, ext = os.path.splitext(output_path) # strip zip to get scratch dir
head, tail = os.path.split(temp_folder_name) # tail is unqualified folder name "foo"
out_with_folder = os.path.join(temp_folder_name, tail) # foo/foo is subdir to zip
istorage.copyFiles(input_path, out_with_folder)
if sf_aggregation:
try:
istorage.copyFiles(input_path + '_resmap.xml', out_with_folder + '_resmap.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_resmap.xml'))
try:
istorage.copyFiles(input_path + '_meta.xml', out_with_folder + '_meta.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_meta.xml'))
istorage.zipup(temp_folder_name, output_path)
istorage.delete(temp_folder_name) # delete working directory; this isn't the zipfile
else: # regular folder to zip
istorage.zipup(input_path, output_path)
except SessionException as ex:
logger.error(ex.stderr)
return False
return True
@shared_task
def create_bag_by_irods(resource_id):
"""Create a resource bag on iRODS side by running the bagit rule and ibun zip.
This function runs as a celery task, invoked asynchronously so that it does not
block the main web thread when it creates bags for very large files which will take some time.
:param
resource_id: the resource uuid that is used to look for the resource to create the bag for.
:return: True if bag creation operation succeeds;
False if there is an exception raised or resource does not exist.
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage()
metadata_dirty = istorage.getAVU(res.root_path, 'metadata_dirty')
# if metadata has been changed, then regenerate metadata xml files
if metadata_dirty is None or metadata_dirty.lower() == "true":
try:
create_bag_files(res)
except Exception as ex:
logger.error('Failed to create bag files. Error:{}'.format(ex.message))
return False
bag_full_name = 'bags/{res_id}.zip'.format(res_id=resource_id)
if res.resource_federation_path:
irods_bagit_input_path = os.path.join(res.resource_federation_path, resource_id)
is_exist = istorage.exists(irods_bagit_input_path)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{fed_path}/{res_id}/readme.txt'.format(
fed_path=res.resource_federation_path,
res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.HS_IRODS_USER_ZONE_DEF_RES)
bag_full_name = os.path.join(res.resource_federation_path, bag_full_name)
bagit_files = [
'{fed_path}/{res_id}/bagit.txt'.format(fed_path=res.resource_federation_path,
res_id=resource_id),
'{fed_path}/{res_id}/manifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/{res_id}/tagmanifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/bags/{res_id}.zip'.format(fed_path=res.resource_federation_path,
res_id=resource_id)
]
else:
is_exist = istorage.exists(resource_id)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{res_id}/readme.txt'.format(res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
irods_dest_prefix = "/" + settings.IRODS_ZONE + "/home/" + settings.IRODS_USERNAME
irods_bagit_input_path = os.path.join(irods_dest_prefix, resource_id)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.IRODS_DEFAULT_RESOURCE)
bagit_files = [
'{res_id}/bagit.txt'.format(res_id=resource_id),
'{res_id}/manifest-md5.txt'.format(res_id=resource_id),
'{res_id}/tagmanifest-md5.txt'.format(res_id=resource_id),
'bags/{res_id}.zip'.format(res_id=resource_id)
]
# only proceed when the resource is not deleted potentially by another request
# when being downloaded
if is_exist:
# if bagit readme.txt does not exist, add it.
if not is_bagit_readme_exist:
from_file_name = getattr(settings, 'HS_BAGIT_README_FILE_WITH_PATH',
'docs/bagit/readme.txt')
istorage.saveFile(from_file_name, bagit_readme_file, True)
# call iRODS bagit rule here
bagit_rule_file = getattr(settings, 'IRODS_BAGIT_RULE',
'hydroshare/irods/ruleGenerateBagIt_HS.r')
try:
# call iRODS run and ibun command to create and zip the bag, ignore SessionException
# for now as a workaround which could be raised from potential race conditions when
# multiple ibun commands try to create the same zip file or the very same resource
# gets deleted by another request when being downloaded
istorage.runBagitRule(bagit_rule_file, bagit_input_path, bagit_input_resource)
istorage.zipup(irods_bagit_input_path, bag_full_name)
istorage.setAVU(irods_bagit_input_path, 'bag_modified', "false")
return True
except SessionException as ex:
# if an exception occurs, delete incomplete files potentially being generated by
# iRODS bagit rule and zipping operations
for fname in bagit_files:
if istorage.exists(fname):
istorage.delete(fname)
logger.error(ex.stderr)
return False
else:
logger.error('Resource does not exist.')
return False
@shared_task
def update_quota_usage_task(username):
"""update quota usage. This function runs as a celery task, invoked asynchronously with 1
minute delay to give enough time for iRODS real time quota update micro-services to update
quota usage AVU for the user before this celery task to check this AVU to get the updated
quota usage for the user. Note iRODS micro-service quota update only happens on HydroShare
iRODS data zone and user zone independently, so the aggregation of usage in both zones need
to be accounted for in this function to update Django DB as an aggregated usage for hydroshare
internal zone.
:param
username: the name of the user that needs to update quota usage for.
:return: True if quota usage update succeeds;
False if there is an exception raised or quota cannot be updated. See log for details.
"""
hs_internal_zone = "hydroshare"
uq = UserQuota.objects.filter(user__username=username, zone=hs_internal_zone).first()
if uq is None:
# the quota row does not exist in Django
logger.error('quota row does not exist in Django for hydroshare zone for '
'user ' + username)
return False
attname = username + '-usage'
istorage = IrodsStorage()
# get quota size for user in iRODS data zone by retrieving AVU set on irods bagit path
# collection
try:
uqDataZoneSize = istorage.getAVU(settings.IRODS_BAGIT_PATH, attname)
if uqDataZoneSize is None:
# user may not have resources in data zone, so corresponding quota size AVU may not
# exist for this user
uqDataZoneSize = -1
else:
uqDataZoneSize = float(uqDataZoneSize)
except SessionException:
# user may not have resources in data zone, so corresponding quota size AVU may not exist
# for this user
uqDataZoneSize = -1
# get quota size for the user in iRODS user zone
try:
uz_bagit_path = os.path.join('/', settings.HS_USER_IRODS_ZONE, 'home',
settings.HS_IRODS_PROXY_USER_IN_USER_ZONE,
settings.IRODS_BAGIT_PATH)
uqUserZoneSize = istorage.getAVU(uz_bagit_path, attname)
if uqUserZoneSize is None:
# user may not have resources in user zone, so corresponding quota size AVU may not
# exist for this user
uqUserZoneSize = -1
else:
uqUserZoneSize = float(uqUserZoneSize)
except SessionException:
# user may not have resources in user zone, so corresponding quota size AVU may not exist
# for this user
uqUserZoneSize = -1
if uqDataZoneSize < 0 and uqUserZoneSize < 0:
logger.error('no quota size AVU in data zone and user zone for the user ' + username)
return False
elif uqUserZoneSize < 0:
used_val = uqDataZoneSize
elif uqDataZoneSize < 0:
used_val = uqUserZoneSize
else:
used_val = uqDataZoneSize + uqUserZoneSize
uq.update_used_value(used_val)
return True
@shared_task
def update_web_services(services_url, api_token, timeout, publish_urls, res_id):
"""Update web services hosted by GeoServer and HydroServer.
This function sends a resource id to the HydroShare web services manager
application, which will check the current status of the resource and register
or unregister services hosted by GeoServer and HydroServer.
The HydroShare web services manager will return a list of endpoint URLs
for both the resource and individual aggregations. If publish_urls is set to
True, these endpoints will be added to the extra metadata fields of the
resource and aggregations.
"""
session = requests.Session()
session.headers.update(
{"Authorization": " ".join(("Token", str(api_token)))}
)
rest_url = str(services_url) + "/" + str(res_id) + "/"
try:
response = session.post(rest_url, timeout=timeout)
if publish_urls and response.status_code == status.HTTP_201_CREATED:
try:
resource = utils.get_resource_by_shortkey(res_id)
response_content = json.loads(response.content)
for key, value in response_content["resource"].iteritems():
resource.extra_metadata[key] = value
resource.save()
for url in response_content["content"]:
lf = resource.logical_files[[i.aggregation_name for i in
resource.logical_files].index(
url["layer_name"].encode("utf-8")
)]
lf.metadata.extra_metadata["Web Services URL"] = url["message"]
lf.metadata.save()
except Exception as e:
logger.error(e)
return e
return response
except (requests.exceptions.RequestException, ValueError) as e:
logger.error(e)
return e
| logger.info("added " + str(add_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id) | conditional_block |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celery.schedules import crontab
from celery.task import periodic_task
from django.conf import settings
from django.core.mail import send_mail
from rest_framework import status
from hs_core.hydroshare import utils
from hs_core.hydroshare.hs_bagit import create_bag_files
from hs_core.hydroshare.resource import get_activated_doi, get_resource_doi, \
get_crossref_url, deposit_res_metadata_with_crossref
from django_irods.storage import IrodsStorage
from theme.models import UserQuota, QuotaMessage, UserProfile, User
from django_irods.icommands import SessionException
from hs_core.models import BaseResource
from theme.utils import get_quota_message
# Pass 'django' into getLogger instead of __name__
# for celery tasks (as this seems to be the
# only way to successfully log in code executed
# by celery, despite our catch-all handler).
logger = logging.getLogger('django')
# Currently there are two different cleanups scheduled.
# One is 20 minutes after creation, the other is nightly.
# TODO Clean up zipfiles in remote federated storage as well.
@periodic_task(ignore_result=True, run_every=crontab(minute=30, hour=23))
def nightly_zips_cleanup():
# delete 2 days ago
date_folder = (date.today() - timedelta(2)).strftime('%Y-%m-%d')
zips_daily_date = "zips/{daily_date}".format(daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage()
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
federated_prefixes = BaseResource.objects.all().values_list('resource_federation_path')\
.distinct()
for p in federated_prefixes:
prefix = p[0] # strip tuple
if prefix != "":
zips_daily_date = "{prefix}/zips/{daily_date}"\
.format(prefix=prefix, daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage("federated")
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def sync_email_subscriptions():
sixty_days = datetime.today() - timedelta(days=60)
active_subscribed = UserProfile.objects.filter(email_opt_out=False,
user__last_login__gte=sixty_days,
user__is_active=True)
sync_mailchimp(active_subscribed, settings.MAILCHIMP_ACTIVE_SUBSCRIBERS)
subscribed = UserProfile.objects.filter(email_opt_out=False, user__is_active=True)
sync_mailchimp(subscribed, settings.MAILCHIMP_SUBSCRIBERS)
def sync_mailchimp(active_subscribed, list_id):
session = requests.Session()
url = "https://us3.api.mailchimp.com/3.0/lists/{list_id}/members"
# get total members
response = session.get(url.format(list_id=list_id), auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
total_items = json.loads(response.content)["total_items"]
# get list of all member ids
response = session.get((url + "?offset=0&count={total_items}").format(list_id=list_id,
total_items=total_items),
auth=requests.auth.HTTPBasicAuth('hs-celery',
settings.MAILCHIMP_PASSWORD))
# clear the email list
delete_count = 0
for member in json.loads(response.content)["members"]:
if member["status"] == "subscribed":
session_response = session.delete(
(url + "/{id}").format(list_id=list_id, id=member["id"]),
auth=requests.auth.HTTPBasicAuth('hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 204:
logger.info("Expected 204 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
delete_count += 1
# add active subscribed users to mailchimp
add_count = 0
for subscriber in active_subscribed:
json_data = {"email_address": subscriber.user.email, "status": "subscribed",
"merge_fields": {"FNAME": subscriber.user.first_name,
"LNAME": subscriber.user.last_name}}
session_response = session.post(
url.format(list_id=list_id), json=json_data, auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 200:
logger.info("Expected 200 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
add_count += 1
if delete_count == active_subscribed.count():
logger.info("successfully cleared mailchimp for list id " + list_id)
else:
logger.info(
"cleared " + str(delete_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
if active_subscribed.count() == add_count:
logger.info("successfully synced all subscriptions for list id " + list_id)
else:
logger.info("added " + str(add_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def manage_task_nightly():
# The nightly running task do DOI activation check
# Check DOI activation on failed and pending resources and send email.
msg_lst = []
# retrieve all published resources with failed metadata deposition with CrossRef if any and
# retry metadata deposition
failed_resources = BaseResource.objects.filter(raccess__published=True, doi__contains='failure')
for res in failed_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
response = deposit_res_metadata_with_crossref(res)
if response.status_code == status.HTTP_200_OK:
# retry of metadata deposition succeeds, change resource flag from failure
# to pending
res.doi = get_resource_doi(act_doi, 'pending')
res.save()
else:
# retry of metadata deposition failed again, notify admin
msg_lst.append("Metadata deposition with CrossRef for the published resource "
"DOI {res_doi} failed again after retry with first metadata "
"deposition requested since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
pending_resources = BaseResource.objects.filter(raccess__published=True,
doi__contains='pending')
for res in pending_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
main_url = get_crossref_url()
req_str = '{MAIN_URL}servlet/submissionDownload?usr={USERNAME}&pwd=' \
'{PASSWORD}&doi_batch_id={DOI_BATCH_ID}&type={TYPE}'
response = requests.get(req_str.format(MAIN_URL=main_url,
USERNAME=settings.CROSSREF_LOGIN_ID,
PASSWORD=settings.CROSSREF_LOGIN_PWD,
DOI_BATCH_ID=res.short_id,
TYPE='result'))
root = ElementTree.fromstring(response.content)
rec_cnt_elem = root.find('.//record_count')
failure_cnt_elem = root.find('.//failure_count')
success = False
if rec_cnt_elem is not None and failure_cnt_elem is not None:
rec_cnt = int(rec_cnt_elem.text)
failure_cnt = int(failure_cnt_elem.text)
if rec_cnt > 0 and failure_cnt == 0:
res.doi = act_doi
res.save()
success = True
if not success:
msg_lst.append("Published resource DOI {res_doi} is not yet activated with request "
"data deposited since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
if msg_lst:
email_msg = '\n'.join(msg_lst)
subject = 'Notification of pending DOI deposition/activation of published resources'
# send email for people monitoring and follow-up as needed
send_mail(subject, email_msg, settings.DEFAULT_FROM_EMAIL, [settings.DEFAULT_SUPPORT_EMAIL])
@periodic_task(ignore_result=True, run_every=crontab(minute=15, hour=0, day_of_week=1,
day_of_month='1-7'))
def send_over_quota_emails():
# check over quota cases and send quota warning emails as needed
|
@shared_task
def add_zip_file_contents_to_resource(pk, zip_file_path):
"""Add zip file to existing resource and remove tmp zip file."""
zfile = None
resource = None
try:
resource = utils.get_resource_by_shortkey(pk, or_404=False)
zfile = zipfile.ZipFile(zip_file_path)
num_files = len(zfile.infolist())
zcontents = utils.ZipContents(zfile)
files = zcontents.get_files()
resource.file_unpack_status = 'Running'
resource.save()
for i, f in enumerate(files):
logger.debug("Adding file {0} to resource {1}".format(f.name, pk))
utils.add_file_to_resource(resource, f)
resource.file_unpack_message = "Imported {0} of about {1} file(s) ...".format(
i, num_files)
resource.save()
# This might make the resource unsuitable for public consumption
resource.update_public_and_discoverable()
# TODO: this is a bit of a lie because a different user requested the bag overwrite
utils.resource_modified(resource, resource.creator, overwrite_bag=False)
# Call success callback
resource.file_unpack_message = None
resource.file_unpack_status = 'Done'
resource.save()
except BaseResource.DoesNotExist:
msg = "Unable to add zip file contents to non-existent resource {pk}."
msg = msg.format(pk=pk)
logger.error(msg)
except:
exc_info = "".join(traceback.format_exception(*sys.exc_info()))
if resource:
resource.file_unpack_status = 'Error'
resource.file_unpack_message = exc_info
resource.save()
if zfile:
zfile.close()
logger.error(exc_info)
finally:
# Delete upload file
os.unlink(zip_file_path)
@shared_task
def delete_zip(zip_path):
istorage = IrodsStorage()
if istorage.exists(zip_path):
istorage.delete(zip_path)
@shared_task
def create_temp_zip(resource_id, input_path, output_path, sf_aggregation, sf_zip=False):
""" Create temporary zip file from input_path and store in output_path
:param input_path: full irods path of input starting with federation path
:param output_path: full irods path of output starting with federation path
:param sf_aggregation: if True, include logical metadata files
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage() # invoke federated storage as necessary
if res.resource_type == "CompositeResource":
if '/data/contents/' in input_path:
short_path = input_path.split('/data/contents/')[1] # strip /data/contents/
res.create_aggregation_xml_documents(aggregation_name=short_path)
else: # all metadata included, e.g., /data/*
res.create_aggregation_xml_documents()
try:
if sf_zip:
# input path points to single file aggregation
# ensure that foo.zip contains aggregation metadata
# by copying these into a temp subdirectory foo/foo parallel to where foo.zip is stored
temp_folder_name, ext = os.path.splitext(output_path) # strip zip to get scratch dir
head, tail = os.path.split(temp_folder_name) # tail is unqualified folder name "foo"
out_with_folder = os.path.join(temp_folder_name, tail) # foo/foo is subdir to zip
istorage.copyFiles(input_path, out_with_folder)
if sf_aggregation:
try:
istorage.copyFiles(input_path + '_resmap.xml', out_with_folder + '_resmap.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_resmap.xml'))
try:
istorage.copyFiles(input_path + '_meta.xml', out_with_folder + '_meta.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_meta.xml'))
istorage.zipup(temp_folder_name, output_path)
istorage.delete(temp_folder_name) # delete working directory; this isn't the zipfile
else: # regular folder to zip
istorage.zipup(input_path, output_path)
except SessionException as ex:
logger.error(ex.stderr)
return False
return True
@shared_task
def create_bag_by_irods(resource_id):
"""Create a resource bag on iRODS side by running the bagit rule and ibun zip.
This function runs as a celery task, invoked asynchronously so that it does not
block the main web thread when it creates bags for very large files which will take some time.
:param
resource_id: the resource uuid that is used to look for the resource to create the bag for.
:return: True if bag creation operation succeeds;
False if there is an exception raised or resource does not exist.
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage()
metadata_dirty = istorage.getAVU(res.root_path, 'metadata_dirty')
# if metadata has been changed, then regenerate metadata xml files
if metadata_dirty is None or metadata_dirty.lower() == "true":
try:
create_bag_files(res)
except Exception as ex:
logger.error('Failed to create bag files. Error:{}'.format(ex.message))
return False
bag_full_name = 'bags/{res_id}.zip'.format(res_id=resource_id)
if res.resource_federation_path:
irods_bagit_input_path = os.path.join(res.resource_federation_path, resource_id)
is_exist = istorage.exists(irods_bagit_input_path)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{fed_path}/{res_id}/readme.txt'.format(
fed_path=res.resource_federation_path,
res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.HS_IRODS_USER_ZONE_DEF_RES)
bag_full_name = os.path.join(res.resource_federation_path, bag_full_name)
bagit_files = [
'{fed_path}/{res_id}/bagit.txt'.format(fed_path=res.resource_federation_path,
res_id=resource_id),
'{fed_path}/{res_id}/manifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/{res_id}/tagmanifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/bags/{res_id}.zip'.format(fed_path=res.resource_federation_path,
res_id=resource_id)
]
else:
is_exist = istorage.exists(resource_id)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{res_id}/readme.txt'.format(res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
irods_dest_prefix = "/" + settings.IRODS_ZONE + "/home/" + settings.IRODS_USERNAME
irods_bagit_input_path = os.path.join(irods_dest_prefix, resource_id)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.IRODS_DEFAULT_RESOURCE)
bagit_files = [
'{res_id}/bagit.txt'.format(res_id=resource_id),
'{res_id}/manifest-md5.txt'.format(res_id=resource_id),
'{res_id}/tagmanifest-md5.txt'.format(res_id=resource_id),
'bags/{res_id}.zip'.format(res_id=resource_id)
]
# only proceed when the resource is not deleted potentially by another request
# when being downloaded
if is_exist:
# if bagit readme.txt does not exist, add it.
if not is_bagit_readme_exist:
from_file_name = getattr(settings, 'HS_BAGIT_README_FILE_WITH_PATH',
'docs/bagit/readme.txt')
istorage.saveFile(from_file_name, bagit_readme_file, True)
# call iRODS bagit rule here
bagit_rule_file = getattr(settings, 'IRODS_BAGIT_RULE',
'hydroshare/irods/ruleGenerateBagIt_HS.r')
try:
# call iRODS run and ibun command to create and zip the bag, ignore SessionException
# for now as a workaround which could be raised from potential race conditions when
# multiple ibun commands try to create the same zip file or the very same resource
# gets deleted by another request when being downloaded
istorage.runBagitRule(bagit_rule_file, bagit_input_path, bagit_input_resource)
istorage.zipup(irods_bagit_input_path, bag_full_name)
istorage.setAVU(irods_bagit_input_path, 'bag_modified', "false")
return True
except SessionException as ex:
# if an exception occurs, delete incomplete files potentially being generated by
# iRODS bagit rule and zipping operations
for fname in bagit_files:
if istorage.exists(fname):
istorage.delete(fname)
logger.error(ex.stderr)
return False
else:
logger.error('Resource does not exist.')
return False
@shared_task
def update_quota_usage_task(username):
"""update quota usage. This function runs as a celery task, invoked asynchronously with 1
minute delay to give enough time for iRODS real time quota update micro-services to update
quota usage AVU for the user before this celery task to check this AVU to get the updated
quota usage for the user. Note iRODS micro-service quota update only happens on HydroShare
iRODS data zone and user zone independently, so the aggregation of usage in both zones need
to be accounted for in this function to update Django DB as an aggregated usage for hydroshare
internal zone.
:param
username: the name of the user that needs to update quota usage for.
:return: True if quota usage update succeeds;
False if there is an exception raised or quota cannot be updated. See log for details.
"""
hs_internal_zone = "hydroshare"
uq = UserQuota.objects.filter(user__username=username, zone=hs_internal_zone).first()
if uq is None:
# the quota row does not exist in Django
logger.error('quota row does not exist in Django for hydroshare zone for '
'user ' + username)
return False
attname = username + '-usage'
istorage = IrodsStorage()
# get quota size for user in iRODS data zone by retrieving AVU set on irods bagit path
# collection
try:
uqDataZoneSize = istorage.getAVU(settings.IRODS_BAGIT_PATH, attname)
if uqDataZoneSize is None:
# user may not have resources in data zone, so corresponding quota size AVU may not
# exist for this user
uqDataZoneSize = -1
else:
uqDataZoneSize = float(uqDataZoneSize)
except SessionException:
# user may not have resources in data zone, so corresponding quota size AVU may not exist
# for this user
uqDataZoneSize = -1
# get quota size for the user in iRODS user zone
try:
uz_bagit_path = os.path.join('/', settings.HS_USER_IRODS_ZONE, 'home',
settings.HS_IRODS_PROXY_USER_IN_USER_ZONE,
settings.IRODS_BAGIT_PATH)
uqUserZoneSize = istorage.getAVU(uz_bagit_path, attname)
if uqUserZoneSize is None:
# user may not have resources in user zone, so corresponding quota size AVU may not
# exist for this user
uqUserZoneSize = -1
else:
uqUserZoneSize = float(uqUserZoneSize)
except SessionException:
# user may not have resources in user zone, so corresponding quota size AVU may not exist
# for this user
uqUserZoneSize = -1
if uqDataZoneSize < 0 and uqUserZoneSize < 0:
logger.error('no quota size AVU in data zone and user zone for the user ' + username)
return False
elif uqUserZoneSize < 0:
used_val = uqDataZoneSize
elif uqDataZoneSize < 0:
used_val = uqUserZoneSize
else:
used_val = uqDataZoneSize + uqUserZoneSize
uq.update_used_value(used_val)
return True
@shared_task
def update_web_services(services_url, api_token, timeout, publish_urls, res_id):
"""Update web services hosted by GeoServer and HydroServer.
This function sends a resource id to the HydroShare web services manager
application, which will check the current status of the resource and register
or unregister services hosted by GeoServer and HydroServer.
The HydroShare web services manager will return a list of endpoint URLs
for both the resource and individual aggregations. If publish_urls is set to
True, these endpoints will be added to the extra metadata fields of the
resource and aggregations.
"""
session = requests.Session()
session.headers.update(
{"Authorization": " ".join(("Token", str(api_token)))}
)
rest_url = str(services_url) + "/" + str(res_id) + "/"
try:
response = session.post(rest_url, timeout=timeout)
if publish_urls and response.status_code == status.HTTP_201_CREATED:
try:
resource = utils.get_resource_by_shortkey(res_id)
response_content = json.loads(response.content)
for key, value in response_content["resource"].iteritems():
resource.extra_metadata[key] = value
resource.save()
for url in response_content["content"]:
lf = resource.logical_files[[i.aggregation_name for i in
resource.logical_files].index(
url["layer_name"].encode("utf-8")
)]
lf.metadata.extra_metadata["Web Services URL"] = url["message"]
lf.metadata.save()
except Exception as e:
logger.error(e)
return e
return response
except (requests.exceptions.RequestException, ValueError) as e:
logger.error(e)
return e
| hs_internal_zone = "hydroshare"
if not QuotaMessage.objects.exists():
QuotaMessage.objects.create()
qmsg = QuotaMessage.objects.first()
users = User.objects.filter(is_active=True).filter(is_superuser=False).all()
for u in users:
uq = UserQuota.objects.filter(user__username=u.username, zone=hs_internal_zone).first()
if uq:
used_percent = uq.used_percent
if used_percent >= qmsg.soft_limit_percent:
if used_percent >= 100 and used_percent < qmsg.hard_limit_percent:
if uq.remaining_grace_period < 0:
# triggers grace period counting
uq.remaining_grace_period = qmsg.grace_period
elif uq.remaining_grace_period > 0:
# reduce remaining_grace_period by one day
uq.remaining_grace_period -= 1
elif used_percent >= qmsg.hard_limit_percent:
# set grace period to 0 when user quota exceeds hard limit
uq.remaining_grace_period = 0
uq.save()
if u.first_name and u.last_name:
sal_name = '{} {}'.format(u.first_name, u.last_name)
elif u.first_name:
sal_name = u.first_name
elif u.last_name:
sal_name = u.last_name
else:
sal_name = u.username
msg_str = 'Dear ' + sal_name + ':\n\n'
ori_qm = get_quota_message(u)
# make embedded settings.DEFAULT_SUPPORT_EMAIL clickable with subject auto-filled
replace_substr = "<a href='mailto:{0}?subject=Request more quota'>{0}</a>".format(
settings.DEFAULT_SUPPORT_EMAIL)
new_qm = ori_qm.replace(settings.DEFAULT_SUPPORT_EMAIL, replace_substr)
msg_str += new_qm
msg_str += '\n\nHydroShare Support'
subject = 'Quota warning'
try:
# send email for people monitoring and follow-up as needed
send_mail(subject, '', settings.DEFAULT_FROM_EMAIL,
[u.email, settings.DEFAULT_SUPPORT_EMAIL],
html_message=msg_str)
except Exception as ex:
logger.debug("Failed to send quota warning email: " + ex.message)
else:
if uq.remaining_grace_period >= 0:
# turn grace period off now that the user is below quota soft limit
uq.remaining_grace_period = -1
uq.save()
else:
logger.debug('user ' + u.username + ' does not have UserQuota foreign key relation') | identifier_body |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celery.schedules import crontab
from celery.task import periodic_task
from django.conf import settings
from django.core.mail import send_mail
from rest_framework import status
from hs_core.hydroshare import utils
from hs_core.hydroshare.hs_bagit import create_bag_files
from hs_core.hydroshare.resource import get_activated_doi, get_resource_doi, \
get_crossref_url, deposit_res_metadata_with_crossref
from django_irods.storage import IrodsStorage
from theme.models import UserQuota, QuotaMessage, UserProfile, User
from django_irods.icommands import SessionException
from hs_core.models import BaseResource
from theme.utils import get_quota_message
# Pass 'django' into getLogger instead of __name__
# for celery tasks (as this seems to be the
# only way to successfully log in code executed
# by celery, despite our catch-all handler).
logger = logging.getLogger('django')
# Currently there are two different cleanups scheduled.
# One is 20 minutes after creation, the other is nightly.
# TODO Clean up zipfiles in remote federated storage as well.
@periodic_task(ignore_result=True, run_every=crontab(minute=30, hour=23))
def nightly_zips_cleanup():
# delete 2 days ago
date_folder = (date.today() - timedelta(2)).strftime('%Y-%m-%d')
zips_daily_date = "zips/{daily_date}".format(daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage()
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
federated_prefixes = BaseResource.objects.all().values_list('resource_federation_path')\
.distinct()
for p in federated_prefixes:
prefix = p[0] # strip tuple
if prefix != "":
zips_daily_date = "{prefix}/zips/{daily_date}"\
.format(prefix=prefix, daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage("federated")
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def sync_email_subscriptions():
sixty_days = datetime.today() - timedelta(days=60)
active_subscribed = UserProfile.objects.filter(email_opt_out=False,
user__last_login__gte=sixty_days,
user__is_active=True)
sync_mailchimp(active_subscribed, settings.MAILCHIMP_ACTIVE_SUBSCRIBERS)
subscribed = UserProfile.objects.filter(email_opt_out=False, user__is_active=True)
sync_mailchimp(subscribed, settings.MAILCHIMP_SUBSCRIBERS)
def sync_mailchimp(active_subscribed, list_id):
session = requests.Session()
url = "https://us3.api.mailchimp.com/3.0/lists/{list_id}/members"
# get total members
response = session.get(url.format(list_id=list_id), auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
total_items = json.loads(response.content)["total_items"]
# get list of all member ids
response = session.get((url + "?offset=0&count={total_items}").format(list_id=list_id,
total_items=total_items),
auth=requests.auth.HTTPBasicAuth('hs-celery',
settings.MAILCHIMP_PASSWORD))
# clear the email list
delete_count = 0
for member in json.loads(response.content)["members"]:
if member["status"] == "subscribed":
session_response = session.delete(
(url + "/{id}").format(list_id=list_id, id=member["id"]),
auth=requests.auth.HTTPBasicAuth('hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 204:
logger.info("Expected 204 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
delete_count += 1
# add active subscribed users to mailchimp
add_count = 0
for subscriber in active_subscribed:
json_data = {"email_address": subscriber.user.email, "status": "subscribed",
"merge_fields": {"FNAME": subscriber.user.first_name,
"LNAME": subscriber.user.last_name}}
session_response = session.post(
url.format(list_id=list_id), json=json_data, auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 200:
logger.info("Expected 200 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
add_count += 1
if delete_count == active_subscribed.count():
logger.info("successfully cleared mailchimp for list id " + list_id)
else:
logger.info(
"cleared " + str(delete_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
if active_subscribed.count() == add_count:
logger.info("successfully synced all subscriptions for list id " + list_id)
else:
logger.info("added " + str(add_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def manage_task_nightly():
# The nightly running task do DOI activation check
# Check DOI activation on failed and pending resources and send email.
msg_lst = []
# retrieve all published resources with failed metadata deposition with CrossRef if any and
# retry metadata deposition
failed_resources = BaseResource.objects.filter(raccess__published=True, doi__contains='failure')
for res in failed_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
response = deposit_res_metadata_with_crossref(res)
if response.status_code == status.HTTP_200_OK:
# retry of metadata deposition succeeds, change resource flag from failure
# to pending
res.doi = get_resource_doi(act_doi, 'pending')
res.save()
else:
# retry of metadata deposition failed again, notify admin
msg_lst.append("Metadata deposition with CrossRef for the published resource "
"DOI {res_doi} failed again after retry with first metadata "
"deposition requested since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
pending_resources = BaseResource.objects.filter(raccess__published=True,
doi__contains='pending')
for res in pending_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
main_url = get_crossref_url()
req_str = '{MAIN_URL}servlet/submissionDownload?usr={USERNAME}&pwd=' \
'{PASSWORD}&doi_batch_id={DOI_BATCH_ID}&type={TYPE}'
response = requests.get(req_str.format(MAIN_URL=main_url,
USERNAME=settings.CROSSREF_LOGIN_ID,
PASSWORD=settings.CROSSREF_LOGIN_PWD,
DOI_BATCH_ID=res.short_id,
TYPE='result'))
root = ElementTree.fromstring(response.content)
rec_cnt_elem = root.find('.//record_count')
failure_cnt_elem = root.find('.//failure_count')
success = False
if rec_cnt_elem is not None and failure_cnt_elem is not None:
rec_cnt = int(rec_cnt_elem.text)
failure_cnt = int(failure_cnt_elem.text)
if rec_cnt > 0 and failure_cnt == 0:
res.doi = act_doi
res.save()
success = True
if not success:
msg_lst.append("Published resource DOI {res_doi} is not yet activated with request "
"data deposited since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
if msg_lst:
email_msg = '\n'.join(msg_lst)
subject = 'Notification of pending DOI deposition/activation of published resources'
# send email for people monitoring and follow-up as needed
send_mail(subject, email_msg, settings.DEFAULT_FROM_EMAIL, [settings.DEFAULT_SUPPORT_EMAIL])
@periodic_task(ignore_result=True, run_every=crontab(minute=15, hour=0, day_of_week=1,
day_of_month='1-7'))
def send_over_quota_emails():
# check over quota cases and send quota warning emails as needed
hs_internal_zone = "hydroshare"
if not QuotaMessage.objects.exists():
QuotaMessage.objects.create()
qmsg = QuotaMessage.objects.first()
users = User.objects.filter(is_active=True).filter(is_superuser=False).all()
for u in users:
uq = UserQuota.objects.filter(user__username=u.username, zone=hs_internal_zone).first()
if uq:
used_percent = uq.used_percent
if used_percent >= qmsg.soft_limit_percent:
if used_percent >= 100 and used_percent < qmsg.hard_limit_percent:
if uq.remaining_grace_period < 0:
# triggers grace period counting
uq.remaining_grace_period = qmsg.grace_period
elif uq.remaining_grace_period > 0:
# reduce remaining_grace_period by one day
uq.remaining_grace_period -= 1
elif used_percent >= qmsg.hard_limit_percent:
# set grace period to 0 when user quota exceeds hard limit
uq.remaining_grace_period = 0
uq.save()
if u.first_name and u.last_name:
sal_name = '{} {}'.format(u.first_name, u.last_name)
elif u.first_name:
sal_name = u.first_name
elif u.last_name:
sal_name = u.last_name
else:
sal_name = u.username
msg_str = 'Dear ' + sal_name + ':\n\n'
ori_qm = get_quota_message(u)
# make embedded settings.DEFAULT_SUPPORT_EMAIL clickable with subject auto-filled
replace_substr = "<a href='mailto:{0}?subject=Request more quota'>{0}</a>".format(
settings.DEFAULT_SUPPORT_EMAIL)
new_qm = ori_qm.replace(settings.DEFAULT_SUPPORT_EMAIL, replace_substr)
msg_str += new_qm
msg_str += '\n\nHydroShare Support'
subject = 'Quota warning'
try:
# send email for people monitoring and follow-up as needed
send_mail(subject, '', settings.DEFAULT_FROM_EMAIL,
[u.email, settings.DEFAULT_SUPPORT_EMAIL],
html_message=msg_str)
except Exception as ex:
logger.debug("Failed to send quota warning email: " + ex.message)
else:
if uq.remaining_grace_period >= 0:
# turn grace period off now that the user is below quota soft limit
uq.remaining_grace_period = -1
uq.save()
else:
logger.debug('user ' + u.username + ' does not have UserQuota foreign key relation')
@shared_task
def | (pk, zip_file_path):
"""Add zip file to existing resource and remove tmp zip file."""
zfile = None
resource = None
try:
resource = utils.get_resource_by_shortkey(pk, or_404=False)
zfile = zipfile.ZipFile(zip_file_path)
num_files = len(zfile.infolist())
zcontents = utils.ZipContents(zfile)
files = zcontents.get_files()
resource.file_unpack_status = 'Running'
resource.save()
for i, f in enumerate(files):
logger.debug("Adding file {0} to resource {1}".format(f.name, pk))
utils.add_file_to_resource(resource, f)
resource.file_unpack_message = "Imported {0} of about {1} file(s) ...".format(
i, num_files)
resource.save()
# This might make the resource unsuitable for public consumption
resource.update_public_and_discoverable()
# TODO: this is a bit of a lie because a different user requested the bag overwrite
utils.resource_modified(resource, resource.creator, overwrite_bag=False)
# Call success callback
resource.file_unpack_message = None
resource.file_unpack_status = 'Done'
resource.save()
except BaseResource.DoesNotExist:
msg = "Unable to add zip file contents to non-existent resource {pk}."
msg = msg.format(pk=pk)
logger.error(msg)
except:
exc_info = "".join(traceback.format_exception(*sys.exc_info()))
if resource:
resource.file_unpack_status = 'Error'
resource.file_unpack_message = exc_info
resource.save()
if zfile:
zfile.close()
logger.error(exc_info)
finally:
# Delete upload file
os.unlink(zip_file_path)
@shared_task
def delete_zip(zip_path):
istorage = IrodsStorage()
if istorage.exists(zip_path):
istorage.delete(zip_path)
@shared_task
def create_temp_zip(resource_id, input_path, output_path, sf_aggregation, sf_zip=False):
""" Create temporary zip file from input_path and store in output_path
:param input_path: full irods path of input starting with federation path
:param output_path: full irods path of output starting with federation path
:param sf_aggregation: if True, include logical metadata files
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage() # invoke federated storage as necessary
if res.resource_type == "CompositeResource":
if '/data/contents/' in input_path:
short_path = input_path.split('/data/contents/')[1] # strip /data/contents/
res.create_aggregation_xml_documents(aggregation_name=short_path)
else: # all metadata included, e.g., /data/*
res.create_aggregation_xml_documents()
try:
if sf_zip:
# input path points to single file aggregation
# ensure that foo.zip contains aggregation metadata
# by copying these into a temp subdirectory foo/foo parallel to where foo.zip is stored
temp_folder_name, ext = os.path.splitext(output_path) # strip zip to get scratch dir
head, tail = os.path.split(temp_folder_name) # tail is unqualified folder name "foo"
out_with_folder = os.path.join(temp_folder_name, tail) # foo/foo is subdir to zip
istorage.copyFiles(input_path, out_with_folder)
if sf_aggregation:
try:
istorage.copyFiles(input_path + '_resmap.xml', out_with_folder + '_resmap.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_resmap.xml'))
try:
istorage.copyFiles(input_path + '_meta.xml', out_with_folder + '_meta.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_meta.xml'))
istorage.zipup(temp_folder_name, output_path)
istorage.delete(temp_folder_name) # delete working directory; this isn't the zipfile
else: # regular folder to zip
istorage.zipup(input_path, output_path)
except SessionException as ex:
logger.error(ex.stderr)
return False
return True
@shared_task
def create_bag_by_irods(resource_id):
"""Create a resource bag on iRODS side by running the bagit rule and ibun zip.
This function runs as a celery task, invoked asynchronously so that it does not
block the main web thread when it creates bags for very large files which will take some time.
:param
resource_id: the resource uuid that is used to look for the resource to create the bag for.
:return: True if bag creation operation succeeds;
False if there is an exception raised or resource does not exist.
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage()
metadata_dirty = istorage.getAVU(res.root_path, 'metadata_dirty')
# if metadata has been changed, then regenerate metadata xml files
if metadata_dirty is None or metadata_dirty.lower() == "true":
try:
create_bag_files(res)
except Exception as ex:
logger.error('Failed to create bag files. Error:{}'.format(ex.message))
return False
bag_full_name = 'bags/{res_id}.zip'.format(res_id=resource_id)
if res.resource_federation_path:
irods_bagit_input_path = os.path.join(res.resource_federation_path, resource_id)
is_exist = istorage.exists(irods_bagit_input_path)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{fed_path}/{res_id}/readme.txt'.format(
fed_path=res.resource_federation_path,
res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.HS_IRODS_USER_ZONE_DEF_RES)
bag_full_name = os.path.join(res.resource_federation_path, bag_full_name)
bagit_files = [
'{fed_path}/{res_id}/bagit.txt'.format(fed_path=res.resource_federation_path,
res_id=resource_id),
'{fed_path}/{res_id}/manifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/{res_id}/tagmanifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/bags/{res_id}.zip'.format(fed_path=res.resource_federation_path,
res_id=resource_id)
]
else:
is_exist = istorage.exists(resource_id)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{res_id}/readme.txt'.format(res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
irods_dest_prefix = "/" + settings.IRODS_ZONE + "/home/" + settings.IRODS_USERNAME
irods_bagit_input_path = os.path.join(irods_dest_prefix, resource_id)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.IRODS_DEFAULT_RESOURCE)
bagit_files = [
'{res_id}/bagit.txt'.format(res_id=resource_id),
'{res_id}/manifest-md5.txt'.format(res_id=resource_id),
'{res_id}/tagmanifest-md5.txt'.format(res_id=resource_id),
'bags/{res_id}.zip'.format(res_id=resource_id)
]
# only proceed when the resource is not deleted potentially by another request
# when being downloaded
if is_exist:
# if bagit readme.txt does not exist, add it.
if not is_bagit_readme_exist:
from_file_name = getattr(settings, 'HS_BAGIT_README_FILE_WITH_PATH',
'docs/bagit/readme.txt')
istorage.saveFile(from_file_name, bagit_readme_file, True)
# call iRODS bagit rule here
bagit_rule_file = getattr(settings, 'IRODS_BAGIT_RULE',
'hydroshare/irods/ruleGenerateBagIt_HS.r')
try:
# call iRODS run and ibun command to create and zip the bag, ignore SessionException
# for now as a workaround which could be raised from potential race conditions when
# multiple ibun commands try to create the same zip file or the very same resource
# gets deleted by another request when being downloaded
istorage.runBagitRule(bagit_rule_file, bagit_input_path, bagit_input_resource)
istorage.zipup(irods_bagit_input_path, bag_full_name)
istorage.setAVU(irods_bagit_input_path, 'bag_modified', "false")
return True
except SessionException as ex:
# if an exception occurs, delete incomplete files potentially being generated by
# iRODS bagit rule and zipping operations
for fname in bagit_files:
if istorage.exists(fname):
istorage.delete(fname)
logger.error(ex.stderr)
return False
else:
logger.error('Resource does not exist.')
return False
@shared_task
def update_quota_usage_task(username):
"""update quota usage. This function runs as a celery task, invoked asynchronously with 1
minute delay to give enough time for iRODS real time quota update micro-services to update
quota usage AVU for the user before this celery task to check this AVU to get the updated
quota usage for the user. Note iRODS micro-service quota update only happens on HydroShare
iRODS data zone and user zone independently, so the aggregation of usage in both zones need
to be accounted for in this function to update Django DB as an aggregated usage for hydroshare
internal zone.
:param
username: the name of the user that needs to update quota usage for.
:return: True if quota usage update succeeds;
False if there is an exception raised or quota cannot be updated. See log for details.
"""
hs_internal_zone = "hydroshare"
uq = UserQuota.objects.filter(user__username=username, zone=hs_internal_zone).first()
if uq is None:
# the quota row does not exist in Django
logger.error('quota row does not exist in Django for hydroshare zone for '
'user ' + username)
return False
attname = username + '-usage'
istorage = IrodsStorage()
# get quota size for user in iRODS data zone by retrieving AVU set on irods bagit path
# collection
try:
uqDataZoneSize = istorage.getAVU(settings.IRODS_BAGIT_PATH, attname)
if uqDataZoneSize is None:
# user may not have resources in data zone, so corresponding quota size AVU may not
# exist for this user
uqDataZoneSize = -1
else:
uqDataZoneSize = float(uqDataZoneSize)
except SessionException:
# user may not have resources in data zone, so corresponding quota size AVU may not exist
# for this user
uqDataZoneSize = -1
# get quota size for the user in iRODS user zone
try:
uz_bagit_path = os.path.join('/', settings.HS_USER_IRODS_ZONE, 'home',
settings.HS_IRODS_PROXY_USER_IN_USER_ZONE,
settings.IRODS_BAGIT_PATH)
uqUserZoneSize = istorage.getAVU(uz_bagit_path, attname)
if uqUserZoneSize is None:
# user may not have resources in user zone, so corresponding quota size AVU may not
# exist for this user
uqUserZoneSize = -1
else:
uqUserZoneSize = float(uqUserZoneSize)
except SessionException:
# user may not have resources in user zone, so corresponding quota size AVU may not exist
# for this user
uqUserZoneSize = -1
if uqDataZoneSize < 0 and uqUserZoneSize < 0:
logger.error('no quota size AVU in data zone and user zone for the user ' + username)
return False
elif uqUserZoneSize < 0:
used_val = uqDataZoneSize
elif uqDataZoneSize < 0:
used_val = uqUserZoneSize
else:
used_val = uqDataZoneSize + uqUserZoneSize
uq.update_used_value(used_val)
return True
@shared_task
def update_web_services(services_url, api_token, timeout, publish_urls, res_id):
"""Update web services hosted by GeoServer and HydroServer.
This function sends a resource id to the HydroShare web services manager
application, which will check the current status of the resource and register
or unregister services hosted by GeoServer and HydroServer.
The HydroShare web services manager will return a list of endpoint URLs
for both the resource and individual aggregations. If publish_urls is set to
True, these endpoints will be added to the extra metadata fields of the
resource and aggregations.
"""
session = requests.Session()
session.headers.update(
{"Authorization": " ".join(("Token", str(api_token)))}
)
rest_url = str(services_url) + "/" + str(res_id) + "/"
try:
response = session.post(rest_url, timeout=timeout)
if publish_urls and response.status_code == status.HTTP_201_CREATED:
try:
resource = utils.get_resource_by_shortkey(res_id)
response_content = json.loads(response.content)
for key, value in response_content["resource"].iteritems():
resource.extra_metadata[key] = value
resource.save()
for url in response_content["content"]:
lf = resource.logical_files[[i.aggregation_name for i in
resource.logical_files].index(
url["layer_name"].encode("utf-8")
)]
lf.metadata.extra_metadata["Web Services URL"] = url["message"]
lf.metadata.save()
except Exception as e:
logger.error(e)
return e
return response
except (requests.exceptions.RequestException, ValueError) as e:
logger.error(e)
return e
| add_zip_file_contents_to_resource | identifier_name |
tasks.py | """Define celery tasks for hs_core app."""
from __future__ import absolute_import
import os
import sys
import traceback
import zipfile
import logging
import json
from datetime import datetime, timedelta, date
from xml.etree import ElementTree
import requests
from celery import shared_task
from celery.schedules import crontab
from celery.task import periodic_task
from django.conf import settings
from django.core.mail import send_mail
from rest_framework import status
from hs_core.hydroshare import utils
from hs_core.hydroshare.hs_bagit import create_bag_files
from hs_core.hydroshare.resource import get_activated_doi, get_resource_doi, \
get_crossref_url, deposit_res_metadata_with_crossref
from django_irods.storage import IrodsStorage
from theme.models import UserQuota, QuotaMessage, UserProfile, User
from django_irods.icommands import SessionException
from hs_core.models import BaseResource
from theme.utils import get_quota_message
# Pass 'django' into getLogger instead of __name__
# for celery tasks (as this seems to be the
# only way to successfully log in code executed
# by celery, despite our catch-all handler).
logger = logging.getLogger('django')
# Currently there are two different cleanups scheduled.
# One is 20 minutes after creation, the other is nightly.
# TODO Clean up zipfiles in remote federated storage as well.
@periodic_task(ignore_result=True, run_every=crontab(minute=30, hour=23))
def nightly_zips_cleanup():
# delete 2 days ago
date_folder = (date.today() - timedelta(2)).strftime('%Y-%m-%d')
zips_daily_date = "zips/{daily_date}".format(daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage()
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
federated_prefixes = BaseResource.objects.all().values_list('resource_federation_path')\
.distinct()
for p in federated_prefixes:
prefix = p[0] # strip tuple
if prefix != "":
zips_daily_date = "{prefix}/zips/{daily_date}"\
.format(prefix=prefix, daily_date=date_folder)
if __debug__:
logger.debug("cleaning up {}".format(zips_daily_date))
istorage = IrodsStorage("federated")
if istorage.exists(zips_daily_date):
istorage.delete(zips_daily_date)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def sync_email_subscriptions():
sixty_days = datetime.today() - timedelta(days=60)
active_subscribed = UserProfile.objects.filter(email_opt_out=False,
user__last_login__gte=sixty_days,
user__is_active=True)
sync_mailchimp(active_subscribed, settings.MAILCHIMP_ACTIVE_SUBSCRIBERS)
subscribed = UserProfile.objects.filter(email_opt_out=False, user__is_active=True)
sync_mailchimp(subscribed, settings.MAILCHIMP_SUBSCRIBERS)
def sync_mailchimp(active_subscribed, list_id):
session = requests.Session()
url = "https://us3.api.mailchimp.com/3.0/lists/{list_id}/members"
# get total members
response = session.get(url.format(list_id=list_id), auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
total_items = json.loads(response.content)["total_items"]
# get list of all member ids
response = session.get((url + "?offset=0&count={total_items}").format(list_id=list_id,
total_items=total_items),
auth=requests.auth.HTTPBasicAuth('hs-celery',
settings.MAILCHIMP_PASSWORD))
# clear the email list
delete_count = 0
for member in json.loads(response.content)["members"]:
if member["status"] == "subscribed":
session_response = session.delete(
(url + "/{id}").format(list_id=list_id, id=member["id"]),
auth=requests.auth.HTTPBasicAuth('hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 204:
logger.info("Expected 204 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
delete_count += 1
# add active subscribed users to mailchimp
add_count = 0
for subscriber in active_subscribed:
json_data = {"email_address": subscriber.user.email, "status": "subscribed",
"merge_fields": {"FNAME": subscriber.user.first_name,
"LNAME": subscriber.user.last_name}}
session_response = session.post(
url.format(list_id=list_id), json=json_data, auth=requests.auth.HTTPBasicAuth(
'hs-celery', settings.MAILCHIMP_PASSWORD))
if session_response.status_code != 200:
logger.info("Expected 200 status code, got " + str(session_response.status_code))
logger.debug(session_response.content)
else:
add_count += 1
if delete_count == active_subscribed.count():
logger.info("successfully cleared mailchimp for list id " + list_id)
else:
logger.info(
"cleared " + str(delete_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
if active_subscribed.count() == add_count:
logger.info("successfully synced all subscriptions for list id " + list_id)
else:
logger.info("added " + str(add_count) + " out of " + str(
active_subscribed.count()) + " for list id " + list_id)
@periodic_task(ignore_result=True, run_every=crontab(minute=0, hour=0))
def manage_task_nightly():
# The nightly running task do DOI activation check
# Check DOI activation on failed and pending resources and send email.
msg_lst = []
# retrieve all published resources with failed metadata deposition with CrossRef if any and
# retry metadata deposition
failed_resources = BaseResource.objects.filter(raccess__published=True, doi__contains='failure')
for res in failed_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
response = deposit_res_metadata_with_crossref(res)
if response.status_code == status.HTTP_200_OK:
# retry of metadata deposition succeeds, change resource flag from failure
# to pending
res.doi = get_resource_doi(act_doi, 'pending')
res.save()
else:
# retry of metadata deposition failed again, notify admin
msg_lst.append("Metadata deposition with CrossRef for the published resource "
"DOI {res_doi} failed again after retry with first metadata "
"deposition requested since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
pending_resources = BaseResource.objects.filter(raccess__published=True,
doi__contains='pending')
for res in pending_resources:
if res.metadata.dates.all().filter(type='published'):
pub_date = res.metadata.dates.all().filter(type='published')[0]
pub_date = pub_date.start_date.strftime('%m/%d/%Y')
act_doi = get_activated_doi(res.doi)
main_url = get_crossref_url()
req_str = '{MAIN_URL}servlet/submissionDownload?usr={USERNAME}&pwd=' \
'{PASSWORD}&doi_batch_id={DOI_BATCH_ID}&type={TYPE}'
response = requests.get(req_str.format(MAIN_URL=main_url,
| DOI_BATCH_ID=res.short_id,
TYPE='result'))
root = ElementTree.fromstring(response.content)
rec_cnt_elem = root.find('.//record_count')
failure_cnt_elem = root.find('.//failure_count')
success = False
if rec_cnt_elem is not None and failure_cnt_elem is not None:
rec_cnt = int(rec_cnt_elem.text)
failure_cnt = int(failure_cnt_elem.text)
if rec_cnt > 0 and failure_cnt == 0:
res.doi = act_doi
res.save()
success = True
if not success:
msg_lst.append("Published resource DOI {res_doi} is not yet activated with request "
"data deposited since {pub_date}.".format(res_doi=act_doi,
pub_date=pub_date))
logger.debug(response.content)
else:
msg_lst.append("{res_id} does not have published date in its metadata.".format(
res_id=res.short_id))
if msg_lst:
email_msg = '\n'.join(msg_lst)
subject = 'Notification of pending DOI deposition/activation of published resources'
# send email for people monitoring and follow-up as needed
send_mail(subject, email_msg, settings.DEFAULT_FROM_EMAIL, [settings.DEFAULT_SUPPORT_EMAIL])
@periodic_task(ignore_result=True, run_every=crontab(minute=15, hour=0, day_of_week=1,
day_of_month='1-7'))
def send_over_quota_emails():
# check over quota cases and send quota warning emails as needed
hs_internal_zone = "hydroshare"
if not QuotaMessage.objects.exists():
QuotaMessage.objects.create()
qmsg = QuotaMessage.objects.first()
users = User.objects.filter(is_active=True).filter(is_superuser=False).all()
for u in users:
uq = UserQuota.objects.filter(user__username=u.username, zone=hs_internal_zone).first()
if uq:
used_percent = uq.used_percent
if used_percent >= qmsg.soft_limit_percent:
if used_percent >= 100 and used_percent < qmsg.hard_limit_percent:
if uq.remaining_grace_period < 0:
# triggers grace period counting
uq.remaining_grace_period = qmsg.grace_period
elif uq.remaining_grace_period > 0:
# reduce remaining_grace_period by one day
uq.remaining_grace_period -= 1
elif used_percent >= qmsg.hard_limit_percent:
# set grace period to 0 when user quota exceeds hard limit
uq.remaining_grace_period = 0
uq.save()
if u.first_name and u.last_name:
sal_name = '{} {}'.format(u.first_name, u.last_name)
elif u.first_name:
sal_name = u.first_name
elif u.last_name:
sal_name = u.last_name
else:
sal_name = u.username
msg_str = 'Dear ' + sal_name + ':\n\n'
ori_qm = get_quota_message(u)
# make embedded settings.DEFAULT_SUPPORT_EMAIL clickable with subject auto-filled
replace_substr = "<a href='mailto:{0}?subject=Request more quota'>{0}</a>".format(
settings.DEFAULT_SUPPORT_EMAIL)
new_qm = ori_qm.replace(settings.DEFAULT_SUPPORT_EMAIL, replace_substr)
msg_str += new_qm
msg_str += '\n\nHydroShare Support'
subject = 'Quota warning'
try:
# send email for people monitoring and follow-up as needed
send_mail(subject, '', settings.DEFAULT_FROM_EMAIL,
[u.email, settings.DEFAULT_SUPPORT_EMAIL],
html_message=msg_str)
except Exception as ex:
logger.debug("Failed to send quota warning email: " + ex.message)
else:
if uq.remaining_grace_period >= 0:
# turn grace period off now that the user is below quota soft limit
uq.remaining_grace_period = -1
uq.save()
else:
logger.debug('user ' + u.username + ' does not have UserQuota foreign key relation')
@shared_task
def add_zip_file_contents_to_resource(pk, zip_file_path):
"""Add zip file to existing resource and remove tmp zip file."""
zfile = None
resource = None
try:
resource = utils.get_resource_by_shortkey(pk, or_404=False)
zfile = zipfile.ZipFile(zip_file_path)
num_files = len(zfile.infolist())
zcontents = utils.ZipContents(zfile)
files = zcontents.get_files()
resource.file_unpack_status = 'Running'
resource.save()
for i, f in enumerate(files):
logger.debug("Adding file {0} to resource {1}".format(f.name, pk))
utils.add_file_to_resource(resource, f)
resource.file_unpack_message = "Imported {0} of about {1} file(s) ...".format(
i, num_files)
resource.save()
# This might make the resource unsuitable for public consumption
resource.update_public_and_discoverable()
# TODO: this is a bit of a lie because a different user requested the bag overwrite
utils.resource_modified(resource, resource.creator, overwrite_bag=False)
# Call success callback
resource.file_unpack_message = None
resource.file_unpack_status = 'Done'
resource.save()
except BaseResource.DoesNotExist:
msg = "Unable to add zip file contents to non-existent resource {pk}."
msg = msg.format(pk=pk)
logger.error(msg)
except:
exc_info = "".join(traceback.format_exception(*sys.exc_info()))
if resource:
resource.file_unpack_status = 'Error'
resource.file_unpack_message = exc_info
resource.save()
if zfile:
zfile.close()
logger.error(exc_info)
finally:
# Delete upload file
os.unlink(zip_file_path)
@shared_task
def delete_zip(zip_path):
istorage = IrodsStorage()
if istorage.exists(zip_path):
istorage.delete(zip_path)
@shared_task
def create_temp_zip(resource_id, input_path, output_path, sf_aggregation, sf_zip=False):
""" Create temporary zip file from input_path and store in output_path
:param input_path: full irods path of input starting with federation path
:param output_path: full irods path of output starting with federation path
:param sf_aggregation: if True, include logical metadata files
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage() # invoke federated storage as necessary
if res.resource_type == "CompositeResource":
if '/data/contents/' in input_path:
short_path = input_path.split('/data/contents/')[1] # strip /data/contents/
res.create_aggregation_xml_documents(aggregation_name=short_path)
else: # all metadata included, e.g., /data/*
res.create_aggregation_xml_documents()
try:
if sf_zip:
# input path points to single file aggregation
# ensure that foo.zip contains aggregation metadata
# by copying these into a temp subdirectory foo/foo parallel to where foo.zip is stored
temp_folder_name, ext = os.path.splitext(output_path) # strip zip to get scratch dir
head, tail = os.path.split(temp_folder_name) # tail is unqualified folder name "foo"
out_with_folder = os.path.join(temp_folder_name, tail) # foo/foo is subdir to zip
istorage.copyFiles(input_path, out_with_folder)
if sf_aggregation:
try:
istorage.copyFiles(input_path + '_resmap.xml', out_with_folder + '_resmap.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_resmap.xml'))
try:
istorage.copyFiles(input_path + '_meta.xml', out_with_folder + '_meta.xml')
except SessionException:
logger.error("cannot copy {}".format(input_path + '_meta.xml'))
istorage.zipup(temp_folder_name, output_path)
istorage.delete(temp_folder_name) # delete working directory; this isn't the zipfile
else: # regular folder to zip
istorage.zipup(input_path, output_path)
except SessionException as ex:
logger.error(ex.stderr)
return False
return True
@shared_task
def create_bag_by_irods(resource_id):
"""Create a resource bag on iRODS side by running the bagit rule and ibun zip.
This function runs as a celery task, invoked asynchronously so that it does not
block the main web thread when it creates bags for very large files which will take some time.
:param
resource_id: the resource uuid that is used to look for the resource to create the bag for.
:return: True if bag creation operation succeeds;
False if there is an exception raised or resource does not exist.
"""
from hs_core.hydroshare.utils import get_resource_by_shortkey
res = get_resource_by_shortkey(resource_id)
istorage = res.get_irods_storage()
metadata_dirty = istorage.getAVU(res.root_path, 'metadata_dirty')
# if metadata has been changed, then regenerate metadata xml files
if metadata_dirty is None or metadata_dirty.lower() == "true":
try:
create_bag_files(res)
except Exception as ex:
logger.error('Failed to create bag files. Error:{}'.format(ex.message))
return False
bag_full_name = 'bags/{res_id}.zip'.format(res_id=resource_id)
if res.resource_federation_path:
irods_bagit_input_path = os.path.join(res.resource_federation_path, resource_id)
is_exist = istorage.exists(irods_bagit_input_path)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{fed_path}/{res_id}/readme.txt'.format(
fed_path=res.resource_federation_path,
res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.HS_IRODS_USER_ZONE_DEF_RES)
bag_full_name = os.path.join(res.resource_federation_path, bag_full_name)
bagit_files = [
'{fed_path}/{res_id}/bagit.txt'.format(fed_path=res.resource_federation_path,
res_id=resource_id),
'{fed_path}/{res_id}/manifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/{res_id}/tagmanifest-md5.txt'.format(
fed_path=res.resource_federation_path, res_id=resource_id),
'{fed_path}/bags/{res_id}.zip'.format(fed_path=res.resource_federation_path,
res_id=resource_id)
]
else:
is_exist = istorage.exists(resource_id)
# check to see if bagit readme.txt file exists or not
bagit_readme_file = '{res_id}/readme.txt'.format(res_id=resource_id)
is_bagit_readme_exist = istorage.exists(bagit_readme_file)
irods_dest_prefix = "/" + settings.IRODS_ZONE + "/home/" + settings.IRODS_USERNAME
irods_bagit_input_path = os.path.join(irods_dest_prefix, resource_id)
bagit_input_path = "*BAGITDATA='{path}'".format(path=irods_bagit_input_path)
bagit_input_resource = "*DESTRESC='{def_res}'".format(
def_res=settings.IRODS_DEFAULT_RESOURCE)
bagit_files = [
'{res_id}/bagit.txt'.format(res_id=resource_id),
'{res_id}/manifest-md5.txt'.format(res_id=resource_id),
'{res_id}/tagmanifest-md5.txt'.format(res_id=resource_id),
'bags/{res_id}.zip'.format(res_id=resource_id)
]
# only proceed when the resource is not deleted potentially by another request
# when being downloaded
if is_exist:
# if bagit readme.txt does not exist, add it.
if not is_bagit_readme_exist:
from_file_name = getattr(settings, 'HS_BAGIT_README_FILE_WITH_PATH',
'docs/bagit/readme.txt')
istorage.saveFile(from_file_name, bagit_readme_file, True)
# call iRODS bagit rule here
bagit_rule_file = getattr(settings, 'IRODS_BAGIT_RULE',
'hydroshare/irods/ruleGenerateBagIt_HS.r')
try:
# call iRODS run and ibun command to create and zip the bag, ignore SessionException
# for now as a workaround which could be raised from potential race conditions when
# multiple ibun commands try to create the same zip file or the very same resource
# gets deleted by another request when being downloaded
istorage.runBagitRule(bagit_rule_file, bagit_input_path, bagit_input_resource)
istorage.zipup(irods_bagit_input_path, bag_full_name)
istorage.setAVU(irods_bagit_input_path, 'bag_modified', "false")
return True
except SessionException as ex:
# if an exception occurs, delete incomplete files potentially being generated by
# iRODS bagit rule and zipping operations
for fname in bagit_files:
if istorage.exists(fname):
istorage.delete(fname)
logger.error(ex.stderr)
return False
else:
logger.error('Resource does not exist.')
return False
@shared_task
def update_quota_usage_task(username):
"""update quota usage. This function runs as a celery task, invoked asynchronously with 1
minute delay to give enough time for iRODS real time quota update micro-services to update
quota usage AVU for the user before this celery task to check this AVU to get the updated
quota usage for the user. Note iRODS micro-service quota update only happens on HydroShare
iRODS data zone and user zone independently, so the aggregation of usage in both zones need
to be accounted for in this function to update Django DB as an aggregated usage for hydroshare
internal zone.
:param
username: the name of the user that needs to update quota usage for.
:return: True if quota usage update succeeds;
False if there is an exception raised or quota cannot be updated. See log for details.
"""
hs_internal_zone = "hydroshare"
uq = UserQuota.objects.filter(user__username=username, zone=hs_internal_zone).first()
if uq is None:
# the quota row does not exist in Django
logger.error('quota row does not exist in Django for hydroshare zone for '
'user ' + username)
return False
attname = username + '-usage'
istorage = IrodsStorage()
# get quota size for user in iRODS data zone by retrieving AVU set on irods bagit path
# collection
try:
uqDataZoneSize = istorage.getAVU(settings.IRODS_BAGIT_PATH, attname)
if uqDataZoneSize is None:
# user may not have resources in data zone, so corresponding quota size AVU may not
# exist for this user
uqDataZoneSize = -1
else:
uqDataZoneSize = float(uqDataZoneSize)
except SessionException:
# user may not have resources in data zone, so corresponding quota size AVU may not exist
# for this user
uqDataZoneSize = -1
# get quota size for the user in iRODS user zone
try:
uz_bagit_path = os.path.join('/', settings.HS_USER_IRODS_ZONE, 'home',
settings.HS_IRODS_PROXY_USER_IN_USER_ZONE,
settings.IRODS_BAGIT_PATH)
uqUserZoneSize = istorage.getAVU(uz_bagit_path, attname)
if uqUserZoneSize is None:
# user may not have resources in user zone, so corresponding quota size AVU may not
# exist for this user
uqUserZoneSize = -1
else:
uqUserZoneSize = float(uqUserZoneSize)
except SessionException:
# user may not have resources in user zone, so corresponding quota size AVU may not exist
# for this user
uqUserZoneSize = -1
if uqDataZoneSize < 0 and uqUserZoneSize < 0:
logger.error('no quota size AVU in data zone and user zone for the user ' + username)
return False
elif uqUserZoneSize < 0:
used_val = uqDataZoneSize
elif uqDataZoneSize < 0:
used_val = uqUserZoneSize
else:
used_val = uqDataZoneSize + uqUserZoneSize
uq.update_used_value(used_val)
return True
@shared_task
def update_web_services(services_url, api_token, timeout, publish_urls, res_id):
"""Update web services hosted by GeoServer and HydroServer.
This function sends a resource id to the HydroShare web services manager
application, which will check the current status of the resource and register
or unregister services hosted by GeoServer and HydroServer.
The HydroShare web services manager will return a list of endpoint URLs
for both the resource and individual aggregations. If publish_urls is set to
True, these endpoints will be added to the extra metadata fields of the
resource and aggregations.
"""
session = requests.Session()
session.headers.update(
{"Authorization": " ".join(("Token", str(api_token)))}
)
rest_url = str(services_url) + "/" + str(res_id) + "/"
try:
response = session.post(rest_url, timeout=timeout)
if publish_urls and response.status_code == status.HTTP_201_CREATED:
try:
resource = utils.get_resource_by_shortkey(res_id)
response_content = json.loads(response.content)
for key, value in response_content["resource"].iteritems():
resource.extra_metadata[key] = value
resource.save()
for url in response_content["content"]:
lf = resource.logical_files[[i.aggregation_name for i in
resource.logical_files].index(
url["layer_name"].encode("utf-8")
)]
lf.metadata.extra_metadata["Web Services URL"] = url["message"]
lf.metadata.save()
except Exception as e:
logger.error(e)
return e
return response
except (requests.exceptions.RequestException, ValueError) as e:
logger.error(e)
return e | USERNAME=settings.CROSSREF_LOGIN_ID,
PASSWORD=settings.CROSSREF_LOGIN_PWD,
| random_line_split |
controllers.js | angular.module('starter.controllers', [])
.controller('HomeCtrl', function($scope) {})
.controller('ChatsCtrl', function($scope, Chats) {
$scope.chats = Chats.all();
$scope.remove = function(chat) {
Chats.remove(chat);
};
})
.controller('PieChartCtrl', function($scope,$stateParams,$timeout,$rootScope,$ionicScrollDelegate) {
// serviceModule.onloadingshow();
$timeout( function() {
serviceModule.onloadinghide();
},1400);
$scope.chartPie = {
options: {
chart: {
type: 'pie',
// marginTop: '10px'
},
colors: ['#00FF80', '#ff0000', '#5882FA'],
},
series: [{
data: [
['Nausea', 20],
['Skin rashes', 50],
['No side effects', 30],
],
name: ' ',
//data:[50,40],
dataLabels: {
rotation: 270,
enabled: false,
format: '{series.name}: <b>{series.percentage:.1f}%</b>',
}
}],
title: {
text: 'Medicine Details'
},
tooltip: {
valueDecimals: 2,
valueSuffix: ' USD',
pointFormat: '{series.name}: <b>{series.percentage:.1f}%</b>'
},
credits: {
enabled: false
},
loading: false
}
})
.controller('LoginCntrl', function($scope,$state) {
$scope.dform={};
$scope.ptform={};
$scope.phform={};
$scope.login = function() {
var user=$scope.dform.username;
var dpass=$scope.dform.password;
var duser=user.toLowerCase();
// if(duser.substr(0,6)=="doctor" && dpass=="doctor123")
if(duser=="blanco" && dpass=="blanco123")
$state.go("tab.dash");
else
document.getElementById("loginErr").innerHTML="Invalid Credentials";
};
$scope.ptLogin = function() {
var tuser=$scope.ptform.username;
var ptpass=$scope.ptform.password;
var ptuser=tuser.toLowerCase();
// if(ptuser.substr(0,7)=="patient" && ptpass=="patient123")
if(ptuser=="sheldon" && ptpass=="sheldon123")
$state.go("patient.dash");
else
document.getElementById("ptErr").innerHTML="Invalid Credentials";
};
$scope.phLogin = function() {
var huser=$scope.phform.username;
var phpass=$scope.phform.password;
var phuser=huser.toLowerCase();
if(phuser.substr(0,8)=="pharmacy" && phpass=="pharmacy123")
$state.go("pharmacy.dash");
else
document.getElementById("phErr").innerHTML="Invalid Credentials";
};
})
.controller('ChatDetailCtrl', function($scope, $stateParams, Chats) {
$scope.chat = Chats.get($stateParams.chatId);
})
.controller('diseasectrl', function($scope, $stateParams,$ionicHistory,Diseases,$ionicPopup) {
/*$scope.goBack = function() {
$ionicHistory.goBack();
};*/
$scope.diseases = Diseases.all();
$scope.remove = function(disease) {
Diseases.remove(disease); }
$scope.showAlert = function(m) {
var alertPopup = $ionicPopup.alert({
title: m,
templateUrl: 'templates/templates/diseasesmed.html'
});
};
})
.controller('diseasectrlPh', function($scope, $stateParams,$ionicHistory,Diseases,$ionicPopup) {
/*$scope.goBack = function() {
$ionicHistory.goBack();
};*/
$scope.diseases = Diseases.all();
$scope.remove = function(disease) {
Diseases.remove(disease); }
$scope.showAlert = function(m) {
var alertPopup = $ionicPopup.alert({
title: m,
templateUrl: 'templates/templatesPh/diseasesmed.html'
});
};
})
.controller('PatientsCtrl', function($scope, Patients,$ionicHistory,$ionicPopup) {
$scope.patients = Patients.all();
$scope.remove = function(patient) {
Patients.remove(patient);
};
$scope.showAlert = function(nam) {
var alertPopup = $ionicPopup.alert({
title: nam,
templateUrl: 'templates/templatesPh/patientmed.html'
});
};
})
.controller('searchcontroller', function($ionicHistory,$scope,$http,$ionicLoading,$timeout,medicines) {
$scope.Result;
$scope.flag=false;
$scope.getMed = function (k) {
$scope.med=medicines.get(k);
}
$scope.getValue = function (key) {
$scope.flag=false;
if($scope.search.length>1){
var id =$scope.search;
//$scope.loading = $ionicLoading.show({content: 'Loading...'});
$scope.mmed=medicines.all();
//alert(JSON.stringify($scope.mmed))
if($scope.mmed.length==0){
$scope.flag=true;
$scope.Result="There are no products matching the selection.";
}
$scope.result=$scope.mmed;
}
}
})
.controller('medctrl', function($scope, $stateParams,medicines,$ionicPopup) {
$scope.med=medicines.all();
$scope.medAlert = function(t) {
var alertPopup = $ionicPopup.alert({
title: t,
templateUrl: 'templates/templates/patientmed.html'
});
};
})
.controller('medctrlPh', function($scope, $stateParams,medicines,$ionicPopup) {
$scope.med=medicines.all();
$scope.medAlert = function(t) {
var alertPopup = $ionicPopup.alert({
title: t,
templateUrl: 'templates/templatesPh/pharmacymed.html'
});
};
})
.controller('DoctCtrl', function($scope, Docts,$ionicHistory,$ionicPopup) {
$scope.patients = Docts.all();
$scope.remove = function(patient) {
Docts.remove(patient);
};
$scope.showAlert = function(nam) {
var alertPopup = $ionicPopup.alert({
title: nam,
templateUrl: 'templates/templatesPh/patientmed1.html'
});
};
})
/*
.controller('MedCtrl', function($scope, medicines,$ionicHistory,$ionicPopup) {
$scope.meds = medicines.all();
$scope.showAlert = function() {
var alertPopup = $ionicPopup.alert({
title: 'Acne',
templateUrl: 'templates/templatesPh/patientmed.html'
});
};
})*/
.controller('PatientDetailCtrl', function($scope, $stateParams, Patients) {
$scope.patient = Patients.get($stateParams.patientsId);
})
.controller('AppointDetailCtrl', function($scope, $stateParams, Patients) {
$scope.patient = Patients.get($stateParams.appointId);
})
.controller('Action', function($scope, $ionicActionSheet,$location, $state,ContactService,Patients) {
/* $scope.showActionsheetDoc = function() {
$ionicActionSheet.show({
buttons: [
{ text: '<div class="padding" >Add Patient</div>' }
],
cancelText: 'Cancel',
cancel: function() {
},
buttonClicked: function(index) {
if(index === 0){ // Allgemein
$state.go('tab.addPrescription');
}
return true;
},
destructiveButtonClicked: function() {
return true;
}
});
};
*/
$scope.showActionsheet = function() {
$ionicActionSheet.show({
buttons: [
{ text: '<div class="padding" >Add Prescription</div>' }
],
cancelText: 'Cancel',
cancel: function() {
},
buttonClicked: function(index) {
if(index === 0){ // Allgemein
$state.go('pharmacy.addPrescription');
}
return true;
},
destructiveButtonClicked: function() {
return true;
}
});
};
$scope.cancelAddress=function(){
$state.go('pharmacy.patients');
};
//uid=3;
$scope.contacts = ContactService.list();
//alert(JSON.stringify($scope.contacts));
$scope.newcontact = {};
$scope.saveAddress=function(){
//alert($scope.newcontact.fname)
ContactService.save($scope.newcontact);
$state.go("pharmacy.patientaddress");
};
$scope.cancel=function(){
$state.go("pharmacy.addPrescription");
}; | $scope.add={};
alert($scope.add.fname);
var id1=$scope.p[$scope.p.length-1].id+1;
var savep={
id: id1,
face: 'img/mike.png',
name: $scope.add.fname,
PatientID: '12556'+id1,
Age : $scope.add.fname,
message : 'Hi doctor',
date:'26/3/2017 3.20PM',
gender:'Male'
};
// Patients.save(savep);
$state.go("pharmacy.patients");
};
})
.controller('AddressCtrl', function($scope, $stateParams) {
//alert(JSON.stringify($stateParams.addr)+" sss");
//$scope.fname=$stateParams.addr;
$scope.addr=$stateParams.addr;
alert($scope.addr);
})
.controller('MedicinesCtrl', function($scope,$state, $ionicPopup) {
$scope.showAlert = function() {
//alert()
/*var alertPopup = $ionicPopup.alert({
title: 'Ibuprofen',
templateUrl: 'templates/medicinedetail.html'
}); */
$state.go("tab.medicineView");
};
})
.controller('mainctrl', function($scope,$state,Questions,PQuestions,PHQuestions,$location,$ionicHistory) {
$scope.goBack = function() {
$ionicHistory.goBack();
};
$scope.questions = Questions.all();
$scope.pquestions = PQuestions.all();
$scope.phquestions = PHQuestions.all();
//alert(JSON.stringify($scope.contacts))
/* $scope.qashow="true";
$scope.quesshow="true";*/
$scope.clearSearch = function() {
$scope.search = '';
};
})
.controller('maindetailctrl', function($scope, $stateParams,$ionicHistory, Questions,PQuestions,PHQuestions) {
$scope.question = Questions.get($stateParams.questionId);
$scope.pquestion = PQuestions.get($stateParams.questionId);
$scope.phquestion = PHQuestions.get($stateParams.questionId);
$scope.goBack = function() {
$ionicHistory.goBack();
};
})
.controller('AccountCtrl', function($scope,$ionicHistory,$state) {
$scope.settings = {
enableFriends: true
};
$scope.logout=function(){
$ionicHistory.clearCache();
$ionicHistory.clearHistory();
$ionicHistory.nextViewOptions({ disableBack: true, historyRoot: true });
$state.go("loginHome");
}
})
.service('ContactService', function () {
//to create unique contact id
var uid = 15567;
//contacts array to hold list of all contacts
var contacts = [];
//save method create a new contact if not already exists
//else update the existing object
this.save = function (contact) {
if (contact.id == null) {
//if this is new contact, add it in contacts array
contact.id = uid++;
contacts.push(contact);
} else {
//for existing contact, find this contact using id
//and update it.
for (i in contacts) {
if (contacts[i].id == contact.id) {
contacts[i] = contact;
}
}
}
}
//simply search contacts list for given id
//and returns the contact object if found
this.get = function (id) {
for (i in contacts) {
if (contacts[i].id == id) {
return contacts[i];
}
}
}
//iterate through contacts list and delete
//contact if found
this.delete = function (id) {
for (i in contacts) {
if (contacts[i].id == id) {
contacts.splice(i, 1);
}
}
}
//simply returns the contacts list
this.list = function () {
return contacts;
}
}); |
$scope.done=function(){
$scope.p=Patients.all(); | random_line_split |
controllers.js | angular.module('starter.controllers', [])
.controller('HomeCtrl', function($scope) {})
.controller('ChatsCtrl', function($scope, Chats) {
$scope.chats = Chats.all();
$scope.remove = function(chat) {
Chats.remove(chat);
};
})
.controller('PieChartCtrl', function($scope,$stateParams,$timeout,$rootScope,$ionicScrollDelegate) {
// serviceModule.onloadingshow();
$timeout( function() {
serviceModule.onloadinghide();
},1400);
$scope.chartPie = {
options: {
chart: {
type: 'pie',
// marginTop: '10px'
},
colors: ['#00FF80', '#ff0000', '#5882FA'],
},
series: [{
data: [
['Nausea', 20],
['Skin rashes', 50],
['No side effects', 30],
],
name: ' ',
//data:[50,40],
dataLabels: {
rotation: 270,
enabled: false,
format: '{series.name}: <b>{series.percentage:.1f}%</b>',
}
}],
title: {
text: 'Medicine Details'
},
tooltip: {
valueDecimals: 2,
valueSuffix: ' USD',
pointFormat: '{series.name}: <b>{series.percentage:.1f}%</b>'
},
credits: {
enabled: false
},
loading: false
}
})
.controller('LoginCntrl', function($scope,$state) {
$scope.dform={};
$scope.ptform={};
$scope.phform={};
$scope.login = function() {
var user=$scope.dform.username;
var dpass=$scope.dform.password;
var duser=user.toLowerCase();
// if(duser.substr(0,6)=="doctor" && dpass=="doctor123")
if(duser=="blanco" && dpass=="blanco123")
$state.go("tab.dash");
else
document.getElementById("loginErr").innerHTML="Invalid Credentials";
};
$scope.ptLogin = function() {
var tuser=$scope.ptform.username;
var ptpass=$scope.ptform.password;
var ptuser=tuser.toLowerCase();
// if(ptuser.substr(0,7)=="patient" && ptpass=="patient123")
if(ptuser=="sheldon" && ptpass=="sheldon123")
$state.go("patient.dash");
else
document.getElementById("ptErr").innerHTML="Invalid Credentials";
};
$scope.phLogin = function() {
var huser=$scope.phform.username;
var phpass=$scope.phform.password;
var phuser=huser.toLowerCase();
if(phuser.substr(0,8)=="pharmacy" && phpass=="pharmacy123")
$state.go("pharmacy.dash");
else
document.getElementById("phErr").innerHTML="Invalid Credentials";
};
})
.controller('ChatDetailCtrl', function($scope, $stateParams, Chats) {
$scope.chat = Chats.get($stateParams.chatId);
})
.controller('diseasectrl', function($scope, $stateParams,$ionicHistory,Diseases,$ionicPopup) {
/*$scope.goBack = function() {
$ionicHistory.goBack();
};*/
$scope.diseases = Diseases.all();
$scope.remove = function(disease) {
Diseases.remove(disease); }
$scope.showAlert = function(m) {
var alertPopup = $ionicPopup.alert({
title: m,
templateUrl: 'templates/templates/diseasesmed.html'
});
};
})
.controller('diseasectrlPh', function($scope, $stateParams,$ionicHistory,Diseases,$ionicPopup) {
/*$scope.goBack = function() {
$ionicHistory.goBack();
};*/
$scope.diseases = Diseases.all();
$scope.remove = function(disease) {
Diseases.remove(disease); }
$scope.showAlert = function(m) {
var alertPopup = $ionicPopup.alert({
title: m,
templateUrl: 'templates/templatesPh/diseasesmed.html'
});
};
})
.controller('PatientsCtrl', function($scope, Patients,$ionicHistory,$ionicPopup) {
$scope.patients = Patients.all();
$scope.remove = function(patient) {
Patients.remove(patient);
};
$scope.showAlert = function(nam) {
var alertPopup = $ionicPopup.alert({
title: nam,
templateUrl: 'templates/templatesPh/patientmed.html'
});
};
})
.controller('searchcontroller', function($ionicHistory,$scope,$http,$ionicLoading,$timeout,medicines) {
$scope.Result;
$scope.flag=false;
$scope.getMed = function (k) {
$scope.med=medicines.get(k);
}
$scope.getValue = function (key) {
$scope.flag=false;
if($scope.search.length>1){
var id =$scope.search;
//$scope.loading = $ionicLoading.show({content: 'Loading...'});
$scope.mmed=medicines.all();
//alert(JSON.stringify($scope.mmed))
if($scope.mmed.length==0){
$scope.flag=true;
$scope.Result="There are no products matching the selection.";
}
$scope.result=$scope.mmed;
}
}
})
.controller('medctrl', function($scope, $stateParams,medicines,$ionicPopup) {
$scope.med=medicines.all();
$scope.medAlert = function(t) {
var alertPopup = $ionicPopup.alert({
title: t,
templateUrl: 'templates/templates/patientmed.html'
});
};
})
.controller('medctrlPh', function($scope, $stateParams,medicines,$ionicPopup) {
$scope.med=medicines.all();
$scope.medAlert = function(t) {
var alertPopup = $ionicPopup.alert({
title: t,
templateUrl: 'templates/templatesPh/pharmacymed.html'
});
};
})
.controller('DoctCtrl', function($scope, Docts,$ionicHistory,$ionicPopup) {
$scope.patients = Docts.all();
$scope.remove = function(patient) {
Docts.remove(patient);
};
$scope.showAlert = function(nam) {
var alertPopup = $ionicPopup.alert({
title: nam,
templateUrl: 'templates/templatesPh/patientmed1.html'
});
};
})
/*
.controller('MedCtrl', function($scope, medicines,$ionicHistory,$ionicPopup) {
$scope.meds = medicines.all();
$scope.showAlert = function() {
var alertPopup = $ionicPopup.alert({
title: 'Acne',
templateUrl: 'templates/templatesPh/patientmed.html'
});
};
})*/
.controller('PatientDetailCtrl', function($scope, $stateParams, Patients) {
$scope.patient = Patients.get($stateParams.patientsId);
})
.controller('AppointDetailCtrl', function($scope, $stateParams, Patients) {
$scope.patient = Patients.get($stateParams.appointId);
})
.controller('Action', function($scope, $ionicActionSheet,$location, $state,ContactService,Patients) {
/* $scope.showActionsheetDoc = function() {
$ionicActionSheet.show({
buttons: [
{ text: '<div class="padding" >Add Patient</div>' }
],
cancelText: 'Cancel',
cancel: function() {
},
buttonClicked: function(index) {
if(index === 0){ // Allgemein
$state.go('tab.addPrescription');
}
return true;
},
destructiveButtonClicked: function() {
return true;
}
});
};
*/
$scope.showActionsheet = function() {
$ionicActionSheet.show({
buttons: [
{ text: '<div class="padding" >Add Prescription</div>' }
],
cancelText: 'Cancel',
cancel: function() {
},
buttonClicked: function(index) {
if(index === 0){ // Allgemein
$state.go('pharmacy.addPrescription');
}
return true;
},
destructiveButtonClicked: function() {
return true;
}
});
};
$scope.cancelAddress=function(){
$state.go('pharmacy.patients');
};
//uid=3;
$scope.contacts = ContactService.list();
//alert(JSON.stringify($scope.contacts));
$scope.newcontact = {};
$scope.saveAddress=function(){
//alert($scope.newcontact.fname)
ContactService.save($scope.newcontact);
$state.go("pharmacy.patientaddress");
};
$scope.cancel=function(){
$state.go("pharmacy.addPrescription");
};
$scope.done=function(){
$scope.p=Patients.all();
$scope.add={};
alert($scope.add.fname);
var id1=$scope.p[$scope.p.length-1].id+1;
var savep={
id: id1,
face: 'img/mike.png',
name: $scope.add.fname,
PatientID: '12556'+id1,
Age : $scope.add.fname,
message : 'Hi doctor',
date:'26/3/2017 3.20PM',
gender:'Male'
};
// Patients.save(savep);
$state.go("pharmacy.patients");
};
})
.controller('AddressCtrl', function($scope, $stateParams) {
//alert(JSON.stringify($stateParams.addr)+" sss");
//$scope.fname=$stateParams.addr;
$scope.addr=$stateParams.addr;
alert($scope.addr);
})
.controller('MedicinesCtrl', function($scope,$state, $ionicPopup) {
$scope.showAlert = function() {
//alert()
/*var alertPopup = $ionicPopup.alert({
title: 'Ibuprofen',
templateUrl: 'templates/medicinedetail.html'
}); */
$state.go("tab.medicineView");
};
})
.controller('mainctrl', function($scope,$state,Questions,PQuestions,PHQuestions,$location,$ionicHistory) {
$scope.goBack = function() {
$ionicHistory.goBack();
};
$scope.questions = Questions.all();
$scope.pquestions = PQuestions.all();
$scope.phquestions = PHQuestions.all();
//alert(JSON.stringify($scope.contacts))
/* $scope.qashow="true";
$scope.quesshow="true";*/
$scope.clearSearch = function() {
$scope.search = '';
};
})
.controller('maindetailctrl', function($scope, $stateParams,$ionicHistory, Questions,PQuestions,PHQuestions) {
$scope.question = Questions.get($stateParams.questionId);
$scope.pquestion = PQuestions.get($stateParams.questionId);
$scope.phquestion = PHQuestions.get($stateParams.questionId);
$scope.goBack = function() {
$ionicHistory.goBack();
};
})
.controller('AccountCtrl', function($scope,$ionicHistory,$state) {
$scope.settings = {
enableFriends: true
};
$scope.logout=function(){
$ionicHistory.clearCache();
$ionicHistory.clearHistory();
$ionicHistory.nextViewOptions({ disableBack: true, historyRoot: true });
$state.go("loginHome");
}
})
.service('ContactService', function () {
//to create unique contact id
var uid = 15567;
//contacts array to hold list of all contacts
var contacts = [];
//save method create a new contact if not already exists
//else update the existing object
this.save = function (contact) {
if (contact.id == null) {
//if this is new contact, add it in contacts array
contact.id = uid++;
contacts.push(contact);
} else {
//for existing contact, find this contact using id
//and update it.
for (i in contacts) {
if (contacts[i].id == contact.id) {
contacts[i] = contact;
}
}
}
}
//simply search contacts list for given id
//and returns the contact object if found
this.get = function (id) {
for (i in contacts) {
if (contacts[i].id == id) |
}
}
//iterate through contacts list and delete
//contact if found
this.delete = function (id) {
for (i in contacts) {
if (contacts[i].id == id) {
contacts.splice(i, 1);
}
}
}
//simply returns the contacts list
this.list = function () {
return contacts;
}
});
| {
return contacts[i];
} | conditional_block |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.remove('overflow');
preloader.remove();
}, 800);
}
/* Slider >>>>>>>>>>>>>>>>>>>*/
var rightArrow = document.getElementById('right-arrow');
var leftArrow = document.getElementById('left-arrow');
var slides = document.getElementsByClassName('review-item');
var activeSlide = document.querySelector('.review-item.active')
function changeSlideRight() {
//activeSlide.classList.remove('active');
for (var i = 0; i < slides.length; i++) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i < slides.length - 1)
slides[++i].classList.add('active');
else
slides[0].classList.add('active');
return;
}
}
}
function changeSlideLeft() {
//activeSlide.classList.remove('active');
for (var i = slides.length - 1; i >= 0; i--) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i > 0)
slides[--i].classList.add('active');
else
slides[slides.length - 1].classList.add('active');
return;
}
}
}
rightArrow.addEventListener('click', function () {
changeSlideRight()
})
leftArrow.addEventListener('click', function () {
changeSlideLeft()
})
/* Slider />>>>>>>>>>>>>>>>>>>*/
/* carousel >>>>>>>>>>>>>>>>>>>*/
var root = document.documentElement;
var carouselElementsDisplayed = getComputedStyle(root).getPropertyValue("--carousel-elements-displayed");
var carouselContent = document.querySelector("ul.carousel-content");
root.style.setProperty("--carousel-elements", carouselContent.children.length);
for (var i = 0; i < carouselElementsDisplayed; i++) {
carouselContent.appendChild(carouselContent.children[i].cloneNode(true));
}
/* carousel />>>>>>>>>>>>>>>>>>>*/
//load-more >>>>>>>>>>>>>>>>>>>>>>*/
var loadMore = document.querySelector("#load-more");
var hiddenWorks = document.querySelectorAll(".portfolio-hidden");
var catalogBlock = document.querySelector('.portfolio-content');
loadMore.addEventListener('click', loadContent);
function loadContent() {
loadMore.style.display = 'none';
for (var i = 0; i < hiddenWorks.length; i++) {
catalogBlock.appendChild(hiddenWorks[i]);
}
}
//load-more />>>>>>>>>>>>>>>>>>>>>>*/
/* filter >>>>>>>>>>>>>>>>>>>>>>*/
var closestsElementClass = function (elem, className) {
var node = elem;
while (node) {
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
node = node.parentElement;
}
return null;
}
var catalog = document.querySelector('.portfolio-content');
//блок с табами
var catalogNav = document.querySelector('.portfolio-filter');
var catalogItems = document.querySelectorAll('.portfolio-content__item');
//Очистка блока с элементами, чтобы при фильрации добавлялись новые в чиситый блок
function removeChildren(item) {
while (item.firstChild) {
item.removeChild(item.firstChild)
}
}
//обновляем элементы в каталоге | item это блок каталога
function updateChildren(item, children) {
removeChildren(item);
for (var i = 0; i < children.length; i++) {
item.appendChild(children[i]);
}
}
catalogNav.addEventListener('click', function (e) {
var target = e.target;
var item = closestsElementClass(target, 'portfolio-filter__link');
if (item === null || item.classList.contains('is-active')) {
return;
}
loadContent();
e.preventDefault();
//Получаем значение из атрибута data-filter=""
var filterValue = item.getAttribute('data-filter');
var previousActiveBtn = document.querySelector('.portfolio-filter__link.is-active');
previousActiveBtn.classList.remove('is-active');
item.classList.add('is-active');
//Если выбраны ВСЕ, то просто их всех выводим
if (filterValue === 'all') {
updateChildren(catalog, catalogItems);
return;
}
//Отфильтрованные элементы перемещаем в массив
var filteredItems = [];
for (var i = 0; i < catalogItems.length; i++) {
var currentItem = catalogItems[i];
if (currentItem.getAttribute('data-category') === filterValue) {
filteredItems.push(currentItem);
}
}
updateChildren(catalog, filteredItems);
});
/* filter />>>>>>>>>>>>>>>>>>>>>>*/
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
var smoothScroll = function (targetEl, duration) {
var headerElHeight = document.querySelector('#header').clientHeight; // класс хедера
var target = document.querySelector(targetEl);
var targetPosition = target.getBoundingClientRect().top; //- headerElHeight; //вычитаем размер хедера, если он фиксированный
var startPosition = window.pageYOffset;
var startTime = null;
var ease = function (t, b, c, d) {
t /= d / 2;
if (t < 1) return c / 2 * t * t + b;
t--;
return -c / 2 * (t * (t - 2) - 1) + b;
};
var animation = function (currentTime) {
if (startTime === null) startTime = currentTime;
var timeElapsed = currentTime - startTime;
var run = ease(timeElapsed, startPosition, targetPosition, duration);
window.scrollTo(0, run);
if (timeElapsed < duration) requestAnimationFrame(animation);
};
requestAnimationFrame(animation);
};
var scrollTo = function () {
var headerNav = document.querySelector('.navigation');
//var links = document.querySelectorAll('.js-scroll'); //добавляем классы к линкам
var links = document.querySelectorAll('.nav-link'); //добавляем классы к линкам
links.forEach(each => {
each.addEventListener('click', function () {
var currentTarget = this.getAttribute('href');
smoothScroll(currentTarget, 1000);
//выход из мобильного меню
headerNav.classList.remove('active');
document.querySelector("#burger").classList.remove('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
});
});
};
scrollTo();
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
/* мобильное меню >>>>>>>>>>>>>>>>>>>>>>*/
var burger = document.querySelector("#burger");
var navigation = document.querySelector(".navigation");
var contactBtn = document.querySelector(".hire--btn");
burger.addEventListener('click', function () {
body.classList.toggle('overflow')
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
})
contactBtn.addEventListener('click', function () {
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
})
/* мобильное меню />>>>>>>>>>>>>>>>>>>>>>*/
//filter >>>>>>>>>>>>>>>>>>>>>>*/
var filter = document.querySelector("#filter");
var filterBlock = document.querySelector(".portfolio-filter");
filter.addEventListener('click', function () {
filterBlock.classList.toggle('open');
})
//filter />>>>>>>>>>>>>>>>>>>>>>*/
//popup >>>>>>>>>>>>>>>>>>>>>>*/
//Функция для поиска атрибута по вложенным тегам
var closestsElementAttr = function (elem, attr) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* атрибут родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
var attribute = node.getAttribute(attr);
if (attribute) {
return attribute; //атрибут есть — значит его и возвращаем, прекращая функцию
}
/*/ если атрибут пуст, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется атрибут,
* иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего атрибута ни у элемента, ни у его дочерних узлов
return null;
}
//Поиск ближайшего элемента по классу
var closestsElementClass = function (elem, className) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* класс родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
/*/ если текущий элемент содержит тот класс, который мы ему передали,
* при вызове функции, то просто возвращаем этот элемент,
/*/
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
/*/ если класса нет, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется класс,
* который мы передали, иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего класса ни у элемента, ни у его дочерних узлов
return null;
}
//Показ попапа
function showPopup(target) {
target.classList.add('is-active');
}
//Скрытие попапа
function closePopup(target) {
target.classList.remove('is-active');
}
//BODY overflow hidden, чтобы при открытом попапе фон не скролился
function bodyOverflow() {
body.classList.toggle('overflow');
}
//Открытие попапа при клике на бургер меню
body.addEventListener('click', function (e) {
var target = e.target;
//Поиск названия data-popup, который задан у кнопки бургера
//var popupClass = target.getAttribute('data-popup');
var popupClass = closestsElementAttr(target, 'data-popup');
//если элемент, на котором кликнули, не имеет аттрибут data-popup, то выходим
if (popupClass === null) {
return;
}
e.preventDefault();
var popup = document.querySelector('.' + popupClass);
if (popup) {
showPopup(popup);
bodyOverflow();
}
})
//Закрытие попапа при клике X или на область вне попапа
body.addEventListener('click', function (e) {
var target = e.target;
//Если клик был на кнопку Х или фон вне попапа, то закрываем его
if (e.target.classList.contains('popup__close') || e.target.classList.contains('popup__wrapper') || e.target.classList.contains('popup__inner')) {
//поиск той кноки Х, которая относится к конкретному попапу
var pop | estsElementClass(target, 'popup');
closePopup(popup);
bodyOverflow();
}
});
//Закрытие попапа при клике на escape (Esc)
body.addEventListener('keydown', function (e) {
if (e.keyCode !== 27)
return;
else {
var popup = document.querySelector('.popup.is-active');
closePopup(popup);
bodyOverflow();
}
});
//popup />>>>>>>>>>>>>>>>>>>>>>*/
//scroll-up >>>>>>>>>>>>>>>>>>>>>>*/
var intervalId = 0; // Needed to cancel the scrolling when we're at the top of the page
var scrollButton = document.querySelector('.to-top'); // Reference to our scroll button
var header = document.querySelector('#header');
var headerHeight = header.clientHeight;
window.addEventListener('scroll', function () {
if (window.pageYOffset > headerHeight)
scrollButton.style.display = "block";
else
scrollButton.style.display = "none";
});
function scrollStep() {
if (window.pageYOffset === 0) {
clearInterval(intervalId);
}
window.scroll(0, window.pageYOffset - 50);
}
function scrollToTop() {
//speed
intervalId = setInterval(scrollStep, 10);
}
scrollButton.addEventListener('click', scrollToTop);
//scroll-up />>>>>>>>>>>>>>>>>>>>>>*/
//tooltip >>>>>>>>>>>>>>>>>>>>>>*/
let tooltipElem;
document.onmouseover = function (event) {
let target = event.target;
// если у нас есть подсказка...
let tooltipHtml = target.dataset.tooltip;
if (!tooltipHtml) return;
// ...создадим элемент для подсказки
tooltipElem = document.createElement('div');
tooltipElem.className = 'tooltip';
tooltipElem.innerHTML = tooltipHtml;
document.body.append(tooltipElem);
// спозиционируем его сверху от аннотируемого элемента (top-center)
let coords = target.getBoundingClientRect();
let left = coords.left + (target.offsetWidth - tooltipElem.offsetWidth) / 2;
if (left < 0) left = 0; // не заезжать за левый край окна
let top = coords.top - tooltipElem.offsetHeight - 5;
if (top < 0) { // если подсказка не помещается сверху, то отображать её снизу
top = coords.top + target.offsetHeight + 5;
}
tooltipElem.style.left = left + 'px';
tooltipElem.style.top = top + 'px';
};
document.onmouseout = function (e) {
if (tooltipElem) {
tooltipElem.remove();
tooltipElem = null;
}
};
//tooltip />>>>>>>>>>>>>>>>>>>>>>*/
})()
| up = clos | identifier_name |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.remove('overflow');
preloader.remove();
}, 800);
}
/* Slider >>>>>>>>>>>>>>>>>>>*/
var rightArrow = document.getElementById('right-arrow');
var leftArrow = document.getElementById('left-arrow');
var slides = document.getElementsByClassName('review-item');
var activeSlide = document.querySelector('.review-item.active')
function changeSlideRight() {
//activeSlide.classList.remove('active');
for (var i = 0; i < slides.length; i++) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i < slides.length - 1)
slides[++i].classList.add('active');
else
slides[0].classList.add('active');
return;
}
}
}
function changeSlideLeft() {
//activeSlide.classList.remove('active');
for (var i = slides.length - 1; i >= 0; i--) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i > 0)
slides[--i].classList.add('active');
else
slides[slides.length - 1].classList.add('active');
return;
}
}
}
rightArrow.addEventListener('click', function () {
changeSlideRight()
})
leftArrow.addEventListener('click', function () {
changeSlideLeft()
})
/* Slider />>>>>>>>>>>>>>>>>>>*/
/* carousel >>>>>>>>>>>>>>>>>>>*/
var root = document.documentElement;
var carouselElementsDisplayed = getComputedStyle(root).getPropertyValue("--carousel-elements-displayed");
var carouselContent = document.querySelector("ul.carousel-content");
root.style.setProperty("--carousel-elements", carouselContent.children.length);
for (var i = 0; i < carouselElementsDisplayed; i++) {
carouselContent.appendChild(carouselContent.children[i].cloneNode(true));
}
/* carousel />>>>>>>>>>>>>>>>>>>*/
//load-more >>>>>>>>>>>>>>>>>>>>>>*/
var loadMore = document.querySelector("#load-more");
var hiddenWorks = document.querySelectorAll(".portfolio-hidden");
var catalogBlock = document.querySelector('.portfolio-content');
loadMore.addEventListener('click', loadContent);
function loadContent() {
loadMore.style.display = 'none';
for (var i = 0; i < hiddenWorks.length; i++) {
catalogBlock.appendChild(hiddenWorks[i]);
}
}
//load-more />>>>>>>>>>>>>>>>>>>>>>*/
/* filter >>>>>>>>>>>>>>>>>>>>>>*/
var closestsElementClass = function (elem, className) {
var node = elem;
while (node) {
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
node = node.parentElement;
}
return null;
}
var catalog = document.querySelector('.portfolio-content');
//блок с табами
var catalogNav = document.querySelector('.portfolio-filter');
var catalogItems = document.querySelectorAll('.portfolio-content__item');
//Очистка блока с элементами, чтобы при фильрации добавлялись новые в чиситый блок
function removeChildren(item) {
while (item.firstChild) {
item.removeChild(item.firstChild)
}
}
//обновляем элементы в каталоге | item это блок каталога
function updateChildren(item, children) {
removeChildren(item);
for (var i = 0; i < children.length; i++) {
item.appendChild(children[i]);
}
}
catalogNav.addEventListener('click', function (e) {
var target = e.target;
var item = closestsElementClass(target, 'portfolio-filter__link');
if (item === null || item.classList.contains('is-active')) {
return;
}
loadContent();
e.preventDefault();
//Получаем значение из атрибута data-filter=""
var filterValue = item.getAttribute('data-filter');
var previousActiveBtn = document.querySelector('.portfolio-filter__link.is-active');
previousActiveBtn.classList.remove('is-active');
item.classList.add('is-active');
//Если выбраны ВСЕ, то просто их всех выводим
if (filterValue === 'all') {
updateChildren(catalog, catalogItems);
return;
}
//Отфильтрованные элементы перемещаем в массив
var filteredItems = [];
for (var i = 0; i < catalogItems.length; i++) {
var currentItem = catalogItems[i];
if (currentItem.getAttribute('data-category') === filterValue) {
filteredItems.push(currentItem);
}
}
updateChildren(catalog, filteredItems);
});
/* filter />>>>>>>>>>>>>>>>>>>>>>*/
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
var smoothScroll = function (targetEl, duration) {
var headerElHeight = document.querySelector('#header').clientHeight; // класс хедера
var target = document.querySelector(targetEl);
var targetPosition = target.getBoundingClientRect().top; //- headerElHeight; //вычитаем размер хедера, если он фиксированный
var startPosition = window.pageYOffset;
var startTime = null;
var ease = function (t, b, c, d) {
t /= d / 2;
if (t < 1) return c / 2 * t * t + b;
t--;
return -c / 2 * (t * (t - 2) - 1) + b;
};
var animation = function (currentTime) {
if (startTime === null) startTime = currentTime;
var timeElapsed = currentTime - startTime;
var run = ease(timeElapsed, startPosition, targetPosition, duration);
window.scrollTo(0, run);
if (timeElapsed < duration) requestAnimationFrame(animation);
};
requestAnimationFrame(animation);
};
var scrollTo = function () {
var headerNav = document.querySelector('.navigation');
//var links = document.querySelectorAll('.js-scroll'); //добавляем классы к линкам
var links = document.querySelectorAll('.nav-link'); //добавляем классы к линкам
links.forEach(each => {
each.addEventListener('click', function () {
var currentTarget = this.getAttribute('href');
smoothScroll(currentTarget, 1000);
//выход из мобильного меню
headerNav.classList.remove('active');
document.querySelector("#burger").classList.remove('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
});
});
};
scrollTo();
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
/* мобильное меню >>>>>>>>>>>>>>>>>>>>>>*/
var burger = document.querySelector("#burger");
var navigation = document.querySelector(".navigation");
var contactBtn = document.querySelector(".hire--btn");
burger.addEventListener('click', function () {
body.classList.toggle('overflow')
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
})
contactBtn.addEventListener('click', function () {
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
})
/* мобильное меню />>>>>>>>>>>>>>>>>>>>>>*/
//filter >>>>>>>>>>>>>>>>>>>>>>*/
var filter = document.querySelector("#filter");
var filterBlock = document.querySelector(".portfolio-filter");
filter.addEventListener('click', function () {
filterBlock.classList.toggle('open');
})
//filter />>>>>>>>>>>>>>>>>>>>>>*/
//popup >>>>>>>>>>>>>>>>>>>>>>*/
//Функция для поиска атрибута по вложенным тегам
var closestsElementAttr = function (elem, attr) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* атрибут родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
var attribute = node.getAttribute(attr);
if (attribute) {
return attribute; //атрибут есть — значит его и возвращаем, прекращая функцию
}
/*/ если атрибут пуст, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется атрибут,
* иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего атрибута ни у элемента, ни у его дочерних узлов
return null;
}
//Поиск ближайшего элемента по классу
var closestsElementClass = function (elem, className) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* класс родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
/*/ если текущий элемент содержит тот класс, который мы ему передали,
* при вызове функции, то просто возвращаем этот элемент,
/*/
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
/*/ если класса нет, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется класс,
* который мы передали, иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего класса ни у элемента, ни у его дочерних узлов
return null;
}
//Показ попапа
function showPopup(target) {
target.classList.add('is-active');
}
//Скрытие попапа
function closePopup(target) {
target.classList.remove('is-active');
}
//BODY overflow hidden, чтобы при открытом попапе фон не скролился
function bodyOverflow() {
body.classList.toggle('overflow');
}
//Открытие попапа при клике на бургер меню
body.addEventListener('click', function (e) { | //Поиск названия data-popup, который задан у кнопки бургера
//var popupClass = target.getAttribute('data-popup');
var popupClass = closestsElementAttr(target, 'data-popup');
//если элемент, на котором кликнули, не имеет аттрибут data-popup, то выходим
if (popupClass === null) {
return;
}
e.preventDefault();
var popup = document.querySelector('.' + popupClass);
if (popup) {
showPopup(popup);
bodyOverflow();
}
})
//Закрытие попапа при клике X или на область вне попапа
body.addEventListener('click', function (e) {
var target = e.target;
//Если клик был на кнопку Х или фон вне попапа, то закрываем его
if (e.target.classList.contains('popup__close') || e.target.classList.contains('popup__wrapper') || e.target.classList.contains('popup__inner')) {
//поиск той кноки Х, которая относится к конкретному попапу
var popup = closestsElementClass(target, 'popup');
closePopup(popup);
bodyOverflow();
}
});
//Закрытие попапа при клике на escape (Esc)
body.addEventListener('keydown', function (e) {
if (e.keyCode !== 27)
return;
else {
var popup = document.querySelector('.popup.is-active');
closePopup(popup);
bodyOverflow();
}
});
//popup />>>>>>>>>>>>>>>>>>>>>>*/
//scroll-up >>>>>>>>>>>>>>>>>>>>>>*/
var intervalId = 0; // Needed to cancel the scrolling when we're at the top of the page
var scrollButton = document.querySelector('.to-top'); // Reference to our scroll button
var header = document.querySelector('#header');
var headerHeight = header.clientHeight;
window.addEventListener('scroll', function () {
if (window.pageYOffset > headerHeight)
scrollButton.style.display = "block";
else
scrollButton.style.display = "none";
});
function scrollStep() {
if (window.pageYOffset === 0) {
clearInterval(intervalId);
}
window.scroll(0, window.pageYOffset - 50);
}
function scrollToTop() {
//speed
intervalId = setInterval(scrollStep, 10);
}
scrollButton.addEventListener('click', scrollToTop);
//scroll-up />>>>>>>>>>>>>>>>>>>>>>*/
//tooltip >>>>>>>>>>>>>>>>>>>>>>*/
let tooltipElem;
document.onmouseover = function (event) {
let target = event.target;
// если у нас есть подсказка...
let tooltipHtml = target.dataset.tooltip;
if (!tooltipHtml) return;
// ...создадим элемент для подсказки
tooltipElem = document.createElement('div');
tooltipElem.className = 'tooltip';
tooltipElem.innerHTML = tooltipHtml;
document.body.append(tooltipElem);
// спозиционируем его сверху от аннотируемого элемента (top-center)
let coords = target.getBoundingClientRect();
let left = coords.left + (target.offsetWidth - tooltipElem.offsetWidth) / 2;
if (left < 0) left = 0; // не заезжать за левый край окна
let top = coords.top - tooltipElem.offsetHeight - 5;
if (top < 0) { // если подсказка не помещается сверху, то отображать её снизу
top = coords.top + target.offsetHeight + 5;
}
tooltipElem.style.left = left + 'px';
tooltipElem.style.top = top + 'px';
};
document.onmouseout = function (e) {
if (tooltipElem) {
tooltipElem.remove();
tooltipElem = null;
}
};
//tooltip />>>>>>>>>>>>>>>>>>>>>>*/
})() | var target = e.target; | random_line_split |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.remove('overflow');
preloader.remove();
}, 800);
}
/* Slider >>>>>>>>>>>>>>>>>>>*/
var rightArrow = document.getElementById('right-arrow');
var leftArrow = document.getElementById('left-arrow');
var slides = document.getElementsByClassName('review-item');
var activeSlide = document.querySelector('.review-item.active')
function changeSlideRight() {
//activeSlide.classList.remove('active');
for (var i = 0; i < slides.length; i++) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i < slides.length - 1)
slides[++i].classList.add('active');
else
slides[0].classList.add('active');
return;
}
}
}
function changeSlideLeft() {
//activeSlide.classList.remove('active');
for (var i = slides.length - 1; i >= 0; i--) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i > 0)
slides[--i].classList.add('active');
else
slides[slides.length - 1].classList.add('active');
return;
}
}
}
rightArrow.addEventListener('click', function () {
changeSlideRight()
})
leftArrow.addEventListener('click', function () {
changeSlideLeft()
})
/* Slider />>>>>>>>>>>>>>>>>>>*/
/* carousel >>>>>>>>>>>>>>>>>>>*/
var root = document.documentElement;
var carouselElementsDisplayed = getComputedStyle(root).getPropertyValue("--carousel-elements-displayed");
var carouselContent = document.querySelector("ul.carousel-content");
root.style.setProperty("--carousel-elements", carouselContent.children.length);
for (var i = 0; i < carouselElementsDisplayed; i++) {
carouselContent.appendChild(carouselContent.children[i].cloneNode(true));
}
/* carousel />>>>>>>>>>>>>>>>>>>*/
//load-more >>>>>>>>>>>>>>>>>>>>>>*/
var loadMore = document.querySelector("#load-more");
var hiddenWorks = document.querySelectorAll(".portfolio-hidden");
var catalogBlock = document.querySelector('.portfolio-content');
loadMore.addEventListener('click', loadContent);
function loadContent() {
loadMore.style.display = 'none';
for (var i = 0; i < hiddenWorks.length; i++) {
catalogBlock.appendChild(hiddenWorks[i]);
}
}
//load-more />>>>>>>>>>>>>>>>>>>>>>*/
/* filter >>>>>>>>>>>>>>>>>>>>>>*/
var closestsElementClass = function (elem, className) {
var node = elem;
while (node) {
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
node = node.parentElement;
}
return null;
}
var catalog = document.querySelector('.portfolio-content');
//блок с табами
var catalogNav = document.querySelector('.portfolio-filter');
var catalogItems = document.querySelectorAll('.portfolio-content__item');
//Очистка блока с элементами, чтобы при фильрации добавлялись новые в чиситый блок
function removeChildren(item) {
while (item.firstChild) {
item.removeChild(item.firstChild)
}
}
//обновляем элементы в каталоге | item это блок каталога
function updateChildren(item, children) {
removeChildren(item);
for (var i = 0; i < children.length; i++) {
item.appendChild(children[i]);
}
}
catalogNav.addEventListener('click', function (e) {
var target = e.target;
var item = closestsElementClass(target, 'portfolio-filter__link');
if (item === null || item.classList.contains('is-active')) {
return;
}
loadContent();
e.preventDefault();
//Получаем значение из атрибута data-filter=""
var filterValue = item.getAttribute('data-filter');
var previousActiveBtn = document.querySelector('.portfolio-filter__link.is-active');
previousActiveBtn.classList.remove('is-active');
item.classList.add('is-active');
//Если выбраны ВСЕ, то просто их всех выводим
if (filterValue === 'all') {
updateChildren(catalog, catalogItems);
return;
}
//Отфильтрованные элементы перемещаем в массив
var filteredItems = [];
for (var i = 0; i < catalogItems.length; i++) {
var currentItem = catalogItems[i];
if (currentItem.getAttribute('data-category') === filterValue) {
filteredItems.push(currentItem);
}
}
updateChildren(catalog, filteredItems);
});
/* filter />>>>>>>>>>>>>>>>>>>>>>*/
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
var smoothScroll = function (targetEl, duration) {
var headerElHeight = document.querySelector('#header').clientHeight; // класс хедера
var target = document.querySelector(targetEl);
var targetPosition = target.getBoundingClientRect().top; //- headerElHeight; //вычитаем размер хедера, если он фиксированный
var startPosition = window.pageYOffset;
var startTime = null;
var ease = function (t, b, c, d) {
t /= d / 2;
if (t < 1) return c / 2 * t * t + b;
t--;
return -c / 2 * (t * (t - 2) - 1) + b;
};
var animation = function (currentTime) {
if (startTime === null) startTime = currentTime;
var timeElapsed = currentTime - startTime;
var run = ease(timeElapsed, startPosition, targetPosition, duration);
window.scrollTo(0, run);
if (timeElapsed < duration) requestAnimationFrame(animation);
};
requestAnimationFrame(animation);
};
var scrollTo = function () {
var headerNav = document.querySelector('.navigation');
//var links = document.querySelectorAll('.js-scroll'); //добавляем классы к линкам
var links = document.querySelectorAll('.nav-link'); //добавляем классы к линкам
links.forEach(each => {
each.addEventListener('click', function () {
var currentTarget = this.getAttribute('href');
smoothScroll(currentTarget, 1000);
//выход из мобильного меню
headerNav.classList.remove('active');
document.querySelector("#burger").classList.remove('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
});
});
};
scrollTo();
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
/* мобильное меню >>>>>>>>>>>>>>>>>>>>>>*/
var burger = document.querySelector("#burger");
var navigation = document.querySelector(".navigation");
var contactBtn = document.querySelector(".hire--btn");
burger.addEventListener('click', function () {
body.classList.toggle('overflow')
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
})
contactBtn.addEventListener('click', function () {
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
})
/* мобильное меню />>>>>>>>>>>>>>>>>>>>>>*/
//filter >>>>>>>>>>>>>>>>>>>>>>*/
var filter = document.querySelector("#filter");
var filterBlock = document.querySelector(".portfolio-filter");
filter.addEventListener('click', function () {
filterBlock.classList.toggle('open');
})
//filter />>>>>>>>>>>>>>>>>>>>>>*/
//popup >>>>>>>>>>>>>>>>>>>>>>*/
//Функция для поиска атрибута по вложенным тегам
var closestsElementAttr = function (elem, attr) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* атрибут родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
var attribute = node.getAttribute(attr);
if (attribute) {
return attribute; //атрибут есть — значит его и возвращаем, прекращая функцию
}
/*/ если атрибут пуст, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется атрибут,
* иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего атрибута ни у элемента, ни у его дочерних узлов
return null;
}
//Поиск ближайшего элемента по классу
var closestsElementClass = function (elem, className) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* класс родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
/*/ если текущий элемент содержит тот класс, который мы ему передали,
* при вызове функции, то просто возвращаем этот элемент,
/*/
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
/*/ если класса нет, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется класс,
* который мы передали, иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего класса ни у элемента, ни у его дочерних узлов
return null;
}
//Показ попапа
function showPopup(target) {
target.classList.add('is-active');
}
//Скрытие попапа
function closePopup(target) {
target.classList.remove('is-active');
}
//BODY overflow hidden, чтобы при открытом попапе фон не скролился
function bodyOverflow() {
body.classList.toggle('overflow');
}
//Открытие попапа при клике на бургер меню
body.addEventListener('click', function (e) {
var target = e.target;
//Поиск названия data-popup, который задан у кнопки бургера
//var popupClass = target.getAttribute('data-popup');
var popupClass = closestsElementAttr(target, ' | eturn;
}
e.preventDefault();
var popup = document.querySelector('.' + popupClass);
if (popup) {
showPopup(popup);
bodyOverflow();
}
})
//Закрытие попапа при клике X или на область вне попапа
body.addEventListener('click', function (e) {
var target = e.target;
//Если клик был на кнопку Х или фон вне попапа, то закрываем его
if (e.target.classList.contains('popup__close') || e.target.classList.contains('popup__wrapper') || e.target.classList.contains('popup__inner')) {
//поиск той кноки Х, которая относится к конкретному попапу
var popup = closestsElementClass(target, 'popup');
closePopup(popup);
bodyOverflow();
}
});
//Закрытие попапа при клике на escape (Esc)
body.addEventListener('keydown', function (e) {
if (e.keyCode !== 27)
return;
else {
var popup = document.querySelector('.popup.is-active');
closePopup(popup);
bodyOverflow();
}
});
//popup />>>>>>>>>>>>>>>>>>>>>>*/
//scroll-up >>>>>>>>>>>>>>>>>>>>>>*/
var intervalId = 0; // Needed to cancel the scrolling when we're at the top of the page
var scrollButton = document.querySelector('.to-top'); // Reference to our scroll button
var header = document.querySelector('#header');
var headerHeight = header.clientHeight;
window.addEventListener('scroll', function () {
if (window.pageYOffset > headerHeight)
scrollButton.style.display = "block";
else
scrollButton.style.display = "none";
});
function scrollStep() {
if (window.pageYOffset === 0) {
clearInterval(intervalId);
}
window.scroll(0, window.pageYOffset - 50);
}
function scrollToTop() {
//speed
intervalId = setInterval(scrollStep, 10);
}
scrollButton.addEventListener('click', scrollToTop);
//scroll-up />>>>>>>>>>>>>>>>>>>>>>*/
//tooltip >>>>>>>>>>>>>>>>>>>>>>*/
let tooltipElem;
document.onmouseover = function (event) {
let target = event.target;
// если у нас есть подсказка...
let tooltipHtml = target.dataset.tooltip;
if (!tooltipHtml) return;
// ...создадим элемент для подсказки
tooltipElem = document.createElement('div');
tooltipElem.className = 'tooltip';
tooltipElem.innerHTML = tooltipHtml;
document.body.append(tooltipElem);
// спозиционируем его сверху от аннотируемого элемента (top-center)
let coords = target.getBoundingClientRect();
let left = coords.left + (target.offsetWidth - tooltipElem.offsetWidth) / 2;
if (left < 0) left = 0; // не заезжать за левый край окна
let top = coords.top - tooltipElem.offsetHeight - 5;
if (top < 0) { // если подсказка не помещается сверху, то отображать её снизу
top = coords.top + target.offsetHeight + 5;
}
tooltipElem.style.left = left + 'px';
tooltipElem.style.top = top + 'px';
};
document.onmouseout = function (e) {
if (tooltipElem) {
tooltipElem.remove();
tooltipElem = null;
}
};
//tooltip />>>>>>>>>>>>>>>>>>>>>>*/
})()
| data-popup');
//если элемент, на котором кликнули, не имеет аттрибут data-popup, то выходим
if (popupClass === null) {
r | conditional_block |
mamikon.js | (function () {
var body = document.querySelector('body');
//прелоадер >>>>>>>>>>>>>>>>>>>>>>*/
var preloader = document.querySelector('.loader');
//body.classList.add('overflow');
window.onload = function () {
window.setTimeout(function () {
preloader.classList.add('disable');
//document.body.classList.remove('overflow');
preloader.remove();
}, 800);
}
/* Slider >>>>>>>>>>>>>>>>>>>*/
var rightArrow = document.getElementById('right-arrow');
var leftArrow = document.getElementById('left-arrow');
var slides = document.getElementsByClassName('review-item');
var activeSlide = document.querySelector('.review-item.active')
function changeSlideRight() {
//act | on changeSlideLeft() {
//activeSlide.classList.remove('active');
for (var i = slides.length - 1; i >= 0; i--) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i > 0)
slides[--i].classList.add('active');
else
slides[slides.length - 1].classList.add('active');
return;
}
}
}
rightArrow.addEventListener('click', function () {
changeSlideRight()
})
leftArrow.addEventListener('click', function () {
changeSlideLeft()
})
/* Slider />>>>>>>>>>>>>>>>>>>*/
/* carousel >>>>>>>>>>>>>>>>>>>*/
var root = document.documentElement;
var carouselElementsDisplayed = getComputedStyle(root).getPropertyValue("--carousel-elements-displayed");
var carouselContent = document.querySelector("ul.carousel-content");
root.style.setProperty("--carousel-elements", carouselContent.children.length);
for (var i = 0; i < carouselElementsDisplayed; i++) {
carouselContent.appendChild(carouselContent.children[i].cloneNode(true));
}
/* carousel />>>>>>>>>>>>>>>>>>>*/
//load-more >>>>>>>>>>>>>>>>>>>>>>*/
var loadMore = document.querySelector("#load-more");
var hiddenWorks = document.querySelectorAll(".portfolio-hidden");
var catalogBlock = document.querySelector('.portfolio-content');
loadMore.addEventListener('click', loadContent);
function loadContent() {
loadMore.style.display = 'none';
for (var i = 0; i < hiddenWorks.length; i++) {
catalogBlock.appendChild(hiddenWorks[i]);
}
}
//load-more />>>>>>>>>>>>>>>>>>>>>>*/
/* filter >>>>>>>>>>>>>>>>>>>>>>*/
var closestsElementClass = function (elem, className) {
var node = elem;
while (node) {
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
node = node.parentElement;
}
return null;
}
var catalog = document.querySelector('.portfolio-content');
//блок с табами
var catalogNav = document.querySelector('.portfolio-filter');
var catalogItems = document.querySelectorAll('.portfolio-content__item');
//Очистка блока с элементами, чтобы при фильрации добавлялись новые в чиситый блок
function removeChildren(item) {
while (item.firstChild) {
item.removeChild(item.firstChild)
}
}
//обновляем элементы в каталоге | item это блок каталога
function updateChildren(item, children) {
removeChildren(item);
for (var i = 0; i < children.length; i++) {
item.appendChild(children[i]);
}
}
catalogNav.addEventListener('click', function (e) {
var target = e.target;
var item = closestsElementClass(target, 'portfolio-filter__link');
if (item === null || item.classList.contains('is-active')) {
return;
}
loadContent();
e.preventDefault();
//Получаем значение из атрибута data-filter=""
var filterValue = item.getAttribute('data-filter');
var previousActiveBtn = document.querySelector('.portfolio-filter__link.is-active');
previousActiveBtn.classList.remove('is-active');
item.classList.add('is-active');
//Если выбраны ВСЕ, то просто их всех выводим
if (filterValue === 'all') {
updateChildren(catalog, catalogItems);
return;
}
//Отфильтрованные элементы перемещаем в массив
var filteredItems = [];
for (var i = 0; i < catalogItems.length; i++) {
var currentItem = catalogItems[i];
if (currentItem.getAttribute('data-category') === filterValue) {
filteredItems.push(currentItem);
}
}
updateChildren(catalog, filteredItems);
});
/* filter />>>>>>>>>>>>>>>>>>>>>>*/
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
var smoothScroll = function (targetEl, duration) {
var headerElHeight = document.querySelector('#header').clientHeight; // класс хедера
var target = document.querySelector(targetEl);
var targetPosition = target.getBoundingClientRect().top; //- headerElHeight; //вычитаем размер хедера, если он фиксированный
var startPosition = window.pageYOffset;
var startTime = null;
var ease = function (t, b, c, d) {
t /= d / 2;
if (t < 1) return c / 2 * t * t + b;
t--;
return -c / 2 * (t * (t - 2) - 1) + b;
};
var animation = function (currentTime) {
if (startTime === null) startTime = currentTime;
var timeElapsed = currentTime - startTime;
var run = ease(timeElapsed, startPosition, targetPosition, duration);
window.scrollTo(0, run);
if (timeElapsed < duration) requestAnimationFrame(animation);
};
requestAnimationFrame(animation);
};
var scrollTo = function () {
var headerNav = document.querySelector('.navigation');
//var links = document.querySelectorAll('.js-scroll'); //добавляем классы к линкам
var links = document.querySelectorAll('.nav-link'); //добавляем классы к линкам
links.forEach(each => {
each.addEventListener('click', function () {
var currentTarget = this.getAttribute('href');
smoothScroll(currentTarget, 1000);
//выход из мобильного меню
headerNav.classList.remove('active');
document.querySelector("#burger").classList.remove('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
});
});
};
scrollTo();
/* переход по якорям />>>>>>>>>>>>>>>>>>>>>>*/
/* мобильное меню >>>>>>>>>>>>>>>>>>>>>>*/
var burger = document.querySelector("#burger");
var navigation = document.querySelector(".navigation");
var contactBtn = document.querySelector(".hire--btn");
burger.addEventListener('click', function () {
body.classList.toggle('overflow')
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
})
contactBtn.addEventListener('click', function () {
navigation.classList.toggle('active');
burger.classList.toggle('hamburger_active');
//body.classList.toggle('overflow')
if (body.classList.contains('overflow'))
body.classList.remove('overflow')
})
/* мобильное меню />>>>>>>>>>>>>>>>>>>>>>*/
//filter >>>>>>>>>>>>>>>>>>>>>>*/
var filter = document.querySelector("#filter");
var filterBlock = document.querySelector(".portfolio-filter");
filter.addEventListener('click', function () {
filterBlock.classList.toggle('open');
})
//filter />>>>>>>>>>>>>>>>>>>>>>*/
//popup >>>>>>>>>>>>>>>>>>>>>>*/
//Функция для поиска атрибута по вложенным тегам
var closestsElementAttr = function (elem, attr) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* атрибут родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
var attribute = node.getAttribute(attr);
if (attribute) {
return attribute; //атрибут есть — значит его и возвращаем, прекращая функцию
}
/*/ если атрибут пуст, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется атрибут,
* иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего атрибута ни у элемента, ни у его дочерних узлов
return null;
}
//Поиск ближайшего элемента по классу
var closestsElementClass = function (elem, className) {
var node = elem;
/*/ если клик по дочернему элементу, то возвращаем
* класс родителя, перескакивая вверх через ноду по циклу
/*/
while (node) {
/*/ если текущий элемент содержит тот класс, который мы ему передали,
* при вызове функции, то просто возвращаем этот элемент,
/*/
if (node.classList.contains(className)) {
return node; //класс есть — значит его и возвращаем, прекращая функцию
}
/*/ если класса нет, то вместо текущего елемента берется его родительский
* и так по циклу до тех пор, пока у конечного родителя не найдется класс,
* который мы передали, иначе return null
/*/
node = node.parentElement;
}
//возврат null если нет нашего класса ни у элемента, ни у его дочерних узлов
return null;
}
//Показ попапа
function showPopup(target) {
target.classList.add('is-active');
}
//Скрытие попапа
function closePopup(target) {
target.classList.remove('is-active');
}
//BODY overflow hidden, чтобы при открытом попапе фон не скролился
function bodyOverflow() {
body.classList.toggle('overflow');
}
//Открытие попапа при клике на бургер меню
body.addEventListener('click', function (e) {
var target = e.target;
//Поиск названия data-popup, который задан у кнопки бургера
//var popupClass = target.getAttribute('data-popup');
var popupClass = closestsElementAttr(target, 'data-popup');
//если элемент, на котором кликнули, не имеет аттрибут data-popup, то выходим
if (popupClass === null) {
return;
}
e.preventDefault();
var popup = document.querySelector('.' + popupClass);
if (popup) {
showPopup(popup);
bodyOverflow();
}
})
//Закрытие попапа при клике X или на область вне попапа
body.addEventListener('click', function (e) {
var target = e.target;
//Если клик был на кнопку Х или фон вне попапа, то закрываем его
if (e.target.classList.contains('popup__close') || e.target.classList.contains('popup__wrapper') || e.target.classList.contains('popup__inner')) {
//поиск той кноки Х, которая относится к конкретному попапу
var popup = closestsElementClass(target, 'popup');
closePopup(popup);
bodyOverflow();
}
});
//Закрытие попапа при клике на escape (Esc)
body.addEventListener('keydown', function (e) {
if (e.keyCode !== 27)
return;
else {
var popup = document.querySelector('.popup.is-active');
closePopup(popup);
bodyOverflow();
}
});
//popup />>>>>>>>>>>>>>>>>>>>>>*/
//scroll-up >>>>>>>>>>>>>>>>>>>>>>*/
var intervalId = 0; // Needed to cancel the scrolling when we're at the top of the page
var scrollButton = document.querySelector('.to-top'); // Reference to our scroll button
var header = document.querySelector('#header');
var headerHeight = header.clientHeight;
window.addEventListener('scroll', function () {
if (window.pageYOffset > headerHeight)
scrollButton.style.display = "block";
else
scrollButton.style.display = "none";
});
function scrollStep() {
if (window.pageYOffset === 0) {
clearInterval(intervalId);
}
window.scroll(0, window.pageYOffset - 50);
}
function scrollToTop() {
//speed
intervalId = setInterval(scrollStep, 10);
}
scrollButton.addEventListener('click', scrollToTop);
//scroll-up />>>>>>>>>>>>>>>>>>>>>>*/
//tooltip >>>>>>>>>>>>>>>>>>>>>>*/
let tooltipElem;
document.onmouseover = function (event) {
let target = event.target;
// если у нас есть подсказка...
let tooltipHtml = target.dataset.tooltip;
if (!tooltipHtml) return;
// ...создадим элемент для подсказки
tooltipElem = document.createElement('div');
tooltipElem.className = 'tooltip';
tooltipElem.innerHTML = tooltipHtml;
document.body.append(tooltipElem);
// спозиционируем его сверху от аннотируемого элемента (top-center)
let coords = target.getBoundingClientRect();
let left = coords.left + (target.offsetWidth - tooltipElem.offsetWidth) / 2;
if (left < 0) left = 0; // не заезжать за левый край окна
let top = coords.top - tooltipElem.offsetHeight - 5;
if (top < 0) { // если подсказка не помещается сверху, то отображать её снизу
top = coords.top + target.offsetHeight + 5;
}
tooltipElem.style.left = left + 'px';
tooltipElem.style.top = top + 'px';
};
document.onmouseout = function (e) {
if (tooltipElem) {
tooltipElem.remove();
tooltipElem = null;
}
};
//tooltip />>>>>>>>>>>>>>>>>>>>>>*/
})()
| iveSlide.classList.remove('active');
for (var i = 0; i < slides.length; i++) {
if (slides[i].classList.contains('active')) {
slides[i].classList.remove('active');
if (i < slides.length - 1)
slides[++i].classList.add('active');
else
slides[0].classList.add('active');
return;
}
}
}
functi | identifier_body |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}
public AddKey(t:number, v:number){
this.m_keys.push(t);
this.m_Values.push(v);
}
public Evaluate(t:number):number{
let m_Values = this.m_Values;
let m_keys = this.m_keys;
if (t >= m_keys[m_keys.length-1]) {
return m_Values[m_Values.length-1];
}
else if (t <= m_keys[0]) {
return this.m_Values[0];
}
for (let i = 0; i < m_keys.length - 1; i++)
{
let key = m_keys[i];
let nextKey = m_keys[i + 1];
if (t >= key && t < nextKey)
{
let val = m_Values[i];
let nextVal = m_Values[i + 1];
let value = val + (nextVal - val) * (t - key) / (nextKey - key);
return value;
}
}
return m_Values[m_Values.length - 1];
}
public Length():number {
return this.m_keys.length;
}
public GetKeys(i:number):number {
return this.m_keys[i];
}
public GetValues(i:number):number {
return this.m_Values[i];
}
};
export class GameScene extends BaseGameScene
{
public static Inst:GameScene = null;
private widths:Array<number> = [];
private m_Playerlength:number;
private m_WidthToView:AnimationCurve = new AnimationCurve();
private m_PlayerInfo:SlitherPlayerInfo = new SlitherPlayerInfo();
private m_SlitherContainer:egret.DisplayObjectContainer;
private m_FlyBeanContainer:egret.DisplayObjectContainer;
private m_TileBackground:TiledBackground;
private m_AllSlithers:Array<Slither> = [];
private m_ActivityFlyBeanName:Array<string> = [];
private m_GameOver:boolean;
private m_FirstSynced:boolean;
private m_SortingOrderCounter:number;
private m_ExtraViewSize:number;
private m_LastOrthoSizeTarget:number;
private m_CurrOrthoSizeTarget:number;
private m_CameraViewAnimDuration:number = 1.0;
private m_CameraViewFactor:number = 1.0;
protected m_Time:number;
protected m_Radius:number;
protected allNames:Object = new Object();
protected m_PlayerNameInfo:NameInfo = new NameInfo();
protected m_PlayerID:number;
protected m_EnemyID:number;
private m_BeanView:GameSceneBeanView;
private m_CamaraViewFactor:number;
public constructor()
{
super(SceneType.kSceneGame)
GameScene.Inst = this;
this.m_CamaraViewFactor=1.0;
this.m_CameraViewAnimDuration=1.0;
this.m_ExtraViewSize = 1.0;
this.m_GameOver = false;
this.m_SortingOrderCounter = 0;
this.m_FirstSynced = false;
this.m_PlayerID = 0;
this.m_LastOrthoSizeTarget = 3.2;
this.m_CurrOrthoSizeTarget = 3.2;
this.m_Time = 0.0;
this.m_BeanView = null;
this.m_TileBackground = null;
this.m_WidthToView.AddKey(0.0, 3.675);
this.m_WidthToView.AddKey(0.4, 3.675);
this.m_WidthToView.AddKey(0.5, 4.1);
this.m_WidthToView.AddKey(0.65, 4.633);
this.m_WidthToView.AddKey(0.75, 4.841);
this.m_WidthToView.AddKey(0.8, 4.91);
this.m_WidthToView.AddKey(1.0, 5.25);
this.m_WidthToView.AddKey(1.5, 6.0);
this.m_WidthToView.AddKey(1.971, 6.471);
this.m_WidthToView.AddKey(2.654, 2.801);
this.m_WidthToView.AddKey(3.2, 6.868);
let gameLayer = this;
this.m_SlitherContainer = new egret.DisplayObjectContainer();
this.m_FlyBeanContainer = new egret.DisplayObjectContainer();
this.m_TileBackground = new TiledBackground(this);
this.m_BeanView = new GameSceneBeanView(this);
gameLayer.addChild(this.m_TileBackground);
gameLayer.addChild(this.m_BeanView);
gameLayer.addChild(this.m_FlyBeanContainer);
gameLayer.addChild(this.m_SlitherContainer);
this.m_Radius = MainEnterGame.GetInstance().SceneInitialize.sceneRadius;
let net = GameNetManager.GetInstance();
net.AddEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.AddEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.AddEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.AddEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.AddEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
//net.AddEventListener(CmdIDs.kRpcKiller, this.OnRpcKiller, this);
//net.AddEventListener(CmdIDs.kRpcKilled, this.OnRpcKilled, this);
}
public InvokeGameOver() { this.m_GameOver = true; }
public IsGameOver():boolean { return this.m_GameOver; }
public GetPlayerInfo():SlitherPlayerInfo { return this.m_PlayerInfo; }
public GetPlayerScore():number {
let score = this.m_PlayerInfo.score;
if (score < 0){
score = 0;
}
return score;
}
public GetPlayerLength():number { return this.m_Playerlength; }
public GetSlithers():Array<Slither> { return this.m_AllSlithers; }
public GetEnemyID():number { return this.m_EnemyID; }
public GetPlayerID():number { return this.m_PlayerID; }
public GetRadius():number { return this.m_Radius; }
public GetPlayerNameInfo():NameInfo { return this.m_PlayerNameInfo; }
public dispose()
{
GameScene.Inst = null;
this.StopTweenCamera();
let net = GameNetManager.GetInstance();
net.RemoveEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.RemoveEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.RemoveEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
this.DestroyAllSlithers();
let gameLayer = this;
gameLayer.removeChild(this.m_TileBackground);
gameLayer.removeChild(this.m_BeanView);
gameLayer.removeChild(this.m_FlyBeanContainer);
gameLayer.removeChild(this.m_SlitherContainer);
this.allNames = {};
this.m_TileBackground = null;
this.m_BeanView = null;
this.m_FlyBeanContainer = null;
this.m_SlitherContainer = null;
}
public StopTweenCamera()
{
}
public LateUpdate(deltaTime:number)
{
/*let UIWidth = SceneManager.GetInstance().GetUIViewWidth();
let UIHeight = SceneManager.GetInstance().GetUIViewHeight();
Camera3D *gameCamera = SceneManager.GetInstance().GetGameCamera();
if (PlayerController.Ins && !IsGameOver())
{
Vector2D headPos = PlayerController.Ins.GetSlitherBody().GetHeadPos();
gameCamera.SetPosition(Vector3D(headPos.x, headPos.y, 0));
v:numberiewHalfHeight = this.m_WidthToView.Evaluate(PlayerController.Ins.GetSlitherBody().GetWidth());
viewHalfHeight *= this.m_ExtraViewSize;
if (UIWidth > UIHeight) {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight);
} else {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight / (UIWidth / UIHeight));
}
}
// all slither update
for (auto slither : this.m_AllSlithers)
{
slither.LateUpdate();
}*/
}
public SetOrthoSize(size)
{
}
public ContainesSlitherID(data:Array<SlitherHeadInfo>, id:number):boolean
{
for (let i = 0; i < data.length; ++i)
{
if (data[i].id == id)
{
return true;
}
}
return false;
}
public OnReSpawn(msg:RpcReSpawn)
{
this.m_PlayerID = msg.playerID;
this.m_PlayerNameInfo = msg.playerNameInfo;
this.AddNameInfo(this.m_PlayerNameInfo);
this.m_FirstSynced = false;
this.DestroyAllSlithers();
//SceneManager.GetInstance().GetGameCamera().SetPosition(Vector3D(msg.initialPos.x, msg.initialPos.y, 0));
//DispatchEvent(InGameEvent.kInGamePlayerRespawn);
}
public IsNpc(id:number):boolean
{
let it = this.allNames[id];
if (it) {
return it.npc;
}
return false;
}
public FindSlither(name:string):Slither;
public FindSlither(name:number):Slither;
public FindSlither(name:any):Slither
{
let attr = (typeof name == "number")?"GetID":"GetName";
let size = this.m_AllSlithers.length;
for (let i = 0; i < size; ++i) {
let slither = this.m_AllSlithers[i];
if (slither[attr]() == name) {
return slither;
}
}
return null;
}
public AddNameInfo(name:NameInfo)
{
this.allNames[name.id] = name;
}
public SendSlitherCmd(targetDirection:Vector2D, accelarating:boolean)
{
}
public SetSlitherNameInfo(slither:Slither, id:number)
{
let info = this.allNames[id];
if (!info) {
return;
}
slither.SetName(info.name);
slither.GetBody().SetSkinID(info.skinID);
slither.GetBody().SetDecorationID(info.decorationID);
slither.GetBody().SetNameInfo(info);
slither.SetArea(info.publicInfo.area);
}
public OnSlitherBirthDeathSync(msg:RpcSlitherBirthDeathSync)
{
let foundPlayer = false;
let count = msg.slithers.length;
for (let i = 0; i < count; i++)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
let isPlayer = info.id == this.m_PlayerID;
if (isPlayer) {
foundPlayer = true;
}
if (info.type == SlitherBirthDeath.EnterView)
{
//进视野
if (slither == null)
{
if (isPlayer)
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherPlayerMP);
slitherBody.SetAsMainPlayer();
slither = new Slither(slitherBody);
slither.SetController(new PlayerController(slitherBody, slither));
}
else
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherOtherMP);
slither = new Slither(slitherBody);
}
this.SetSlitherNameInfo(slither, info.id);
this.m_AllSlithers.push(slither);
this.m_SlitherContainer.addChild(slither.GetBody());
}
slither.Sync(info.id);
}
else if (info.type == SlitherBirthDeath.ExitView)
{
//出视野
if (slither != null)
{
for (let m = 0; m < this.m_AllSlithers.length; ++m) {
if (this.m_AllSlithers[m] == slither) {
this.m_AllSlithers.splice(m, 1);
break;
}
}
this.m_BeanView.OnDeleteSlither(slither);
if (slither.GetBody().GetVisible()) {
slither.GetBody().Die();
egret.setTimeout((slither)=>{
slither.dispose();
}, this, slither.GetBody().DieDestroyDelay * 1000 + 100, slither);
}
else
{
slither.dispose();
}
}
else
{
console.log("Slither exit game but not found slither entity.\n");
}
}
}
// 如果第一次同步没有玩家信息，则判定死亡
if (this.m_PlayerID != 0 && !this.m_FirstSynced) {
this.m_FirstSynced = true;
}
}
public OnSlitherHeadSync(msg:RpcSlitherHeadSync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
if (this.m_PlayerID == info.id) {//记录成绩
this.m_Playerlength = info.length;
}
slither.SyncInfo(info);
}
}
}
public OnPlayerInfoSync(msg:RpcPlayerInfoSync)
{
this.m_PlayerInfo = msg.playerInfo;
if (PlayerController.Ins) {
PlayerController.Ins.GetSlither().SyncPlayerInfo(this.m_PlayerInfo);
}
}
public OnSlitherBodySync(msg:RpcSlitherBodySync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
slither.SyncPoints(info.points);
}
}
}
public DestroyAllSlithers()
{
let list = this.m_AllSlithers;
let size = list.length;
for (let i = 0; i < size; ++i) {
list[i].dispose();
delete list[i];
}
this.m_AllSlithers.length = 0;
//this.m_BodyDataMgr.DestroyAllSlithers();
}
public DoGameOver()
{
this.m_GameOver = true;
//SoundManager.GetInstance().StopBackgroundMusic();
for (let i = 0; i < this.m_AllSlithers.length; i++) {
let slither = this.m_AllSlithers[i];
if (slither) {
let speed = slither.GetBody().GetSpeed();
speed.Normalize();
speed.x *= 0.001;
speed.y *= 0.001;
slither.m_Body.SetSpeed(speed);
}
}
// 隐藏游戏主界面
//SceneManager.GetInstance().HideApp(AppModuleType.kAppInGameMainUI);
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameTimeOver,true);
}
public Update(deltaTime:number)
{
if (this.m_GameOver) {
return;
}
this.m_Time += deltaTime;
for (let i = 0; i < this.m_AllSlithers.length; ++i) {
this.m_AllSlithers[i].Update(deltaTime);
}
this.m_BeanView.Up | }
public GetTimeLeft():number
{
return 0;
}
public GetNameInfo(id:number):NameInfo
{
return this.allNames[id];
}
public Enter()
{
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameMainUI, false, false, false);
//SoundManager.GetInstance().PlayBackgroundMusic("sound/music/GameScene");
}
public BackToLobby()
{
//SceneManager.GetInstance().HideAll();
//SoundManager.GetInstance().StopBackgroundMusic();
//EnterMainGame.Ins().BackToLobby();
}
public Leave()
{
GameScene.Inst = null;
}
}
} | date(deltaTime);
this.LateUpdate(deltaTime);
| conditional_block |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}
public AddKey(t:number, v:number){
this.m_keys.push(t);
this.m_Values.push(v);
}
public Evaluate(t:number):number{
let m_Values = this.m_Values;
let m_keys = this.m_keys;
if (t >= m_keys[m_keys.length-1]) {
return m_Values[m_Values.length-1];
}
else if (t <= m_keys[0]) {
return this.m_Values[0];
}
for (let i = 0; i < m_keys.length - 1; i++)
{
let key = m_keys[i];
let nextKey = m_keys[i + 1];
if (t >= key && t < nextKey)
{
let val = m_Values[i];
let nextVal = m_Values[i + 1];
let value = val + (nextVal - val) * (t - key) / (nextKey - key);
return value;
}
}
return m_Values[m_Values.length - 1];
}
public Length():number {
return this.m_keys.length;
}
public GetKeys(i:number):number {
return this.m_keys[i];
}
public GetValues(i:number):number {
return this.m_Values[i];
}
};
export class GameScene extends BaseGameScene
{
public static Inst:GameScene = null;
private widths:Array<number> = [];
private m_Playerlength:number;
private m_WidthToView:AnimationCurve = new AnimationCurve();
private m_PlayerInfo:SlitherPlayerInfo = new SlitherPlayerInfo();
private m_SlitherContainer:egret.DisplayObjectContainer;
private m_FlyBeanContainer:egret.DisplayObjectContainer;
private m_TileBackground:TiledBackground;
private m_AllSlithers:Array<Slither> = [];
private m_ActivityFlyBeanName:Array<string> = [];
private m_GameOver:boolean;
private m_FirstSynced:boolean;
private m_SortingOrderCounter:number;
private m_ExtraViewSize:number;
private m_LastOrthoSizeTarget:number;
private m_CurrOrthoSizeTarget:number;
private m_CameraViewAnimDuration:number = 1.0;
private m_CameraViewFactor:number = 1.0;
protected m_Time:number;
protected m_Radius:number;
protected allNames:Object = new Object();
protected m_PlayerNameInfo:NameInfo = new NameInfo();
protected m_PlayerID:number;
protected m_EnemyID:number;
private m_BeanView:GameSceneBeanView;
private m_CamaraViewFactor:number;
public constructor()
{
super(SceneType.kSceneGame)
GameScene.Inst = this;
this.m_CamaraViewFactor=1.0;
this.m_CameraViewAnimDuration=1.0;
this.m_ExtraViewSize = 1.0;
this.m_GameOver = false;
this.m_SortingOrderCounter = 0;
this.m_FirstSynced = false;
this.m_PlayerID = 0;
this.m_LastOrthoSizeTarget = 3.2;
this.m_CurrOrthoSizeTarget = 3.2;
this.m_Time = 0.0;
this.m_BeanView = null;
this.m_TileBackground = null;
this.m_WidthToView.AddKey(0.0, 3.675);
this.m_WidthToView.AddKey(0.4, 3.675);
this.m_WidthToView.AddKey(0.5, 4.1);
this.m_WidthToView.AddKey(0.65, 4.633);
this.m_WidthToView.AddKey(0.75, 4.841);
this.m_WidthToView.AddKey(0.8, 4.91);
this.m_WidthToView.AddKey(1.0, 5.25);
this.m_WidthToView.AddKey(1.5, 6.0);
this.m_WidthToView.AddKey(1.971, 6.471);
this.m_WidthToView.AddKey(2.654, 2.801);
this.m_WidthToView.AddKey(3.2, 6.868);
let gameLayer = this;
this.m_SlitherContainer = new egret.DisplayObjectContainer();
this.m_FlyBeanContainer = new egret.DisplayObjectContainer();
this.m_TileBackground = new TiledBackground(this);
this.m_BeanView = new GameSceneBeanView(this);
gameLayer.addChild(this.m_TileBackground);
gameLayer.addChild(this.m_BeanView);
gameLayer.addChild(this.m_FlyBeanContainer);
gameLayer.addChild(this.m_SlitherContainer);
this.m_Radius = MainEnterGame.GetInstance().SceneInitialize.sceneRadius;
let net = GameNetManager.GetInstance();
net.AddEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.AddEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.AddEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.AddEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.AddEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
//net.AddEventListener(CmdIDs.kRpcKiller, this.OnRpcKiller, this);
//net.AddEventListener(CmdIDs.kRpcKilled, this.OnRpcKilled, this);
}
public InvokeGameOver() { this.m_GameOver = true; }
public IsGameOver():boolean { return this.m_GameOver; }
public GetPlayerInfo():SlitherPlayerInfo { return this.m_PlayerInfo; }
public GetPlayerScore():number {
let score = this.m_PlayerInfo.score;
if (score < 0){
score = 0;
}
return score;
}
public GetPlayerLength():number { return this.m_Playerlength; }
public GetSlithers():Array<Slither> { return this.m_AllSlithers; }
public GetEnemyID():number { return this.m_EnemyID; }
public GetPlayerID():number { return this.m_PlayerID; }
public GetRadius():number { return this.m_Radius; }
public GetPlayerNameInfo():NameInfo { return this.m_PlayerNameInfo; }
public dispose()
{
GameScene.Inst = null;
this.StopTweenCamera();
let net = GameNetManager.GetInstance();
net.RemoveEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.RemoveEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.RemoveEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
this.DestroyAllSlithers();
let gameLayer = this;
gameLayer.removeChild(this.m_TileBackground);
gameLayer.removeChild(this.m_BeanView);
gameLayer.removeChild(this.m_FlyBeanContainer);
gameLayer.removeChild(this.m_SlitherContainer);
this.allNames = {};
this.m_TileBackground = null;
this.m_BeanView = null;
this.m_FlyBeanContainer = null;
this.m_SlitherContainer = null;
}
public StopTweenCamera()
{
}
public LateUpdate(deltaTime:number)
{
/*let UIWidth = SceneManager.GetInstance().GetUIViewWidth();
let UIHeight = SceneManager.GetInstance().GetUIViewHeight();
Camera3D *gameCamera = SceneManager.GetInstance().GetGameCamera();
if (PlayerController.Ins && !IsGameOver())
{
Vector2D headPos = PlayerController.Ins.GetSlitherBody().GetHeadPos();
gameCamera.SetPosition(Vector3D(headPos.x, headPos.y, 0));
v:numberiewHalfHeight = this.m_WidthToView.Evaluate(PlayerController.Ins.GetSlitherBody().GetWidth());
viewHalfHeight *= this.m_ExtraViewSize;
if (UIWidth > UIHeight) {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight);
} else {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight / (UIWidth / UIHeight));
}
}
// all slither update
for (auto slither : this.m_AllSlithers)
{
slither.LateUpdate();
}*/
}
public SetOrthoSize(size)
{
}
public ContainesSlitherID(data:Array<SlitherHeadInfo>, id:number):boolean
{
for (let i = 0; i < data.length; ++i)
{
if (data[i].id == id)
{
return true;
}
}
return false;
}
public OnReSpawn(msg:RpcReSpawn)
{
this.m_PlayerID = msg.playerID;
this.m_PlayerNameInfo = msg.playerNameInfo;
this.AddNameInfo(this.m_PlayerNameInfo);
this.m_FirstSynced = false;
this.DestroyAllSlithers();
//SceneManager.GetInstance().GetGameCamera().SetPosition(Vector3D(msg.initialPos.x, msg.initialPos.y, 0));
//DispatchEvent(InGameEvent.kInGamePlayerRespawn);
}
public IsNpc(id:number):boolean
{
let it = this.allNames[id];
if (it) {
return it.npc;
}
return false;
}
public FindSlither(name:string):Slither;
public FindSlither(name:number):Slither;
public FindSlither(name:any):Slither
{
| public AddNameInfo(name:NameInfo)
{
this.allNames[name.id] = name;
}
public SendSlitherCmd(targetDirection:Vector2D, accelarating:boolean)
{
}
public SetSlitherNameInfo(slither:Slither, id:number)
{
let info = this.allNames[id];
if (!info) {
return;
}
slither.SetName(info.name);
slither.GetBody().SetSkinID(info.skinID);
slither.GetBody().SetDecorationID(info.decorationID);
slither.GetBody().SetNameInfo(info);
slither.SetArea(info.publicInfo.area);
}
public OnSlitherBirthDeathSync(msg:RpcSlitherBirthDeathSync)
{
let foundPlayer = false;
let count = msg.slithers.length;
for (let i = 0; i < count; i++)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
let isPlayer = info.id == this.m_PlayerID;
if (isPlayer) {
foundPlayer = true;
}
if (info.type == SlitherBirthDeath.EnterView)
{
//进视野
if (slither == null)
{
if (isPlayer)
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherPlayerMP);
slitherBody.SetAsMainPlayer();
slither = new Slither(slitherBody);
slither.SetController(new PlayerController(slitherBody, slither));
}
else
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherOtherMP);
slither = new Slither(slitherBody);
}
this.SetSlitherNameInfo(slither, info.id);
this.m_AllSlithers.push(slither);
this.m_SlitherContainer.addChild(slither.GetBody());
}
slither.Sync(info.id);
}
else if (info.type == SlitherBirthDeath.ExitView)
{
//出视野
if (slither != null)
{
for (let m = 0; m < this.m_AllSlithers.length; ++m) {
if (this.m_AllSlithers[m] == slither) {
this.m_AllSlithers.splice(m, 1);
break;
}
}
this.m_BeanView.OnDeleteSlither(slither);
if (slither.GetBody().GetVisible()) {
slither.GetBody().Die();
egret.setTimeout((slither)=>{
slither.dispose();
}, this, slither.GetBody().DieDestroyDelay * 1000 + 100, slither);
}
else
{
slither.dispose();
}
}
else
{
console.log("Slither exit game but not found slither entity.\n");
}
}
}
// 如果第一次同步没有玩家信息，则判定死亡
if (this.m_PlayerID != 0 && !this.m_FirstSynced) {
this.m_FirstSynced = true;
}
}
public OnSlitherHeadSync(msg:RpcSlitherHeadSync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
if (this.m_PlayerID == info.id) {//记录成绩
this.m_Playerlength = info.length;
}
slither.SyncInfo(info);
}
}
}
public OnPlayerInfoSync(msg:RpcPlayerInfoSync)
{
this.m_PlayerInfo = msg.playerInfo;
if (PlayerController.Ins) {
PlayerController.Ins.GetSlither().SyncPlayerInfo(this.m_PlayerInfo);
}
}
public OnSlitherBodySync(msg:RpcSlitherBodySync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
slither.SyncPoints(info.points);
}
}
}
public DestroyAllSlithers()
{
let list = this.m_AllSlithers;
let size = list.length;
for (let i = 0; i < size; ++i) {
list[i].dispose();
delete list[i];
}
this.m_AllSlithers.length = 0;
//this.m_BodyDataMgr.DestroyAllSlithers();
}
public DoGameOver()
{
this.m_GameOver = true;
//SoundManager.GetInstance().StopBackgroundMusic();
for (let i = 0; i < this.m_AllSlithers.length; i++) {
let slither = this.m_AllSlithers[i];
if (slither) {
let speed = slither.GetBody().GetSpeed();
speed.Normalize();
speed.x *= 0.001;
speed.y *= 0.001;
slither.m_Body.SetSpeed(speed);
}
}
// 隐藏游戏主界面
//SceneManager.GetInstance().HideApp(AppModuleType.kAppInGameMainUI);
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameTimeOver,true);
}
public Update(deltaTime:number)
{
if (this.m_GameOver) {
return;
}
this.m_Time += deltaTime;
for (let i = 0; i < this.m_AllSlithers.length; ++i) {
this.m_AllSlithers[i].Update(deltaTime);
}
this.m_BeanView.Update(deltaTime);
this.LateUpdate(deltaTime);
}
public GetTimeLeft():number
{
return 0;
}
public GetNameInfo(id:number):NameInfo
{
return this.allNames[id];
}
public Enter()
{
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameMainUI, false, false, false);
//SoundManager.GetInstance().PlayBackgroundMusic("sound/music/GameScene");
}
public BackToLobby()
{
//SceneManager.GetInstance().HideAll();
//SoundManager.GetInstance().StopBackgroundMusic();
//EnterMainGame.Ins().BackToLobby();
}
public Leave()
{
GameScene.Inst = null;
}
}
} | let attr = (typeof name == "number")?"GetID":"GetName";
let size = this.m_AllSlithers.length;
for (let i = 0; i < size; ++i) {
let slither = this.m_AllSlithers[i];
if (slither[attr]() == name) {
return slither;
}
}
return null;
}
| identifier_body |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}
public AddKey(t:number, v:number){
this.m_keys.push(t);
this.m_Values.push(v);
}
public Evaluate(t:number):number{
let m_Values = this.m_Values;
let m_keys = this.m_keys;
if (t >= m_keys[m_keys.length-1]) {
return m_Values[m_Values.length-1];
}
else if (t <= m_keys[0]) {
return this.m_Values[0];
}
for (let i = 0; i < m_keys.length - 1; i++)
{
let key = m_keys[i];
let nextKey = m_keys[i + 1];
if (t >= key && t < nextKey)
{
let val = m_Values[i];
let nextVal = m_Values[i + 1];
let value = val + (nextVal - val) * (t - key) / (nextKey - key);
return value;
}
}
return m_Values[m_Values.length - 1];
}
public Length():number {
return this.m_keys.length;
}
public GetKeys(i:number):number {
return this.m_keys[i];
}
public GetValues(i:number):number {
return this.m_Values[i];
}
};
export class GameScene extends BaseGameScene
{
public static Inst:GameScene = null;
private widths:Array<number> = [];
private m_Playerlength:number;
private m_WidthToView:AnimationCurve = new AnimationCurve();
private m_PlayerInfo:SlitherPlayerInfo = new SlitherPlayerInfo();
private m_SlitherContainer:egret.DisplayObjectContainer;
private m_FlyBeanContainer:egret.DisplayObjectContainer;
private m_TileBackground:TiledBackground;
private m_AllSlithers:Array<Slither> = [];
private m_ActivityFlyBeanName:Array<string> = [];
private m_GameOver:boolean;
private m_FirstSynced:boolean;
private m_SortingOrderCounter:number;
private m_ExtraViewSize:number;
private m_LastOrthoSizeTarget:number;
private m_CurrOrthoSizeTarget:number;
private m_CameraViewAnimDuration:number = 1.0;
private m_CameraViewFactor:number = 1.0;
protected m_Time:number;
protected m_Radius:number;
protected allNames:Object = new Object();
protected m_PlayerNameInfo:NameInfo = new NameInfo();
protected m_PlayerID:number;
protected m_EnemyID:number;
private m_BeanView:GameSceneBeanView;
private m_CamaraViewFactor:number;
public constructor()
{
super(SceneType.kSceneGame)
GameScene.Inst = this;
this.m_CamaraViewFactor=1.0;
this.m_CameraViewAnimDuration=1.0;
this.m_ExtraViewSize = 1.0;
this.m_GameOver = false;
this.m_SortingOrderCounter = 0;
this.m_FirstSynced = false;
this.m_PlayerID = 0;
this.m_LastOrthoSizeTarget = 3.2;
this.m_CurrOrthoSizeTarget = 3.2;
this.m_Time = 0.0;
this.m_BeanView = null;
this.m_TileBackground = null;
this.m_WidthToView.AddKey(0.0, 3.675);
this.m_WidthToView.AddKey(0.4, 3.675);
this.m_WidthToView.AddKey(0.5, 4.1);
this.m_WidthToView.AddKey(0.65, 4.633);
this.m_WidthToView.AddKey(0.75, 4.841);
this.m_WidthToView.AddKey(0.8, 4.91);
this.m_WidthToView.AddKey(1.0, 5.25);
this.m_WidthToView.AddKey(1.5, 6.0);
this.m_WidthToView.AddKey(1.971, 6.471);
this.m_WidthToView.AddKey(2.654, 2.801);
this.m_WidthToView.AddKey(3.2, 6.868);
let gameLayer = this;
this.m_SlitherContainer = new egret.DisplayObjectContainer();
this.m_FlyBeanContainer = new egret.DisplayObjectContainer();
this.m_TileBackground = new TiledBackground(this);
this.m_BeanView = new GameSceneBeanView(this);
gameLayer.addChild(this.m_TileBackground);
gameLayer.addChild(this.m_BeanView);
gameLayer.addChild(this.m_FlyBeanContainer);
gameLayer.addChild(this.m_SlitherContainer);
this.m_Radius = MainEnterGame.GetInstance().SceneInitialize.sceneRadius;
let net = GameNetManager.GetInstance();
net.AddEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.AddEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.AddEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.AddEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.AddEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
//net.AddEventListener(CmdIDs.kRpcKiller, this.OnRpcKiller, this);
//net.AddEventListener(CmdIDs.kRpcKilled, this.OnRpcKilled, this);
}
public InvokeGameOver() { this.m_GameOver = true; }
public IsGameOver():boolean { return this.m_GameOver; }
public GetPlayerInfo():SlitherPlayerInfo { return this.m_PlayerInfo; }
public GetPlayerScore():number {
let score = this.m_PlayerInfo.score;
if (score < 0){
score = 0;
}
return score;
}
public GetPlayerLength():number { return this.m_Playerlength; }
public GetSlithers():Array<Slither> { return this.m_AllSlithers; }
public GetEnemyID():number { return this.m_EnemyID; }
public GetPlayerID():number { return this.m_PlayerID; }
public GetRadius():number { return this.m_Radius; }
public GetPlayerNameInfo():NameInfo { return this.m_PlayerNameInfo; }
public dispose()
{
GameScene.Inst = null;
this.StopTweenCamera();
let net = GameNetManager.GetInstance();
net.RemoveEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.RemoveEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.RemoveEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
this.DestroyAllSlithers();
let gameLayer = this;
gameLayer.removeChild(this.m_TileBackground);
gameLayer.removeChild(this.m_BeanView);
gameLayer.removeChild(this.m_FlyBeanContainer);
gameLayer.removeChild(this.m_SlitherContainer);
this.allNames = {};
this.m_TileBackground = null;
this.m_BeanView = null;
this.m_FlyBeanContainer = null;
this.m_SlitherContainer = null;
}
public StopTweenCamera()
{
}
public LateUpdate(deltaTime:number)
{
/*let UIWidth = SceneManager.GetInstance().GetUIViewWidth();
let UIHeight = SceneManager.GetInstance().GetUIViewHeight();
Camera3D *gameCamera = SceneManager.GetInstance().GetGameCamera();
if (PlayerController.Ins && !IsGameOver())
{
Vector2D headPos = PlayerController.Ins.GetSlitherBody().GetHeadPos();
gameCamera.SetPosition(Vector3D(headPos.x, headPos.y, 0));
v:numberiewHalfHeight = this.m_WidthToView.Evaluate(PlayerController.Ins.GetSlitherBody().GetWidth());
viewHalfHeight *= this.m_ExtraViewSize;
if (UIWidth > UIHeight) {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight);
} else {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight / (UIWidth / UIHeight));
}
}
// all slither update
for (auto slither : this.m_AllSlithers)
{
slither.LateUpdate();
}*/
}
public SetOrthoSize(size)
{
}
public ContainesSlitherID(data:Array<SlitherHeadInfo>, id:number):boolean
{
for (let i = 0; i < data.length; ++i)
{
if (data[i].id == id)
{
return true;
}
}
return false;
}
public OnReSpawn(msg:RpcReSpawn)
{
this.m_PlayerID = msg.playerID;
this.m_PlayerNameInfo = msg.playerNameInfo;
this.AddNameInfo(this.m_PlayerNameInfo);
this.m_FirstSynced = false;
this.DestroyAllSlithers();
//SceneManager.GetInstance().GetGameCamera().SetPosition(Vector3D(msg.initialPos.x, msg.initialPos.y, 0));
//DispatchEvent(InGameEvent.kInGamePlayerRespawn);
}
public IsNpc(id:number):boolean
{
let it = this.allNames[id];
if (it) {
return it.npc;
}
return false;
}
public FindSlither(name:string):Slither;
public FindSlither(name:number):Slither;
public FindSlither(name:any):Slither
{
let attr = (typeof name == "number")?"GetID":"GetName";
let size = this.m_AllSlithers.length;
for (let i = 0; i < size; ++i) {
let slither = this.m_AllSlithers[i];
if (slither[attr]() == name) {
return slither;
}
}
return null;
}
public AddNameInfo(name:NameInfo)
{
this.allNames[name.id] = name;
}
public SendSlitherCmd(targetDirection:Vector2D, accelarating:boolean)
{
}
public SetSlitherNameInfo(slither:Slither, id:number)
{
let info = this.allNames[id];
if (!info) {
return;
}
slither.SetName(info.name);
slither.GetBody().SetSkinID(info.skinID);
slither.GetBody().SetDecorationID(info.decorationID);
slither.GetBody().SetNameInfo(info);
slither.SetArea(info.publicInfo.area);
}
public On | sg:RpcSlitherBirthDeathSync)
{
let foundPlayer = false;
let count = msg.slithers.length;
for (let i = 0; i < count; i++)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
let isPlayer = info.id == this.m_PlayerID;
if (isPlayer) {
foundPlayer = true;
}
if (info.type == SlitherBirthDeath.EnterView)
{
//进视野
if (slither == null)
{
if (isPlayer)
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherPlayerMP);
slitherBody.SetAsMainPlayer();
slither = new Slither(slitherBody);
slither.SetController(new PlayerController(slitherBody, slither));
}
else
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherOtherMP);
slither = new Slither(slitherBody);
}
this.SetSlitherNameInfo(slither, info.id);
this.m_AllSlithers.push(slither);
this.m_SlitherContainer.addChild(slither.GetBody());
}
slither.Sync(info.id);
}
else if (info.type == SlitherBirthDeath.ExitView)
{
//出视野
if (slither != null)
{
for (let m = 0; m < this.m_AllSlithers.length; ++m) {
if (this.m_AllSlithers[m] == slither) {
this.m_AllSlithers.splice(m, 1);
break;
}
}
this.m_BeanView.OnDeleteSlither(slither);
if (slither.GetBody().GetVisible()) {
slither.GetBody().Die();
egret.setTimeout((slither)=>{
slither.dispose();
}, this, slither.GetBody().DieDestroyDelay * 1000 + 100, slither);
}
else
{
slither.dispose();
}
}
else
{
console.log("Slither exit game but not found slither entity.\n");
}
}
}
// 如果第一次同步没有玩家信息，则判定死亡
if (this.m_PlayerID != 0 && !this.m_FirstSynced) {
this.m_FirstSynced = true;
}
}
public OnSlitherHeadSync(msg:RpcSlitherHeadSync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
if (this.m_PlayerID == info.id) {//记录成绩
this.m_Playerlength = info.length;
}
slither.SyncInfo(info);
}
}
}
public OnPlayerInfoSync(msg:RpcPlayerInfoSync)
{
this.m_PlayerInfo = msg.playerInfo;
if (PlayerController.Ins) {
PlayerController.Ins.GetSlither().SyncPlayerInfo(this.m_PlayerInfo);
}
}
public OnSlitherBodySync(msg:RpcSlitherBodySync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
slither.SyncPoints(info.points);
}
}
}
public DestroyAllSlithers()
{
let list = this.m_AllSlithers;
let size = list.length;
for (let i = 0; i < size; ++i) {
list[i].dispose();
delete list[i];
}
this.m_AllSlithers.length = 0;
//this.m_BodyDataMgr.DestroyAllSlithers();
}
public DoGameOver()
{
this.m_GameOver = true;
//SoundManager.GetInstance().StopBackgroundMusic();
for (let i = 0; i < this.m_AllSlithers.length; i++) {
let slither = this.m_AllSlithers[i];
if (slither) {
let speed = slither.GetBody().GetSpeed();
speed.Normalize();
speed.x *= 0.001;
speed.y *= 0.001;
slither.m_Body.SetSpeed(speed);
}
}
// 隐藏游戏主界面
//SceneManager.GetInstance().HideApp(AppModuleType.kAppInGameMainUI);
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameTimeOver,true);
}
public Update(deltaTime:number)
{
if (this.m_GameOver) {
return;
}
this.m_Time += deltaTime;
for (let i = 0; i < this.m_AllSlithers.length; ++i) {
this.m_AllSlithers[i].Update(deltaTime);
}
this.m_BeanView.Update(deltaTime);
this.LateUpdate(deltaTime);
}
public GetTimeLeft():number
{
return 0;
}
public GetNameInfo(id:number):NameInfo
{
return this.allNames[id];
}
public Enter()
{
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameMainUI, false, false, false);
//SoundManager.GetInstance().PlayBackgroundMusic("sound/music/GameScene");
}
public BackToLobby()
{
//SceneManager.GetInstance().HideAll();
//SoundManager.GetInstance().StopBackgroundMusic();
//EnterMainGame.Ins().BackToLobby();
}
public Leave()
{
GameScene.Inst = null;
}
}
} | SlitherBirthDeathSync(m | identifier_name |
GameScene.ts | module wqq
{
import Vector2D = snake.Vector2;
export enum InGameEvent
{
kInGamePlayerRespawn = 30000,
kInGamePlayerPlayerDead = 30001,
kInGameEndlessRankPlayer = 30002
};
export class AnimationCurve
{
private m_keys:Array<number> = [];
private m_Values:Array<number> = [];
public constructor(){
}
public AddKey(t:number, v:number){
this.m_keys.push(t);
this.m_Values.push(v);
}
public Evaluate(t:number):number{
let m_Values = this.m_Values;
let m_keys = this.m_keys;
if (t >= m_keys[m_keys.length-1]) {
return m_Values[m_Values.length-1];
}
else if (t <= m_keys[0]) {
return this.m_Values[0];
}
for (let i = 0; i < m_keys.length - 1; i++)
{
let key = m_keys[i];
let nextKey = m_keys[i + 1];
if (t >= key && t < nextKey)
{
let val = m_Values[i];
let nextVal = m_Values[i + 1];
let value = val + (nextVal - val) * (t - key) / (nextKey - key);
return value;
}
}
return m_Values[m_Values.length - 1];
}
public Length():number {
return this.m_keys.length;
}
public GetKeys(i:number):number {
return this.m_keys[i];
}
public GetValues(i:number):number {
return this.m_Values[i];
}
};
export class GameScene extends BaseGameScene
{
public static Inst:GameScene = null;
private widths:Array<number> = [];
private m_Playerlength:number;
private m_WidthToView:AnimationCurve = new AnimationCurve();
private m_PlayerInfo:SlitherPlayerInfo = new SlitherPlayerInfo();
private m_SlitherContainer:egret.DisplayObjectContainer;
private m_FlyBeanContainer:egret.DisplayObjectContainer;
private m_TileBackground:TiledBackground;
private m_AllSlithers:Array<Slither> = [];
private m_ActivityFlyBeanName:Array<string> = [];
private m_GameOver:boolean;
private m_FirstSynced:boolean;
private m_SortingOrderCounter:number;
private m_ExtraViewSize:number;
private m_LastOrthoSizeTarget:number;
private m_CurrOrthoSizeTarget:number;
private m_CameraViewAnimDuration:number = 1.0;
private m_CameraViewFactor:number = 1.0;
protected m_Time:number;
protected m_Radius:number;
protected allNames:Object = new Object();
protected m_PlayerNameInfo:NameInfo = new NameInfo();
protected m_PlayerID:number;
protected m_EnemyID:number;
private m_BeanView:GameSceneBeanView;
private m_CamaraViewFactor:number;
public constructor()
{
super(SceneType.kSceneGame)
GameScene.Inst = this;
this.m_CamaraViewFactor=1.0;
this.m_CameraViewAnimDuration=1.0;
this.m_ExtraViewSize = 1.0;
this.m_GameOver = false;
this.m_SortingOrderCounter = 0;
this.m_FirstSynced = false;
this.m_PlayerID = 0;
this.m_LastOrthoSizeTarget = 3.2;
this.m_CurrOrthoSizeTarget = 3.2;
this.m_Time = 0.0;
this.m_BeanView = null;
this.m_TileBackground = null;
this.m_WidthToView.AddKey(0.0, 3.675);
this.m_WidthToView.AddKey(0.4, 3.675);
this.m_WidthToView.AddKey(0.5, 4.1);
this.m_WidthToView.AddKey(0.65, 4.633);
this.m_WidthToView.AddKey(0.75, 4.841);
this.m_WidthToView.AddKey(0.8, 4.91);
this.m_WidthToView.AddKey(1.0, 5.25);
this.m_WidthToView.AddKey(1.5, 6.0);
this.m_WidthToView.AddKey(1.971, 6.471);
this.m_WidthToView.AddKey(2.654, 2.801);
this.m_WidthToView.AddKey(3.2, 6.868);
let gameLayer = this;
this.m_SlitherContainer = new egret.DisplayObjectContainer();
this.m_FlyBeanContainer = new egret.DisplayObjectContainer();
this.m_TileBackground = new TiledBackground(this);
this.m_BeanView = new GameSceneBeanView(this);
gameLayer.addChild(this.m_TileBackground);
gameLayer.addChild(this.m_BeanView);
gameLayer.addChild(this.m_FlyBeanContainer);
gameLayer.addChild(this.m_SlitherContainer);
this.m_Radius = MainEnterGame.GetInstance().SceneInitialize.sceneRadius;
let net = GameNetManager.GetInstance();
net.AddEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.AddEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.AddEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.AddEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.AddEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this);
//net.AddEventListener(CmdIDs.kRpcKiller, this.OnRpcKiller, this);
//net.AddEventListener(CmdIDs.kRpcKilled, this.OnRpcKilled, this);
}
public InvokeGameOver() { this.m_GameOver = true; }
public IsGameOver():boolean { return this.m_GameOver; }
public GetPlayerInfo():SlitherPlayerInfo { return this.m_PlayerInfo; }
public GetPlayerScore():number {
let score = this.m_PlayerInfo.score;
if (score < 0){
score = 0;
}
return score;
}
public GetPlayerLength():number { return this.m_Playerlength; }
public GetSlithers():Array<Slither> { return this.m_AllSlithers; }
public GetEnemyID():number { return this.m_EnemyID; }
public GetPlayerID():number { return this.m_PlayerID; }
public GetRadius():number { return this.m_Radius; }
public GetPlayerNameInfo():NameInfo { return this.m_PlayerNameInfo; }
public dispose()
{
GameScene.Inst = null;
this.StopTweenCamera();
let net = GameNetManager.GetInstance();
net.RemoveEventListener(CmdIDs.kRpcSlitherBirthDeathSync, this.OnSlitherBirthDeathSync, this);
net.RemoveEventListener(CmdIDs.kRpcPlayerInfoSync, this.OnPlayerInfoSync, this);
net.RemoveEventListener(CmdIDs.kRpcReSpawn, this.OnReSpawn, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherHeadSync, this.OnSlitherHeadSync, this);
net.RemoveEventListener(CmdIDs.kRpcSlitherBodySync, this.OnSlitherBodySync, this); |
this.DestroyAllSlithers();
let gameLayer = this;
gameLayer.removeChild(this.m_TileBackground);
gameLayer.removeChild(this.m_BeanView);
gameLayer.removeChild(this.m_FlyBeanContainer);
gameLayer.removeChild(this.m_SlitherContainer);
this.allNames = {};
this.m_TileBackground = null;
this.m_BeanView = null;
this.m_FlyBeanContainer = null;
this.m_SlitherContainer = null;
}
public StopTweenCamera()
{
}
public LateUpdate(deltaTime:number)
{
/*let UIWidth = SceneManager.GetInstance().GetUIViewWidth();
let UIHeight = SceneManager.GetInstance().GetUIViewHeight();
Camera3D *gameCamera = SceneManager.GetInstance().GetGameCamera();
if (PlayerController.Ins && !IsGameOver())
{
Vector2D headPos = PlayerController.Ins.GetSlitherBody().GetHeadPos();
gameCamera.SetPosition(Vector3D(headPos.x, headPos.y, 0));
v:numberiewHalfHeight = this.m_WidthToView.Evaluate(PlayerController.Ins.GetSlitherBody().GetWidth());
viewHalfHeight *= this.m_ExtraViewSize;
if (UIWidth > UIHeight) {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight);
} else {
SetOrthoSize(this.m_CamaraViewFactor * viewHalfHeight / (UIWidth / UIHeight));
}
}
// all slither update
for (auto slither : this.m_AllSlithers)
{
slither.LateUpdate();
}*/
}
public SetOrthoSize(size)
{
}
public ContainesSlitherID(data:Array<SlitherHeadInfo>, id:number):boolean
{
for (let i = 0; i < data.length; ++i)
{
if (data[i].id == id)
{
return true;
}
}
return false;
}
public OnReSpawn(msg:RpcReSpawn)
{
this.m_PlayerID = msg.playerID;
this.m_PlayerNameInfo = msg.playerNameInfo;
this.AddNameInfo(this.m_PlayerNameInfo);
this.m_FirstSynced = false;
this.DestroyAllSlithers();
//SceneManager.GetInstance().GetGameCamera().SetPosition(Vector3D(msg.initialPos.x, msg.initialPos.y, 0));
//DispatchEvent(InGameEvent.kInGamePlayerRespawn);
}
public IsNpc(id:number):boolean
{
let it = this.allNames[id];
if (it) {
return it.npc;
}
return false;
}
public FindSlither(name:string):Slither;
public FindSlither(name:number):Slither;
public FindSlither(name:any):Slither
{
let attr = (typeof name == "number")?"GetID":"GetName";
let size = this.m_AllSlithers.length;
for (let i = 0; i < size; ++i) {
let slither = this.m_AllSlithers[i];
if (slither[attr]() == name) {
return slither;
}
}
return null;
}
public AddNameInfo(name:NameInfo)
{
this.allNames[name.id] = name;
}
public SendSlitherCmd(targetDirection:Vector2D, accelarating:boolean)
{
}
public SetSlitherNameInfo(slither:Slither, id:number)
{
let info = this.allNames[id];
if (!info) {
return;
}
slither.SetName(info.name);
slither.GetBody().SetSkinID(info.skinID);
slither.GetBody().SetDecorationID(info.decorationID);
slither.GetBody().SetNameInfo(info);
slither.SetArea(info.publicInfo.area);
}
public OnSlitherBirthDeathSync(msg:RpcSlitherBirthDeathSync)
{
let foundPlayer = false;
let count = msg.slithers.length;
for (let i = 0; i < count; i++)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
let isPlayer = info.id == this.m_PlayerID;
if (isPlayer) {
foundPlayer = true;
}
if (info.type == SlitherBirthDeath.EnterView)
{
//进视野
if (slither == null)
{
if (isPlayer)
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherPlayerMP);
slitherBody.SetAsMainPlayer();
slither = new Slither(slitherBody);
slither.SetController(new PlayerController(slitherBody, slither));
}
else
{
let slitherBody = SlitherNodeBody.CreateSlither(SlitherType.kSlitherOtherMP);
slither = new Slither(slitherBody);
}
this.SetSlitherNameInfo(slither, info.id);
this.m_AllSlithers.push(slither);
this.m_SlitherContainer.addChild(slither.GetBody());
}
slither.Sync(info.id);
}
else if (info.type == SlitherBirthDeath.ExitView)
{
//出视野
if (slither != null)
{
for (let m = 0; m < this.m_AllSlithers.length; ++m) {
if (this.m_AllSlithers[m] == slither) {
this.m_AllSlithers.splice(m, 1);
break;
}
}
this.m_BeanView.OnDeleteSlither(slither);
if (slither.GetBody().GetVisible()) {
slither.GetBody().Die();
egret.setTimeout((slither)=>{
slither.dispose();
}, this, slither.GetBody().DieDestroyDelay * 1000 + 100, slither);
}
else
{
slither.dispose();
}
}
else
{
console.log("Slither exit game but not found slither entity.\n");
}
}
}
// 如果第一次同步没有玩家信息，则判定死亡
if (this.m_PlayerID != 0 && !this.m_FirstSynced) {
this.m_FirstSynced = true;
}
}
public OnSlitherHeadSync(msg:RpcSlitherHeadSync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
if (this.m_PlayerID == info.id) {//记录成绩
this.m_Playerlength = info.length;
}
slither.SyncInfo(info);
}
}
}
public OnPlayerInfoSync(msg:RpcPlayerInfoSync)
{
this.m_PlayerInfo = msg.playerInfo;
if (PlayerController.Ins) {
PlayerController.Ins.GetSlither().SyncPlayerInfo(this.m_PlayerInfo);
}
}
public OnSlitherBodySync(msg:RpcSlitherBodySync)
{
for (let i = 0; i < msg.slithers.length; ++i)
{
let info = msg.slithers[i];
let slither = this.FindSlither(info.id);
if (slither != null)
{
slither.SyncPoints(info.points);
}
}
}
public DestroyAllSlithers()
{
let list = this.m_AllSlithers;
let size = list.length;
for (let i = 0; i < size; ++i) {
list[i].dispose();
delete list[i];
}
this.m_AllSlithers.length = 0;
//this.m_BodyDataMgr.DestroyAllSlithers();
}
public DoGameOver()
{
this.m_GameOver = true;
//SoundManager.GetInstance().StopBackgroundMusic();
for (let i = 0; i < this.m_AllSlithers.length; i++) {
let slither = this.m_AllSlithers[i];
if (slither) {
let speed = slither.GetBody().GetSpeed();
speed.Normalize();
speed.x *= 0.001;
speed.y *= 0.001;
slither.m_Body.SetSpeed(speed);
}
}
// 隐藏游戏主界面
//SceneManager.GetInstance().HideApp(AppModuleType.kAppInGameMainUI);
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameTimeOver,true);
}
public Update(deltaTime:number)
{
if (this.m_GameOver) {
return;
}
this.m_Time += deltaTime;
for (let i = 0; i < this.m_AllSlithers.length; ++i) {
this.m_AllSlithers[i].Update(deltaTime);
}
this.m_BeanView.Update(deltaTime);
this.LateUpdate(deltaTime);
}
public GetTimeLeft():number
{
return 0;
}
public GetNameInfo(id:number):NameInfo
{
return this.allNames[id];
}
public Enter()
{
//SceneManager.GetInstance().ShowApp(AppModuleType.kAppInGameMainUI, false, false, false);
//SoundManager.GetInstance().PlayBackgroundMusic("sound/music/GameScene");
}
public BackToLobby()
{
//SceneManager.GetInstance().HideAll();
//SoundManager.GetInstance().StopBackgroundMusic();
//EnterMainGame.Ins().BackToLobby();
}
public Leave()
{
GameScene.Inst = null;
}
}
} | random_line_split | |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associated only with them don't inflate compile times.
//!
//! All of the submodules here correspond to a particular version -- with the current one also
//! included. Each submodule defines a `FileContent` struct that implements the [`FileContent`]
//! trait in this module, so that we can cleanly abstract over the file format without changing the
//! logic in `crate::app`. The `FileContent` from the latest version is re-exported in this module
//! as [`CurrentFileContent`].
//!
//! Each submodule additionally defines a couple items:
//! ```ignore
//! // If this file format has been deprecated, a warning to indicate as such
//! pub const WARNING: Option<Warning> = ...;
//!
//! // Given a file that we know starts with the correct version prefix, parse it
//! //
//! // If any errors are encountered, print them and exit.
//! pub fn parse(file_content: String) -> FileContent { ... }
//! ```
//! Those are used by the `parse` function at the bottom of this file.
use serde::{Deserialize, Serialize};
use std::any::Any;
use std::fmt::{self, Display, Formatter};
use std::fs::read_to_string;
use std::ops::Range;
use std::path::Path;
use std::process::exit;
use std::time::SystemTime;
mod errors;
mod latest;
mod v0_2;
mod v0_3;
mod v0_4;
pub use errors::*;
/// Helper struct for file contents with an attached key
///
/// This is extracted into this module so that it's able to be used by multiple submodules without
/// redefinition.
pub struct Keyed<C> {
key: Option<Vec<u8>>,
unsaved: bool,
content: C,
}
impl<C> Keyed<C> {
/// Creates a new `Keyed` content without the key
fn new(content: C) -> Self {
Keyed {
key: None,
unsaved: false,
content,
}
}
}
/// A particular file format, kept object-safe so that we can switch on it at runtime
///
/// The first couple methods here are for providing the "meta" methods -- the rest merely provide
/// the shared facilities for interaction with contents of the file.
pub trait FileContent {
/// Helper function to convert to the latest version, given the user's password
///
/// It's customary for this method to only convert to the next version internally, and instead
/// rely upon that version's implementation of producing the current file content. This chain
/// terminates with with the implementation for `CurrentFileContent`, which just returns itself.
fn to_current(self: Box<Self>, pwd: String) -> Result<Box<CurrentFileContent>, DecryptError>;
/// Provides the string that the file content should be written as
///
/// This method is provided -- instead of directly writing to the file -- so that no error
/// handling needs to be done within the implementation itself.
fn write(&self) -> String;
/// Sets the key, returning `Err` if it was invalid
fn set_key(&mut self, key: String) -> Result<(), DecryptError>;
/// Returns true if there have been changes made to the file without saving
///
/// Changes should be registered as unsaved until a call to `saved` is made
fn unsaved(&self) -> bool;
/// Registers any unsaved change as now being saved
fn mark_saved(&mut self);
/// Returns whether the entries have been decrypted -- true after `set_key` returns `Ok`
fn decrypted(&self) -> bool;
/// Produces the number of entries in the file
fn num_entries(&self) -> usize;
/// Produces the entry corresponding to the given index
fn entry(&self, idx: usize) -> Box<dyn EntryRef + '_>;
/// Produces a mutable reference to the corresponding entry
fn entry_mut(&mut self, idx: usize) -> Box<dyn EntryMut + '_>;
/// Gives access to the specified range of entries
///
/// The default implementation should suffice, but it *may* be possible for other
/// implementations to improve the performance. In practice, the performance should not matter
/// much.
fn entries_range(&self, range: Range<usize>) -> Vec<Box<dyn EntryRef + '_>> {
range.map(|i| self.entry(i)).collect()
}
/// Returns all of the entires
///
/// The default implementation here should suffice
fn all_entries(&self) -> Vec<Box<dyn EntryRef + '_>> {
let len = self.num_entries();
self.entries_range(0..len)
}
/// Adds an empty entry with the given name and returns its index
fn add_empty_entry(&mut self, name: String) -> usize;
/// Removes the entry at the given index | /// An immutable handle on an entry in the file
pub trait EntryRef {
/// Returns the title of the entry
fn name(&self) -> &str;
/// Returns all the tags associated with the entry
fn tags(&self) -> Vec<&str>;
/// Returns the date + time at which the
fn first_added(&self) -> SystemTime;
/// Returns the date + time the entry was last updated
fn last_update(&self) -> SystemTime;
/// Returns a reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field(&self, idx: usize) -> Box<dyn FieldRef + '_>;
/// Returns the number of fields in the entry
fn num_fields(&self) -> usize;
}
/// A mutable handle on an entry in the file
pub trait EntryMut: EntryRef {
/// Sets the title of the entry
fn set_name(&mut self, name: String);
/// Sets the tags associated with the entry
fn set_tags(&mut self, tags: Vec<String>);
/// Returns a mutable reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field_mut(&mut self, idx: usize) -> Box<dyn FieldMut + '_>;
/// Creates a `FieldBuilder` that will (possibly) later be provided back
fn field_builder(&self) -> Box<dyn FieldBuilder>;
/// Sets the field at the given index, using the result of a previous call to
/// `self.field_builder()`
///
/// The index may be one greater than the current number of fields, in which case the value
/// should be appended.
fn set_field(
&mut self,
idx: usize,
builder: Box<dyn FieldBuilder>,
) -> Result<(), SetFieldError>;
/// Removes the given field
fn remove_field(&mut self, idx: usize);
}
/// An immutable handle on a single field of an entry
pub trait FieldRef {
/// The name of the field
fn name(&self) -> &str;
/// Returns the type of value inside this field
fn value_kind(&self) -> ValueKind;
/// The value of the field
///
/// For TOTP fields, this is expected to perform the necessary calculations and return the
/// current OTP.
fn value(&self) -> Result<String, GetValueError>;
/// Returns the "plaintext" value of the field
///
/// Unlike `value`, this returns the underlying secret for TOTP fields.
fn plaintext_value(&self) -> Result<PlaintextValue, GetValueError>;
}
/// A mutable handle on a single field of an entry
pub trait FieldMut: FieldRef {
/// Swaps the encryption of the field
fn swap_encryption(&mut self) -> Result<(), SwapEncryptionError>;
}
/// The types of values a field might have
#[derive(Debug, Copy, Clone)]
pub enum ValueKind {
Basic,
Protected,
Totp,
}
impl Display for ValueKind {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
ValueKind::Basic => f.write_str("Basic"),
ValueKind::Protected => f.write_str("Protected"),
ValueKind::Totp => f.write_str("TOTP"),
}
}
}
/// Helper type for constructing a field
pub trait FieldBuilder: Any {
/// Helper method to recover the original type
fn as_any_mut(&mut self) -> &mut dyn Any;
/// Converts the builder to build a "manual" field
fn make_manual(&mut self);
/// Converts the builder to build a TOTP field
fn make_totp(&mut self) -> Result<(), UnsupportedFeature>;
/// Sets the name of the field
fn set_name(&mut self, name: String);
/// Sets the value of the field
///
/// ## Panics
///
/// This method panics if there was no previous successful call to the matching `make_*` method
/// for the value (`make_manual` or `make_totp`).
fn set_value(&mut self, value: PlaintextValue);
}
/// The latest version of the file content -- the most recent implementor of [`FileContent`]
pub type CurrentFileContent = Keyed<v0_4::FileContent>;
/// A warning given after opening a file with a particular format version
pub struct Warning {
pub reason: &'static str,
}
/// Parses a `FileContent` from the provided file, exiting the program on failure
pub fn parse(file: &Path) -> (Box<dyn FileContent>, Option<Warning>) {
let content = match read_to_string(file) {
Ok(c) => c,
Err(e) => {
eprintln!("failed to read file {:?}: {}", file.to_string_lossy(), e);
exit(1);
}
};
macro_rules! prefix_match {
($val:expr => { $($str:literal => $arm:expr,)* _ => $else_arm:expr, }) => {{
let v = $val;
$(if v.starts_with($str) {
$arm
} else)* {
$else_arm
}
}};
}
prefix_match!(content.as_str() => {
"---\nversion: v0.2\n" => (Box::new(v0_2::parse(content)), v0_2::WARNING),
"---\nversion: v0.3\n" => (Box::new(v0_3::parse(content)), v0_3::WARNING),
"---\nversion: v0.4\n" => (Box::new(v0_4::parse(content)), v0_4::WARNING),
_ => {
eprintln!("unrecognized file version, should be one of: ['v0.2', 'v0.3', 'v0.4']");
exit(1)
},
})
}
/// Return type for [`CurrentFileContent::to_plaintext`]
///
/// This is used both to convert between `FileContent` versions *and* to within the
/// `emit-plaintext` and `from-plaintext` subcommands.
#[derive(Serialize, Deserialize)]
pub struct PlaintextContent {
last_update: SystemTime,
entries: Vec<PlaintextEntry>,
}
#[derive(Serialize, Deserialize)]
struct PlaintextEntry {
name: String,
tags: Vec<String>,
fields: Vec<PlaintextField>,
first_added: SystemTime,
last_update: SystemTime,
}
#[derive(Serialize, Deserialize)]
struct PlaintextField {
name: String,
value: PlaintextValue,
}
#[derive(Serialize, Deserialize)]
pub enum PlaintextValue {
Manual { value: String, protected: bool },
Totp { secret: String, issuer: String },
}
impl PlaintextContent {
/// Produces a new, empty `PlaintextContent` with the current time as its last update
fn init() -> Self {
PlaintextContent {
last_update: SystemTime::now(),
entries: Vec::new(),
}
}
} | fn remove_entry(&mut self, idx: usize);
}
| random_line_split |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associated only with them don't inflate compile times.
//!
//! All of the submodules here correspond to a particular version -- with the current one also
//! included. Each submodule defines a `FileContent` struct that implements the [`FileContent`]
//! trait in this module, so that we can cleanly abstract over the file format without changing the
//! logic in `crate::app`. The `FileContent` from the latest version is re-exported in this module
//! as [`CurrentFileContent`].
//!
//! Each submodule additionally defines a couple items:
//! ```ignore
//! // If this file format has been deprecated, a warning to indicate as such
//! pub const WARNING: Option<Warning> = ...;
//!
//! // Given a file that we know starts with the correct version prefix, parse it
//! //
//! // If any errors are encountered, print them and exit.
//! pub fn parse(file_content: String) -> FileContent { ... }
//! ```
//! Those are used by the `parse` function at the bottom of this file.
use serde::{Deserialize, Serialize};
use std::any::Any;
use std::fmt::{self, Display, Formatter};
use std::fs::read_to_string;
use std::ops::Range;
use std::path::Path;
use std::process::exit;
use std::time::SystemTime;
mod errors;
mod latest;
mod v0_2;
mod v0_3;
mod v0_4;
pub use errors::*;
/// Helper struct for file contents with an attached key
///
/// This is extracted into this module so that it's able to be used by multiple submodules without
/// redefinition.
pub struct Keyed<C> {
key: Option<Vec<u8>>,
unsaved: bool,
content: C,
}
impl<C> Keyed<C> {
/// Creates a new `Keyed` content without the key
fn new(content: C) -> Self {
Keyed {
key: None,
unsaved: false,
content,
}
}
}
/// A particular file format, kept object-safe so that we can switch on it at runtime
///
/// The first couple methods here are for providing the "meta" methods -- the rest merely provide
/// the shared facilities for interaction with contents of the file.
pub trait FileContent {
/// Helper function to convert to the latest version, given the user's password
///
/// It's customary for this method to only convert to the next version internally, and instead
/// rely upon that version's implementation of producing the current file content. This chain
/// terminates with with the implementation for `CurrentFileContent`, which just returns itself.
fn to_current(self: Box<Self>, pwd: String) -> Result<Box<CurrentFileContent>, DecryptError>;
/// Provides the string that the file content should be written as
///
/// This method is provided -- instead of directly writing to the file -- so that no error
/// handling needs to be done within the implementation itself.
fn write(&self) -> String;
/// Sets the key, returning `Err` if it was invalid
fn set_key(&mut self, key: String) -> Result<(), DecryptError>;
/// Returns true if there have been changes made to the file without saving
///
/// Changes should be registered as unsaved until a call to `saved` is made
fn unsaved(&self) -> bool;
/// Registers any unsaved change as now being saved
fn mark_saved(&mut self);
/// Returns whether the entries have been decrypted -- true after `set_key` returns `Ok`
fn decrypted(&self) -> bool;
/// Produces the number of entries in the file
fn num_entries(&self) -> usize;
/// Produces the entry corresponding to the given index
fn entry(&self, idx: usize) -> Box<dyn EntryRef + '_>;
/// Produces a mutable reference to the corresponding entry
fn entry_mut(&mut self, idx: usize) -> Box<dyn EntryMut + '_>;
/// Gives access to the specified range of entries
///
/// The default implementation should suffice, but it *may* be possible for other
/// implementations to improve the performance. In practice, the performance should not matter
/// much.
fn entries_range(&self, range: Range<usize>) -> Vec<Box<dyn EntryRef + '_>> {
range.map(|i| self.entry(i)).collect()
}
/// Returns all of the entires
///
/// The default implementation here should suffice
fn all_entries(&self) -> Vec<Box<dyn EntryRef + '_>> {
let len = self.num_entries();
self.entries_range(0..len)
}
/// Adds an empty entry with the given name and returns its index
fn add_empty_entry(&mut self, name: String) -> usize;
/// Removes the entry at the given index
fn remove_entry(&mut self, idx: usize);
}
/// An immutable handle on an entry in the file
pub trait EntryRef {
/// Returns the title of the entry
fn name(&self) -> &str;
/// Returns all the tags associated with the entry
fn tags(&self) -> Vec<&str>;
/// Returns the date + time at which the
fn first_added(&self) -> SystemTime;
/// Returns the date + time the entry was last updated
fn last_update(&self) -> SystemTime;
/// Returns a reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field(&self, idx: usize) -> Box<dyn FieldRef + '_>;
/// Returns the number of fields in the entry
fn num_fields(&self) -> usize;
}
/// A mutable handle on an entry in the file
pub trait EntryMut: EntryRef {
/// Sets the title of the entry
fn set_name(&mut self, name: String);
/// Sets the tags associated with the entry
fn set_tags(&mut self, tags: Vec<String>);
/// Returns a mutable reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field_mut(&mut self, idx: usize) -> Box<dyn FieldMut + '_>;
/// Creates a `FieldBuilder` that will (possibly) later be provided back
fn field_builder(&self) -> Box<dyn FieldBuilder>;
/// Sets the field at the given index, using the result of a previous call to
/// `self.field_builder()`
///
/// The index may be one greater than the current number of fields, in which case the value
/// should be appended.
fn set_field(
&mut self,
idx: usize,
builder: Box<dyn FieldBuilder>,
) -> Result<(), SetFieldError>;
/// Removes the given field
fn remove_field(&mut self, idx: usize);
}
/// An immutable handle on a single field of an entry
pub trait FieldRef {
/// The name of the field
fn name(&self) -> &str;
/// Returns the type of value inside this field
fn value_kind(&self) -> ValueKind;
/// The value of the field
///
/// For TOTP fields, this is expected to perform the necessary calculations and return the
/// current OTP.
fn value(&self) -> Result<String, GetValueError>;
/// Returns the "plaintext" value of the field
///
/// Unlike `value`, this returns the underlying secret for TOTP fields.
fn plaintext_value(&self) -> Result<PlaintextValue, GetValueError>;
}
/// A mutable handle on a single field of an entry
pub trait FieldMut: FieldRef {
/// Swaps the encryption of the field
fn swap_encryption(&mut self) -> Result<(), SwapEncryptionError>;
}
/// The types of values a field might have
#[derive(Debug, Copy, Clone)]
pub enum ValueKind {
Basic,
Protected,
Totp,
}
impl Display for ValueKind {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
ValueKind::Basic => f.write_str("Basic"),
ValueKind::Protected => f.write_str("Protected"),
ValueKind::Totp => f.write_str("TOTP"),
}
}
}
/// Helper type for constructing a field
pub trait FieldBuilder: Any {
/// Helper method to recover the original type
fn as_any_mut(&mut self) -> &mut dyn Any;
/// Converts the builder to build a "manual" field
fn make_manual(&mut self);
/// Converts the builder to build a TOTP field
fn make_totp(&mut self) -> Result<(), UnsupportedFeature>;
/// Sets the name of the field
fn set_name(&mut self, name: String);
/// Sets the value of the field
///
/// ## Panics
///
/// This method panics if there was no previous successful call to the matching `make_*` method
/// for the value (`make_manual` or `make_totp`).
fn set_value(&mut self, value: PlaintextValue);
}
/// The latest version of the file content -- the most recent implementor of [`FileContent`]
pub type CurrentFileContent = Keyed<v0_4::FileContent>;
/// A warning given after opening a file with a particular format version
pub struct Warning {
pub reason: &'static str,
}
/// Parses a `FileContent` from the provided file, exiting the program on failure
pub fn parse(file: &Path) -> (Box<dyn FileContent>, Option<Warning>) {
let content = match read_to_string(file) {
Ok(c) => c,
Err(e) => {
eprintln!("failed to read file {:?}: {}", file.to_string_lossy(), e);
exit(1);
}
};
macro_rules! prefix_match {
($val:expr => { $($str:literal => $arm:expr,)* _ => $else_arm:expr, }) => {{
let v = $val;
$(if v.starts_with($str) {
$arm
} else)* {
$else_arm
}
}};
}
prefix_match!(content.as_str() => {
"---\nversion: v0.2\n" => (Box::new(v0_2::parse(content)), v0_2::WARNING),
"---\nversion: v0.3\n" => (Box::new(v0_3::parse(content)), v0_3::WARNING),
"---\nversion: v0.4\n" => (Box::new(v0_4::parse(content)), v0_4::WARNING),
_ => {
eprintln!("unrecognized file version, should be one of: ['v0.2', 'v0.3', 'v0.4']");
exit(1)
},
})
}
/// Return type for [`CurrentFileContent::to_plaintext`]
///
/// This is used both to convert between `FileContent` versions *and* to within the
/// `emit-plaintext` and `from-plaintext` subcommands.
#[derive(Serialize, Deserialize)]
pub struct PlaintextContent {
last_update: SystemTime,
entries: Vec<PlaintextEntry>,
}
#[derive(Serialize, Deserialize)]
struct PlaintextEntry {
name: String,
tags: Vec<String>,
fields: Vec<PlaintextField>,
first_added: SystemTime,
last_update: SystemTime,
}
#[derive(Serialize, Deserialize)]
struct PlaintextField {
name: String,
value: PlaintextValue,
}
#[derive(Serialize, Deserialize)]
pub enum PlaintextValue {
Manual { value: String, protected: bool },
Totp { secret: String, issuer: String },
}
impl PlaintextContent {
/// Produces a new, empty `PlaintextContent` with the current time as its last update
fn init() -> Self |
}
| {
PlaintextContent {
last_update: SystemTime::now(),
entries: Vec::new(),
}
} | identifier_body |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associated only with them don't inflate compile times.
//!
//! All of the submodules here correspond to a particular version -- with the current one also
//! included. Each submodule defines a `FileContent` struct that implements the [`FileContent`]
//! trait in this module, so that we can cleanly abstract over the file format without changing the
//! logic in `crate::app`. The `FileContent` from the latest version is re-exported in this module
//! as [`CurrentFileContent`].
//!
//! Each submodule additionally defines a couple items:
//! ```ignore
//! // If this file format has been deprecated, a warning to indicate as such
//! pub const WARNING: Option<Warning> = ...;
//!
//! // Given a file that we know starts with the correct version prefix, parse it
//! //
//! // If any errors are encountered, print them and exit.
//! pub fn parse(file_content: String) -> FileContent { ... }
//! ```
//! Those are used by the `parse` function at the bottom of this file.
use serde::{Deserialize, Serialize};
use std::any::Any;
use std::fmt::{self, Display, Formatter};
use std::fs::read_to_string;
use std::ops::Range;
use std::path::Path;
use std::process::exit;
use std::time::SystemTime;
mod errors;
mod latest;
mod v0_2;
mod v0_3;
mod v0_4;
pub use errors::*;
/// Helper struct for file contents with an attached key
///
/// This is extracted into this module so that it's able to be used by multiple submodules without
/// redefinition.
pub struct Keyed<C> {
key: Option<Vec<u8>>,
unsaved: bool,
content: C,
}
impl<C> Keyed<C> {
/// Creates a new `Keyed` content without the key
fn new(content: C) -> Self {
Keyed {
key: None,
unsaved: false,
content,
}
}
}
/// A particular file format, kept object-safe so that we can switch on it at runtime
///
/// The first couple methods here are for providing the "meta" methods -- the rest merely provide
/// the shared facilities for interaction with contents of the file.
pub trait FileContent {
/// Helper function to convert to the latest version, given the user's password
///
/// It's customary for this method to only convert to the next version internally, and instead
/// rely upon that version's implementation of producing the current file content. This chain
/// terminates with with the implementation for `CurrentFileContent`, which just returns itself.
fn to_current(self: Box<Self>, pwd: String) -> Result<Box<CurrentFileContent>, DecryptError>;
/// Provides the string that the file content should be written as
///
/// This method is provided -- instead of directly writing to the file -- so that no error
/// handling needs to be done within the implementation itself.
fn write(&self) -> String;
/// Sets the key, returning `Err` if it was invalid
fn set_key(&mut self, key: String) -> Result<(), DecryptError>;
/// Returns true if there have been changes made to the file without saving
///
/// Changes should be registered as unsaved until a call to `saved` is made
fn unsaved(&self) -> bool;
/// Registers any unsaved change as now being saved
fn mark_saved(&mut self);
/// Returns whether the entries have been decrypted -- true after `set_key` returns `Ok`
fn decrypted(&self) -> bool;
/// Produces the number of entries in the file
fn num_entries(&self) -> usize;
/// Produces the entry corresponding to the given index
fn entry(&self, idx: usize) -> Box<dyn EntryRef + '_>;
/// Produces a mutable reference to the corresponding entry
fn entry_mut(&mut self, idx: usize) -> Box<dyn EntryMut + '_>;
/// Gives access to the specified range of entries
///
/// The default implementation should suffice, but it *may* be possible for other
/// implementations to improve the performance. In practice, the performance should not matter
/// much.
fn entries_range(&self, range: Range<usize>) -> Vec<Box<dyn EntryRef + '_>> {
range.map(|i| self.entry(i)).collect()
}
/// Returns all of the entires
///
/// The default implementation here should suffice
fn all_entries(&self) -> Vec<Box<dyn EntryRef + '_>> {
let len = self.num_entries();
self.entries_range(0..len)
}
/// Adds an empty entry with the given name and returns its index
fn add_empty_entry(&mut self, name: String) -> usize;
/// Removes the entry at the given index
fn remove_entry(&mut self, idx: usize);
}
/// An immutable handle on an entry in the file
pub trait EntryRef {
/// Returns the title of the entry
fn name(&self) -> &str;
/// Returns all the tags associated with the entry
fn tags(&self) -> Vec<&str>;
/// Returns the date + time at which the
fn first_added(&self) -> SystemTime;
/// Returns the date + time the entry was last updated
fn last_update(&self) -> SystemTime;
/// Returns a reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field(&self, idx: usize) -> Box<dyn FieldRef + '_>;
/// Returns the number of fields in the entry
fn num_fields(&self) -> usize;
}
/// A mutable handle on an entry in the file
pub trait EntryMut: EntryRef {
/// Sets the title of the entry
fn set_name(&mut self, name: String);
/// Sets the tags associated with the entry
fn set_tags(&mut self, tags: Vec<String>);
/// Returns a mutable reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field_mut(&mut self, idx: usize) -> Box<dyn FieldMut + '_>;
/// Creates a `FieldBuilder` that will (possibly) later be provided back
fn field_builder(&self) -> Box<dyn FieldBuilder>;
/// Sets the field at the given index, using the result of a previous call to
/// `self.field_builder()`
///
/// The index may be one greater than the current number of fields, in which case the value
/// should be appended.
fn set_field(
&mut self,
idx: usize,
builder: Box<dyn FieldBuilder>,
) -> Result<(), SetFieldError>;
/// Removes the given field
fn remove_field(&mut self, idx: usize);
}
/// An immutable handle on a single field of an entry
pub trait FieldRef {
/// The name of the field
fn name(&self) -> &str;
/// Returns the type of value inside this field
fn value_kind(&self) -> ValueKind;
/// The value of the field
///
/// For TOTP fields, this is expected to perform the necessary calculations and return the
/// current OTP.
fn value(&self) -> Result<String, GetValueError>;
/// Returns the "plaintext" value of the field
///
/// Unlike `value`, this returns the underlying secret for TOTP fields.
fn plaintext_value(&self) -> Result<PlaintextValue, GetValueError>;
}
/// A mutable handle on a single field of an entry
pub trait FieldMut: FieldRef {
/// Swaps the encryption of the field
fn swap_encryption(&mut self) -> Result<(), SwapEncryptionError>;
}
/// The types of values a field might have
#[derive(Debug, Copy, Clone)]
pub enum ValueKind {
Basic,
Protected,
Totp,
}
impl Display for ValueKind {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
ValueKind::Basic => f.write_str("Basic"),
ValueKind::Protected => f.write_str("Protected"),
ValueKind::Totp => f.write_str("TOTP"),
}
}
}
/// Helper type for constructing a field
pub trait FieldBuilder: Any {
/// Helper method to recover the original type
fn as_any_mut(&mut self) -> &mut dyn Any;
/// Converts the builder to build a "manual" field
fn make_manual(&mut self);
/// Converts the builder to build a TOTP field
fn make_totp(&mut self) -> Result<(), UnsupportedFeature>;
/// Sets the name of the field
fn set_name(&mut self, name: String);
/// Sets the value of the field
///
/// ## Panics
///
/// This method panics if there was no previous successful call to the matching `make_*` method
/// for the value (`make_manual` or `make_totp`).
fn set_value(&mut self, value: PlaintextValue);
}
/// The latest version of the file content -- the most recent implementor of [`FileContent`]
pub type CurrentFileContent = Keyed<v0_4::FileContent>;
/// A warning given after opening a file with a particular format version
pub struct Warning {
pub reason: &'static str,
}
/// Parses a `FileContent` from the provided file, exiting the program on failure
pub fn parse(file: &Path) -> (Box<dyn FileContent>, Option<Warning>) {
let content = match read_to_string(file) {
Ok(c) => c,
Err(e) => |
};
macro_rules! prefix_match {
($val:expr => { $($str:literal => $arm:expr,)* _ => $else_arm:expr, }) => {{
let v = $val;
$(if v.starts_with($str) {
$arm
} else)* {
$else_arm
}
}};
}
prefix_match!(content.as_str() => {
"---\nversion: v0.2\n" => (Box::new(v0_2::parse(content)), v0_2::WARNING),
"---\nversion: v0.3\n" => (Box::new(v0_3::parse(content)), v0_3::WARNING),
"---\nversion: v0.4\n" => (Box::new(v0_4::parse(content)), v0_4::WARNING),
_ => {
eprintln!("unrecognized file version, should be one of: ['v0.2', 'v0.3', 'v0.4']");
exit(1)
},
})
}
/// Return type for [`CurrentFileContent::to_plaintext`]
///
/// This is used both to convert between `FileContent` versions *and* to within the
/// `emit-plaintext` and `from-plaintext` subcommands.
#[derive(Serialize, Deserialize)]
pub struct PlaintextContent {
last_update: SystemTime,
entries: Vec<PlaintextEntry>,
}
#[derive(Serialize, Deserialize)]
struct PlaintextEntry {
name: String,
tags: Vec<String>,
fields: Vec<PlaintextField>,
first_added: SystemTime,
last_update: SystemTime,
}
#[derive(Serialize, Deserialize)]
struct PlaintextField {
name: String,
value: PlaintextValue,
}
#[derive(Serialize, Deserialize)]
pub enum PlaintextValue {
Manual { value: String, protected: bool },
Totp { secret: String, issuer: String },
}
impl PlaintextContent {
/// Produces a new, empty `PlaintextContent` with the current time as its last update
fn init() -> Self {
PlaintextContent {
last_update: SystemTime::now(),
entries: Vec::new(),
}
}
}
| {
eprintln!("failed to read file {:?}: {}", file.to_string_lossy(), e);
exit(1);
} | conditional_block |
mod.rs | //! Abstraction over multiple versions of the file format allowed
//!
//! Because we want to continue to properly handle old config file formats - even when they'll no
//! longer be generated by default. In the future, we might provide some kind of feature-gating for
//! older versions, so that the dependencies associated only with them don't inflate compile times.
//!
//! All of the submodules here correspond to a particular version -- with the current one also
//! included. Each submodule defines a `FileContent` struct that implements the [`FileContent`]
//! trait in this module, so that we can cleanly abstract over the file format without changing the
//! logic in `crate::app`. The `FileContent` from the latest version is re-exported in this module
//! as [`CurrentFileContent`].
//!
//! Each submodule additionally defines a couple items:
//! ```ignore
//! // If this file format has been deprecated, a warning to indicate as such
//! pub const WARNING: Option<Warning> = ...;
//!
//! // Given a file that we know starts with the correct version prefix, parse it
//! //
//! // If any errors are encountered, print them and exit.
//! pub fn parse(file_content: String) -> FileContent { ... }
//! ```
//! Those are used by the `parse` function at the bottom of this file.
use serde::{Deserialize, Serialize};
use std::any::Any;
use std::fmt::{self, Display, Formatter};
use std::fs::read_to_string;
use std::ops::Range;
use std::path::Path;
use std::process::exit;
use std::time::SystemTime;
mod errors;
mod latest;
mod v0_2;
mod v0_3;
mod v0_4;
pub use errors::*;
/// Helper struct for file contents with an attached key
///
/// This is extracted into this module so that it's able to be used by multiple submodules without
/// redefinition.
pub struct Keyed<C> {
key: Option<Vec<u8>>,
unsaved: bool,
content: C,
}
impl<C> Keyed<C> {
/// Creates a new `Keyed` content without the key
fn new(content: C) -> Self {
Keyed {
key: None,
unsaved: false,
content,
}
}
}
/// A particular file format, kept object-safe so that we can switch on it at runtime
///
/// The first couple methods here are for providing the "meta" methods -- the rest merely provide
/// the shared facilities for interaction with contents of the file.
pub trait FileContent {
/// Helper function to convert to the latest version, given the user's password
///
/// It's customary for this method to only convert to the next version internally, and instead
/// rely upon that version's implementation of producing the current file content. This chain
/// terminates with with the implementation for `CurrentFileContent`, which just returns itself.
fn to_current(self: Box<Self>, pwd: String) -> Result<Box<CurrentFileContent>, DecryptError>;
/// Provides the string that the file content should be written as
///
/// This method is provided -- instead of directly writing to the file -- so that no error
/// handling needs to be done within the implementation itself.
fn write(&self) -> String;
/// Sets the key, returning `Err` if it was invalid
fn set_key(&mut self, key: String) -> Result<(), DecryptError>;
/// Returns true if there have been changes made to the file without saving
///
/// Changes should be registered as unsaved until a call to `saved` is made
fn unsaved(&self) -> bool;
/// Registers any unsaved change as now being saved
fn mark_saved(&mut self);
/// Returns whether the entries have been decrypted -- true after `set_key` returns `Ok`
fn decrypted(&self) -> bool;
/// Produces the number of entries in the file
fn num_entries(&self) -> usize;
/// Produces the entry corresponding to the given index
fn entry(&self, idx: usize) -> Box<dyn EntryRef + '_>;
/// Produces a mutable reference to the corresponding entry
fn entry_mut(&mut self, idx: usize) -> Box<dyn EntryMut + '_>;
/// Gives access to the specified range of entries
///
/// The default implementation should suffice, but it *may* be possible for other
/// implementations to improve the performance. In practice, the performance should not matter
/// much.
fn entries_range(&self, range: Range<usize>) -> Vec<Box<dyn EntryRef + '_>> {
range.map(|i| self.entry(i)).collect()
}
/// Returns all of the entires
///
/// The default implementation here should suffice
fn all_entries(&self) -> Vec<Box<dyn EntryRef + '_>> {
let len = self.num_entries();
self.entries_range(0..len)
}
/// Adds an empty entry with the given name and returns its index
fn add_empty_entry(&mut self, name: String) -> usize;
/// Removes the entry at the given index
fn remove_entry(&mut self, idx: usize);
}
/// An immutable handle on an entry in the file
pub trait EntryRef {
/// Returns the title of the entry
fn name(&self) -> &str;
/// Returns all the tags associated with the entry
fn tags(&self) -> Vec<&str>;
/// Returns the date + time at which the
fn first_added(&self) -> SystemTime;
/// Returns the date + time the entry was last updated
fn last_update(&self) -> SystemTime;
/// Returns a reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field(&self, idx: usize) -> Box<dyn FieldRef + '_>;
/// Returns the number of fields in the entry
fn num_fields(&self) -> usize;
}
/// A mutable handle on an entry in the file
pub trait EntryMut: EntryRef {
/// Sets the title of the entry
fn set_name(&mut self, name: String);
/// Sets the tags associated with the entry
fn set_tags(&mut self, tags: Vec<String>);
/// Returns a mutable reference to the field with index `idx`
///
/// ## Panics
///
/// This function *should* panic if `idx` is greater than `self.num_fields()`
fn field_mut(&mut self, idx: usize) -> Box<dyn FieldMut + '_>;
/// Creates a `FieldBuilder` that will (possibly) later be provided back
fn field_builder(&self) -> Box<dyn FieldBuilder>;
/// Sets the field at the given index, using the result of a previous call to
/// `self.field_builder()`
///
/// The index may be one greater than the current number of fields, in which case the value
/// should be appended.
fn set_field(
&mut self,
idx: usize,
builder: Box<dyn FieldBuilder>,
) -> Result<(), SetFieldError>;
/// Removes the given field
fn remove_field(&mut self, idx: usize);
}
/// An immutable handle on a single field of an entry
pub trait FieldRef {
/// The name of the field
fn name(&self) -> &str;
/// Returns the type of value inside this field
fn value_kind(&self) -> ValueKind;
/// The value of the field
///
/// For TOTP fields, this is expected to perform the necessary calculations and return the
/// current OTP.
fn value(&self) -> Result<String, GetValueError>;
/// Returns the "plaintext" value of the field
///
/// Unlike `value`, this returns the underlying secret for TOTP fields.
fn plaintext_value(&self) -> Result<PlaintextValue, GetValueError>;
}
/// A mutable handle on a single field of an entry
pub trait FieldMut: FieldRef {
/// Swaps the encryption of the field
fn swap_encryption(&mut self) -> Result<(), SwapEncryptionError>;
}
/// The types of values a field might have
#[derive(Debug, Copy, Clone)]
pub enum | {
Basic,
Protected,
Totp,
}
impl Display for ValueKind {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
ValueKind::Basic => f.write_str("Basic"),
ValueKind::Protected => f.write_str("Protected"),
ValueKind::Totp => f.write_str("TOTP"),
}
}
}
/// Helper type for constructing a field
pub trait FieldBuilder: Any {
/// Helper method to recover the original type
fn as_any_mut(&mut self) -> &mut dyn Any;
/// Converts the builder to build a "manual" field
fn make_manual(&mut self);
/// Converts the builder to build a TOTP field
fn make_totp(&mut self) -> Result<(), UnsupportedFeature>;
/// Sets the name of the field
fn set_name(&mut self, name: String);
/// Sets the value of the field
///
/// ## Panics
///
/// This method panics if there was no previous successful call to the matching `make_*` method
/// for the value (`make_manual` or `make_totp`).
fn set_value(&mut self, value: PlaintextValue);
}
/// The latest version of the file content -- the most recent implementor of [`FileContent`]
pub type CurrentFileContent = Keyed<v0_4::FileContent>;
/// A warning given after opening a file with a particular format version
pub struct Warning {
pub reason: &'static str,
}
/// Parses a `FileContent` from the provided file, exiting the program on failure
pub fn parse(file: &Path) -> (Box<dyn FileContent>, Option<Warning>) {
let content = match read_to_string(file) {
Ok(c) => c,
Err(e) => {
eprintln!("failed to read file {:?}: {}", file.to_string_lossy(), e);
exit(1);
}
};
macro_rules! prefix_match {
($val:expr => { $($str:literal => $arm:expr,)* _ => $else_arm:expr, }) => {{
let v = $val;
$(if v.starts_with($str) {
$arm
} else)* {
$else_arm
}
}};
}
prefix_match!(content.as_str() => {
"---\nversion: v0.2\n" => (Box::new(v0_2::parse(content)), v0_2::WARNING),
"---\nversion: v0.3\n" => (Box::new(v0_3::parse(content)), v0_3::WARNING),
"---\nversion: v0.4\n" => (Box::new(v0_4::parse(content)), v0_4::WARNING),
_ => {
eprintln!("unrecognized file version, should be one of: ['v0.2', 'v0.3', 'v0.4']");
exit(1)
},
})
}
/// Return type for [`CurrentFileContent::to_plaintext`]
///
/// This is used both to convert between `FileContent` versions *and* to within the
/// `emit-plaintext` and `from-plaintext` subcommands.
#[derive(Serialize, Deserialize)]
pub struct PlaintextContent {
last_update: SystemTime,
entries: Vec<PlaintextEntry>,
}
#[derive(Serialize, Deserialize)]
struct PlaintextEntry {
name: String,
tags: Vec<String>,
fields: Vec<PlaintextField>,
first_added: SystemTime,
last_update: SystemTime,
}
#[derive(Serialize, Deserialize)]
struct PlaintextField {
name: String,
value: PlaintextValue,
}
#[derive(Serialize, Deserialize)]
pub enum PlaintextValue {
Manual { value: String, protected: bool },
Totp { secret: String, issuer: String },
}
impl PlaintextContent {
/// Produces a new, empty `PlaintextContent` with the current time as its last update
fn init() -> Self {
PlaintextContent {
last_update: SystemTime::now(),
entries: Vec::new(),
}
}
}
| ValueKind | identifier_name |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; //that pink color on their chest
}
else {//juvenile or maturing
return "#EDE9DD"; //cream
}
};
var pickSize = (category) => {
if(category == "pup") {
return 2;
}
else if(category == "weanling") {
return 3;
}
else if(category == "yearling") {
return 5;
}
else if(category == "juvenile") {
return 6;
}
else if(category == "adult_female") {
return 7.5;
}
else if(category == "adult_male") {
return 15;
}
else {//classified as SA
return 7.5;
}
}
//we're going to split up the month by weeks! See what happens
let monthData = function(year, month) {
let censusArray = sealCensus[year][month];
let censuses = {
week1: [],
week2: [],
week3: [],
week4: []
};
//assign censuses to weeks
censusArray.forEach(census => {
let day = census.date.day;
let week = Math.ceil( day/7 );
switch(week) {
case 1:
censusArray.week1.push(census);
break;
case 2:
censusArray.week2.push(census);
break;
case 3:
censusArray.week3.push(census);
break;
case 4:
censusArray.week4.push(census);
break;
case 5:
censusArray.week4.push(census);
break;
}
return censuses;
});
}
//Add circles where the seals are!
// Create SVG element
let width = 1000;
let height = 500;
var addSVG = function() {
debug("in addSVG()");
let row = -1;
//create svg element
var svg = d3.select("#chart")
.append("svg")
.attr("width", width)
.attr("height", height)
.append("g")
.attr("transform", "translate(0,0)");
//get census data acoording to the slider's value/date
var sliderValue = document.getElementById("myRange").value;
//let dataYear = d3.select("#year").value;
var dataYear = 1976 + (sliderValue/12)|0;
var dataMonth = sliderValue%12 < 0 ? sliderValue%12 : 12;
var dataLocation;
var data;
var noCensus = false;
//var data = sealCensus[dataYear][dataMonth];
let censusArray = sealCensus[dataYear][dataMonth];
let census;
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
}
else {
census = []; //no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else {
data = census;
}
data = fixData(data, dataLocation);
console.log("Extracted data for the force simulation: ");
console.log(data);
let xPadding = width/10;
let yPadding = height/10;
//data = [0,1,2,3,4,5,6,7,7,8,9,0,1,2,3,4,5,6,7,8,9,0,9,3,7,9];
//Create and append circle elements element
var circles = svg.selectAll(".seal")
.data(data)
.enter().append("circle")
.attr("class", "seal")
.attr("cx", (d, i) => (i%11) * xPadding)
//.attr("cx", 250)
//.attr("cy", 250)
.attr("cy", (d, i) => (((i/11)|0) + 1) * yPadding)
.attr("r", d => pickSize(d.type))
//.attr("fill", (sliderValue % 2 == 0) ? "blue" : "green");
.attr("fill", d => pickColor(d.type));
//actions for when the slider is updated
//help from http://bl.ocks.org/kbroman/2044064e9517985f2f25
d3.select("input[type=range]#myRange").on("input", function() {
dataYear = 1976 + (this.value/12)|0;
dataMonth = this.value%12 > 0 ? this.value%12 : 12;
console.log("Slider updated to " + dataMonth + " " + dataYear);
//var data = sealCensus[dataYear][dataMonth];
censusArray = sealCensus[dataYear][dataMonth];
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
noCensus = false;
}
else {
census = []; // no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else
data = census;
data = fixData(data, dataLocation);
//console.log("New data being displayed: ");
//console.log(data);
//slightly redundant since this is done in autoplay as well
//BUT we also want this to happen when the user picks a year WITHOUT using the autoplayer
d3.select("output#year")
.text(convertSliderValue(this.value));
//update circles with the changes
//help from http://bl.ocks.org/alansmithy/e984477a741bc56db5a5
//let circles = d3.selectAll("circle.seal");
circles.data(data);//.join("circle")
circles.exit().remove(); //remove unneeded circles
circles.enter().append("circle")
.attr("r", d => pickSize(d.type))
.attr("cx", width/2)
.attr("cy", height/2)
.attr("fill", d => pickColor(d.type))
.attr("id", "new")
;//.merge(circles);
//debug("Slider changed to " + year);
//console.log(this);
simulation
.alphaTarget(0.25)
.restart();
simulation.nodes(data).on("tick", ticked);
});
//add text labels
//top left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/12 + ")")
.text("North Point");
//top right text
svg.append("text")
.style("text-anchor", "middle")
| .style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/2 + ")")
.text("Mid Bight Beach");
//bottom right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/2 + ")")
.text("Ano Point");
//legend container
svg.append("rect")
.attr("fill", "white")
.attr("x", width - 150)
.attr("y", 10)
.attr("height", 150)
.attr("width", 140);
//black is for pups
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#220C08")
.attr("x", width - 140)
.attr("y", 20)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 37)
.text("Pup, Weanling");
//cream is for juveniles
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#EDE9DD")
.attr("x", width - 140)
.attr("y", 50)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 67)
.text("Yearling, Juvenile");
//tan is for females
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#9B8576")
.attr("x", width - 140)
.attr("y", 80)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 97)
.text("Adult Female");
//pink/brown is for males
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#BC8D7D")
.attr("x", width - 140)
.attr("y", 110)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 127)
.text("Adult Male");
//the simulation is a collection of forces
//about where we want our circles to go
//and how we want our circles to interact
simulation.nodes(data).on("tick", ticked);
function ticked() {
circles
.attr("cx", d => d.x)
.attr("cy", d => d.y)
}
}
// bubble cluster physics
// help from https://youtu.be/NTS7uXOxQeM
var forceX = d3.forceX( d => {
if(d.location == "North Point") { //North Point
return width*1/3;
}
else if(d.location == "Bight Beach North") { //Bight Beach North
return width*2/3;
}
else if(d.location == "Mid Bight Beach") { //Mid Bight Beach
return width*1/3;
}
else {//Other
return width*2/3;
}
})
.strength(0.1);
var forceY = d3.forceY( d => {
if(d.location == "North Point" || d.location == "Bight Beach North") {
return height/4;
}
else {//d.data[0].long > medianLong
return height*3/4;
}
})
.strength(0.1);
var simulation = d3.forceSimulation()
.force("x", forceX)
.force("y", forceY)
.force("collide", d3.forceCollide( d => pickSize(d.type) ));
//this function specifically exists to modify the data array for the force simulation
//Uncaught TypeError: Cannot create property 'vx' on string 'SA2'
//the force simulation ONLY accepts objects! So we turn the array of strings, into objects.
function fixData(old, location) {
let newData;
console.log("Fixing this data: ");
console.log(old);
//create new array where each element is an object with the seal type and where it is
newData = old.map( seal => {
return {type: seal, location: location};
});
return newData;
} | .attr("transform", "translate(" + width*2/3 + ", " + height/12 + ")")
.text("Bight Beach North");
//bottom left text
svg.append("text")
| random_line_split |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; //that pink color on their chest
}
else {//juvenile or maturing
return "#EDE9DD"; //cream
}
};
var pickSize = (category) => {
if(category == "pup") {
return 2;
}
else if(category == "weanling") {
return 3;
}
else if(category == "yearling") {
return 5;
}
else if(category == "juvenile") {
return 6;
}
else if(category == "adult_female") {
return 7.5;
}
else if(category == "adult_male") {
return 15;
}
else {//classified as SA
return 7.5;
}
}
//we're going to split up the month by weeks! See what happens
let monthData = function(year, month) {
let censusArray = sealCensus[year][month];
let censuses = {
week1: [],
week2: [],
week3: [],
week4: []
};
//assign censuses to weeks
censusArray.forEach(census => {
let day = census.date.day;
let week = Math.ceil( day/7 );
switch(week) {
case 1:
censusArray.week1.push(census);
break;
case 2:
censusArray.week2.push(census);
break;
case 3:
censusArray.week3.push(census);
break;
case 4:
censusArray.week4.push(census);
break;
case 5:
censusArray.week4.push(census);
break;
}
return censuses;
});
}
//Add circles where the seals are!
// Create SVG element
let width = 1000;
let height = 500;
var addSVG = function() {
debug("in addSVG()");
let row = -1;
//create svg element
var svg = d3.select("#chart")
.append("svg")
.attr("width", width)
.attr("height", height)
.append("g")
.attr("transform", "translate(0,0)");
//get census data acoording to the slider's value/date
var sliderValue = document.getElementById("myRange").value;
//let dataYear = d3.select("#year").value;
var dataYear = 1976 + (sliderValue/12)|0;
var dataMonth = sliderValue%12 < 0 ? sliderValue%12 : 12;
var dataLocation;
var data;
var noCensus = false;
//var data = sealCensus[dataYear][dataMonth];
let censusArray = sealCensus[dataYear][dataMonth];
let census;
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
}
else {
census = []; //no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else {
data = census;
}
data = fixData(data, dataLocation);
console.log("Extracted data for the force simulation: ");
console.log(data);
let xPadding = width/10;
let yPadding = height/10;
//data = [0,1,2,3,4,5,6,7,7,8,9,0,1,2,3,4,5,6,7,8,9,0,9,3,7,9];
//Create and append circle elements element
var circles = svg.selectAll(".seal")
.data(data)
.enter().append("circle")
.attr("class", "seal")
.attr("cx", (d, i) => (i%11) * xPadding)
//.attr("cx", 250)
//.attr("cy", 250)
.attr("cy", (d, i) => (((i/11)|0) + 1) * yPadding)
.attr("r", d => pickSize(d.type))
//.attr("fill", (sliderValue % 2 == 0) ? "blue" : "green");
.attr("fill", d => pickColor(d.type));
//actions for when the slider is updated
//help from http://bl.ocks.org/kbroman/2044064e9517985f2f25
d3.select("input[type=range]#myRange").on("input", function() {
dataYear = 1976 + (this.value/12)|0;
dataMonth = this.value%12 > 0 ? this.value%12 : 12;
console.log("Slider updated to " + dataMonth + " " + dataYear);
//var data = sealCensus[dataYear][dataMonth];
censusArray = sealCensus[dataYear][dataMonth];
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
noCensus = false;
}
else {
census = []; // no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else
data = census;
data = fixData(data, dataLocation);
//console.log("New data being displayed: ");
//console.log(data);
//slightly redundant since this is done in autoplay as well
//BUT we also want this to happen when the user picks a year WITHOUT using the autoplayer
d3.select("output#year")
.text(convertSliderValue(this.value));
//update circles with the changes
//help from http://bl.ocks.org/alansmithy/e984477a741bc56db5a5
//let circles = d3.selectAll("circle.seal");
circles.data(data);//.join("circle")
circles.exit().remove(); //remove unneeded circles
circles.enter().append("circle")
.attr("r", d => pickSize(d.type))
.attr("cx", width/2)
.attr("cy", height/2)
.attr("fill", d => pickColor(d.type))
.attr("id", "new")
;//.merge(circles);
//debug("Slider changed to " + year);
//console.log(this);
simulation
.alphaTarget(0.25)
.restart();
simulation.nodes(data).on("tick", ticked);
});
//add text labels
//top left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/12 + ")")
.text("North Point");
//top right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/12 + ")")
.text("Bight Beach North");
//bottom left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/2 + ")")
.text("Mid Bight Beach");
//bottom right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/2 + ")")
.text("Ano Point");
//legend container
svg.append("rect")
.attr("fill", "white")
.attr("x", width - 150)
.attr("y", 10)
.attr("height", 150)
.attr("width", 140);
//black is for pups
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#220C08")
.attr("x", width - 140)
.attr("y", 20)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 37)
.text("Pup, Weanling");
//cream is for juveniles
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#EDE9DD")
.attr("x", width - 140)
.attr("y", 50)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 67)
.text("Yearling, Juvenile");
//tan is for females
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#9B8576")
.attr("x", width - 140)
.attr("y", 80)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 97)
.text("Adult Female");
//pink/brown is for males
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#BC8D7D")
.attr("x", width - 140)
.attr("y", 110)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 127)
.text("Adult Male");
//the simulation is a collection of forces
//about where we want our circles to go
//and how we want our circles to interact
simulation.nodes(data).on("tick", ticked);
function ticked() {
circles
.attr("cx", d => d.x)
.attr("cy", d => d.y)
}
}
// bubble cluster physics
// help from https://youtu.be/NTS7uXOxQeM
var forceX = d3.forceX( d => {
if(d.location == "North Point") { //North Point
return width*1/3;
}
else if(d.location == "Bight Beach North") { //Bight Beach North
return width*2/3;
}
else if(d.location == "Mid Bight Beach") { //Mid Bight Beach
return width*1/3;
}
else {//Other
return width*2/3;
}
})
.strength(0.1);
var forceY = d3.forceY( d => {
if(d.location == "North Point" || d.location == "Bight Beach North") {
return height/4;
}
else {//d.data[0].long > medianLong
return height*3/4;
}
})
.strength(0.1);
var simulation = d3.forceSimulation()
.force("x", forceX)
.force("y", forceY)
.force("collide", d3.forceCollide( d => pickSize(d.type) ));
//this function specifically exists to modify the data array for the force simulation
//Uncaught TypeError: Cannot create property 'vx' on string 'SA2'
//the force simulation ONLY accepts objects! So we turn the array of strings, into objects.
function | (old, location) {
let newData;
console.log("Fixing this data: ");
console.log(old);
//create new array where each element is an object with the seal type and where it is
newData = old.map( seal => {
return {type: seal, location: location};
});
return newData;
} | fixData | identifier_name |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; //that pink color on their chest
}
else {//juvenile or maturing
return "#EDE9DD"; //cream
}
};
var pickSize = (category) => {
if(category == "pup") {
return 2;
}
else if(category == "weanling") {
return 3;
}
else if(category == "yearling") {
return 5;
}
else if(category == "juvenile") {
return 6;
}
else if(category == "adult_female") {
return 7.5;
}
else if(category == "adult_male") {
return 15;
}
else {//classified as SA
return 7.5;
}
}
//we're going to split up the month by weeks! See what happens
let monthData = function(year, month) {
let censusArray = sealCensus[year][month];
let censuses = {
week1: [],
week2: [],
week3: [],
week4: []
};
//assign censuses to weeks
censusArray.forEach(census => {
let day = census.date.day;
let week = Math.ceil( day/7 );
switch(week) {
case 1:
censusArray.week1.push(census);
break;
case 2:
censusArray.week2.push(census);
break;
case 3:
censusArray.week3.push(census);
break;
case 4:
censusArray.week4.push(census);
break;
case 5:
censusArray.week4.push(census);
break;
}
return censuses;
});
}
//Add circles where the seals are!
// Create SVG element
let width = 1000;
let height = 500;
var addSVG = function() {
debug("in addSVG()");
let row = -1;
//create svg element
var svg = d3.select("#chart")
.append("svg")
.attr("width", width)
.attr("height", height)
.append("g")
.attr("transform", "translate(0,0)");
//get census data acoording to the slider's value/date
var sliderValue = document.getElementById("myRange").value;
//let dataYear = d3.select("#year").value;
var dataYear = 1976 + (sliderValue/12)|0;
var dataMonth = sliderValue%12 < 0 ? sliderValue%12 : 12;
var dataLocation;
var data;
var noCensus = false;
//var data = sealCensus[dataYear][dataMonth];
let censusArray = sealCensus[dataYear][dataMonth];
let census;
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
}
else {
census = []; //no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else {
data = census;
}
data = fixData(data, dataLocation);
console.log("Extracted data for the force simulation: ");
console.log(data);
let xPadding = width/10;
let yPadding = height/10;
//data = [0,1,2,3,4,5,6,7,7,8,9,0,1,2,3,4,5,6,7,8,9,0,9,3,7,9];
//Create and append circle elements element
var circles = svg.selectAll(".seal")
.data(data)
.enter().append("circle")
.attr("class", "seal")
.attr("cx", (d, i) => (i%11) * xPadding)
//.attr("cx", 250)
//.attr("cy", 250)
.attr("cy", (d, i) => (((i/11)|0) + 1) * yPadding)
.attr("r", d => pickSize(d.type))
//.attr("fill", (sliderValue % 2 == 0) ? "blue" : "green");
.attr("fill", d => pickColor(d.type));
//actions for when the slider is updated
//help from http://bl.ocks.org/kbroman/2044064e9517985f2f25
d3.select("input[type=range]#myRange").on("input", function() {
dataYear = 1976 + (this.value/12)|0;
dataMonth = this.value%12 > 0 ? this.value%12 : 12;
console.log("Slider updated to " + dataMonth + " " + dataYear);
//var data = sealCensus[dataYear][dataMonth];
censusArray = sealCensus[dataYear][dataMonth];
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
noCensus = false;
}
else {
census = []; // no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else
data = census;
data = fixData(data, dataLocation);
//console.log("New data being displayed: ");
//console.log(data);
//slightly redundant since this is done in autoplay as well
//BUT we also want this to happen when the user picks a year WITHOUT using the autoplayer
d3.select("output#year")
.text(convertSliderValue(this.value));
//update circles with the changes
//help from http://bl.ocks.org/alansmithy/e984477a741bc56db5a5
//let circles = d3.selectAll("circle.seal");
circles.data(data);//.join("circle")
circles.exit().remove(); //remove unneeded circles
circles.enter().append("circle")
.attr("r", d => pickSize(d.type))
.attr("cx", width/2)
.attr("cy", height/2)
.attr("fill", d => pickColor(d.type))
.attr("id", "new")
;//.merge(circles);
//debug("Slider changed to " + year);
//console.log(this);
simulation
.alphaTarget(0.25)
.restart();
simulation.nodes(data).on("tick", ticked);
});
//add text labels
//top left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/12 + ")")
.text("North Point");
//top right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/12 + ")")
.text("Bight Beach North");
//bottom left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/2 + ")")
.text("Mid Bight Beach");
//bottom right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/2 + ")")
.text("Ano Point");
//legend container
svg.append("rect")
.attr("fill", "white")
.attr("x", width - 150)
.attr("y", 10)
.attr("height", 150)
.attr("width", 140);
//black is for pups
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#220C08")
.attr("x", width - 140)
.attr("y", 20)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 37)
.text("Pup, Weanling");
//cream is for juveniles
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#EDE9DD")
.attr("x", width - 140)
.attr("y", 50)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 67)
.text("Yearling, Juvenile");
//tan is for females
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#9B8576")
.attr("x", width - 140)
.attr("y", 80)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 97)
.text("Adult Female");
//pink/brown is for males
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#BC8D7D")
.attr("x", width - 140)
.attr("y", 110)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 127)
.text("Adult Male");
//the simulation is a collection of forces
//about where we want our circles to go
//and how we want our circles to interact
simulation.nodes(data).on("tick", ticked);
function ticked() |
}
// bubble cluster physics
// help from https://youtu.be/NTS7uXOxQeM
var forceX = d3.forceX( d => {
if(d.location == "North Point") { //North Point
return width*1/3;
}
else if(d.location == "Bight Beach North") { //Bight Beach North
return width*2/3;
}
else if(d.location == "Mid Bight Beach") { //Mid Bight Beach
return width*1/3;
}
else {//Other
return width*2/3;
}
})
.strength(0.1);
var forceY = d3.forceY( d => {
if(d.location == "North Point" || d.location == "Bight Beach North") {
return height/4;
}
else {//d.data[0].long > medianLong
return height*3/4;
}
})
.strength(0.1);
var simulation = d3.forceSimulation()
.force("x", forceX)
.force("y", forceY)
.force("collide", d3.forceCollide( d => pickSize(d.type) ));
//this function specifically exists to modify the data array for the force simulation
//Uncaught TypeError: Cannot create property 'vx' on string 'SA2'
//the force simulation ONLY accepts objects! So we turn the array of strings, into objects.
function fixData(old, location) {
let newData;
console.log("Fixing this data: ");
console.log(old);
//create new array where each element is an object with the seal type and where it is
newData = old.map( seal => {
return {type: seal, location: location};
});
return newData;
} | {
circles
.attr("cx", d => d.x)
.attr("cy", d => d.y)
} | identifier_body |
draw.js | var pickColor = (category) => {
if(category == "pup" || category == "weanling" || category == "yearling") {
return "#220C08"; //chocolate black
}
else if (category == "adult_female") {
return "#9B8576"; //tan
}
else if (category == "adult_male") {
return "#BC8D7D"; //that pink color on their chest
}
else {//juvenile or maturing
return "#EDE9DD"; //cream
}
};
var pickSize = (category) => {
if(category == "pup") {
return 2;
}
else if(category == "weanling") {
return 3;
}
else if(category == "yearling") {
return 5;
}
else if(category == "juvenile") {
return 6;
}
else if(category == "adult_female") {
return 7.5;
}
else if(category == "adult_male") {
return 15;
}
else {//classified as SA
return 7.5;
}
}
//we're going to split up the month by weeks! See what happens
let monthData = function(year, month) {
let censusArray = sealCensus[year][month];
let censuses = {
week1: [],
week2: [],
week3: [],
week4: []
};
//assign censuses to weeks
censusArray.forEach(census => {
let day = census.date.day;
let week = Math.ceil( day/7 );
switch(week) {
case 1:
censusArray.week1.push(census);
break;
case 2:
censusArray.week2.push(census);
break;
case 3:
censusArray.week3.push(census);
break;
case 4:
censusArray.week4.push(census);
break;
case 5:
censusArray.week4.push(census);
break;
}
return censuses;
});
}
//Add circles where the seals are!
// Create SVG element
let width = 1000;
let height = 500;
var addSVG = function() {
debug("in addSVG()");
let row = -1;
//create svg element
var svg = d3.select("#chart")
.append("svg")
.attr("width", width)
.attr("height", height)
.append("g")
.attr("transform", "translate(0,0)");
//get census data acoording to the slider's value/date
var sliderValue = document.getElementById("myRange").value;
//let dataYear = d3.select("#year").value;
var dataYear = 1976 + (sliderValue/12)|0;
var dataMonth = sliderValue%12 < 0 ? sliderValue%12 : 12;
var dataLocation;
var data;
var noCensus = false;
//var data = sealCensus[dataYear][dataMonth];
let censusArray = sealCensus[dataYear][dataMonth];
let census;
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
}
else {
census = []; //no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else {
data = census;
}
data = fixData(data, dataLocation);
console.log("Extracted data for the force simulation: ");
console.log(data);
let xPadding = width/10;
let yPadding = height/10;
//data = [0,1,2,3,4,5,6,7,7,8,9,0,1,2,3,4,5,6,7,8,9,0,9,3,7,9];
//Create and append circle elements element
var circles = svg.selectAll(".seal")
.data(data)
.enter().append("circle")
.attr("class", "seal")
.attr("cx", (d, i) => (i%11) * xPadding)
//.attr("cx", 250)
//.attr("cy", 250)
.attr("cy", (d, i) => (((i/11)|0) + 1) * yPadding)
.attr("r", d => pickSize(d.type))
//.attr("fill", (sliderValue % 2 == 0) ? "blue" : "green");
.attr("fill", d => pickColor(d.type));
//actions for when the slider is updated
//help from http://bl.ocks.org/kbroman/2044064e9517985f2f25
d3.select("input[type=range]#myRange").on("input", function() {
dataYear = 1976 + (this.value/12)|0;
dataMonth = this.value%12 > 0 ? this.value%12 : 12;
console.log("Slider updated to " + dataMonth + " " + dataYear);
//var data = sealCensus[dataYear][dataMonth];
censusArray = sealCensus[dataYear][dataMonth];
if(censusArray != undefined && censusArray != "undefined") {
census = censusArray[ Math.floor( Math.random() * censusArray.length ) ];
noCensus = false;
}
else {
census = []; // no recorded censuses for given month
noCensus = true;
}
if(!noCensus) {
dataLocation = generalLocation(census.location);
data = census.sealCensusLong;
}
else
data = census;
data = fixData(data, dataLocation);
//console.log("New data being displayed: ");
//console.log(data);
//slightly redundant since this is done in autoplay as well
//BUT we also want this to happen when the user picks a year WITHOUT using the autoplayer
d3.select("output#year")
.text(convertSliderValue(this.value));
//update circles with the changes
//help from http://bl.ocks.org/alansmithy/e984477a741bc56db5a5
//let circles = d3.selectAll("circle.seal");
circles.data(data);//.join("circle")
circles.exit().remove(); //remove unneeded circles
circles.enter().append("circle")
.attr("r", d => pickSize(d.type))
.attr("cx", width/2)
.attr("cy", height/2)
.attr("fill", d => pickColor(d.type))
.attr("id", "new")
;//.merge(circles);
//debug("Slider changed to " + year);
//console.log(this);
simulation
.alphaTarget(0.25)
.restart();
simulation.nodes(data).on("tick", ticked);
});
//add text labels
//top left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/12 + ")")
.text("North Point");
//top right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/12 + ")")
.text("Bight Beach North");
//bottom left text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width/3 + ", " + height/2 + ")")
.text("Mid Bight Beach");
//bottom right text
svg.append("text")
.style("text-anchor", "middle")
.attr("transform", "translate(" + width*2/3 + ", " + height/2 + ")")
.text("Ano Point");
//legend container
svg.append("rect")
.attr("fill", "white")
.attr("x", width - 150)
.attr("y", 10)
.attr("height", 150)
.attr("width", 140);
//black is for pups
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#220C08")
.attr("x", width - 140)
.attr("y", 20)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 37)
.text("Pup, Weanling");
//cream is for juveniles
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#EDE9DD")
.attr("x", width - 140)
.attr("y", 50)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 67)
.text("Yearling, Juvenile");
//tan is for females
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#9B8576")
.attr("x", width - 140)
.attr("y", 80)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 97)
.text("Adult Female");
//pink/brown is for males
svg.append("rect")
.attr("stroke", "black")
.attr("fill", "#BC8D7D")
.attr("x", width - 140)
.attr("y", 110)
.attr("height", 25)
.attr("width", 25);
svg.append("text")
.attr("fill", "black")
.attr("x", width - 105)
.attr("y", 127)
.text("Adult Male");
//the simulation is a collection of forces
//about where we want our circles to go
//and how we want our circles to interact
simulation.nodes(data).on("tick", ticked);
function ticked() {
circles
.attr("cx", d => d.x)
.attr("cy", d => d.y)
}
}
// bubble cluster physics
// help from https://youtu.be/NTS7uXOxQeM
var forceX = d3.forceX( d => {
if(d.location == "North Point") { //North Point
return width*1/3;
}
else if(d.location == "Bight Beach North") { //Bight Beach North
return width*2/3;
}
else if(d.location == "Mid Bight Beach") { //Mid Bight Beach
return width*1/3;
}
else {//Other
return width*2/3;
}
})
.strength(0.1);
var forceY = d3.forceY( d => {
if(d.location == "North Point" || d.location == "Bight Beach North") |
else {//d.data[0].long > medianLong
return height*3/4;
}
})
.strength(0.1);
var simulation = d3.forceSimulation()
.force("x", forceX)
.force("y", forceY)
.force("collide", d3.forceCollide( d => pickSize(d.type) ));
//this function specifically exists to modify the data array for the force simulation
//Uncaught TypeError: Cannot create property 'vx' on string 'SA2'
//the force simulation ONLY accepts objects! So we turn the array of strings, into objects.
function fixData(old, location) {
let newData;
console.log("Fixing this data: ");
console.log(old);
//create new array where each element is an object with the seal type and where it is
newData = old.map( seal => {
return {type: seal, location: location};
});
return newData;
} | {
return height/4;
} | conditional_block |
main.rs | extern crate petgraph;
extern crate rand;
extern crate time;
extern crate clap;
use std::cmp::{max, min};
use std::collections::HashSet;
use rand::Rng;
use time::PreciseTime;
enum Method {
Any,
All,
}
fn main() {
let matches = clap::App::new("square-sum")
.about("Calculates solutions to the square sum problem")
.author("Matt Williams")
.arg(clap::Arg::with_name("start")
.short("s")
.long("start")
.value_name("N")
.default_value("0")
.help("The start of the sequence to calculate"))
.arg(clap::Arg::with_name("end")
.short("e")
.long("end")
.value_name("N")
.default_value("100")
.help("The end of the sequence to calculate (exclusive)"))
.arg(clap::Arg::with_name("find")
.short("f")
.long("find")
.value_name("METHOD")
.default_value("any")
.possible_values(&["any", "all"])
.help("Whether to find *all* paths for each graph or *any* path for each graph"))
.get_matches();
let start_time = PreciseTime::now();
let start: usize = matches.value_of("start").unwrap().parse().expect("Could not parse start value");
let limit: usize = matches.value_of("end").unwrap().parse().expect("Could not parse end value");
let method = match matches.value_of("find").unwrap() {
"any" => Method::Any,
"all" => Method::All,
_ => panic!(),
};
let mut g = init_square_sum_path(limit);
let s: Vec<usize> = squares().take_while(|&x| x <= (limit * 2) - 1).collect();
// Prime the graph up to the start of the search
for _ in 1..start {
add_square_sum_node(&mut g, &s);
}
let mut ham = None; // Cache for previous loop's path
match method {
Method::All => {
for _ in start..limit {
add_square_sum_node(&mut g, &s);
let paths = find_all_paths(&g);
if !paths.is_empty() {
let next_num = g.node_count() + 1;
let relevant_squares: Vec<_> = squares()
.skip_while(|&sq| sq <= next_num)
.take_while(|&sq| sq <= (next_num * 2) - 1)
.collect();
let magic_paths: Vec<_> = paths
.iter()
.filter(|&p| {
relevant_squares
.iter()
.any(|sq| *p.first().unwrap() == sq - next_num || *p.last().unwrap() == sq - next_num)
})
.collect();
if magic_paths.is_empty() {
println!("{} has no magic paths", g.node_count());
} else {
println!("{} has {} magic paths", g.node_count(), magic_paths.len());
}
}
}
},
Method::Any => {
for _ in start..limit {
add_square_sum_node(&mut g, &s);
ham = find_any_path(&g, ham);
}
}
}
let end_time = PreciseTime::now();
println!("{} seconds.", start_time.to(end_time).num_seconds());
}
fn find_any_path<N, E, Ty>(
g: &petgraph::Graph<N, E, Ty, usize>,
ham: Option<Vec<usize>>,
) -> Option<Vec<usize>>
where
Ty: petgraph::EdgeType,
{
match find_hamiltonian(g, ham) {
Ok(h) => Some(h),
Err(e) => {
println!("{} fails with {}", g.node_count(), e);
None
}
}
}
fn find_all_paths<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> HashSet<std::vec::Vec<usize>>
where
Ty: petgraph::EdgeType,
{
let mut tries = 0;
let mut failed_tries = 0;
let mut paths = HashSet::new();
loop {
tries += 1;
let ham = match find_hamiltonian(g, None) {
Ok(h) => Some(h),
Err(_) => None,
};
if let Some(mut p) = ham.clone() {
if p.first().unwrap() > p.last().unwrap() {
p.reverse();
}
if paths.insert(p) {
failed_tries = 0;
} else {
failed_tries += 1;
}
} else {
failed_tries += 1;
}
if failed_tries > max(3, (tries as f32 * 0.7) as usize) {
break;
}
}
println!(
"{} has {} paths from {} tries",
g.node_count(),
paths.len(),
tries
);
paths
}
fn integers() -> std::ops::Range<usize> {
1..usize::max_value()
}
fn squares() -> std::iter::Map<std::ops::Range<usize>, fn(usize) -> usize> {
integers().map(|x| x * x)
}
fn init_square_sum_path(n: usize) -> petgraph::Graph<(), (), petgraph::Undirected, usize> {
let num_edges: usize = integers()
.take(n)
.map(|i| {
f64::floor(f64::sqrt(((i * 2) - 1) as f64)) as usize
- f64::floor(f64::sqrt(i as f64)) as usize
})
.sum();
petgraph::Graph::with_capacity(n, num_edges)
}
fn | (
g: &mut petgraph::Graph<(), (), petgraph::Undirected, usize>,
square_numbers: &[usize],
) {
let i = g.node_count() + 1;
g.add_node(());
for sq in square_numbers
.iter()
.skip_while(|&sq| sq <= &i)
.take_while(|&sq| sq <= &((i * 2) - 1))
{
let i_index = petgraph::graph::node_index(i - 1);
let j_index = petgraph::graph::node_index(sq - i - 1);
g.update_edge(i_index, j_index, ());
}
}
struct Path {
path: Vec<usize>,
member: Vec<bool>,
}
impl Path {
fn new(size: usize) -> Path {
Path {
path: Vec::with_capacity(size),
member: vec![false; size],
}
}
fn from_seed(seed: &[usize], size: usize) -> Path {
// TODO check that size >= seed.len()
let mut path = Vec::with_capacity(size);
let mut member = vec![false; size];
for i in seed.iter() {
path.push(i - 1);
member[*i - 1] = true;
}
Path { path, member }
}
fn push(&mut self, node_index: usize) {
self.path.push(node_index);
self.member[node_index] = true;
}
fn len(&self) -> usize {
self.path.len()
}
fn contains(&self, node_index: usize) -> bool {
self.member[node_index]
}
fn backtrack(&mut self, amount: usize) {
let actual_backtrack_amount = min(amount, self.path.len() - 2);
for i in &self.path[(self.path.len() - actual_backtrack_amount)..] {
self.member[*i] = false;
}
let new_size = self.path.len() - actual_backtrack_amount;
self.path.truncate(new_size);
}
fn reverse(&mut self) {
self.path.reverse();
}
fn iter(&self) -> std::slice::Iter<usize> {
self.path.iter()
}
}
fn setup_path<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> Result<Path, &'static str>
where
Ty: petgraph::EdgeType,
{
let mut rng = rand::thread_rng();
let start = petgraph::graph::node_index(rng.gen_range(0, g.node_count()));
let neighbours = g.neighbors(start).collect::<Vec<_>>();
let next = rng.choose(&neighbours).ok_or("Node had no neighbours!")?;
let mut path = Path::new(g.node_count());
path.push(start.index());
path.push(next.index());
Ok(path)
}
fn find_hamiltonian<N, E, Ty>(
g: &petgraph::Graph<N, E, Ty, usize>,
seed: Option<Vec<usize>>,
) -> Result<Vec<usize>, &'static str>
where
Ty: petgraph::EdgeType,
{
if petgraph::algo::connected_components(&g) != 1 {
return Err("Not a fully-connected graph");
}
let reverse_rate = max(100, g.node_count() / 1000);
let backtrack_rate = max(1000, g.node_count() / 100);
let backtrack_amount = max(5, g.node_count() / 10_000);
let reset_rate = g.node_count() * 10; // Must be larger than num nodes
let max_iterations = reset_rate * 5;
let mut rng = rand::thread_rng();
let mut path = match seed {
Some(s) => Path::from_seed(&s, g.node_count()),
None => setup_path(g)?,
};
let mut longest_path: Vec<usize> = Vec::with_capacity(g.node_count());
let mut iteration = 0;
let mut resets = 0;
loop {
// Reverse the path often
if iteration % reverse_rate == 0 {
path.reverse();
}
// Reset the search occasionally
if iteration > reset_rate {
iteration = 1;
resets += 1;
path = setup_path(g)?;
continue;
}
// Backtrack a smidge now and again
if iteration % backtrack_rate == 0 {
path.backtrack(backtrack_amount);
}
// Current vertex is `v`
let v = *path.path
.last()
.ok_or("There should be at least one node in the path")?;
// Create list of possible next vertices
let possible_next_nodes: Vec<_> = g.neighbors(v.into())
.filter(|n| !path.contains(n.index()))
.collect();
// If there are any, choose one randomly and add it to the path
if let Some(v) = rng.choose(&possible_next_nodes) {
path.push(v.index());
} else {
// but we have a new longest path anyway, so set `longest_path`
if path.len() > longest_path.len() {
longest_path = path.path.clone();
}
// choose any neighbour, `n`, of `v` (which must already be in `path`) and reverse path from `n` (not including n) to `v`
let previous_node = path.path[path.len() - 2];
let possible_pivots: Vec<_> = g.neighbors(v.into())
.filter(|n| n.index() != previous_node)
.collect();
if let Some(pivot) = rng.choose(&possible_pivots) {
let pivot_pos = path.iter()
.position(|&v| v == pivot.index())
.ok_or("Pivot must be in the path")?;
path.path[pivot_pos + 1..].reverse();
}
}
// If we've found all nodes, return
if path.len() == g.node_count() {
return Ok(path.iter().map(|&a| a + 1).collect());
}
// If we've 'timed out', fail
if resets * reset_rate > max_iterations {
return Err("Timeout");
}
iteration += 1;
}
}
fn check_sum_squares(vals: &[usize]) -> bool {
let s: Vec<usize> = squares()
.take_while(|&x| x <= (vals.len() * 2) - 1)
.collect();
vals.iter()
.zip(vals.iter().skip(1))
.all(|(&a, &b)| s.contains(&(a + b)))
}
| add_square_sum_node | identifier_name |
main.rs | extern crate petgraph;
extern crate rand;
extern crate time;
extern crate clap;
use std::cmp::{max, min};
use std::collections::HashSet;
use rand::Rng;
use time::PreciseTime;
enum Method {
Any,
All,
}
fn main() {
let matches = clap::App::new("square-sum")
.about("Calculates solutions to the square sum problem")
.author("Matt Williams")
.arg(clap::Arg::with_name("start")
.short("s")
.long("start")
.value_name("N")
.default_value("0")
.help("The start of the sequence to calculate"))
.arg(clap::Arg::with_name("end")
.short("e")
.long("end")
.value_name("N")
.default_value("100")
.help("The end of the sequence to calculate (exclusive)"))
.arg(clap::Arg::with_name("find")
.short("f")
.long("find")
.value_name("METHOD")
.default_value("any")
.possible_values(&["any", "all"])
.help("Whether to find *all* paths for each graph or *any* path for each graph"))
.get_matches();
let start_time = PreciseTime::now();
let start: usize = matches.value_of("start").unwrap().parse().expect("Could not parse start value");
let limit: usize = matches.value_of("end").unwrap().parse().expect("Could not parse end value");
let method = match matches.value_of("find").unwrap() {
"any" => Method::Any,
"all" => Method::All,
_ => panic!(),
};
let mut g = init_square_sum_path(limit);
let s: Vec<usize> = squares().take_while(|&x| x <= (limit * 2) - 1).collect();
// Prime the graph up to the start of the search
for _ in 1..start {
add_square_sum_node(&mut g, &s);
}
let mut ham = None; // Cache for previous loop's path
match method {
Method::All => {
for _ in start..limit {
add_square_sum_node(&mut g, &s);
let paths = find_all_paths(&g);
if !paths.is_empty() {
let next_num = g.node_count() + 1;
let relevant_squares: Vec<_> = squares()
.skip_while(|&sq| sq <= next_num)
.take_while(|&sq| sq <= (next_num * 2) - 1)
.collect();
let magic_paths: Vec<_> = paths
.iter()
.filter(|&p| {
relevant_squares
.iter()
.any(|sq| *p.first().unwrap() == sq - next_num || *p.last().unwrap() == sq - next_num)
})
.collect();
if magic_paths.is_empty() {
println!("{} has no magic paths", g.node_count());
} else {
println!("{} has {} magic paths", g.node_count(), magic_paths.len());
}
}
}
},
Method::Any => {
for _ in start..limit {
add_square_sum_node(&mut g, &s);
ham = find_any_path(&g, ham);
}
}
}
let end_time = PreciseTime::now();
println!("{} seconds.", start_time.to(end_time).num_seconds());
}
fn find_any_path<N, E, Ty>(
g: &petgraph::Graph<N, E, Ty, usize>,
ham: Option<Vec<usize>>,
) -> Option<Vec<usize>>
where
Ty: petgraph::EdgeType,
{
match find_hamiltonian(g, ham) {
Ok(h) => Some(h),
Err(e) => {
println!("{} fails with {}", g.node_count(), e);
None
}
}
}
fn find_all_paths<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> HashSet<std::vec::Vec<usize>>
where
Ty: petgraph::EdgeType,
{
let mut tries = 0;
let mut failed_tries = 0;
let mut paths = HashSet::new();
loop {
tries += 1;
let ham = match find_hamiltonian(g, None) {
Ok(h) => Some(h),
Err(_) => None,
};
if let Some(mut p) = ham.clone() {
if p.first().unwrap() > p.last().unwrap() {
p.reverse();
}
if paths.insert(p) {
failed_tries = 0;
} else {
failed_tries += 1;
}
} else {
failed_tries += 1;
}
if failed_tries > max(3, (tries as f32 * 0.7) as usize) {
break;
}
}
println!(
"{} has {} paths from {} tries",
g.node_count(),
paths.len(),
tries
);
paths
}
fn integers() -> std::ops::Range<usize> {
1..usize::max_value()
}
fn squares() -> std::iter::Map<std::ops::Range<usize>, fn(usize) -> usize> {
integers().map(|x| x * x)
}
fn init_square_sum_path(n: usize) -> petgraph::Graph<(), (), petgraph::Undirected, usize> {
let num_edges: usize = integers()
.take(n)
.map(|i| {
f64::floor(f64::sqrt(((i * 2) - 1) as f64)) as usize
- f64::floor(f64::sqrt(i as f64)) as usize
})
.sum();
petgraph::Graph::with_capacity(n, num_edges)
}
fn add_square_sum_node(
g: &mut petgraph::Graph<(), (), petgraph::Undirected, usize>,
square_numbers: &[usize],
) {
let i = g.node_count() + 1;
g.add_node(());
for sq in square_numbers
.iter()
.skip_while(|&sq| sq <= &i)
.take_while(|&sq| sq <= &((i * 2) - 1))
{
let i_index = petgraph::graph::node_index(i - 1);
let j_index = petgraph::graph::node_index(sq - i - 1);
g.update_edge(i_index, j_index, ());
}
}
struct Path {
path: Vec<usize>,
member: Vec<bool>,
}
impl Path {
fn new(size: usize) -> Path {
Path {
path: Vec::with_capacity(size),
member: vec![false; size],
}
}
fn from_seed(seed: &[usize], size: usize) -> Path |
fn push(&mut self, node_index: usize) {
self.path.push(node_index);
self.member[node_index] = true;
}
fn len(&self) -> usize {
self.path.len()
}
fn contains(&self, node_index: usize) -> bool {
self.member[node_index]
}
fn backtrack(&mut self, amount: usize) {
let actual_backtrack_amount = min(amount, self.path.len() - 2);
for i in &self.path[(self.path.len() - actual_backtrack_amount)..] {
self.member[*i] = false;
}
let new_size = self.path.len() - actual_backtrack_amount;
self.path.truncate(new_size);
}
fn reverse(&mut self) {
self.path.reverse();
}
fn iter(&self) -> std::slice::Iter<usize> {
self.path.iter()
}
}
fn setup_path<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> Result<Path, &'static str>
where
Ty: petgraph::EdgeType,
{
let mut rng = rand::thread_rng();
let start = petgraph::graph::node_index(rng.gen_range(0, g.node_count()));
let neighbours = g.neighbors(start).collect::<Vec<_>>();
let next = rng.choose(&neighbours).ok_or("Node had no neighbours!")?;
let mut path = Path::new(g.node_count());
path.push(start.index());
path.push(next.index());
Ok(path)
}
fn find_hamiltonian<N, E, Ty>(
g: &petgraph::Graph<N, E, Ty, usize>,
seed: Option<Vec<usize>>,
) -> Result<Vec<usize>, &'static str>
where
Ty: petgraph::EdgeType,
{
if petgraph::algo::connected_components(&g) != 1 {
return Err("Not a fully-connected graph");
}
let reverse_rate = max(100, g.node_count() / 1000);
let backtrack_rate = max(1000, g.node_count() / 100);
let backtrack_amount = max(5, g.node_count() / 10_000);
let reset_rate = g.node_count() * 10; // Must be larger than num nodes
let max_iterations = reset_rate * 5;
let mut rng = rand::thread_rng();
let mut path = match seed {
Some(s) => Path::from_seed(&s, g.node_count()),
None => setup_path(g)?,
};
let mut longest_path: Vec<usize> = Vec::with_capacity(g.node_count());
let mut iteration = 0;
let mut resets = 0;
loop {
// Reverse the path often
if iteration % reverse_rate == 0 {
path.reverse();
}
// Reset the search occasionally
if iteration > reset_rate {
iteration = 1;
resets += 1;
path = setup_path(g)?;
continue;
}
// Backtrack a smidge now and again
if iteration % backtrack_rate == 0 {
path.backtrack(backtrack_amount);
}
// Current vertex is `v`
let v = *path.path
.last()
.ok_or("There should be at least one node in the path")?;
// Create list of possible next vertices
let possible_next_nodes: Vec<_> = g.neighbors(v.into())
.filter(|n| !path.contains(n.index()))
.collect();
// If there are any, choose one randomly and add it to the path
if let Some(v) = rng.choose(&possible_next_nodes) {
path.push(v.index());
} else {
// but we have a new longest path anyway, so set `longest_path`
if path.len() > longest_path.len() {
longest_path = path.path.clone();
}
// choose any neighbour, `n`, of `v` (which must already be in `path`) and reverse path from `n` (not including n) to `v`
let previous_node = path.path[path.len() - 2];
let possible_pivots: Vec<_> = g.neighbors(v.into())
.filter(|n| n.index() != previous_node)
.collect();
if let Some(pivot) = rng.choose(&possible_pivots) {
let pivot_pos = path.iter()
.position(|&v| v == pivot.index())
.ok_or("Pivot must be in the path")?;
path.path[pivot_pos + 1..].reverse();
}
}
// If we've found all nodes, return
if path.len() == g.node_count() {
return Ok(path.iter().map(|&a| a + 1).collect());
}
// If we've 'timed out', fail
if resets * reset_rate > max_iterations {
return Err("Timeout");
}
iteration += 1;
}
}
fn check_sum_squares(vals: &[usize]) -> bool {
let s: Vec<usize> = squares()
.take_while(|&x| x <= (vals.len() * 2) - 1)
.collect();
vals.iter()
.zip(vals.iter().skip(1))
.all(|(&a, &b)| s.contains(&(a + b)))
}
| {
// TODO check that size >= seed.len()
let mut path = Vec::with_capacity(size);
let mut member = vec![false; size];
for i in seed.iter() {
path.push(i - 1);
member[*i - 1] = true;
}
Path { path, member }
} | identifier_body |
main.rs | extern crate petgraph;
extern crate rand;
extern crate time;
extern crate clap;
use std::cmp::{max, min};
use std::collections::HashSet;
use rand::Rng;
use time::PreciseTime;
enum Method {
Any,
All,
}
fn main() {
let matches = clap::App::new("square-sum")
.about("Calculates solutions to the square sum problem")
.author("Matt Williams")
.arg(clap::Arg::with_name("start")
.short("s")
.long("start")
.value_name("N")
.default_value("0")
.help("The start of the sequence to calculate"))
.arg(clap::Arg::with_name("end")
.short("e")
.long("end")
.value_name("N")
.default_value("100")
.help("The end of the sequence to calculate (exclusive)"))
.arg(clap::Arg::with_name("find")
.short("f")
.long("find")
.value_name("METHOD")
.default_value("any")
.possible_values(&["any", "all"])
.help("Whether to find *all* paths for each graph or *any* path for each graph"))
.get_matches();
let start_time = PreciseTime::now();
let start: usize = matches.value_of("start").unwrap().parse().expect("Could not parse start value");
let limit: usize = matches.value_of("end").unwrap().parse().expect("Could not parse end value");
let method = match matches.value_of("find").unwrap() {
"any" => Method::Any,
"all" => Method::All,
_ => panic!(),
};
let mut g = init_square_sum_path(limit);
let s: Vec<usize> = squares().take_while(|&x| x <= (limit * 2) - 1).collect();
// Prime the graph up to the start of the search
for _ in 1..start {
add_square_sum_node(&mut g, &s);
}
let mut ham = None; // Cache for previous loop's path
match method {
Method::All => {
for _ in start..limit {
add_square_sum_node(&mut g, &s);
let paths = find_all_paths(&g);
if !paths.is_empty() {
let next_num = g.node_count() + 1;
let relevant_squares: Vec<_> = squares()
.skip_while(|&sq| sq <= next_num)
.take_while(|&sq| sq <= (next_num * 2) - 1)
.collect();
let magic_paths: Vec<_> = paths
.iter()
.filter(|&p| {
relevant_squares
.iter()
.any(|sq| *p.first().unwrap() == sq - next_num || *p.last().unwrap() == sq - next_num)
})
.collect();
if magic_paths.is_empty() {
println!("{} has no magic paths", g.node_count());
} else {
println!("{} has {} magic paths", g.node_count(), magic_paths.len());
}
}
}
},
Method::Any => {
for _ in start..limit {
add_square_sum_node(&mut g, &s);
ham = find_any_path(&g, ham);
}
}
}
let end_time = PreciseTime::now();
println!("{} seconds.", start_time.to(end_time).num_seconds());
}
fn find_any_path<N, E, Ty>(
g: &petgraph::Graph<N, E, Ty, usize>,
ham: Option<Vec<usize>>,
) -> Option<Vec<usize>>
where
Ty: petgraph::EdgeType,
{
match find_hamiltonian(g, ham) {
Ok(h) => Some(h),
Err(e) => {
println!("{} fails with {}", g.node_count(), e);
None
}
}
}
fn find_all_paths<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> HashSet<std::vec::Vec<usize>>
where
Ty: petgraph::EdgeType,
{
let mut tries = 0;
let mut failed_tries = 0;
let mut paths = HashSet::new();
loop {
tries += 1;
let ham = match find_hamiltonian(g, None) {
Ok(h) => Some(h),
Err(_) => None,
};
if let Some(mut p) = ham.clone() {
if p.first().unwrap() > p.last().unwrap() {
p.reverse();
}
if paths.insert(p) {
failed_tries = 0;
} else {
failed_tries += 1;
}
} else {
failed_tries += 1;
}
if failed_tries > max(3, (tries as f32 * 0.7) as usize) {
break;
}
}
println!(
"{} has {} paths from {} tries",
g.node_count(),
paths.len(),
tries
);
paths
}
fn integers() -> std::ops::Range<usize> {
1..usize::max_value()
}
fn squares() -> std::iter::Map<std::ops::Range<usize>, fn(usize) -> usize> {
integers().map(|x| x * x)
}
fn init_square_sum_path(n: usize) -> petgraph::Graph<(), (), petgraph::Undirected, usize> {
let num_edges: usize = integers()
.take(n)
.map(|i| {
f64::floor(f64::sqrt(((i * 2) - 1) as f64)) as usize
- f64::floor(f64::sqrt(i as f64)) as usize
})
.sum();
petgraph::Graph::with_capacity(n, num_edges)
}
fn add_square_sum_node(
g: &mut petgraph::Graph<(), (), petgraph::Undirected, usize>,
square_numbers: &[usize],
) {
let i = g.node_count() + 1;
g.add_node(());
for sq in square_numbers
.iter()
.skip_while(|&sq| sq <= &i)
.take_while(|&sq| sq <= &((i * 2) - 1))
{
let i_index = petgraph::graph::node_index(i - 1);
let j_index = petgraph::graph::node_index(sq - i - 1);
g.update_edge(i_index, j_index, ());
}
}
struct Path {
path: Vec<usize>,
member: Vec<bool>,
}
impl Path {
fn new(size: usize) -> Path {
Path {
path: Vec::with_capacity(size),
member: vec![false; size],
}
}
fn from_seed(seed: &[usize], size: usize) -> Path {
// TODO check that size >= seed.len()
let mut path = Vec::with_capacity(size);
let mut member = vec![false; size];
for i in seed.iter() {
path.push(i - 1);
member[*i - 1] = true;
}
Path { path, member }
}
fn push(&mut self, node_index: usize) {
self.path.push(node_index);
self.member[node_index] = true;
}
fn len(&self) -> usize {
self.path.len()
}
fn contains(&self, node_index: usize) -> bool {
self.member[node_index]
}
fn backtrack(&mut self, amount: usize) {
let actual_backtrack_amount = min(amount, self.path.len() - 2);
for i in &self.path[(self.path.len() - actual_backtrack_amount)..] {
self.member[*i] = false;
}
let new_size = self.path.len() - actual_backtrack_amount; | fn reverse(&mut self) {
self.path.reverse();
}
fn iter(&self) -> std::slice::Iter<usize> {
self.path.iter()
}
}
fn setup_path<N, E, Ty>(g: &petgraph::Graph<N, E, Ty, usize>) -> Result<Path, &'static str>
where
Ty: petgraph::EdgeType,
{
let mut rng = rand::thread_rng();
let start = petgraph::graph::node_index(rng.gen_range(0, g.node_count()));
let neighbours = g.neighbors(start).collect::<Vec<_>>();
let next = rng.choose(&neighbours).ok_or("Node had no neighbours!")?;
let mut path = Path::new(g.node_count());
path.push(start.index());
path.push(next.index());
Ok(path)
}
fn find_hamiltonian<N, E, Ty>(
g: &petgraph::Graph<N, E, Ty, usize>,
seed: Option<Vec<usize>>,
) -> Result<Vec<usize>, &'static str>
where
Ty: petgraph::EdgeType,
{
if petgraph::algo::connected_components(&g) != 1 {
return Err("Not a fully-connected graph");
}
let reverse_rate = max(100, g.node_count() / 1000);
let backtrack_rate = max(1000, g.node_count() / 100);
let backtrack_amount = max(5, g.node_count() / 10_000);
let reset_rate = g.node_count() * 10; // Must be larger than num nodes
let max_iterations = reset_rate * 5;
let mut rng = rand::thread_rng();
let mut path = match seed {
Some(s) => Path::from_seed(&s, g.node_count()),
None => setup_path(g)?,
};
let mut longest_path: Vec<usize> = Vec::with_capacity(g.node_count());
let mut iteration = 0;
let mut resets = 0;
loop {
// Reverse the path often
if iteration % reverse_rate == 0 {
path.reverse();
}
// Reset the search occasionally
if iteration > reset_rate {
iteration = 1;
resets += 1;
path = setup_path(g)?;
continue;
}
// Backtrack a smidge now and again
if iteration % backtrack_rate == 0 {
path.backtrack(backtrack_amount);
}
// Current vertex is `v`
let v = *path.path
.last()
.ok_or("There should be at least one node in the path")?;
// Create list of possible next vertices
let possible_next_nodes: Vec<_> = g.neighbors(v.into())
.filter(|n| !path.contains(n.index()))
.collect();
// If there are any, choose one randomly and add it to the path
if let Some(v) = rng.choose(&possible_next_nodes) {
path.push(v.index());
} else {
// but we have a new longest path anyway, so set `longest_path`
if path.len() > longest_path.len() {
longest_path = path.path.clone();
}
// choose any neighbour, `n`, of `v` (which must already be in `path`) and reverse path from `n` (not including n) to `v`
let previous_node = path.path[path.len() - 2];
let possible_pivots: Vec<_> = g.neighbors(v.into())
.filter(|n| n.index() != previous_node)
.collect();
if let Some(pivot) = rng.choose(&possible_pivots) {
let pivot_pos = path.iter()
.position(|&v| v == pivot.index())
.ok_or("Pivot must be in the path")?;
path.path[pivot_pos + 1..].reverse();
}
}
// If we've found all nodes, return
if path.len() == g.node_count() {
return Ok(path.iter().map(|&a| a + 1).collect());
}
// If we've 'timed out', fail
if resets * reset_rate > max_iterations {
return Err("Timeout");
}
iteration += 1;
}
}
fn check_sum_squares(vals: &[usize]) -> bool {
let s: Vec<usize> = squares()
.take_while(|&x| x <= (vals.len() * 2) - 1)
.collect();
vals.iter()
.zip(vals.iter().skip(1))
.all(|(&a, &b)| s.contains(&(a + b)))
} | self.path.truncate(new_size);
}
| random_line_split |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure | self.delta_ground = delta_ground
self.delta_h_circle = delta_h_circle
self.nl = nl
def find_min_z(zL, step):
# TODO: Ask Bea the reason why this function. Apparently minPercent is not used
# histogram of zL, step = 0.2. minZ is set to the value over 0
# with at maximum 5% of points under it.
mybins = np.arange(np.amin(zL), np.amax(zL), step)
myhisto = np.histogram(zL, mybins)
mycount = myhisto[0]
idx = np.where(mycount > 100)
minZ = myhisto[1][idx[0][0]]
return minZ
def draw_dart(im, points, proj, h_scanner, alpha0, nb_layers=64):
"""im: as an input image just the size is important. As an output
image it contains the dart board
x0,y0,hScanner: scanner position
alpha0: first angle
res_x,res_y : spatial resolution of input image
nb_layers
The output draws a chess board according to the size of the each
"""
# x0, y0 Je l'utilise avec une image smil...
y0, x0 = get_scanner_xy(points, proj)
# 5 pixels / m, 1 px = 20 cm
res_x = proj.projector.res_x
# 5 pixels / m , 1 px = 20 cm
# res_y = proj.projector.res_y
res_alpha = 26.9 / nb_layers
radius_index = {}
for i in range(nb_layers):
angle = alpha0 - (res_alpha * i)
angle_rad = ((90-angle) * np.pi) / 180.0
radius = int(np.round(abs(h_scanner * np.tan(angle_rad) * res_x)))
if radius > (im.getWidth() + im.getHeight()):
radius_index[i] = max(im.getWidth(), im.getHeight())
else:
radius_index[i] = radius
# for each distance to scanner, get the layer index
inverse_radius_index = {}
index = 0
# get the maximum index falling into the image
imsize = max(im.getHeight(), im.getWidth())
while imsize <= radius_index[index]:
index = index + 1
# for this index, get the corresponding radius
# for larger radius assign max_index+1
r = im.getHeight() + im.getWidth()
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
# each r (radius) has its layer number (inverse_radius_index).
# index0 close to horizontal, the maximum index close to vertical
while r > 0:
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
index = index + 1
if index == nb_layers:
break
# close to the scanner (masked zone)
while r >= 0:
inverse_radius_index[r] = nb_layers + 1
r = r - 1
im_label = sm.Image(im, "UINT16")
# Start faster version that generates dart
# convert the dict to a numpy array
max_r = max(inverse_radius_index.keys())
arr_inv_radius = np.zeros(max_r + 1)
for k in inverse_radius_index.keys():
arr_inv_radius[k] = inverse_radius_index[k]
# fill the image with radius and angular sector
nr, nc = smil_2_np(im).shape
np_rows = np.repeat(np.arange(nr), nc).reshape(nr, nc)
np_cols = np.repeat(np.arange(nc), nr).reshape((nr, nc), order='F')
deltax = np_cols - x0
deltay = np_rows - y0
np_theta = np.round(180+(180*np.arctan2(deltay, deltax))/(2*np.pi)).astype(int)
# smil and numpy have swapped axes
np_theta[y0, x0] = 0
np_r = np.sqrt(deltax**2 + deltay**2).astype(int)
np_r = arr_inv_radius[np_r]
im_r = np_2_smil(np_r)
im_theta = np_2_smil(np_theta)
# label 2 partitions
sm.labelWithoutFunctor2Partitions(im_r, im_theta, im_label, sm.CrossSE())
return im_label
def get_scanner_xy(points, proj):
""" get x0,y0 coordinates of the scanner location """
# Find the pixel corresponding to (x=0,y=0)
res_x = proj.projector.res_x # 5 pixels / m, 1 px = 20 cm
res_y = proj.projector.res_y # 5 pixels / m , 1 px = 20 cm
min_x, min_y, min_z = points.min(0)
# the first coordinate is associated to the row coordinate of the image
y0 = int(np.floor((0 - min_y) * res_y).astype(np.int))
# the second coordinate is associated to the column coordinate of the image
x0 = int(np.floor((0 - min_x) * res_x).astype(np.int))
return x0, y0
def compute_circle(points, proj, im_max, nl):
# je l'utilise avec une image smil... (y et x inverse expres)
y0, x0 = get_scanner_xy(points, proj)
# Get the circle where the scanner is located
im_mark = sm.Image(im_max)
im_tmp, im_circle = sm.Image(im_max), sm.Image(im_max)
im_mark.setPixel(x0, y0, 255)
# empty pixels
sm.compare(im_max, "==", 0, 255, 0, im_tmp)
# get the circle
sm.build(im_mark, im_tmp, im_circle, nl)
# Pb circle trop grand (image 900. Restreindre à une fenetre de 10m x 10m
sm.fill(im_tmp, 0)
circle_size = int(5.5 * proj.projector.res_x)
xinit, yinit = x0 - circle_size, y0 - circle_size
sm.copy(im_circle, xinit, yinit, 2*circle_size, 2*circle_size, im_tmp, xinit, yinit)
sm.copy(im_tmp, im_circle)
return im_circle
def dart_interp(points, proj, im, im_interp, nl):
""" input: points 3D. Required to compute the x0,y0 of the scanner
im: the image to be interpolated
imInterp: the output image
nl: neighborhood
Each chess board sector takes the value of the pixel inside, but only if it is alone
"""
# Une classe avec toute cette info serait utile, plutot que de definir ces variables plusieurs fois...
nb_layers = 64
alpha0 = 0
h_scanner = 1.73
# get chess board ## TODO: define immax
im_dart = draw_dart(im, points, proj, h_scanner, alpha0, nb_layers)
mymax = sm.maxVal(im)
sm.compare(im, "==", 0, mymax + 1, im, im)
# propagation de la valeur min (!=0) sur toute la cellule
label_with_measure(im_dart, im, im_interp, "min", nl)
# BMI
sm.compare(im_interp, "==", mymax + 1, 0, im_interp, im_interp) # empty cells have max-value
sm.compare(im, "==", mymax + 1, 0, im, im) # mymax+1 -> 0 again
im_obj = sm.Image(im)
sm.sub(im, im_interp, im_obj)
sm.compare(im, "==", 0, im_interp, im, im_interp) # only empty pixels are interpolated
# return im_chess, imObj
return im_dart, im_obj
def im_dart_interp(points, proj, im_max, nl):
im_interp = sm.Image(im_max)
im_dart, im_obj = dart_interp(points, proj, im_max, im_interp, nl)
return im_interp, im_dart, im_obj
def ground_detection_min_circle(params, points, proj, res_z, im_min, im_max):
"""
Parameters
----------
params: LambdaGDParameters
points: ndarray
proj: Projection
res_z: float
im_min: sm.Image
im_max: sm.Image
"""
my_lambda, nl = params.my_lambda, params.nl
im_ground = sm.Image(im_min)
im_circle = compute_circle(points, proj, im_max, nl)
im_tmp = sm.Image(im_circle)
# NEW:
sm.dilate(im_circle, im_tmp, nl(1 * proj.res_x))
# OLD: sm.dilate(im_circle, im_tmp, nl(4))
sm.compare(im_tmp, ">", im_circle, im_max, 0, im_tmp)
histo = sm.histogram(im_tmp)
del (histo[0])
hist_keys = histo.keys()
hist_val = histo.values()
my_min = 0
for k in range(len(hist_keys)):
if hist_val[k] > 0:
my_min = hist_keys[k]
break
# NEW:
delta = int(params.delta_h_circle * res_z)
sm.threshold(im_tmp, my_min, min(255, my_min + delta), im_ground)
# OLD:
# sm.threshold(im_tmp, my_min, min(255, my_min + 5), im_ground)
sm.sub(im_max, im_min, im_tmp)
# put to zero all the non zero pixels in imGround
sm.compare(im_tmp, ">", int(np.round(0.3 * res_z)), 0, im_ground, im_ground)
# NEW:
if proj.res_x > 1:
# open with se_2x2
se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
sm.open(im_ground, im_ground, se_2x2)
# OLD:
# se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
# sm.open(im_ground, im_ground, se_2x2)
im_interp, im_dart, im_obj = im_dart_interp(points, proj, im_max, nl)
# Lambda flat zones
im_label = sm.Image(im_interp, "UINT32")
sm.lambdaLabel(im_interp, my_lambda, im_label, nl)
label_with_measure(im_label, im_ground, im_ground, "max", nl)
# todo: parametrize the 3 value
sm.compare(im_obj, ">", 3, 0, im_ground, im_ground)
# empty pixels set to 0 again
sm.compare(im_max, "==", 0, 0, im_ground, im_ground)
# evaluate
# conf_mat, conf_mat_norm = evaluate(im_class, im_ground, selectedId, condensedId)
return im_ground, im_interp
def evaluate_2d_pred(im_class, im_pred, selected_id, condensed_id, classes, savedir, filename):
"""
Auxiliary function to evaluate prediction in 2D
Parameters
----------
im_class: ndarray
im_pred: ndarray
selected_id: list
condensed_id: list
classes: list
savedir: str
filename: str
"""
from smutsia.utils.scores import get_confusion_matrix, condense_confusion_matrix, normalize_confusion_matrix
from smutsia.utils.viz import plot_confusion_matrix
# 40: "road", 44: "parking", 48: "sidewalk", 49: "other-ground", 10: "car", 50: "building"
sm.compare(im_pred, ">", 0, 40, 0, im_pred)
np_gt = smil_2_np(im_class)
np_pred = smil_2_np(im_pred)
conf_mat1, conf_mat_norm1 = get_confusion_matrix(np_gt.flat, np_pred.flat, selected_id)
conf_mat = condense_confusion_matrix(conf_mat1, selected_id, condensed_id)
conf_mat = conf_mat.astype(int)
conf_mat_norm = normalize_confusion_matrix(conf_mat)
plot_confusion_matrix(conf_mat_norm, classes=classes, normalize=True,
savefig=os.path.join(savedir, filename + '.eps'),
title='Confusion Matrix ' + filename.upper())
def dart_ground_detection(cloud,
threshold,
delta_ground,
delta_h_circle,
res_x,
res_y,
res_z,
savedir='',
select_id=None,
condense_id=None,
classes=None):
"""
Parameters
----------
cloud: PyntCloud
threshold: int
delta_ground: float
delta_h_circle: float
res_x: float
res_y: float
res_z: float
savedir: str
path to which save plots of the method
select_id: list
id to use to compute 2D confusion matrix
condense_id: list
id to use to compute 2D confusion matrix
classes: list
list with corresponding names of classes
"""
params = LambdaGDParameters(my_lambda=threshold, delta_ground=delta_ground, delta_h_circle=delta_h_circle)
points = cloud.xyz
labels = cloud.points.labels.values.astype(int)
proj = Projection(proj_type='linear', res_x=res_x, res_y=res_y)
# select the criteria to use to find min z
# z_min = np.percentile(p_z, percent)
# min_z = find_min_z(points[:, 2], 0.2, 5)
min_z = find_min_z(points[:, 2], 0.2)
im_min, im_max, im_acc, im_class = project_img(proj, points=points, labels=labels, res_z=res_z, min_z=min_z,
filter_outliers=True)
im_ground, im_interp = ground_detection_min_circle(params=params,
points=points,
proj=proj,
res_z=res_z,
im_min=im_min,
im_max=im_max)
if len(savedir) > 0:
from smutsia.utils.viz import inspect_missclass
fn = ''
if hasattr(cloud, 'sequence'):
fn += cloud.sequence + '_'
if hasattr(cloud, 'filename'):
fn += cloud.filename + '_'
fn += '{}'
sm.write(im_min, os.path.join(savedir, fn.format('min.png')))
sm.write(im_max, os.path.join(savedir, fn.format('max.png')))
sm.write(im_acc, os.path.join(savedir, fn.format('acc.png')))
sm.write(im_class, os.path.join(savedir, fn.format('class.png')))
bike_ids = [11, 15, 31, 32]
car_ids = [10, 13, 18]
build_id = [50]
inspect_missclass(im_class, im_ground, bike_ids, im_max, im_min, savedir, fn.format('bikes'))
inspect_missclass(im_class, im_ground, car_ids, im_max, im_min, savedir, fn.format('cars'))
inspect_missclass(im_class, im_ground, build_id, im_max, im_min, savedir, fn.format('build'))
if condense_id is not None and select_id is not None:
# evaluate score on 2D image
evaluate_2d_pred(im_class, im_ground,
selected_id=select_id, condensed_id=condense_id, classes=classes,
savedir=savedir, filename=fn.format('2D'))
im_label = sm.Image(im_min, "UINT16")
sm.lambdaLabel(im_min, 1, im_label, params.nl)
im_ground2 = sm.Image(im_ground)
label_with_measure(im_label, im_ground, im_ground2, "max", params.nl)
im_delta = sm.Image(im_ground)
sm.compare(im_ground, ">", 0, 4, 0, im_delta)
sm.compare(im_ground2, ">", im_ground, 1, im_delta, im_delta)
sm.copy(im_ground2, im_ground)
ground = back_projection_ground(proj=proj, points=points, res_z=res_z, im_min=im_min, im_ground=im_ground,
delta_ground=delta_ground, min_z=min_z, im_delta=im_delta)
return ground
if __name__ == "__main__":
from glob import glob
from smutsia.utils.semantickitti import load_pyntcloud, SemanticKittiConfig
from smutsia.utils.viz import plot_cloud
from definitions import SEMANTICKITTI_PATH, SEMANTICKITTI_CONFIG
skconfig = SemanticKittiConfig(SEMANTICKITTI_CONFIG)
basedir = os.path.join(SEMANTICKITTI_PATH, '08', 'velodyne')
files = sorted(glob(os.path.join(basedir, '*.bin')))
idx = 3721
pc = load_pyntcloud(files[idx], add_label=True)
labels = pc.points['labels'].values
plot_cloud(pc.xyz, skconfig.label2color[labels], rgb=True, notebook=False)
out = dart_ground_detection(cloud=pc,
threshold=2,
delta_ground=0.05,
delta_h_circle=0.5,
res_x=5,
res_y=5,
res_z=10)
plot_cloud(pc.xyz, scalars=out, notebook=False)
print("END") |
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_ground=0.2, delta_h_circle=0.5, nl=sm.HexSE()):
self.my_lambda = my_lambda | random_line_split |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_ground=0.2, delta_h_circle=0.5, nl=sm.HexSE()):
self.my_lambda = my_lambda
self.delta_ground = delta_ground
self.delta_h_circle = delta_h_circle
self.nl = nl
def find_min_z(zL, step):
# TODO: Ask Bea the reason why this function. Apparently minPercent is not used
# histogram of zL, step = 0.2. minZ is set to the value over 0
# with at maximum 5% of points under it.
mybins = np.arange(np.amin(zL), np.amax(zL), step)
myhisto = np.histogram(zL, mybins)
mycount = myhisto[0]
idx = np.where(mycount > 100)
minZ = myhisto[1][idx[0][0]]
return minZ
def draw_dart(im, points, proj, h_scanner, alpha0, nb_layers=64):
"""im: as an input image just the size is important. As an output
image it contains the dart board
x0,y0,hScanner: scanner position
alpha0: first angle
res_x,res_y : spatial resolution of input image
nb_layers
The output draws a chess board according to the size of the each
"""
# x0, y0 Je l'utilise avec une image smil...
y0, x0 = get_scanner_xy(points, proj)
# 5 pixels / m, 1 px = 20 cm
res_x = proj.projector.res_x
# 5 pixels / m , 1 px = 20 cm
# res_y = proj.projector.res_y
res_alpha = 26.9 / nb_layers
radius_index = {}
for i in range(nb_layers):
angle = alpha0 - (res_alpha * i)
angle_rad = ((90-angle) * np.pi) / 180.0
radius = int(np.round(abs(h_scanner * np.tan(angle_rad) * res_x)))
if radius > (im.getWidth() + im.getHeight()):
radius_index[i] = max(im.getWidth(), im.getHeight())
else:
|
# for each distance to scanner, get the layer index
inverse_radius_index = {}
index = 0
# get the maximum index falling into the image
imsize = max(im.getHeight(), im.getWidth())
while imsize <= radius_index[index]:
index = index + 1
# for this index, get the corresponding radius
# for larger radius assign max_index+1
r = im.getHeight() + im.getWidth()
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
# each r (radius) has its layer number (inverse_radius_index).
# index0 close to horizontal, the maximum index close to vertical
while r > 0:
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
index = index + 1
if index == nb_layers:
break
# close to the scanner (masked zone)
while r >= 0:
inverse_radius_index[r] = nb_layers + 1
r = r - 1
im_label = sm.Image(im, "UINT16")
# Start faster version that generates dart
# convert the dict to a numpy array
max_r = max(inverse_radius_index.keys())
arr_inv_radius = np.zeros(max_r + 1)
for k in inverse_radius_index.keys():
arr_inv_radius[k] = inverse_radius_index[k]
# fill the image with radius and angular sector
nr, nc = smil_2_np(im).shape
np_rows = np.repeat(np.arange(nr), nc).reshape(nr, nc)
np_cols = np.repeat(np.arange(nc), nr).reshape((nr, nc), order='F')
deltax = np_cols - x0
deltay = np_rows - y0
np_theta = np.round(180+(180*np.arctan2(deltay, deltax))/(2*np.pi)).astype(int)
# smil and numpy have swapped axes
np_theta[y0, x0] = 0
np_r = np.sqrt(deltax**2 + deltay**2).astype(int)
np_r = arr_inv_radius[np_r]
im_r = np_2_smil(np_r)
im_theta = np_2_smil(np_theta)
# label 2 partitions
sm.labelWithoutFunctor2Partitions(im_r, im_theta, im_label, sm.CrossSE())
return im_label
def get_scanner_xy(points, proj):
""" get x0,y0 coordinates of the scanner location """
# Find the pixel corresponding to (x=0,y=0)
res_x = proj.projector.res_x # 5 pixels / m, 1 px = 20 cm
res_y = proj.projector.res_y # 5 pixels / m , 1 px = 20 cm
min_x, min_y, min_z = points.min(0)
# the first coordinate is associated to the row coordinate of the image
y0 = int(np.floor((0 - min_y) * res_y).astype(np.int))
# the second coordinate is associated to the column coordinate of the image
x0 = int(np.floor((0 - min_x) * res_x).astype(np.int))
return x0, y0
def compute_circle(points, proj, im_max, nl):
# je l'utilise avec une image smil... (y et x inverse expres)
y0, x0 = get_scanner_xy(points, proj)
# Get the circle where the scanner is located
im_mark = sm.Image(im_max)
im_tmp, im_circle = sm.Image(im_max), sm.Image(im_max)
im_mark.setPixel(x0, y0, 255)
# empty pixels
sm.compare(im_max, "==", 0, 255, 0, im_tmp)
# get the circle
sm.build(im_mark, im_tmp, im_circle, nl)
# Pb circle trop grand (image 900. Restreindre à une fenetre de 10m x 10m
sm.fill(im_tmp, 0)
circle_size = int(5.5 * proj.projector.res_x)
xinit, yinit = x0 - circle_size, y0 - circle_size
sm.copy(im_circle, xinit, yinit, 2*circle_size, 2*circle_size, im_tmp, xinit, yinit)
sm.copy(im_tmp, im_circle)
return im_circle
def dart_interp(points, proj, im, im_interp, nl):
""" input: points 3D. Required to compute the x0,y0 of the scanner
im: the image to be interpolated
imInterp: the output image
nl: neighborhood
Each chess board sector takes the value of the pixel inside, but only if it is alone
"""
# Une classe avec toute cette info serait utile, plutot que de definir ces variables plusieurs fois...
nb_layers = 64
alpha0 = 0
h_scanner = 1.73
# get chess board ## TODO: define immax
im_dart = draw_dart(im, points, proj, h_scanner, alpha0, nb_layers)
mymax = sm.maxVal(im)
sm.compare(im, "==", 0, mymax + 1, im, im)
# propagation de la valeur min (!=0) sur toute la cellule
label_with_measure(im_dart, im, im_interp, "min", nl)
# BMI
sm.compare(im_interp, "==", mymax + 1, 0, im_interp, im_interp) # empty cells have max-value
sm.compare(im, "==", mymax + 1, 0, im, im) # mymax+1 -> 0 again
im_obj = sm.Image(im)
sm.sub(im, im_interp, im_obj)
sm.compare(im, "==", 0, im_interp, im, im_interp) # only empty pixels are interpolated
# return im_chess, imObj
return im_dart, im_obj
def im_dart_interp(points, proj, im_max, nl):
im_interp = sm.Image(im_max)
im_dart, im_obj = dart_interp(points, proj, im_max, im_interp, nl)
return im_interp, im_dart, im_obj
def ground_detection_min_circle(params, points, proj, res_z, im_min, im_max):
"""
Parameters
----------
params: LambdaGDParameters
points: ndarray
proj: Projection
res_z: float
im_min: sm.Image
im_max: sm.Image
"""
my_lambda, nl = params.my_lambda, params.nl
im_ground = sm.Image(im_min)
im_circle = compute_circle(points, proj, im_max, nl)
im_tmp = sm.Image(im_circle)
# NEW:
sm.dilate(im_circle, im_tmp, nl(1 * proj.res_x))
# OLD: sm.dilate(im_circle, im_tmp, nl(4))
sm.compare(im_tmp, ">", im_circle, im_max, 0, im_tmp)
histo = sm.histogram(im_tmp)
del (histo[0])
hist_keys = histo.keys()
hist_val = histo.values()
my_min = 0
for k in range(len(hist_keys)):
if hist_val[k] > 0:
my_min = hist_keys[k]
break
# NEW:
delta = int(params.delta_h_circle * res_z)
sm.threshold(im_tmp, my_min, min(255, my_min + delta), im_ground)
# OLD:
# sm.threshold(im_tmp, my_min, min(255, my_min + 5), im_ground)
sm.sub(im_max, im_min, im_tmp)
# put to zero all the non zero pixels in imGround
sm.compare(im_tmp, ">", int(np.round(0.3 * res_z)), 0, im_ground, im_ground)
# NEW:
if proj.res_x > 1:
# open with se_2x2
se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
sm.open(im_ground, im_ground, se_2x2)
# OLD:
# se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
# sm.open(im_ground, im_ground, se_2x2)
im_interp, im_dart, im_obj = im_dart_interp(points, proj, im_max, nl)
# Lambda flat zones
im_label = sm.Image(im_interp, "UINT32")
sm.lambdaLabel(im_interp, my_lambda, im_label, nl)
label_with_measure(im_label, im_ground, im_ground, "max", nl)
# todo: parametrize the 3 value
sm.compare(im_obj, ">", 3, 0, im_ground, im_ground)
# empty pixels set to 0 again
sm.compare(im_max, "==", 0, 0, im_ground, im_ground)
# evaluate
# conf_mat, conf_mat_norm = evaluate(im_class, im_ground, selectedId, condensedId)
return im_ground, im_interp
def evaluate_2d_pred(im_class, im_pred, selected_id, condensed_id, classes, savedir, filename):
"""
Auxiliary function to evaluate prediction in 2D
Parameters
----------
im_class: ndarray
im_pred: ndarray
selected_id: list
condensed_id: list
classes: list
savedir: str
filename: str
"""
from smutsia.utils.scores import get_confusion_matrix, condense_confusion_matrix, normalize_confusion_matrix
from smutsia.utils.viz import plot_confusion_matrix
# 40: "road", 44: "parking", 48: "sidewalk", 49: "other-ground", 10: "car", 50: "building"
sm.compare(im_pred, ">", 0, 40, 0, im_pred)
np_gt = smil_2_np(im_class)
np_pred = smil_2_np(im_pred)
conf_mat1, conf_mat_norm1 = get_confusion_matrix(np_gt.flat, np_pred.flat, selected_id)
conf_mat = condense_confusion_matrix(conf_mat1, selected_id, condensed_id)
conf_mat = conf_mat.astype(int)
conf_mat_norm = normalize_confusion_matrix(conf_mat)
plot_confusion_matrix(conf_mat_norm, classes=classes, normalize=True,
savefig=os.path.join(savedir, filename + '.eps'),
title='Confusion Matrix ' + filename.upper())
def dart_ground_detection(cloud,
threshold,
delta_ground,
delta_h_circle,
res_x,
res_y,
res_z,
savedir='',
select_id=None,
condense_id=None,
classes=None):
"""
Parameters
----------
cloud: PyntCloud
threshold: int
delta_ground: float
delta_h_circle: float
res_x: float
res_y: float
res_z: float
savedir: str
path to which save plots of the method
select_id: list
id to use to compute 2D confusion matrix
condense_id: list
id to use to compute 2D confusion matrix
classes: list
list with corresponding names of classes
"""
params = LambdaGDParameters(my_lambda=threshold, delta_ground=delta_ground, delta_h_circle=delta_h_circle)
points = cloud.xyz
labels = cloud.points.labels.values.astype(int)
proj = Projection(proj_type='linear', res_x=res_x, res_y=res_y)
# select the criteria to use to find min z
# z_min = np.percentile(p_z, percent)
# min_z = find_min_z(points[:, 2], 0.2, 5)
min_z = find_min_z(points[:, 2], 0.2)
im_min, im_max, im_acc, im_class = project_img(proj, points=points, labels=labels, res_z=res_z, min_z=min_z,
filter_outliers=True)
im_ground, im_interp = ground_detection_min_circle(params=params,
points=points,
proj=proj,
res_z=res_z,
im_min=im_min,
im_max=im_max)
if len(savedir) > 0:
from smutsia.utils.viz import inspect_missclass
fn = ''
if hasattr(cloud, 'sequence'):
fn += cloud.sequence + '_'
if hasattr(cloud, 'filename'):
fn += cloud.filename + '_'
fn += '{}'
sm.write(im_min, os.path.join(savedir, fn.format('min.png')))
sm.write(im_max, os.path.join(savedir, fn.format('max.png')))
sm.write(im_acc, os.path.join(savedir, fn.format('acc.png')))
sm.write(im_class, os.path.join(savedir, fn.format('class.png')))
bike_ids = [11, 15, 31, 32]
car_ids = [10, 13, 18]
build_id = [50]
inspect_missclass(im_class, im_ground, bike_ids, im_max, im_min, savedir, fn.format('bikes'))
inspect_missclass(im_class, im_ground, car_ids, im_max, im_min, savedir, fn.format('cars'))
inspect_missclass(im_class, im_ground, build_id, im_max, im_min, savedir, fn.format('build'))
if condense_id is not None and select_id is not None:
# evaluate score on 2D image
evaluate_2d_pred(im_class, im_ground,
selected_id=select_id, condensed_id=condense_id, classes=classes,
savedir=savedir, filename=fn.format('2D'))
im_label = sm.Image(im_min, "UINT16")
sm.lambdaLabel(im_min, 1, im_label, params.nl)
im_ground2 = sm.Image(im_ground)
label_with_measure(im_label, im_ground, im_ground2, "max", params.nl)
im_delta = sm.Image(im_ground)
sm.compare(im_ground, ">", 0, 4, 0, im_delta)
sm.compare(im_ground2, ">", im_ground, 1, im_delta, im_delta)
sm.copy(im_ground2, im_ground)
ground = back_projection_ground(proj=proj, points=points, res_z=res_z, im_min=im_min, im_ground=im_ground,
delta_ground=delta_ground, min_z=min_z, im_delta=im_delta)
return ground
if __name__ == "__main__":
from glob import glob
from smutsia.utils.semantickitti import load_pyntcloud, SemanticKittiConfig
from smutsia.utils.viz import plot_cloud
from definitions import SEMANTICKITTI_PATH, SEMANTICKITTI_CONFIG
skconfig = SemanticKittiConfig(SEMANTICKITTI_CONFIG)
basedir = os.path.join(SEMANTICKITTI_PATH, '08', 'velodyne')
files = sorted(glob(os.path.join(basedir, '*.bin')))
idx = 3721
pc = load_pyntcloud(files[idx], add_label=True)
labels = pc.points['labels'].values
plot_cloud(pc.xyz, skconfig.label2color[labels], rgb=True, notebook=False)
out = dart_ground_detection(cloud=pc,
threshold=2,
delta_ground=0.05,
delta_h_circle=0.5,
res_x=5,
res_y=5,
res_z=10)
plot_cloud(pc.xyz, scalars=out, notebook=False)
print("END")
| radius_index[i] = radius | conditional_block |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_ground=0.2, delta_h_circle=0.5, nl=sm.HexSE()):
self.my_lambda = my_lambda
self.delta_ground = delta_ground
self.delta_h_circle = delta_h_circle
self.nl = nl
def find_min_z(zL, step):
# TODO: Ask Bea the reason why this function. Apparently minPercent is not used
# histogram of zL, step = 0.2. minZ is set to the value over 0
# with at maximum 5% of points under it.
mybins = np.arange(np.amin(zL), np.amax(zL), step)
myhisto = np.histogram(zL, mybins)
mycount = myhisto[0]
idx = np.where(mycount > 100)
minZ = myhisto[1][idx[0][0]]
return minZ
def draw_dart(im, points, proj, h_scanner, alpha0, nb_layers=64):
|
def get_scanner_xy(points, proj):
""" get x0,y0 coordinates of the scanner location """
# Find the pixel corresponding to (x=0,y=0)
res_x = proj.projector.res_x # 5 pixels / m, 1 px = 20 cm
res_y = proj.projector.res_y # 5 pixels / m , 1 px = 20 cm
min_x, min_y, min_z = points.min(0)
# the first coordinate is associated to the row coordinate of the image
y0 = int(np.floor((0 - min_y) * res_y).astype(np.int))
# the second coordinate is associated to the column coordinate of the image
x0 = int(np.floor((0 - min_x) * res_x).astype(np.int))
return x0, y0
def compute_circle(points, proj, im_max, nl):
# je l'utilise avec une image smil... (y et x inverse expres)
y0, x0 = get_scanner_xy(points, proj)
# Get the circle where the scanner is located
im_mark = sm.Image(im_max)
im_tmp, im_circle = sm.Image(im_max), sm.Image(im_max)
im_mark.setPixel(x0, y0, 255)
# empty pixels
sm.compare(im_max, "==", 0, 255, 0, im_tmp)
# get the circle
sm.build(im_mark, im_tmp, im_circle, nl)
# Pb circle trop grand (image 900. Restreindre à une fenetre de 10m x 10m
sm.fill(im_tmp, 0)
circle_size = int(5.5 * proj.projector.res_x)
xinit, yinit = x0 - circle_size, y0 - circle_size
sm.copy(im_circle, xinit, yinit, 2*circle_size, 2*circle_size, im_tmp, xinit, yinit)
sm.copy(im_tmp, im_circle)
return im_circle
def dart_interp(points, proj, im, im_interp, nl):
""" input: points 3D. Required to compute the x0,y0 of the scanner
im: the image to be interpolated
imInterp: the output image
nl: neighborhood
Each chess board sector takes the value of the pixel inside, but only if it is alone
"""
# Une classe avec toute cette info serait utile, plutot que de definir ces variables plusieurs fois...
nb_layers = 64
alpha0 = 0
h_scanner = 1.73
# get chess board ## TODO: define immax
im_dart = draw_dart(im, points, proj, h_scanner, alpha0, nb_layers)
mymax = sm.maxVal(im)
sm.compare(im, "==", 0, mymax + 1, im, im)
# propagation de la valeur min (!=0) sur toute la cellule
label_with_measure(im_dart, im, im_interp, "min", nl)
# BMI
sm.compare(im_interp, "==", mymax + 1, 0, im_interp, im_interp) # empty cells have max-value
sm.compare(im, "==", mymax + 1, 0, im, im) # mymax+1 -> 0 again
im_obj = sm.Image(im)
sm.sub(im, im_interp, im_obj)
sm.compare(im, "==", 0, im_interp, im, im_interp) # only empty pixels are interpolated
# return im_chess, imObj
return im_dart, im_obj
def im_dart_interp(points, proj, im_max, nl):
im_interp = sm.Image(im_max)
im_dart, im_obj = dart_interp(points, proj, im_max, im_interp, nl)
return im_interp, im_dart, im_obj
def ground_detection_min_circle(params, points, proj, res_z, im_min, im_max):
"""
Parameters
----------
params: LambdaGDParameters
points: ndarray
proj: Projection
res_z: float
im_min: sm.Image
im_max: sm.Image
"""
my_lambda, nl = params.my_lambda, params.nl
im_ground = sm.Image(im_min)
im_circle = compute_circle(points, proj, im_max, nl)
im_tmp = sm.Image(im_circle)
# NEW:
sm.dilate(im_circle, im_tmp, nl(1 * proj.res_x))
# OLD: sm.dilate(im_circle, im_tmp, nl(4))
sm.compare(im_tmp, ">", im_circle, im_max, 0, im_tmp)
histo = sm.histogram(im_tmp)
del (histo[0])
hist_keys = histo.keys()
hist_val = histo.values()
my_min = 0
for k in range(len(hist_keys)):
if hist_val[k] > 0:
my_min = hist_keys[k]
break
# NEW:
delta = int(params.delta_h_circle * res_z)
sm.threshold(im_tmp, my_min, min(255, my_min + delta), im_ground)
# OLD:
# sm.threshold(im_tmp, my_min, min(255, my_min + 5), im_ground)
sm.sub(im_max, im_min, im_tmp)
# put to zero all the non zero pixels in imGround
sm.compare(im_tmp, ">", int(np.round(0.3 * res_z)), 0, im_ground, im_ground)
# NEW:
if proj.res_x > 1:
# open with se_2x2
se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
sm.open(im_ground, im_ground, se_2x2)
# OLD:
# se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
# sm.open(im_ground, im_ground, se_2x2)
im_interp, im_dart, im_obj = im_dart_interp(points, proj, im_max, nl)
# Lambda flat zones
im_label = sm.Image(im_interp, "UINT32")
sm.lambdaLabel(im_interp, my_lambda, im_label, nl)
label_with_measure(im_label, im_ground, im_ground, "max", nl)
# todo: parametrize the 3 value
sm.compare(im_obj, ">", 3, 0, im_ground, im_ground)
# empty pixels set to 0 again
sm.compare(im_max, "==", 0, 0, im_ground, im_ground)
# evaluate
# conf_mat, conf_mat_norm = evaluate(im_class, im_ground, selectedId, condensedId)
return im_ground, im_interp
def evaluate_2d_pred(im_class, im_pred, selected_id, condensed_id, classes, savedir, filename):
"""
Auxiliary function to evaluate prediction in 2D
Parameters
----------
im_class: ndarray
im_pred: ndarray
selected_id: list
condensed_id: list
classes: list
savedir: str
filename: str
"""
from smutsia.utils.scores import get_confusion_matrix, condense_confusion_matrix, normalize_confusion_matrix
from smutsia.utils.viz import plot_confusion_matrix
# 40: "road", 44: "parking", 48: "sidewalk", 49: "other-ground", 10: "car", 50: "building"
sm.compare(im_pred, ">", 0, 40, 0, im_pred)
np_gt = smil_2_np(im_class)
np_pred = smil_2_np(im_pred)
conf_mat1, conf_mat_norm1 = get_confusion_matrix(np_gt.flat, np_pred.flat, selected_id)
conf_mat = condense_confusion_matrix(conf_mat1, selected_id, condensed_id)
conf_mat = conf_mat.astype(int)
conf_mat_norm = normalize_confusion_matrix(conf_mat)
plot_confusion_matrix(conf_mat_norm, classes=classes, normalize=True,
savefig=os.path.join(savedir, filename + '.eps'),
title='Confusion Matrix ' + filename.upper())
def dart_ground_detection(cloud,
threshold,
delta_ground,
delta_h_circle,
res_x,
res_y,
res_z,
savedir='',
select_id=None,
condense_id=None,
classes=None):
"""
Parameters
----------
cloud: PyntCloud
threshold: int
delta_ground: float
delta_h_circle: float
res_x: float
res_y: float
res_z: float
savedir: str
path to which save plots of the method
select_id: list
id to use to compute 2D confusion matrix
condense_id: list
id to use to compute 2D confusion matrix
classes: list
list with corresponding names of classes
"""
params = LambdaGDParameters(my_lambda=threshold, delta_ground=delta_ground, delta_h_circle=delta_h_circle)
points = cloud.xyz
labels = cloud.points.labels.values.astype(int)
proj = Projection(proj_type='linear', res_x=res_x, res_y=res_y)
# select the criteria to use to find min z
# z_min = np.percentile(p_z, percent)
# min_z = find_min_z(points[:, 2], 0.2, 5)
min_z = find_min_z(points[:, 2], 0.2)
im_min, im_max, im_acc, im_class = project_img(proj, points=points, labels=labels, res_z=res_z, min_z=min_z,
filter_outliers=True)
im_ground, im_interp = ground_detection_min_circle(params=params,
points=points,
proj=proj,
res_z=res_z,
im_min=im_min,
im_max=im_max)
if len(savedir) > 0:
from smutsia.utils.viz import inspect_missclass
fn = ''
if hasattr(cloud, 'sequence'):
fn += cloud.sequence + '_'
if hasattr(cloud, 'filename'):
fn += cloud.filename + '_'
fn += '{}'
sm.write(im_min, os.path.join(savedir, fn.format('min.png')))
sm.write(im_max, os.path.join(savedir, fn.format('max.png')))
sm.write(im_acc, os.path.join(savedir, fn.format('acc.png')))
sm.write(im_class, os.path.join(savedir, fn.format('class.png')))
bike_ids = [11, 15, 31, 32]
car_ids = [10, 13, 18]
build_id = [50]
inspect_missclass(im_class, im_ground, bike_ids, im_max, im_min, savedir, fn.format('bikes'))
inspect_missclass(im_class, im_ground, car_ids, im_max, im_min, savedir, fn.format('cars'))
inspect_missclass(im_class, im_ground, build_id, im_max, im_min, savedir, fn.format('build'))
if condense_id is not None and select_id is not None:
# evaluate score on 2D image
evaluate_2d_pred(im_class, im_ground,
selected_id=select_id, condensed_id=condense_id, classes=classes,
savedir=savedir, filename=fn.format('2D'))
im_label = sm.Image(im_min, "UINT16")
sm.lambdaLabel(im_min, 1, im_label, params.nl)
im_ground2 = sm.Image(im_ground)
label_with_measure(im_label, im_ground, im_ground2, "max", params.nl)
im_delta = sm.Image(im_ground)
sm.compare(im_ground, ">", 0, 4, 0, im_delta)
sm.compare(im_ground2, ">", im_ground, 1, im_delta, im_delta)
sm.copy(im_ground2, im_ground)
ground = back_projection_ground(proj=proj, points=points, res_z=res_z, im_min=im_min, im_ground=im_ground,
delta_ground=delta_ground, min_z=min_z, im_delta=im_delta)
return ground
if __name__ == "__main__":
from glob import glob
from smutsia.utils.semantickitti import load_pyntcloud, SemanticKittiConfig
from smutsia.utils.viz import plot_cloud
from definitions import SEMANTICKITTI_PATH, SEMANTICKITTI_CONFIG
skconfig = SemanticKittiConfig(SEMANTICKITTI_CONFIG)
basedir = os.path.join(SEMANTICKITTI_PATH, '08', 'velodyne')
files = sorted(glob(os.path.join(basedir, '*.bin')))
idx = 3721
pc = load_pyntcloud(files[idx], add_label=True)
labels = pc.points['labels'].values
plot_cloud(pc.xyz, skconfig.label2color[labels], rgb=True, notebook=False)
out = dart_ground_detection(cloud=pc,
threshold=2,
delta_ground=0.05,
delta_h_circle=0.5,
res_x=5,
res_y=5,
res_z=10)
plot_cloud(pc.xyz, scalars=out, notebook=False)
print("END")
| """im: as an input image just the size is important. As an output
image it contains the dart board
x0,y0,hScanner: scanner position
alpha0: first angle
res_x,res_y : spatial resolution of input image
nb_layers
The output draws a chess board according to the size of the each
"""
# x0, y0 Je l'utilise avec une image smil...
y0, x0 = get_scanner_xy(points, proj)
# 5 pixels / m, 1 px = 20 cm
res_x = proj.projector.res_x
# 5 pixels / m , 1 px = 20 cm
# res_y = proj.projector.res_y
res_alpha = 26.9 / nb_layers
radius_index = {}
for i in range(nb_layers):
angle = alpha0 - (res_alpha * i)
angle_rad = ((90-angle) * np.pi) / 180.0
radius = int(np.round(abs(h_scanner * np.tan(angle_rad) * res_x)))
if radius > (im.getWidth() + im.getHeight()):
radius_index[i] = max(im.getWidth(), im.getHeight())
else:
radius_index[i] = radius
# for each distance to scanner, get the layer index
inverse_radius_index = {}
index = 0
# get the maximum index falling into the image
imsize = max(im.getHeight(), im.getWidth())
while imsize <= radius_index[index]:
index = index + 1
# for this index, get the corresponding radius
# for larger radius assign max_index+1
r = im.getHeight() + im.getWidth()
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
# each r (radius) has its layer number (inverse_radius_index).
# index0 close to horizontal, the maximum index close to vertical
while r > 0:
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
index = index + 1
if index == nb_layers:
break
# close to the scanner (masked zone)
while r >= 0:
inverse_radius_index[r] = nb_layers + 1
r = r - 1
im_label = sm.Image(im, "UINT16")
# Start faster version that generates dart
# convert the dict to a numpy array
max_r = max(inverse_radius_index.keys())
arr_inv_radius = np.zeros(max_r + 1)
for k in inverse_radius_index.keys():
arr_inv_radius[k] = inverse_radius_index[k]
# fill the image with radius and angular sector
nr, nc = smil_2_np(im).shape
np_rows = np.repeat(np.arange(nr), nc).reshape(nr, nc)
np_cols = np.repeat(np.arange(nc), nr).reshape((nr, nc), order='F')
deltax = np_cols - x0
deltay = np_rows - y0
np_theta = np.round(180+(180*np.arctan2(deltay, deltax))/(2*np.pi)).astype(int)
# smil and numpy have swapped axes
np_theta[y0, x0] = 0
np_r = np.sqrt(deltax**2 + deltay**2).astype(int)
np_r = arr_inv_radius[np_r]
im_r = np_2_smil(np_r)
im_theta = np_2_smil(np_theta)
# label 2 partitions
sm.labelWithoutFunctor2Partitions(im_r, im_theta, im_label, sm.CrossSE())
return im_label | identifier_body |
_bev_qfz.py | import os
import smilPython as sm
import numpy as np
from pyntcloud import PyntCloud
from smutsia.point_cloud.projection import Projection, project_img, back_projection_ground
from smutsia.utils.image import np_2_smil, smil_2_np, label_with_measure
class LambdaGDParameters:
def __init__(self, my_lambda=2, delta_ground=0.2, delta_h_circle=0.5, nl=sm.HexSE()):
self.my_lambda = my_lambda
self.delta_ground = delta_ground
self.delta_h_circle = delta_h_circle
self.nl = nl
def | (zL, step):
# TODO: Ask Bea the reason why this function. Apparently minPercent is not used
# histogram of zL, step = 0.2. minZ is set to the value over 0
# with at maximum 5% of points under it.
mybins = np.arange(np.amin(zL), np.amax(zL), step)
myhisto = np.histogram(zL, mybins)
mycount = myhisto[0]
idx = np.where(mycount > 100)
minZ = myhisto[1][idx[0][0]]
return minZ
def draw_dart(im, points, proj, h_scanner, alpha0, nb_layers=64):
"""im: as an input image just the size is important. As an output
image it contains the dart board
x0,y0,hScanner: scanner position
alpha0: first angle
res_x,res_y : spatial resolution of input image
nb_layers
The output draws a chess board according to the size of the each
"""
# x0, y0 Je l'utilise avec une image smil...
y0, x0 = get_scanner_xy(points, proj)
# 5 pixels / m, 1 px = 20 cm
res_x = proj.projector.res_x
# 5 pixels / m , 1 px = 20 cm
# res_y = proj.projector.res_y
res_alpha = 26.9 / nb_layers
radius_index = {}
for i in range(nb_layers):
angle = alpha0 - (res_alpha * i)
angle_rad = ((90-angle) * np.pi) / 180.0
radius = int(np.round(abs(h_scanner * np.tan(angle_rad) * res_x)))
if radius > (im.getWidth() + im.getHeight()):
radius_index[i] = max(im.getWidth(), im.getHeight())
else:
radius_index[i] = radius
# for each distance to scanner, get the layer index
inverse_radius_index = {}
index = 0
# get the maximum index falling into the image
imsize = max(im.getHeight(), im.getWidth())
while imsize <= radius_index[index]:
index = index + 1
# for this index, get the corresponding radius
# for larger radius assign max_index+1
r = im.getHeight() + im.getWidth()
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
# each r (radius) has its layer number (inverse_radius_index).
# index0 close to horizontal, the maximum index close to vertical
while r > 0:
while r > radius_index[index]:
inverse_radius_index[r] = index + 1
r = r - 1
index = index + 1
if index == nb_layers:
break
# close to the scanner (masked zone)
while r >= 0:
inverse_radius_index[r] = nb_layers + 1
r = r - 1
im_label = sm.Image(im, "UINT16")
# Start faster version that generates dart
# convert the dict to a numpy array
max_r = max(inverse_radius_index.keys())
arr_inv_radius = np.zeros(max_r + 1)
for k in inverse_radius_index.keys():
arr_inv_radius[k] = inverse_radius_index[k]
# fill the image with radius and angular sector
nr, nc = smil_2_np(im).shape
np_rows = np.repeat(np.arange(nr), nc).reshape(nr, nc)
np_cols = np.repeat(np.arange(nc), nr).reshape((nr, nc), order='F')
deltax = np_cols - x0
deltay = np_rows - y0
np_theta = np.round(180+(180*np.arctan2(deltay, deltax))/(2*np.pi)).astype(int)
# smil and numpy have swapped axes
np_theta[y0, x0] = 0
np_r = np.sqrt(deltax**2 + deltay**2).astype(int)
np_r = arr_inv_radius[np_r]
im_r = np_2_smil(np_r)
im_theta = np_2_smil(np_theta)
# label 2 partitions
sm.labelWithoutFunctor2Partitions(im_r, im_theta, im_label, sm.CrossSE())
return im_label
def get_scanner_xy(points, proj):
""" get x0,y0 coordinates of the scanner location """
# Find the pixel corresponding to (x=0,y=0)
res_x = proj.projector.res_x # 5 pixels / m, 1 px = 20 cm
res_y = proj.projector.res_y # 5 pixels / m , 1 px = 20 cm
min_x, min_y, min_z = points.min(0)
# the first coordinate is associated to the row coordinate of the image
y0 = int(np.floor((0 - min_y) * res_y).astype(np.int))
# the second coordinate is associated to the column coordinate of the image
x0 = int(np.floor((0 - min_x) * res_x).astype(np.int))
return x0, y0
def compute_circle(points, proj, im_max, nl):
# je l'utilise avec une image smil... (y et x inverse expres)
y0, x0 = get_scanner_xy(points, proj)
# Get the circle where the scanner is located
im_mark = sm.Image(im_max)
im_tmp, im_circle = sm.Image(im_max), sm.Image(im_max)
im_mark.setPixel(x0, y0, 255)
# empty pixels
sm.compare(im_max, "==", 0, 255, 0, im_tmp)
# get the circle
sm.build(im_mark, im_tmp, im_circle, nl)
# Pb circle trop grand (image 900. Restreindre à une fenetre de 10m x 10m
sm.fill(im_tmp, 0)
circle_size = int(5.5 * proj.projector.res_x)
xinit, yinit = x0 - circle_size, y0 - circle_size
sm.copy(im_circle, xinit, yinit, 2*circle_size, 2*circle_size, im_tmp, xinit, yinit)
sm.copy(im_tmp, im_circle)
return im_circle
def dart_interp(points, proj, im, im_interp, nl):
""" input: points 3D. Required to compute the x0,y0 of the scanner
im: the image to be interpolated
imInterp: the output image
nl: neighborhood
Each chess board sector takes the value of the pixel inside, but only if it is alone
"""
# Une classe avec toute cette info serait utile, plutot que de definir ces variables plusieurs fois...
nb_layers = 64
alpha0 = 0
h_scanner = 1.73
# get chess board ## TODO: define immax
im_dart = draw_dart(im, points, proj, h_scanner, alpha0, nb_layers)
mymax = sm.maxVal(im)
sm.compare(im, "==", 0, mymax + 1, im, im)
# propagation de la valeur min (!=0) sur toute la cellule
label_with_measure(im_dart, im, im_interp, "min", nl)
# BMI
sm.compare(im_interp, "==", mymax + 1, 0, im_interp, im_interp) # empty cells have max-value
sm.compare(im, "==", mymax + 1, 0, im, im) # mymax+1 -> 0 again
im_obj = sm.Image(im)
sm.sub(im, im_interp, im_obj)
sm.compare(im, "==", 0, im_interp, im, im_interp) # only empty pixels are interpolated
# return im_chess, imObj
return im_dart, im_obj
def im_dart_interp(points, proj, im_max, nl):
im_interp = sm.Image(im_max)
im_dart, im_obj = dart_interp(points, proj, im_max, im_interp, nl)
return im_interp, im_dart, im_obj
def ground_detection_min_circle(params, points, proj, res_z, im_min, im_max):
"""
Parameters
----------
params: LambdaGDParameters
points: ndarray
proj: Projection
res_z: float
im_min: sm.Image
im_max: sm.Image
"""
my_lambda, nl = params.my_lambda, params.nl
im_ground = sm.Image(im_min)
im_circle = compute_circle(points, proj, im_max, nl)
im_tmp = sm.Image(im_circle)
# NEW:
sm.dilate(im_circle, im_tmp, nl(1 * proj.res_x))
# OLD: sm.dilate(im_circle, im_tmp, nl(4))
sm.compare(im_tmp, ">", im_circle, im_max, 0, im_tmp)
histo = sm.histogram(im_tmp)
del (histo[0])
hist_keys = histo.keys()
hist_val = histo.values()
my_min = 0
for k in range(len(hist_keys)):
if hist_val[k] > 0:
my_min = hist_keys[k]
break
# NEW:
delta = int(params.delta_h_circle * res_z)
sm.threshold(im_tmp, my_min, min(255, my_min + delta), im_ground)
# OLD:
# sm.threshold(im_tmp, my_min, min(255, my_min + 5), im_ground)
sm.sub(im_max, im_min, im_tmp)
# put to zero all the non zero pixels in imGround
sm.compare(im_tmp, ">", int(np.round(0.3 * res_z)), 0, im_ground, im_ground)
# NEW:
if proj.res_x > 1:
# open with se_2x2
se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
sm.open(im_ground, im_ground, se_2x2)
# OLD:
# se_2x2 = sm.StrElt(True, [0, 1, 2, 3])
# sm.open(im_ground, im_ground, se_2x2)
im_interp, im_dart, im_obj = im_dart_interp(points, proj, im_max, nl)
# Lambda flat zones
im_label = sm.Image(im_interp, "UINT32")
sm.lambdaLabel(im_interp, my_lambda, im_label, nl)
label_with_measure(im_label, im_ground, im_ground, "max", nl)
# todo: parametrize the 3 value
sm.compare(im_obj, ">", 3, 0, im_ground, im_ground)
# empty pixels set to 0 again
sm.compare(im_max, "==", 0, 0, im_ground, im_ground)
# evaluate
# conf_mat, conf_mat_norm = evaluate(im_class, im_ground, selectedId, condensedId)
return im_ground, im_interp
def evaluate_2d_pred(im_class, im_pred, selected_id, condensed_id, classes, savedir, filename):
"""
Auxiliary function to evaluate prediction in 2D
Parameters
----------
im_class: ndarray
im_pred: ndarray
selected_id: list
condensed_id: list
classes: list
savedir: str
filename: str
"""
from smutsia.utils.scores import get_confusion_matrix, condense_confusion_matrix, normalize_confusion_matrix
from smutsia.utils.viz import plot_confusion_matrix
# 40: "road", 44: "parking", 48: "sidewalk", 49: "other-ground", 10: "car", 50: "building"
sm.compare(im_pred, ">", 0, 40, 0, im_pred)
np_gt = smil_2_np(im_class)
np_pred = smil_2_np(im_pred)
conf_mat1, conf_mat_norm1 = get_confusion_matrix(np_gt.flat, np_pred.flat, selected_id)
conf_mat = condense_confusion_matrix(conf_mat1, selected_id, condensed_id)
conf_mat = conf_mat.astype(int)
conf_mat_norm = normalize_confusion_matrix(conf_mat)
plot_confusion_matrix(conf_mat_norm, classes=classes, normalize=True,
savefig=os.path.join(savedir, filename + '.eps'),
title='Confusion Matrix ' + filename.upper())
def dart_ground_detection(cloud,
threshold,
delta_ground,
delta_h_circle,
res_x,
res_y,
res_z,
savedir='',
select_id=None,
condense_id=None,
classes=None):
"""
Parameters
----------
cloud: PyntCloud
threshold: int
delta_ground: float
delta_h_circle: float
res_x: float
res_y: float
res_z: float
savedir: str
path to which save plots of the method
select_id: list
id to use to compute 2D confusion matrix
condense_id: list
id to use to compute 2D confusion matrix
classes: list
list with corresponding names of classes
"""
params = LambdaGDParameters(my_lambda=threshold, delta_ground=delta_ground, delta_h_circle=delta_h_circle)
points = cloud.xyz
labels = cloud.points.labels.values.astype(int)
proj = Projection(proj_type='linear', res_x=res_x, res_y=res_y)
# select the criteria to use to find min z
# z_min = np.percentile(p_z, percent)
# min_z = find_min_z(points[:, 2], 0.2, 5)
min_z = find_min_z(points[:, 2], 0.2)
im_min, im_max, im_acc, im_class = project_img(proj, points=points, labels=labels, res_z=res_z, min_z=min_z,
filter_outliers=True)
im_ground, im_interp = ground_detection_min_circle(params=params,
points=points,
proj=proj,
res_z=res_z,
im_min=im_min,
im_max=im_max)
if len(savedir) > 0:
from smutsia.utils.viz import inspect_missclass
fn = ''
if hasattr(cloud, 'sequence'):
fn += cloud.sequence + '_'
if hasattr(cloud, 'filename'):
fn += cloud.filename + '_'
fn += '{}'
sm.write(im_min, os.path.join(savedir, fn.format('min.png')))
sm.write(im_max, os.path.join(savedir, fn.format('max.png')))
sm.write(im_acc, os.path.join(savedir, fn.format('acc.png')))
sm.write(im_class, os.path.join(savedir, fn.format('class.png')))
bike_ids = [11, 15, 31, 32]
car_ids = [10, 13, 18]
build_id = [50]
inspect_missclass(im_class, im_ground, bike_ids, im_max, im_min, savedir, fn.format('bikes'))
inspect_missclass(im_class, im_ground, car_ids, im_max, im_min, savedir, fn.format('cars'))
inspect_missclass(im_class, im_ground, build_id, im_max, im_min, savedir, fn.format('build'))
if condense_id is not None and select_id is not None:
# evaluate score on 2D image
evaluate_2d_pred(im_class, im_ground,
selected_id=select_id, condensed_id=condense_id, classes=classes,
savedir=savedir, filename=fn.format('2D'))
im_label = sm.Image(im_min, "UINT16")
sm.lambdaLabel(im_min, 1, im_label, params.nl)
im_ground2 = sm.Image(im_ground)
label_with_measure(im_label, im_ground, im_ground2, "max", params.nl)
im_delta = sm.Image(im_ground)
sm.compare(im_ground, ">", 0, 4, 0, im_delta)
sm.compare(im_ground2, ">", im_ground, 1, im_delta, im_delta)
sm.copy(im_ground2, im_ground)
ground = back_projection_ground(proj=proj, points=points, res_z=res_z, im_min=im_min, im_ground=im_ground,
delta_ground=delta_ground, min_z=min_z, im_delta=im_delta)
return ground
if __name__ == "__main__":
from glob import glob
from smutsia.utils.semantickitti import load_pyntcloud, SemanticKittiConfig
from smutsia.utils.viz import plot_cloud
from definitions import SEMANTICKITTI_PATH, SEMANTICKITTI_CONFIG
skconfig = SemanticKittiConfig(SEMANTICKITTI_CONFIG)
basedir = os.path.join(SEMANTICKITTI_PATH, '08', 'velodyne')
files = sorted(glob(os.path.join(basedir, '*.bin')))
idx = 3721
pc = load_pyntcloud(files[idx], add_label=True)
labels = pc.points['labels'].values
plot_cloud(pc.xyz, skconfig.label2color[labels], rgb=True, notebook=False)
out = dart_ground_detection(cloud=pc,
threshold=2,
delta_ground=0.05,
delta_h_circle=0.5,
res_x=5,
res_y=5,
res_z=10)
plot_cloud(pc.xyz, scalars=out, notebook=False)
print("END")
| find_min_z | identifier_name |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY = (150,150,150)
WHITE = (255, 255, 255)
RED = (255, 0, 0)
GREEN = (0, 255, 0)
BLUE = (0, 0, 255)
def normalize(v):
return v / np.linalg.norm(v)
class Particle(pygame.sprite.Sprite):
def __init__(self, imgfile, radius, mass=1.0):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load(imgfile)
self.image = pygame.transform.scale(self.image, (radius, radius))
self.state = [0, 0, 0, 0]
self.mass = mass
self.t = 0
self.radius = radius
self.gravity = -9.8
def set_pos(self, pos):
self.state[0:2] = pos
return self
def set_vel(self, vel):
self.state[2:] = vel
return self
def update(self, dt):
self.t += dt
self.state[3] += dt * self.gravity
self.state[0] += self.state[2] * dt
self.state[1] += self.state[3] * dt
def move_by(self, delta):
self.state[0:2] = np.add(self.pos, delta)
return self
def draw(self, surface):
rect = self.image.get_rect()
rect.center = (self.state[0], win_height-self.state[1]) # Flipping y
surface.blit(self.image, rect)
def pprint(self):
print 'Particle', self.state
class Wheel(pygame.sprite.Sprite):
def __init__(self, center, radius, mass=1000):
pygame.sprite.Sprite.__init__(self)
self.state = np.zeros(4)
self.state[0:2] = np.zeros(2) # position
self.state[2] = 1 # angular velocity
self.state[3] = 0 # angular momentum
self.lines = []
self.mass = mass
self.t = 0
self.center = center
self.radius = radius
self.angle = 0
self.torque = 0
def set_vel(self, vel):
self.state[2] = vel
return self
def update(self, dt):
self.t += dt
def draw(self, surface):
self.angle += self.state[2]
for i in range(0,316, 45):
x = self.center[0] + math.cos(math.radians(self.angle + i)) * self.radius
y = self.center[1] + math.sin(math.radians(self.angle + i)) * self.radius
if (len(self.lines) <= 7):
self.lines.append(pygame.draw.line(surface, BLACK, self.center, (x,y), 5))
else:
self.lines[i/45] = pygame.draw.line(surface, BLACK, self.center, (x,y), 5)
self.circle = pygame.draw.circle(surface, BLACK, self.center, (int)(self.radius*.7), 10)
def pprint(self):
print 'Wheel', self.state
class World:
def __init__(self, height, width):
self.particles = []
self.wheels =[]
self.height = height
self.width = width
self.e = .2 # Coefficient of restitution
def add(self, imgfile, radius, mass=1.0):
particle = Particle(imgfile, radius, mass)
self.particles.append(particle)
return particle
def addWheel(self, centre, radius):
wheel = Wheel(centre, radius)
self.wheels.append(wheel)
return wheel
def pprint(self):
print '#particles', len(self.particles)
for d in self.particles:
d.pprint()
def draw(self, screen):
for d in self.particles:
d.draw(screen)
for w in self.wheels:
w.draw(screen)
def update(self, dt):
t = []
for d in self.particles:
d.update(dt)
for i in range(0, len(self.particles)):
self.check_for_collision(i)
try:
for j in range(len(self.wheels)):
t.append(threading.Thread(target=self.check_wheel_collision(i, j)))
t[i].start()
except:
print "Collision detection threading error"
for x in t:
x.join()
self.check_outside_screen()
def check_outside_screen(self):
self.particles = [x for x in self.particles if self.outside_screen(x)]
def outside_screen(self, particle):
if (particle.state[0] < -particle.radius):
return False
elif (particle.state[0] > win_width + particle.radius):
return False
elif (particle.state[1] < -particle.radius):
return False
else:
return True
# check for inter-particle collision
def check_for_collision(self, i):
if (self.particles[i].state[0] - self.particles[i].radius <= 0 or
self.particles[i].state[0] + self.particles[i].radius >= 800):
self.particles[i].state[2] *= -1*self.e
elif (self.particles[i].state[1] - self.particles[i].radius <= 0):
self.particles[i].state[3] = 0
for j in range(i+1, len(self.particles)):
if i == j:
return
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.particles[j].state[0:2])
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.particles[j].radius
if dist_ij > radius_i + radius_j:
return
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = np.array(self.particles[j].state[2:])
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.particles[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
vel_j_aftercollision = vel_j - n_ij * J / mass_j
self.particles[i].set_vel(vel_i_aftercollision)
self.particles[j].set_vel(vel_j_aftercollision)
# check for particle - wheel collision
def check_wheel_collision(self, i, j):
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.wheels[j].center)
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.wheels[j].radius*.7
if dist_ij > radius_i + radius_j:
return
# ensures particles do not cross wheel boundaries
dist_in = -(dist_ij - radius_j - radius_i) # distance inside of wheel
theta = math.asin((pos_i[1] - pos_j[1]) /dist_ij) #angle from centre of wheel
newPos = [(math.cos(theta) * dist_in), (math.sin(theta) * dist_in)]
# makes sure to flip new x pos to the left
if pos_i[0] < pos_j[0]:
newPos[0] *= -1
# updates the particle position
self.particles[i].set_pos([pos_i[0] + newPos[0], pos_i[1] + newPos[1]])
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = 0
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.wheels[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
self.particles[i].set_vel(vel_i_aftercollision)
# ANGULAR COLISION #
# detect collision with lines on wheel
for x in range(len(self.wheels[j].lines)):
line = self.wheels[j].lines[x]
A = self.wheels[j].center
C = self.particles[i].state[0:2]
if A == line.topleft:
B = line.bottomright
elif A == line.bottomright:
B = line.topleft
elif A == line.topright:
B = line.bottomleft
else:
B = line.topright
dist = np.sqrt((B[0]-A[0])**2+(B[1]-A[1])**2)
Dx = (B[0]-A[0])/dist
Dy = (B[1]-A[1])/dist
t = Dx*(C[0]-A[0])+Dy*(C[1]-A[1])
Ex = t*Dx+A[0]
Ey = t*Dy+A[1]
dist2 = np.sqrt((Ex-C[0])**2+(Ey-C[1])**2)
#if (dist2 < self.particles[i].radius):
#Do conservation of momentum for angular momentum
def main():
# initializing pygame
pygame.init()
clock = pygame.time.Clock()
# top left corner is (0,0)
screen = pygame.display.set_mode((win_width, win_height))
pygame.display.set_caption('Water Wheel of Fortune')
world = World(win_height, win_width)
world.addWheel([400, 300], 200)
# spout position and width for when rain == false
spoutPos = 380
spoutWidth = 40
pause = False
rain = False # particles randomly appear at top along widith when true, spout when false
maxP = 100 # maximum number of particles
dt = 0.3
pRadius = 10 # smallest radius is 3, anything smaller is invisible
pMass = 1
# timer to create more particles
pygame.time.set_timer(pygame.USEREVENT + 1, 50)
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
print "\n\nPress P key to pause or resume"
print "Press R key to toggle rain or spout"
print "Press A or D keys to move spout left or right\n\n"
| event = pygame.event.poll()
if event.type == pygame.QUIT:
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_q:
pygame.quit()
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_p:
pause = not pause
elif event.type == pygame.KEYDOWN and event.key == pygame.K_r:
rain = not rain
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
elif event.type == pygame.USEREVENT + 1 and not pause:
# new particle generation
if (len(world.particles) < maxP):
# make sure particle is within the walls
newPos = np.array([rand.uniform(range[0],range[1]), win_height])
newVel = np.array([0, 0])
world.add('waterdroplet.png', pRadius, pMass).set_pos(newPos).set_vel(newVel)
# moves spout left
elif event.type == pygame.KEYDOWN and event.key == pygame.K_a and not rain:
if spoutPos - 10 >= 0: # stops spout at edge
spoutPos -= 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
# moves spout right
elif event.type == pygame.KEYDOWN and event.key == pygame.K_d and not rain:
if spoutPos + 10 + spoutWidth*1.5 <= win_width: # stops spout at edge
spoutPos += 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
else:
pass
if not pause:
# Clear the background, and draw the sprites
screen.fill(WHITE)
world.draw(screen)
world.update(dt)
if not rain:
pygame.draw.rect(screen, GREY, (spoutPos, 0, spoutWidth*1.5, 30))
pygame.display.update()
if __name__ == '__main__':
main() | while True:
# 30 fps
if not pause:
clock.tick(30)
| random_line_split |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY = (150,150,150)
WHITE = (255, 255, 255)
RED = (255, 0, 0)
GREEN = (0, 255, 0)
BLUE = (0, 0, 255)
def normalize(v):
return v / np.linalg.norm(v)
class Particle(pygame.sprite.Sprite):
def __init__(self, imgfile, radius, mass=1.0):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load(imgfile)
self.image = pygame.transform.scale(self.image, (radius, radius))
self.state = [0, 0, 0, 0]
self.mass = mass
self.t = 0
self.radius = radius
self.gravity = -9.8
def set_pos(self, pos):
self.state[0:2] = pos
return self
def set_vel(self, vel):
self.state[2:] = vel
return self
def update(self, dt):
self.t += dt
self.state[3] += dt * self.gravity
self.state[0] += self.state[2] * dt
self.state[1] += self.state[3] * dt
def move_by(self, delta):
self.state[0:2] = np.add(self.pos, delta)
return self
def draw(self, surface):
rect = self.image.get_rect()
rect.center = (self.state[0], win_height-self.state[1]) # Flipping y
surface.blit(self.image, rect)
def pprint(self):
print 'Particle', self.state
class Wheel(pygame.sprite.Sprite):
def __init__(self, center, radius, mass=1000):
pygame.sprite.Sprite.__init__(self)
self.state = np.zeros(4)
self.state[0:2] = np.zeros(2) # position
self.state[2] = 1 # angular velocity
self.state[3] = 0 # angular momentum
self.lines = []
self.mass = mass
self.t = 0
self.center = center
self.radius = radius
self.angle = 0
self.torque = 0
def set_vel(self, vel):
self.state[2] = vel
return self
def update(self, dt):
self.t += dt
def draw(self, surface):
self.angle += self.state[2]
for i in range(0,316, 45):
x = self.center[0] + math.cos(math.radians(self.angle + i)) * self.radius
y = self.center[1] + math.sin(math.radians(self.angle + i)) * self.radius
if (len(self.lines) <= 7):
self.lines.append(pygame.draw.line(surface, BLACK, self.center, (x,y), 5))
else:
self.lines[i/45] = pygame.draw.line(surface, BLACK, self.center, (x,y), 5)
self.circle = pygame.draw.circle(surface, BLACK, self.center, (int)(self.radius*.7), 10)
def pprint(self):
print 'Wheel', self.state
class World:
def __init__(self, height, width):
self.particles = []
self.wheels =[]
self.height = height
self.width = width
self.e = .2 # Coefficient of restitution
def add(self, imgfile, radius, mass=1.0):
particle = Particle(imgfile, radius, mass)
self.particles.append(particle)
return particle
def addWheel(self, centre, radius):
wheel = Wheel(centre, radius)
self.wheels.append(wheel)
return wheel
def pprint(self):
print '#particles', len(self.particles)
for d in self.particles:
d.pprint()
def draw(self, screen):
for d in self.particles:
d.draw(screen)
for w in self.wheels:
w.draw(screen)
def update(self, dt):
t = []
for d in self.particles:
d.update(dt)
for i in range(0, len(self.particles)):
self.check_for_collision(i)
try:
for j in range(len(self.wheels)):
t.append(threading.Thread(target=self.check_wheel_collision(i, j)))
t[i].start()
except:
print "Collision detection threading error"
for x in t:
x.join()
self.check_outside_screen()
def check_outside_screen(self):
self.particles = [x for x in self.particles if self.outside_screen(x)]
def outside_screen(self, particle):
if (particle.state[0] < -particle.radius):
return False
elif (particle.state[0] > win_width + particle.radius):
return False
elif (particle.state[1] < -particle.radius):
return False
else:
return True
# check for inter-particle collision
def check_for_collision(self, i):
if (self.particles[i].state[0] - self.particles[i].radius <= 0 or
self.particles[i].state[0] + self.particles[i].radius >= 800):
self.particles[i].state[2] *= -1*self.e
elif (self.particles[i].state[1] - self.particles[i].radius <= 0):
self.particles[i].state[3] = 0
for j in range(i+1, len(self.particles)):
if i == j:
return
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.particles[j].state[0:2])
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.particles[j].radius
if dist_ij > radius_i + radius_j:
return
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = np.array(self.particles[j].state[2:])
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.particles[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
vel_j_aftercollision = vel_j - n_ij * J / mass_j
self.particles[i].set_vel(vel_i_aftercollision)
self.particles[j].set_vel(vel_j_aftercollision)
# check for particle - wheel collision
def check_wheel_collision(self, i, j):
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.wheels[j].center)
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.wheels[j].radius*.7
if dist_ij > radius_i + radius_j:
return
# ensures particles do not cross wheel boundaries
dist_in = -(dist_ij - radius_j - radius_i) # distance inside of wheel
theta = math.asin((pos_i[1] - pos_j[1]) /dist_ij) #angle from centre of wheel
newPos = [(math.cos(theta) * dist_in), (math.sin(theta) * dist_in)]
# makes sure to flip new x pos to the left
if pos_i[0] < pos_j[0]:
newPos[0] *= -1
# updates the particle position
self.particles[i].set_pos([pos_i[0] + newPos[0], pos_i[1] + newPos[1]])
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = 0
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.wheels[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
self.particles[i].set_vel(vel_i_aftercollision)
# ANGULAR COLISION #
# detect collision with lines on wheel
for x in range(len(self.wheels[j].lines)):
line = self.wheels[j].lines[x]
A = self.wheels[j].center
C = self.particles[i].state[0:2]
if A == line.topleft:
B = line.bottomright
elif A == line.bottomright:
B = line.topleft
elif A == line.topright:
B = line.bottomleft
else:
B = line.topright
dist = np.sqrt((B[0]-A[0])**2+(B[1]-A[1])**2)
Dx = (B[0]-A[0])/dist
Dy = (B[1]-A[1])/dist
t = Dx*(C[0]-A[0])+Dy*(C[1]-A[1])
Ex = t*Dx+A[0]
Ey = t*Dy+A[1]
dist2 = np.sqrt((Ex-C[0])**2+(Ey-C[1])**2)
#if (dist2 < self.particles[i].radius):
#Do conservation of momentum for angular momentum
def main():
# initializing pygame
pygame.init()
clock = pygame.time.Clock()
# top left corner is (0,0)
screen = pygame.display.set_mode((win_width, win_height))
pygame.display.set_caption('Water Wheel of Fortune')
world = World(win_height, win_width)
world.addWheel([400, 300], 200)
# spout position and width for when rain == false
spoutPos = 380
spoutWidth = 40
pause = False
rain = False # particles randomly appear at top along widith when true, spout when false
maxP = 100 # maximum number of particles
dt = 0.3
pRadius = 10 # smallest radius is 3, anything smaller is invisible
pMass = 1
# timer to create more particles
pygame.time.set_timer(pygame.USEREVENT + 1, 50)
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
print "\n\nPress P key to pause or resume"
print "Press R key to toggle rain or spout"
print "Press A or D keys to move spout left or right\n\n"
while True:
# 30 fps
|
if __name__ == '__main__':
main() | if not pause:
clock.tick(30)
event = pygame.event.poll()
if event.type == pygame.QUIT:
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_q:
pygame.quit()
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_p:
pause = not pause
elif event.type == pygame.KEYDOWN and event.key == pygame.K_r:
rain = not rain
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
elif event.type == pygame.USEREVENT + 1 and not pause:
# new particle generation
if (len(world.particles) < maxP):
# make sure particle is within the walls
newPos = np.array([rand.uniform(range[0],range[1]), win_height])
newVel = np.array([0, 0])
world.add('waterdroplet.png', pRadius, pMass).set_pos(newPos).set_vel(newVel)
# moves spout left
elif event.type == pygame.KEYDOWN and event.key == pygame.K_a and not rain:
if spoutPos - 10 >= 0: # stops spout at edge
spoutPos -= 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
# moves spout right
elif event.type == pygame.KEYDOWN and event.key == pygame.K_d and not rain:
if spoutPos + 10 + spoutWidth*1.5 <= win_width: # stops spout at edge
spoutPos += 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
else:
pass
if not pause:
# Clear the background, and draw the sprites
screen.fill(WHITE)
world.draw(screen)
world.update(dt)
if not rain:
pygame.draw.rect(screen, GREY, (spoutPos, 0, spoutWidth*1.5, 30))
pygame.display.update() | conditional_block |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY = (150,150,150)
WHITE = (255, 255, 255)
RED = (255, 0, 0)
GREEN = (0, 255, 0)
BLUE = (0, 0, 255)
def normalize(v):
return v / np.linalg.norm(v)
class Particle(pygame.sprite.Sprite):
def __init__(self, imgfile, radius, mass=1.0):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load(imgfile)
self.image = pygame.transform.scale(self.image, (radius, radius))
self.state = [0, 0, 0, 0]
self.mass = mass
self.t = 0
self.radius = radius
self.gravity = -9.8
def set_pos(self, pos):
self.state[0:2] = pos
return self
def set_vel(self, vel):
self.state[2:] = vel
return self
def update(self, dt):
self.t += dt
self.state[3] += dt * self.gravity
self.state[0] += self.state[2] * dt
self.state[1] += self.state[3] * dt
def move_by(self, delta):
self.state[0:2] = np.add(self.pos, delta)
return self
def draw(self, surface):
rect = self.image.get_rect()
rect.center = (self.state[0], win_height-self.state[1]) # Flipping y
surface.blit(self.image, rect)
def pprint(self):
print 'Particle', self.state
class Wheel(pygame.sprite.Sprite):
def __init__(self, center, radius, mass=1000):
pygame.sprite.Sprite.__init__(self)
self.state = np.zeros(4)
self.state[0:2] = np.zeros(2) # position
self.state[2] = 1 # angular velocity
self.state[3] = 0 # angular momentum
self.lines = []
self.mass = mass
self.t = 0
self.center = center
self.radius = radius
self.angle = 0
self.torque = 0
def set_vel(self, vel):
self.state[2] = vel
return self
def update(self, dt):
self.t += dt
def draw(self, surface):
self.angle += self.state[2]
for i in range(0,316, 45):
x = self.center[0] + math.cos(math.radians(self.angle + i)) * self.radius
y = self.center[1] + math.sin(math.radians(self.angle + i)) * self.radius
if (len(self.lines) <= 7):
self.lines.append(pygame.draw.line(surface, BLACK, self.center, (x,y), 5))
else:
self.lines[i/45] = pygame.draw.line(surface, BLACK, self.center, (x,y), 5)
self.circle = pygame.draw.circle(surface, BLACK, self.center, (int)(self.radius*.7), 10)
def pprint(self):
print 'Wheel', self.state
class World:
def __init__(self, height, width):
self.particles = []
self.wheels =[]
self.height = height
self.width = width
self.e = .2 # Coefficient of restitution
def add(self, imgfile, radius, mass=1.0):
particle = Particle(imgfile, radius, mass)
self.particles.append(particle)
return particle
def addWheel(self, centre, radius):
wheel = Wheel(centre, radius)
self.wheels.append(wheel)
return wheel
def pprint(self):
print '#particles', len(self.particles)
for d in self.particles:
d.pprint()
def draw(self, screen):
for d in self.particles:
d.draw(screen)
for w in self.wheels:
w.draw(screen)
def update(self, dt):
t = []
for d in self.particles:
d.update(dt)
for i in range(0, len(self.particles)):
self.check_for_collision(i)
try:
for j in range(len(self.wheels)):
t.append(threading.Thread(target=self.check_wheel_collision(i, j)))
t[i].start()
except:
print "Collision detection threading error"
for x in t:
x.join()
self.check_outside_screen()
def check_outside_screen(self):
|
def outside_screen(self, particle):
if (particle.state[0] < -particle.radius):
return False
elif (particle.state[0] > win_width + particle.radius):
return False
elif (particle.state[1] < -particle.radius):
return False
else:
return True
# check for inter-particle collision
def check_for_collision(self, i):
if (self.particles[i].state[0] - self.particles[i].radius <= 0 or
self.particles[i].state[0] + self.particles[i].radius >= 800):
self.particles[i].state[2] *= -1*self.e
elif (self.particles[i].state[1] - self.particles[i].radius <= 0):
self.particles[i].state[3] = 0
for j in range(i+1, len(self.particles)):
if i == j:
return
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.particles[j].state[0:2])
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.particles[j].radius
if dist_ij > radius_i + radius_j:
return
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = np.array(self.particles[j].state[2:])
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.particles[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
vel_j_aftercollision = vel_j - n_ij * J / mass_j
self.particles[i].set_vel(vel_i_aftercollision)
self.particles[j].set_vel(vel_j_aftercollision)
# check for particle - wheel collision
def check_wheel_collision(self, i, j):
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.wheels[j].center)
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.wheels[j].radius*.7
if dist_ij > radius_i + radius_j:
return
# ensures particles do not cross wheel boundaries
dist_in = -(dist_ij - radius_j - radius_i) # distance inside of wheel
theta = math.asin((pos_i[1] - pos_j[1]) /dist_ij) #angle from centre of wheel
newPos = [(math.cos(theta) * dist_in), (math.sin(theta) * dist_in)]
# makes sure to flip new x pos to the left
if pos_i[0] < pos_j[0]:
newPos[0] *= -1
# updates the particle position
self.particles[i].set_pos([pos_i[0] + newPos[0], pos_i[1] + newPos[1]])
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = 0
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.wheels[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
self.particles[i].set_vel(vel_i_aftercollision)
# ANGULAR COLISION #
# detect collision with lines on wheel
for x in range(len(self.wheels[j].lines)):
line = self.wheels[j].lines[x]
A = self.wheels[j].center
C = self.particles[i].state[0:2]
if A == line.topleft:
B = line.bottomright
elif A == line.bottomright:
B = line.topleft
elif A == line.topright:
B = line.bottomleft
else:
B = line.topright
dist = np.sqrt((B[0]-A[0])**2+(B[1]-A[1])**2)
Dx = (B[0]-A[0])/dist
Dy = (B[1]-A[1])/dist
t = Dx*(C[0]-A[0])+Dy*(C[1]-A[1])
Ex = t*Dx+A[0]
Ey = t*Dy+A[1]
dist2 = np.sqrt((Ex-C[0])**2+(Ey-C[1])**2)
#if (dist2 < self.particles[i].radius):
#Do conservation of momentum for angular momentum
def main():
# initializing pygame
pygame.init()
clock = pygame.time.Clock()
# top left corner is (0,0)
screen = pygame.display.set_mode((win_width, win_height))
pygame.display.set_caption('Water Wheel of Fortune')
world = World(win_height, win_width)
world.addWheel([400, 300], 200)
# spout position and width for when rain == false
spoutPos = 380
spoutWidth = 40
pause = False
rain = False # particles randomly appear at top along widith when true, spout when false
maxP = 100 # maximum number of particles
dt = 0.3
pRadius = 10 # smallest radius is 3, anything smaller is invisible
pMass = 1
# timer to create more particles
pygame.time.set_timer(pygame.USEREVENT + 1, 50)
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
print "\n\nPress P key to pause or resume"
print "Press R key to toggle rain or spout"
print "Press A or D keys to move spout left or right\n\n"
while True:
# 30 fps
if not pause:
clock.tick(30)
event = pygame.event.poll()
if event.type == pygame.QUIT:
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_q:
pygame.quit()
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_p:
pause = not pause
elif event.type == pygame.KEYDOWN and event.key == pygame.K_r:
rain = not rain
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
elif event.type == pygame.USEREVENT + 1 and not pause:
# new particle generation
if (len(world.particles) < maxP):
# make sure particle is within the walls
newPos = np.array([rand.uniform(range[0],range[1]), win_height])
newVel = np.array([0, 0])
world.add('waterdroplet.png', pRadius, pMass).set_pos(newPos).set_vel(newVel)
# moves spout left
elif event.type == pygame.KEYDOWN and event.key == pygame.K_a and not rain:
if spoutPos - 10 >= 0: # stops spout at edge
spoutPos -= 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
# moves spout right
elif event.type == pygame.KEYDOWN and event.key == pygame.K_d and not rain:
if spoutPos + 10 + spoutWidth*1.5 <= win_width: # stops spout at edge
spoutPos += 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
else:
pass
if not pause:
# Clear the background, and draw the sprites
screen.fill(WHITE)
world.draw(screen)
world.update(dt)
if not rain:
pygame.draw.rect(screen, GREY, (spoutPos, 0, spoutWidth*1.5, 30))
pygame.display.update()
if __name__ == '__main__':
main() | self.particles = [x for x in self.particles if self.outside_screen(x)] | identifier_body |
particle.py | '''
Water Wheel of Fortune
By Nathaniel Yearwood
Cody Macedo
'''
import pygame, sys
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import ode
import random as rand
import math
import threading
win_width = 800 # 500 cm = 5 m
win_height = 600
# set up the colors
BLACK = (0, 0, 0)
GREY = (150,150,150)
WHITE = (255, 255, 255)
RED = (255, 0, 0)
GREEN = (0, 255, 0)
BLUE = (0, 0, 255)
def normalize(v):
return v / np.linalg.norm(v)
class Particle(pygame.sprite.Sprite):
def __init__(self, imgfile, radius, mass=1.0):
pygame.sprite.Sprite.__init__(self)
self.image = pygame.image.load(imgfile)
self.image = pygame.transform.scale(self.image, (radius, radius))
self.state = [0, 0, 0, 0]
self.mass = mass
self.t = 0
self.radius = radius
self.gravity = -9.8
def set_pos(self, pos):
self.state[0:2] = pos
return self
def set_vel(self, vel):
self.state[2:] = vel
return self
def update(self, dt):
self.t += dt
self.state[3] += dt * self.gravity
self.state[0] += self.state[2] * dt
self.state[1] += self.state[3] * dt
def move_by(self, delta):
self.state[0:2] = np.add(self.pos, delta)
return self
def draw(self, surface):
rect = self.image.get_rect()
rect.center = (self.state[0], win_height-self.state[1]) # Flipping y
surface.blit(self.image, rect)
def pprint(self):
print 'Particle', self.state
class Wheel(pygame.sprite.Sprite):
def __init__(self, center, radius, mass=1000):
pygame.sprite.Sprite.__init__(self)
self.state = np.zeros(4)
self.state[0:2] = np.zeros(2) # position
self.state[2] = 1 # angular velocity
self.state[3] = 0 # angular momentum
self.lines = []
self.mass = mass
self.t = 0
self.center = center
self.radius = radius
self.angle = 0
self.torque = 0
def set_vel(self, vel):
self.state[2] = vel
return self
def update(self, dt):
self.t += dt
def draw(self, surface):
self.angle += self.state[2]
for i in range(0,316, 45):
x = self.center[0] + math.cos(math.radians(self.angle + i)) * self.radius
y = self.center[1] + math.sin(math.radians(self.angle + i)) * self.radius
if (len(self.lines) <= 7):
self.lines.append(pygame.draw.line(surface, BLACK, self.center, (x,y), 5))
else:
self.lines[i/45] = pygame.draw.line(surface, BLACK, self.center, (x,y), 5)
self.circle = pygame.draw.circle(surface, BLACK, self.center, (int)(self.radius*.7), 10)
def pprint(self):
print 'Wheel', self.state
class World:
def __init__(self, height, width):
self.particles = []
self.wheels =[]
self.height = height
self.width = width
self.e = .2 # Coefficient of restitution
def | (self, imgfile, radius, mass=1.0):
particle = Particle(imgfile, radius, mass)
self.particles.append(particle)
return particle
def addWheel(self, centre, radius):
wheel = Wheel(centre, radius)
self.wheels.append(wheel)
return wheel
def pprint(self):
print '#particles', len(self.particles)
for d in self.particles:
d.pprint()
def draw(self, screen):
for d in self.particles:
d.draw(screen)
for w in self.wheels:
w.draw(screen)
def update(self, dt):
t = []
for d in self.particles:
d.update(dt)
for i in range(0, len(self.particles)):
self.check_for_collision(i)
try:
for j in range(len(self.wheels)):
t.append(threading.Thread(target=self.check_wheel_collision(i, j)))
t[i].start()
except:
print "Collision detection threading error"
for x in t:
x.join()
self.check_outside_screen()
def check_outside_screen(self):
self.particles = [x for x in self.particles if self.outside_screen(x)]
def outside_screen(self, particle):
if (particle.state[0] < -particle.radius):
return False
elif (particle.state[0] > win_width + particle.radius):
return False
elif (particle.state[1] < -particle.radius):
return False
else:
return True
# check for inter-particle collision
def check_for_collision(self, i):
if (self.particles[i].state[0] - self.particles[i].radius <= 0 or
self.particles[i].state[0] + self.particles[i].radius >= 800):
self.particles[i].state[2] *= -1*self.e
elif (self.particles[i].state[1] - self.particles[i].radius <= 0):
self.particles[i].state[3] = 0
for j in range(i+1, len(self.particles)):
if i == j:
return
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.particles[j].state[0:2])
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.particles[j].radius
if dist_ij > radius_i + radius_j:
return
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = np.array(self.particles[j].state[2:])
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.particles[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
vel_j_aftercollision = vel_j - n_ij * J / mass_j
self.particles[i].set_vel(vel_i_aftercollision)
self.particles[j].set_vel(vel_j_aftercollision)
# check for particle - wheel collision
def check_wheel_collision(self, i, j):
pos_i = np.array(self.particles[i].state[0:2])
pos_j = np.array(self.wheels[j].center)
dist_ij = np.sqrt(np.sum((pos_i - pos_j)**2))
radius_i = self.particles[i].radius
radius_j = self.wheels[j].radius*.7
if dist_ij > radius_i + radius_j:
return
# ensures particles do not cross wheel boundaries
dist_in = -(dist_ij - radius_j - radius_i) # distance inside of wheel
theta = math.asin((pos_i[1] - pos_j[1]) /dist_ij) #angle from centre of wheel
newPos = [(math.cos(theta) * dist_in), (math.sin(theta) * dist_in)]
# makes sure to flip new x pos to the left
if pos_i[0] < pos_j[0]:
newPos[0] *= -1
# updates the particle position
self.particles[i].set_pos([pos_i[0] + newPos[0], pos_i[1] + newPos[1]])
# May be a collision
vel_i = np.array(self.particles[i].state[2:])
vel_j = 0
relative_vel_ij = vel_i - vel_j
n_ij = normalize(pos_i - pos_j)
if np.dot(relative_vel_ij, n_ij) >= 0:
return
mass_i = self.particles[i].mass
mass_j = self.wheels[j].mass
J = -(1+self.e) * np.dot(relative_vel_ij, n_ij) / ((1./mass_i) + (1./mass_j))
vel_i_aftercollision = vel_i + n_ij * J / mass_i
self.particles[i].set_vel(vel_i_aftercollision)
# ANGULAR COLISION #
# detect collision with lines on wheel
for x in range(len(self.wheels[j].lines)):
line = self.wheels[j].lines[x]
A = self.wheels[j].center
C = self.particles[i].state[0:2]
if A == line.topleft:
B = line.bottomright
elif A == line.bottomright:
B = line.topleft
elif A == line.topright:
B = line.bottomleft
else:
B = line.topright
dist = np.sqrt((B[0]-A[0])**2+(B[1]-A[1])**2)
Dx = (B[0]-A[0])/dist
Dy = (B[1]-A[1])/dist
t = Dx*(C[0]-A[0])+Dy*(C[1]-A[1])
Ex = t*Dx+A[0]
Ey = t*Dy+A[1]
dist2 = np.sqrt((Ex-C[0])**2+(Ey-C[1])**2)
#if (dist2 < self.particles[i].radius):
#Do conservation of momentum for angular momentum
def main():
# initializing pygame
pygame.init()
clock = pygame.time.Clock()
# top left corner is (0,0)
screen = pygame.display.set_mode((win_width, win_height))
pygame.display.set_caption('Water Wheel of Fortune')
world = World(win_height, win_width)
world.addWheel([400, 300], 200)
# spout position and width for when rain == false
spoutPos = 380
spoutWidth = 40
pause = False
rain = False # particles randomly appear at top along widith when true, spout when false
maxP = 100 # maximum number of particles
dt = 0.3
pRadius = 10 # smallest radius is 3, anything smaller is invisible
pMass = 1
# timer to create more particles
pygame.time.set_timer(pygame.USEREVENT + 1, 50)
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
print "\n\nPress P key to pause or resume"
print "Press R key to toggle rain or spout"
print "Press A or D keys to move spout left or right\n\n"
while True:
# 30 fps
if not pause:
clock.tick(30)
event = pygame.event.poll()
if event.type == pygame.QUIT:
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_q:
pygame.quit()
sys.exit(0)
elif event.type == pygame.KEYDOWN and event.key == pygame.K_p:
pause = not pause
elif event.type == pygame.KEYDOWN and event.key == pygame.K_r:
rain = not rain
if rain:
range = [0 + pRadius, win_width - pRadius]
else:
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
elif event.type == pygame.USEREVENT + 1 and not pause:
# new particle generation
if (len(world.particles) < maxP):
# make sure particle is within the walls
newPos = np.array([rand.uniform(range[0],range[1]), win_height])
newVel = np.array([0, 0])
world.add('waterdroplet.png', pRadius, pMass).set_pos(newPos).set_vel(newVel)
# moves spout left
elif event.type == pygame.KEYDOWN and event.key == pygame.K_a and not rain:
if spoutPos - 10 >= 0: # stops spout at edge
spoutPos -= 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
# moves spout right
elif event.type == pygame.KEYDOWN and event.key == pygame.K_d and not rain:
if spoutPos + 10 + spoutWidth*1.5 <= win_width: # stops spout at edge
spoutPos += 10
range = [spoutPos + pRadius, spoutPos + spoutWidth + pRadius]
else:
pass
if not pause:
# Clear the background, and draw the sprites
screen.fill(WHITE)
world.draw(screen)
world.update(dt)
if not rain:
pygame.draw.rect(screen, GREY, (spoutPos, 0, spoutWidth*1.5, 30))
pygame.display.update()
if __name__ == '__main__':
main() | add | identifier_name |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual.getMonth() + 1;
var fechaActualIncio = moment().format("YYYY-MM-DD");
//
$("#min-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language : "es"
}
);
$("#max-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language: "es"
}
);
$('#tb_rutasBitacora').DataTable({
language: {
lengthMenu: "Mostrar _MENU_ registros",
zeroRecords: "No hay registros",
info: "Mostrando la página _PAGE_ de _PAGES_",
infoEmpty: "No hay registros disponibles.",
infoFiltered: "(filtered from _MAX_ total records)",
search: "Busqueda rapida: ",
oPaginate: {
"sFirst": "Primero",
"sLast": "Último",
"sNext": "Siguiente",
"sPrevious": "Anterior"
}
},
lengthMenu: [[10, 25, 50, -1], [10, 25, 50, "Todos"]],
function(start, end, label) {
maxDateFilter = end;
minDateFilter = start;
table.draw();
},
dom: 'lBfrtip',
buttons: [
{
extend: 'excelHtml5',
text: '<span class="icon-file-excel"></span>',
titleAttr: 'Excel',
title: 'Bitacora de Rutas del Vendedor',
customize: function (xlsx) {
var sheet = xlsx.xl.worksheets['sheet1.xml'];
//All cells
$('row c', sheet).attr('s', '25');
//First row
$('row:first c', sheet).attr('s', '32');
//Second row
$('row c[r*="2"]', sheet).attr('s', '47');
//doce row
$('row c[r*="12"]', sheet).attr('s', '25');
$('row c[r*="24"]', sheet).attr('s', '25');
},
//Para que excel solo me exporte ciertas columnas
exportOptions: {
columns: [0, 1, 2, 3, 4, 5]
}
}],
//Para que el DataTable no me muestre ciertas Columnas.
columnDefs: [
{
"width": "8%",
targets: [0],
},
{
"width": "8%",
targets: [1],
},
{
"width": "8%",
targets: [2],
},
{
"width": "5%",
targets: [3],
},
{
"width": "10%",
targets: [3],
},
{
"width": "2%",
targets: [5],
render: function (data) {
return moment(data).format('DD/MM/YYYY');
}
}],
});
//creo variables despues de que el DataTable este creado en el DOM.
var tabla = $("#tb_rutasBitacora").dataTable(); //funcion jquery
var table = $("#tb_rutasBitacora").DataTable(); //funcion DataTable-libreria
//para ajustar el diseño de tabla
table.columns.adjust().draw();
function addRowDT(data) {
//DESCRIPCION : Funcion que me crea el listado de rutas en el body del DataTable
var clientRazonS;
var replaceCli;
var clientRuc;
var visita;
var motivo;
for (var i = 0; i < data.length; i++) {
replaceCli = data[i].cliente;
clientRuc = replaceCli.replace(/ /g, "");
if (clientRuc == "") {
clientRazonS = data[i].razonsocial;
}
else {
clientRazonS = data[i].cliente;
}
if (data[i].visita == 1) {
visita = "Si";
} else {
visita = "No";
}
if (data[i].motivo == "") {
motivo = "--";
} else {
motivo = data[i].motivo;
}
tabla.fnAddData([
data[i].vendedor,
data[i].descripcion,
clientRazonS,
visita,
motivo,
data[i].fecha,
data[i].coordenadaX,
data[i].coordenadaY,
]);
}
$.fn.dataTableExt.afnFiltering.push(
function(settings, data, dataIndex) {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var createdAt = data[5] || 0;
var createdAtr = createdAt.split('/').join('-');
var createdAtf = moment(createdAtr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
var diffDate = moment(createdAtf, "YYYY-MM-DD");
//console.log(startDate);
if ((min != "" && max != "") && (endDate < startDate)) {
return true;
} else {
if ((min == "" || max == "") || (diffDate.isBetween(startDate, endDate, null, '[]'))) {
return true;
}
return false;
}
});
// Re-draw the table when the a date range filter changes
$('.date-range-filter').change(function () {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
if ((min != "" && max != "") && (endDate < startDate)) {
MmensajeOrdenFecha.css('opacity', '1')
.css('height', '40px');
setTimeout(function () {
MmensajeOrdenFecha.css('opacity', '0');
}, 2000);
setTimeout(function () {
MmensajeOrdenFecha.css('height', '0px')
}, 4000)
} else {
if (min != "" && max != "") {
var optionSelected = $("#vendedores").find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 0, startDate, endDate);
} else {
// table.draw();
}
}
});
}
function addSelectVendedor(data) {
//DESCRIPCION : Funcion para llenar la lista de opciones del select del Vendedor.
for (var i = 0; i < data.length; i++) {
vendedores.append("<option value=" + data[i]["ntraUsuario"] + ">" + data[i]["vendedor"] + "</option>");
}
}
//LLAMANDO A LA FUNCIO NDE AJAX VENDEDORES
function ListarVendedores() {
//DESCRIPCION : Funcion que me trae la lista de vendedores
$.ajax({
type: "POST",
url: "frmRutasAsignadas.aspx/ListarVendedores",
data: "{'flag': '1' }",
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
addSelectVendedor(data.d);
}
})
}
ListarVendedores();
function ListarBitacoras(idVendedor, Mes, flagFiltro,fechaIncio,fechaFin) {
//DESCRICION : Funcion que me obtiene la lista de bitacoras
var json = JSON.stringify({
codVendedor: idVendedor,
fechaActual: Mes,
flagFiltro: flagFiltro,
fechaIncio: fechaIncio,
fechaFin: fechaFin
});
$.ajax({
type: "POST",
url: "frmRutasBitacora.aspx/ListarRutasBitacora",
data: json,
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
console.log(data.d);
table.clear().draw();
addRowDT(data.d);
}
})
}
function SeleccionarVendedor() {
| SeleccionarVendedor();
//GOOGLE MAPS
}); | //DESCRICION : Funcion que me obtiene la lista de rutas asignadas segun el vendedor seleccionado.
vendedores.change(function () {
var optionSelected = $(this).find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 1, fechaActualIncio, fechaActualIncio);
if (valueSelected > 0) {
rangoFecha.css("display", "block")
} else {
rangoFecha.css("display", "none");
}
});
}
| identifier_body |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual.getMonth() + 1;
var fechaActualIncio = moment().format("YYYY-MM-DD");
//
$("#min-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language : "es"
}
);
$("#max-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language: "es"
}
);
$('#tb_rutasBitacora').DataTable({
language: {
lengthMenu: "Mostrar _MENU_ registros",
zeroRecords: "No hay registros",
info: "Mostrando la página _PAGE_ de _PAGES_",
infoEmpty: "No hay registros disponibles.",
infoFiltered: "(filtered from _MAX_ total records)",
search: "Busqueda rapida: ",
oPaginate: {
"sFirst": "Primero",
"sLast": "Último",
"sNext": "Siguiente",
"sPrevious": "Anterior"
}
},
lengthMenu: [[10, 25, 50, -1], [10, 25, 50, "Todos"]],
function(start, end, label) {
maxDateFilter = end;
minDateFilter = start;
table.draw();
},
dom: 'lBfrtip',
buttons: [
{
extend: 'excelHtml5',
text: '<span class="icon-file-excel"></span>',
titleAttr: 'Excel',
title: 'Bitacora de Rutas del Vendedor',
customize: function (xlsx) {
var sheet = xlsx.xl.worksheets['sheet1.xml'];
//All cells
$('row c', sheet).attr('s', '25');
//First row
$('row:first c', sheet).attr('s', '32');
//Second row
$('row c[r*="2"]', sheet).attr('s', '47');
//doce row
$('row c[r*="12"]', sheet).attr('s', '25');
$('row c[r*="24"]', sheet).attr('s', '25');
},
//Para que excel solo me exporte ciertas columnas
exportOptions: {
columns: [0, 1, 2, 3, 4, 5]
}
}],
//Para que el DataTable no me muestre ciertas Columnas.
columnDefs: [
{
"width": "8%",
targets: [0],
},
{
"width": "8%",
targets: [1],
},
{
"width": "8%",
targets: [2],
},
{
"width": "5%",
targets: [3],
},
{
"width": "10%",
targets: [3],
},
{
"width": "2%",
targets: [5],
render: function (data) {
return moment(data).format('DD/MM/YYYY');
}
}],
});
//creo variables despues de que el DataTable este creado en el DOM.
var tabla = $("#tb_rutasBitacora").dataTable(); //funcion jquery
var table = $("#tb_rutasBitacora").DataTable(); //funcion DataTable-libreria
//para ajustar el diseño de tabla
table.columns.adjust().draw();
function addRowDT(data) {
//DESCRIPCION : Funcion que me crea el listado de rutas en el body del DataTable
var clientRazonS;
var replaceCli;
var clientRuc;
var visita;
var motivo;
for (var i = 0; i < data.length; i++) {
replaceCli = data[i].cliente;
clientRuc = replaceCli.replace(/ /g, "");
if (clientRuc == "") {
clientRazonS = data[i].razonsocial;
}
else {
clientRazonS = data[i].cliente;
}
if (data[i].visita == 1) {
visita = "Si";
} else {
visita = "No";
}
if (data[i].motivo == "") {
motivo = "--";
} else {
motivo = data[i].motivo;
}
tabla.fnAddData([
data[i].vendedor,
data[i].descripcion,
clientRazonS,
visita,
motivo,
data[i].fecha,
data[i].coordenadaX,
data[i].coordenadaY,
]);
}
$.fn.dataTableExt.afnFiltering.push(
function(settings, data, dataIndex) {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var createdAt = data[5] || 0;
var createdAtr = createdAt.split('/').join('-');
var createdAtf = moment(createdAtr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
var diffDate = moment(createdAtf, "YYYY-MM-DD");
//console.log(startDate);
if ((min != "" && max != "") && (endDate < startDate)) {
return true;
} else {
if ((min == "" || max == "") || (diffDate.isBetween(startDate, endDate, null, '[]'))) {
return true;
}
return false;
}
});
// Re-draw the table when the a date range filter changes
$('.date-range-filter').change(function () {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
if ((min != "" && max != "") && (endDate < startDate)) {
MmensajeOrdenFecha.css('opacity', '1')
.css('height', '40px');
setTimeout(function () {
MmensajeOrdenFecha.css('opacity', '0');
}, 2000);
setTimeout(function () {
MmensajeOrdenFecha.css('height', '0px')
}, 4000)
} else {
if (min != "" && max != "") {
var optionSelected = $("#vendedores").find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 0, startDate, endDate);
} else {
// table.draw();
}
}
});
}
function addSelectVendedor(data) {
//DESCRIPCION : Funcion para llenar la lista de opciones del select del Vendedor.
for (var i = 0; i < data.length; i++) {
vendedores.append("<option value=" + data[i]["ntraUsuario"] + ">" + data[i]["vendedor"] + "</option>");
}
}
//LLAMANDO A LA FUNCIO NDE AJAX VENDEDORES
function ListarVendedores() {
//DESCRIPCION : Funcion que me trae la lista de vendedores
$.ajax({
type: "POST",
url: "frmRutasAsignadas.aspx/ListarVendedores",
data: "{'flag': '1' }",
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
addSelectVendedor(data.d);
}
})
}
ListarVendedores();
function Lista | ndedor, Mes, flagFiltro,fechaIncio,fechaFin) {
//DESCRICION : Funcion que me obtiene la lista de bitacoras
var json = JSON.stringify({
codVendedor: idVendedor,
fechaActual: Mes,
flagFiltro: flagFiltro,
fechaIncio: fechaIncio,
fechaFin: fechaFin
});
$.ajax({
type: "POST",
url: "frmRutasBitacora.aspx/ListarRutasBitacora",
data: json,
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
console.log(data.d);
table.clear().draw();
addRowDT(data.d);
}
})
}
function SeleccionarVendedor() {
//DESCRICION : Funcion que me obtiene la lista de rutas asignadas segun el vendedor seleccionado.
vendedores.change(function () {
var optionSelected = $(this).find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 1, fechaActualIncio, fechaActualIncio);
if (valueSelected > 0) {
rangoFecha.css("display", "block")
} else {
rangoFecha.css("display", "none");
}
});
}
SeleccionarVendedor();
//GOOGLE MAPS
}); | rBitacoras(idVe | identifier_name |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual.getMonth() + 1;
var fechaActualIncio = moment().format("YYYY-MM-DD");
//
$("#min-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language : "es"
}
);
$("#max-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language: "es"
}
);
$('#tb_rutasBitacora').DataTable({
language: {
lengthMenu: "Mostrar _MENU_ registros",
zeroRecords: "No hay registros",
info: "Mostrando la página _PAGE_ de _PAGES_",
infoEmpty: "No hay registros disponibles.",
infoFiltered: "(filtered from _MAX_ total records)",
search: "Busqueda rapida: ",
oPaginate: {
"sFirst": "Primero",
"sLast": "Último",
"sNext": "Siguiente",
"sPrevious": "Anterior"
}
},
lengthMenu: [[10, 25, 50, -1], [10, 25, 50, "Todos"]],
function(start, end, label) {
maxDateFilter = end;
minDateFilter = start;
table.draw();
},
dom: 'lBfrtip',
buttons: [
{
extend: 'excelHtml5',
text: '<span class="icon-file-excel"></span>',
titleAttr: 'Excel',
title: 'Bitacora de Rutas del Vendedor',
customize: function (xlsx) {
var sheet = xlsx.xl.worksheets['sheet1.xml'];
//All cells
$('row c', sheet).attr('s', '25');
//First row
$('row:first c', sheet).attr('s', '32');
//Second row
$('row c[r*="2"]', sheet).attr('s', '47');
//doce row
$('row c[r*="12"]', sheet).attr('s', '25');
$('row c[r*="24"]', sheet).attr('s', '25');
},
//Para que excel solo me exporte ciertas columnas
exportOptions: {
columns: [0, 1, 2, 3, 4, 5]
}
}],
//Para que el DataTable no me muestre ciertas Columnas.
columnDefs: [
{
"width": "8%",
targets: [0],
},
{
"width": "8%",
targets: [1],
},
{
"width": "8%",
targets: [2],
},
{
"width": "5%",
targets: [3],
},
{
"width": "10%",
targets: [3],
},
{
"width": "2%",
targets: [5],
render: function (data) {
return moment(data).format('DD/MM/YYYY');
}
}],
});
//creo variables despues de que el DataTable este creado en el DOM.
var tabla = $("#tb_rutasBitacora").dataTable(); //funcion jquery
var table = $("#tb_rutasBitacora").DataTable(); //funcion DataTable-libreria
//para ajustar el diseño de tabla
table.columns.adjust().draw();
function addRowDT(data) {
//DESCRIPCION : Funcion que me crea el listado de rutas en el body del DataTable
var clientRazonS;
var replaceCli;
var clientRuc;
var visita;
var motivo;
for (var i = 0; i < data.length; i++) {
|
$.fn.dataTableExt.afnFiltering.push(
function(settings, data, dataIndex) {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var createdAt = data[5] || 0;
var createdAtr = createdAt.split('/').join('-');
var createdAtf = moment(createdAtr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
var diffDate = moment(createdAtf, "YYYY-MM-DD");
//console.log(startDate);
if ((min != "" && max != "") && (endDate < startDate)) {
return true;
} else {
if ((min == "" || max == "") || (diffDate.isBetween(startDate, endDate, null, '[]'))) {
return true;
}
return false;
}
});
// Re-draw the table when the a date range filter changes
$('.date-range-filter').change(function () {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
if ((min != "" && max != "") && (endDate < startDate)) {
MmensajeOrdenFecha.css('opacity', '1')
.css('height', '40px');
setTimeout(function () {
MmensajeOrdenFecha.css('opacity', '0');
}, 2000);
setTimeout(function () {
MmensajeOrdenFecha.css('height', '0px')
}, 4000)
} else {
if (min != "" && max != "") {
var optionSelected = $("#vendedores").find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 0, startDate, endDate);
} else {
// table.draw();
}
}
});
}
function addSelectVendedor(data) {
//DESCRIPCION : Funcion para llenar la lista de opciones del select del Vendedor.
for (var i = 0; i < data.length; i++) {
vendedores.append("<option value=" + data[i]["ntraUsuario"] + ">" + data[i]["vendedor"] + "</option>");
}
}
//LLAMANDO A LA FUNCIO NDE AJAX VENDEDORES
function ListarVendedores() {
//DESCRIPCION : Funcion que me trae la lista de vendedores
$.ajax({
type: "POST",
url: "frmRutasAsignadas.aspx/ListarVendedores",
data: "{'flag': '1' }",
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
addSelectVendedor(data.d);
}
})
}
ListarVendedores();
function ListarBitacoras(idVendedor, Mes, flagFiltro,fechaIncio,fechaFin) {
//DESCRICION : Funcion que me obtiene la lista de bitacoras
var json = JSON.stringify({
codVendedor: idVendedor,
fechaActual: Mes,
flagFiltro: flagFiltro,
fechaIncio: fechaIncio,
fechaFin: fechaFin
});
$.ajax({
type: "POST",
url: "frmRutasBitacora.aspx/ListarRutasBitacora",
data: json,
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
console.log(data.d);
table.clear().draw();
addRowDT(data.d);
}
})
}
function SeleccionarVendedor() {
//DESCRICION : Funcion que me obtiene la lista de rutas asignadas segun el vendedor seleccionado.
vendedores.change(function () {
var optionSelected = $(this).find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 1, fechaActualIncio, fechaActualIncio);
if (valueSelected > 0) {
rangoFecha.css("display", "block")
} else {
rangoFecha.css("display", "none");
}
});
}
SeleccionarVendedor();
//GOOGLE MAPS
}); | replaceCli = data[i].cliente;
clientRuc = replaceCli.replace(/ /g, "");
if (clientRuc == "") {
clientRazonS = data[i].razonsocial;
}
else {
clientRazonS = data[i].cliente;
}
if (data[i].visita == 1) {
visita = "Si";
} else {
visita = "No";
}
if (data[i].motivo == "") {
motivo = "--";
} else {
motivo = data[i].motivo;
}
tabla.fnAddData([
data[i].vendedor,
data[i].descripcion,
clientRazonS,
visita,
motivo,
data[i].fecha,
data[i].coordenadaX,
data[i].coordenadaY,
]);
} | conditional_block |
peticiones_bitacora.js | $(document).ready(function () {
var vendedores = $("#vendedores");
//window.moment = require('moment');
var rangoFecha = $("#rangoFecha");
var MmensajeOrdenFecha = $('#MmensajeOrdenFecha');
var map;
//Para enviar la fecha Actual
var fechaActual = new Date();
var MesActual = fechaActual.getMonth() + 1;
var fechaActualIncio = moment().format("YYYY-MM-DD");
//
$("#min-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language : "es"
}
);
$("#max-date").datepicker(
{
changeMonth: true,
changeYear: true,
monthNames: ['Enero', 'Febrero', 'Marzo', 'Abril', 'Mayo', 'Junio',
'Julio', 'Agosto', 'Septiembre', 'Octubre', 'Noviembre', 'Diciembre'
],
monthNamesShort: ['Ene', 'Feb', 'Mar', 'Abr', 'May', 'Jun',
'Jul', 'Ago', 'Sep', 'Oct', 'Nov', 'Dic'
],
dayNames: ['Domingo', 'Lunes', 'Martes', 'Miércoles', 'Jueves', 'Viernes', 'Sábado'],
dayNamesShort: ['Dom', 'Lun', 'Mar', 'Mié', 'Juv', 'Vie', 'Sáb'],
dayNamesMin: ['Do', 'Lu', 'Ma', 'Mi', 'Ju', 'Vi', 'Sá'],
weekHeader: 'Sm',
dateFormat: 'dd/mm/yy',
showOn: "button",
buttonImage: "Imagenes/calendar.gif",
buttonImageOnly: true,
buttonText: "Select date",
language: "es"
}
);
$('#tb_rutasBitacora').DataTable({
language: {
lengthMenu: "Mostrar _MENU_ registros",
zeroRecords: "No hay registros",
info: "Mostrando la página _PAGE_ de _PAGES_",
infoEmpty: "No hay registros disponibles.",
infoFiltered: "(filtered from _MAX_ total records)",
search: "Busqueda rapida: ",
oPaginate: {
"sFirst": "Primero",
"sLast": "Último",
"sNext": "Siguiente",
"sPrevious": "Anterior"
}
},
lengthMenu: [[10, 25, 50, -1], [10, 25, 50, "Todos"]],
function(start, end, label) {
maxDateFilter = end;
minDateFilter = start;
table.draw();
},
dom: 'lBfrtip',
buttons: [
{
extend: 'excelHtml5',
text: '<span class="icon-file-excel"></span>',
titleAttr: 'Excel',
title: 'Bitacora de Rutas del Vendedor',
customize: function (xlsx) {
var sheet = xlsx.xl.worksheets['sheet1.xml'];
//All cells
$('row c', sheet).attr('s', '25');
//First row
$('row:first c', sheet).attr('s', '32');
//Second row
$('row c[r*="2"]', sheet).attr('s', '47');
//doce row
$('row c[r*="12"]', sheet).attr('s', '25');
$('row c[r*="24"]', sheet).attr('s', '25');
},
//Para que excel solo me exporte ciertas columnas
exportOptions: {
columns: [0, 1, 2, 3, 4, 5]
}
}],
//Para que el DataTable no me muestre ciertas Columnas.
columnDefs: [
{
"width": "8%",
targets: [0],
},
{
"width": "8%",
targets: [1],
},
{
"width": "8%",
targets: [2],
},
{ |
},
{
"width": "10%",
targets: [3],
},
{
"width": "2%",
targets: [5],
render: function (data) {
return moment(data).format('DD/MM/YYYY');
}
}],
});
//creo variables despues de que el DataTable este creado en el DOM.
var tabla = $("#tb_rutasBitacora").dataTable(); //funcion jquery
var table = $("#tb_rutasBitacora").DataTable(); //funcion DataTable-libreria
//para ajustar el diseño de tabla
table.columns.adjust().draw();
function addRowDT(data) {
//DESCRIPCION : Funcion que me crea el listado de rutas en el body del DataTable
var clientRazonS;
var replaceCli;
var clientRuc;
var visita;
var motivo;
for (var i = 0; i < data.length; i++) {
replaceCli = data[i].cliente;
clientRuc = replaceCli.replace(/ /g, "");
if (clientRuc == "") {
clientRazonS = data[i].razonsocial;
}
else {
clientRazonS = data[i].cliente;
}
if (data[i].visita == 1) {
visita = "Si";
} else {
visita = "No";
}
if (data[i].motivo == "") {
motivo = "--";
} else {
motivo = data[i].motivo;
}
tabla.fnAddData([
data[i].vendedor,
data[i].descripcion,
clientRazonS,
visita,
motivo,
data[i].fecha,
data[i].coordenadaX,
data[i].coordenadaY,
]);
}
$.fn.dataTableExt.afnFiltering.push(
function(settings, data, dataIndex) {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var createdAt = data[5] || 0;
var createdAtr = createdAt.split('/').join('-');
var createdAtf = moment(createdAtr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
var diffDate = moment(createdAtf, "YYYY-MM-DD");
//console.log(startDate);
if ((min != "" && max != "") && (endDate < startDate)) {
return true;
} else {
if ((min == "" || max == "") || (diffDate.isBetween(startDate, endDate, null, '[]'))) {
return true;
}
return false;
}
});
// Re-draw the table when the a date range filter changes
$('.date-range-filter').change(function () {
var min = $('#min-date').val();
var minr = min.split('/').join('-');
var max = $('#max-date').val()
var maxr = max.split('/').join('-');
var minf = moment(minr, 'DD-MM-YYYY').format("YYYY-MM-DD");
var maxf = moment(maxr, 'DD-MM-YYYY').format("YYYY-MM-DD");
//createdAt=createdAt.split(" ");
var startDate = moment(minf, "YYYY-MM-DD");
var endDate = moment(maxf, "YYYY-MM-DD");
if ((min != "" && max != "") && (endDate < startDate)) {
MmensajeOrdenFecha.css('opacity', '1')
.css('height', '40px');
setTimeout(function () {
MmensajeOrdenFecha.css('opacity', '0');
}, 2000);
setTimeout(function () {
MmensajeOrdenFecha.css('height', '0px')
}, 4000)
} else {
if (min != "" && max != "") {
var optionSelected = $("#vendedores").find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 0, startDate, endDate);
} else {
// table.draw();
}
}
});
}
function addSelectVendedor(data) {
//DESCRIPCION : Funcion para llenar la lista de opciones del select del Vendedor.
for (var i = 0; i < data.length; i++) {
vendedores.append("<option value=" + data[i]["ntraUsuario"] + ">" + data[i]["vendedor"] + "</option>");
}
}
//LLAMANDO A LA FUNCIO NDE AJAX VENDEDORES
function ListarVendedores() {
//DESCRIPCION : Funcion que me trae la lista de vendedores
$.ajax({
type: "POST",
url: "frmRutasAsignadas.aspx/ListarVendedores",
data: "{'flag': '1' }",
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
addSelectVendedor(data.d);
}
})
}
ListarVendedores();
function ListarBitacoras(idVendedor, Mes, flagFiltro,fechaIncio,fechaFin) {
//DESCRICION : Funcion que me obtiene la lista de bitacoras
var json = JSON.stringify({
codVendedor: idVendedor,
fechaActual: Mes,
flagFiltro: flagFiltro,
fechaIncio: fechaIncio,
fechaFin: fechaFin
});
$.ajax({
type: "POST",
url: "frmRutasBitacora.aspx/ListarRutasBitacora",
data: json,
contentType: 'application/json; charset=utf-8',
error: function (xhr, ajaxOtions, thrownError) {
console.log(xhr.status + "\n" + xhr.responseText, "\n" + thrownError);
},
success: function (data) {
console.log(data.d);
table.clear().draw();
addRowDT(data.d);
}
})
}
function SeleccionarVendedor() {
//DESCRICION : Funcion que me obtiene la lista de rutas asignadas segun el vendedor seleccionado.
vendedores.change(function () {
var optionSelected = $(this).find("option:selected");
var valueSelected = optionSelected.val();
ListarBitacoras(valueSelected, MesActual, 1, fechaActualIncio, fechaActualIncio);
if (valueSelected > 0) {
rangoFecha.css("display", "block")
} else {
rangoFecha.css("display", "none");
}
});
}
SeleccionarVendedor();
//GOOGLE MAPS
}); | "width": "5%",
targets: [3], | random_line_split |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as usize;
static mut PIXEL_DATA: [u8; BUFFER_SIZE] = [255; BUFFER_SIZE];
static mut PIXEL_DATA_UPDATING: bool = false;
static mut PIXEL_DATA_UPDATED: bool = false;
// static mut CLIENT_READY: bool = false;
const VERTICES: [f32; 18] = [
-1.0, -1.0, 0.0, // Bottom left
1.0, -1.0, 0.0, // Bottem right
1.0, 1.0, 0.0, // Top right
-1.0, -1.0, 0.0, // Bottom left
1.0, 1.0, 0.0, // Top right
-1.0, 1.0, 0.0, // Top left
];
fn window() -> web_sys::Window {
web_sys::window().expect("no global `window` exists")
}
fn request_animation_frame(f: &Closure<dyn FnMut()>) {
window()
.request_animation_frame(f.as_ref().unchecked_ref())
.expect("should register `requestAnimationFrame` OK");
}
#[wasm_bindgen(start)]
pub fn start() {
utils::set_panic_hook();
log!("Hello there! Compositor canvas starting/loading");
}
#[wasm_bindgen]
pub fn initialise(element_id: String) -> Result<(), JsValue> {
log!(
"Compositor canvas (element_id: String = `{}`) initialisation",
&element_id
);
let document = web_sys::window().unwrap().document().unwrap();
let canvas = document.get_element_by_id(&element_id).unwrap();
let canvas: web_sys::HtmlCanvasElement = canvas.dyn_into::<web_sys::HtmlCanvasElement>()?;
let context = canvas
.get_context("webgl")?
.unwrap()
.dyn_into::<WebGlRenderingContext>()?;
let vert_shader = compile_shader(
&context,
WebGlRenderingContext::VERTEX_SHADER,
r#"
attribute vec4 position;
attribute vec2 textureCoord;
varying highp vec2 vTextureCoord;
void main(void) {
gl_Position = position;
vTextureCoord = textureCoord;
}
"#,
)?;
let frag_shader = compile_shader(
&context,
WebGlRenderingContext::FRAGMENT_SHADER,
r#"
varying highp vec2 vTextureCoord;
uniform sampler2D image;
void main(void) {
gl_FragColor = texture2D(image, vTextureCoord);
gl_FragColor = vec4(gl_FragColor.b, gl_FragColor.g, gl_FragColor.r, gl_FragColor.a);
}
"#,
)?;
let program = link_program(&context, &vert_shader, &frag_shader)?;
let position_location = context.get_attrib_location(&program, "position");
let texcoord_location = context.get_attrib_location(&program, "textureCoord");
let texture_location = context.get_uniform_location(&program, "image"); //.unwrap();
// Bind shader
context.use_program(Some(&program));
// Build model
let vertex_buffer = context
.create_buffer()
.ok_or("failed to create vertex buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&vertex_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let vert_array = js_sys::Float32Array::view(&VERTICES);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&vert_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
position_location as u32,
3,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(position_location as u32);
// Add uvs
let uvs: [f32; 12] = [
0.0, 1.0, // Bottom left
1.0, 1.0, // Bottem right
1.0, 0.0, // Top right
0.0, 1.0, // Bottom left
1.0, 0.0, // Top right
0.0, 0.0, // Top left
];
let uv_buffer = context
.create_buffer()
.ok_or("failed to create uv buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&uv_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let uv_array = js_sys::Float32Array::view(&uvs);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&uv_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
texcoord_location as u32,
2,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(texcoord_location as u32);
// Create a texture
let texture = context.create_texture();
context.bind_texture(WebGlRenderingContext::TEXTURE_2D, texture.as_ref());
unsafe {
context
.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_u8_array(
//context.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_array_buffer_view(
WebGlRenderingContext::TEXTURE_2D,
0,
WebGlRenderingContext::RGBA as i32,
WIDTH,
HEIGHT,
0,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should create GPU memory OK");
}
context.generate_mipmap(WebGlRenderingContext::TEXTURE_2D);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_S,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_T,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_MAG_FILTER,
WebGlRenderingContext::LINEAR as i32,
);
context.uniform1i(Some(texture_location.unwrap().as_ref()), 0);
// draw()
context.clear_color(0.0, 0.0, 0.0, 1.0);
context.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
context.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
input_data_update_loop(context, texture.unwrap());
// Fin
Ok(())
}
pub fn input_data_update_loop(gl: WebGlRenderingContext, texture: web_sys::WebGlTexture) {
let f = Rc::new(RefCell::new(None));
let g = f.clone();
{
*g.borrow_mut() = Some(Closure::wrap(Box::new(move || {
gl.bind_texture(WebGlRenderingContext::TEXTURE_2D, Some(&texture));
unsafe {
if PIXEL_DATA_UPDATED == true {
gl.tex_sub_image_2d_with_i32_and_i32_and_u32_and_type_and_opt_u8_array(
WebGlRenderingContext::TEXTURE_2D,
0,
0,
0,
WIDTH,
HEIGHT,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should update GPU memory OK");
PIXEL_DATA_UPDATED = false;
}
}
gl.clear_color(0.0, 0.0, 0.0, 1.0);
gl.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
gl.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
//update_texture_and_draw(gl, texture, texture_location);
request_animation_frame(f.borrow().as_ref().unwrap());
}) as Box<dyn FnMut()>));
}
request_animation_frame(g.borrow().as_ref().unwrap());
}
pub fn compile_shader(
context: &WebGlRenderingContext,
shader_type: u32,
source: &str,
) -> Result<WebGlShader, String> {
let shader = context
.create_shader(shader_type)
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.shader_source(&shader, source);
context.compile_shader(&shader);
if context
.get_shader_parameter(&shader, WebGlRenderingContext::COMPILE_STATUS)
.as_bool()
.unwrap_or(false)
| else {
Err(context
.get_shader_info_log(&shader)
.unwrap_or_else(|| String::from("Unknown error creating shader")))
}
}
pub fn link_program(
context: &WebGlRenderingContext,
vert_shader: &WebGlShader,
frag_shader: &WebGlShader,
) -> Result<WebGlProgram, String> {
let program = context
.create_program()
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.attach_shader(&program, vert_shader);
context.attach_shader(&program, frag_shader);
context.link_program(&program);
if context
.get_program_parameter(&program, WebGlRenderingContext::LINK_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(program)
} else {
Err(context
.get_program_info_log(&program)
.unwrap_or_else(|| String::from("Unknown error creating program object")))
}
}
#[wasm_bindgen]
pub fn copy(data: &ImageData) -> Result<(), JsValue> {
unsafe {
// TODO use mutex
if PIXEL_DATA_UPDATED == false && PIXEL_DATA_UPDATING == false {
PIXEL_DATA_UPDATING = true;
for i in 0..BUFFER_SIZE {
PIXEL_DATA[i] = data.data()[i];
}
PIXEL_DATA_UPDATING = false;
PIXEL_DATA_UPDATED = true;
}
}
Ok(())
}
| {
Ok(shader)
} | conditional_block |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as usize;
static mut PIXEL_DATA: [u8; BUFFER_SIZE] = [255; BUFFER_SIZE];
static mut PIXEL_DATA_UPDATING: bool = false;
static mut PIXEL_DATA_UPDATED: bool = false;
// static mut CLIENT_READY: bool = false;
const VERTICES: [f32; 18] = [
-1.0, -1.0, 0.0, // Bottom left
1.0, -1.0, 0.0, // Bottem right
1.0, 1.0, 0.0, // Top right
-1.0, -1.0, 0.0, // Bottom left
1.0, 1.0, 0.0, // Top right
-1.0, 1.0, 0.0, // Top left
];
fn window() -> web_sys::Window {
web_sys::window().expect("no global `window` exists")
}
fn request_animation_frame(f: &Closure<dyn FnMut()>) {
window()
.request_animation_frame(f.as_ref().unchecked_ref()) | pub fn start() {
utils::set_panic_hook();
log!("Hello there! Compositor canvas starting/loading");
}
#[wasm_bindgen]
pub fn initialise(element_id: String) -> Result<(), JsValue> {
log!(
"Compositor canvas (element_id: String = `{}`) initialisation",
&element_id
);
let document = web_sys::window().unwrap().document().unwrap();
let canvas = document.get_element_by_id(&element_id).unwrap();
let canvas: web_sys::HtmlCanvasElement = canvas.dyn_into::<web_sys::HtmlCanvasElement>()?;
let context = canvas
.get_context("webgl")?
.unwrap()
.dyn_into::<WebGlRenderingContext>()?;
let vert_shader = compile_shader(
&context,
WebGlRenderingContext::VERTEX_SHADER,
r#"
attribute vec4 position;
attribute vec2 textureCoord;
varying highp vec2 vTextureCoord;
void main(void) {
gl_Position = position;
vTextureCoord = textureCoord;
}
"#,
)?;
let frag_shader = compile_shader(
&context,
WebGlRenderingContext::FRAGMENT_SHADER,
r#"
varying highp vec2 vTextureCoord;
uniform sampler2D image;
void main(void) {
gl_FragColor = texture2D(image, vTextureCoord);
gl_FragColor = vec4(gl_FragColor.b, gl_FragColor.g, gl_FragColor.r, gl_FragColor.a);
}
"#,
)?;
let program = link_program(&context, &vert_shader, &frag_shader)?;
let position_location = context.get_attrib_location(&program, "position");
let texcoord_location = context.get_attrib_location(&program, "textureCoord");
let texture_location = context.get_uniform_location(&program, "image"); //.unwrap();
// Bind shader
context.use_program(Some(&program));
// Build model
let vertex_buffer = context
.create_buffer()
.ok_or("failed to create vertex buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&vertex_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let vert_array = js_sys::Float32Array::view(&VERTICES);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&vert_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
position_location as u32,
3,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(position_location as u32);
// Add uvs
let uvs: [f32; 12] = [
0.0, 1.0, // Bottom left
1.0, 1.0, // Bottem right
1.0, 0.0, // Top right
0.0, 1.0, // Bottom left
1.0, 0.0, // Top right
0.0, 0.0, // Top left
];
let uv_buffer = context
.create_buffer()
.ok_or("failed to create uv buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&uv_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let uv_array = js_sys::Float32Array::view(&uvs);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&uv_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
texcoord_location as u32,
2,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(texcoord_location as u32);
// Create a texture
let texture = context.create_texture();
context.bind_texture(WebGlRenderingContext::TEXTURE_2D, texture.as_ref());
unsafe {
context
.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_u8_array(
//context.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_array_buffer_view(
WebGlRenderingContext::TEXTURE_2D,
0,
WebGlRenderingContext::RGBA as i32,
WIDTH,
HEIGHT,
0,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should create GPU memory OK");
}
context.generate_mipmap(WebGlRenderingContext::TEXTURE_2D);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_S,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_T,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_MAG_FILTER,
WebGlRenderingContext::LINEAR as i32,
);
context.uniform1i(Some(texture_location.unwrap().as_ref()), 0);
// draw()
context.clear_color(0.0, 0.0, 0.0, 1.0);
context.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
context.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
input_data_update_loop(context, texture.unwrap());
// Fin
Ok(())
}
pub fn input_data_update_loop(gl: WebGlRenderingContext, texture: web_sys::WebGlTexture) {
let f = Rc::new(RefCell::new(None));
let g = f.clone();
{
*g.borrow_mut() = Some(Closure::wrap(Box::new(move || {
gl.bind_texture(WebGlRenderingContext::TEXTURE_2D, Some(&texture));
unsafe {
if PIXEL_DATA_UPDATED == true {
gl.tex_sub_image_2d_with_i32_and_i32_and_u32_and_type_and_opt_u8_array(
WebGlRenderingContext::TEXTURE_2D,
0,
0,
0,
WIDTH,
HEIGHT,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should update GPU memory OK");
PIXEL_DATA_UPDATED = false;
}
}
gl.clear_color(0.0, 0.0, 0.0, 1.0);
gl.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
gl.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
//update_texture_and_draw(gl, texture, texture_location);
request_animation_frame(f.borrow().as_ref().unwrap());
}) as Box<dyn FnMut()>));
}
request_animation_frame(g.borrow().as_ref().unwrap());
}
pub fn compile_shader(
context: &WebGlRenderingContext,
shader_type: u32,
source: &str,
) -> Result<WebGlShader, String> {
let shader = context
.create_shader(shader_type)
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.shader_source(&shader, source);
context.compile_shader(&shader);
if context
.get_shader_parameter(&shader, WebGlRenderingContext::COMPILE_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(shader)
} else {
Err(context
.get_shader_info_log(&shader)
.unwrap_or_else(|| String::from("Unknown error creating shader")))
}
}
pub fn link_program(
context: &WebGlRenderingContext,
vert_shader: &WebGlShader,
frag_shader: &WebGlShader,
) -> Result<WebGlProgram, String> {
let program = context
.create_program()
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.attach_shader(&program, vert_shader);
context.attach_shader(&program, frag_shader);
context.link_program(&program);
if context
.get_program_parameter(&program, WebGlRenderingContext::LINK_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(program)
} else {
Err(context
.get_program_info_log(&program)
.unwrap_or_else(|| String::from("Unknown error creating program object")))
}
}
#[wasm_bindgen]
pub fn copy(data: &ImageData) -> Result<(), JsValue> {
unsafe {
// TODO use mutex
if PIXEL_DATA_UPDATED == false && PIXEL_DATA_UPDATING == false {
PIXEL_DATA_UPDATING = true;
for i in 0..BUFFER_SIZE {
PIXEL_DATA[i] = data.data()[i];
}
PIXEL_DATA_UPDATING = false;
PIXEL_DATA_UPDATED = true;
}
}
Ok(())
} | .expect("should register `requestAnimationFrame` OK");
}
#[wasm_bindgen(start)] | random_line_split |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as usize;
static mut PIXEL_DATA: [u8; BUFFER_SIZE] = [255; BUFFER_SIZE];
static mut PIXEL_DATA_UPDATING: bool = false;
static mut PIXEL_DATA_UPDATED: bool = false;
// static mut CLIENT_READY: bool = false;
const VERTICES: [f32; 18] = [
-1.0, -1.0, 0.0, // Bottom left
1.0, -1.0, 0.0, // Bottem right
1.0, 1.0, 0.0, // Top right
-1.0, -1.0, 0.0, // Bottom left
1.0, 1.0, 0.0, // Top right
-1.0, 1.0, 0.0, // Top left
];
fn window() -> web_sys::Window {
web_sys::window().expect("no global `window` exists")
}
fn request_animation_frame(f: &Closure<dyn FnMut()>) {
window()
.request_animation_frame(f.as_ref().unchecked_ref())
.expect("should register `requestAnimationFrame` OK");
}
#[wasm_bindgen(start)]
pub fn start() {
utils::set_panic_hook();
log!("Hello there! Compositor canvas starting/loading");
}
#[wasm_bindgen]
pub fn initialise(element_id: String) -> Result<(), JsValue> {
log!(
"Compositor canvas (element_id: String = `{}`) initialisation",
&element_id
);
let document = web_sys::window().unwrap().document().unwrap();
let canvas = document.get_element_by_id(&element_id).unwrap();
let canvas: web_sys::HtmlCanvasElement = canvas.dyn_into::<web_sys::HtmlCanvasElement>()?;
let context = canvas
.get_context("webgl")?
.unwrap()
.dyn_into::<WebGlRenderingContext>()?;
let vert_shader = compile_shader(
&context,
WebGlRenderingContext::VERTEX_SHADER,
r#"
attribute vec4 position;
attribute vec2 textureCoord;
varying highp vec2 vTextureCoord;
void main(void) {
gl_Position = position;
vTextureCoord = textureCoord;
}
"#,
)?;
let frag_shader = compile_shader(
&context,
WebGlRenderingContext::FRAGMENT_SHADER,
r#"
varying highp vec2 vTextureCoord;
uniform sampler2D image;
void main(void) {
gl_FragColor = texture2D(image, vTextureCoord);
gl_FragColor = vec4(gl_FragColor.b, gl_FragColor.g, gl_FragColor.r, gl_FragColor.a);
}
"#,
)?;
let program = link_program(&context, &vert_shader, &frag_shader)?;
let position_location = context.get_attrib_location(&program, "position");
let texcoord_location = context.get_attrib_location(&program, "textureCoord");
let texture_location = context.get_uniform_location(&program, "image"); //.unwrap();
// Bind shader
context.use_program(Some(&program));
// Build model
let vertex_buffer = context
.create_buffer()
.ok_or("failed to create vertex buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&vertex_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let vert_array = js_sys::Float32Array::view(&VERTICES);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&vert_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
position_location as u32,
3,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(position_location as u32);
// Add uvs
let uvs: [f32; 12] = [
0.0, 1.0, // Bottom left
1.0, 1.0, // Bottem right
1.0, 0.0, // Top right
0.0, 1.0, // Bottom left
1.0, 0.0, // Top right
0.0, 0.0, // Top left
];
let uv_buffer = context
.create_buffer()
.ok_or("failed to create uv buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&uv_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let uv_array = js_sys::Float32Array::view(&uvs);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&uv_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
texcoord_location as u32,
2,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(texcoord_location as u32);
// Create a texture
let texture = context.create_texture();
context.bind_texture(WebGlRenderingContext::TEXTURE_2D, texture.as_ref());
unsafe {
context
.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_u8_array(
//context.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_array_buffer_view(
WebGlRenderingContext::TEXTURE_2D,
0,
WebGlRenderingContext::RGBA as i32,
WIDTH,
HEIGHT,
0,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should create GPU memory OK");
}
context.generate_mipmap(WebGlRenderingContext::TEXTURE_2D);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_S,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_T,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_MAG_FILTER,
WebGlRenderingContext::LINEAR as i32,
);
context.uniform1i(Some(texture_location.unwrap().as_ref()), 0);
// draw()
context.clear_color(0.0, 0.0, 0.0, 1.0);
context.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
context.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
input_data_update_loop(context, texture.unwrap());
// Fin
Ok(())
}
pub fn input_data_update_loop(gl: WebGlRenderingContext, texture: web_sys::WebGlTexture) {
let f = Rc::new(RefCell::new(None));
let g = f.clone();
{
*g.borrow_mut() = Some(Closure::wrap(Box::new(move || {
gl.bind_texture(WebGlRenderingContext::TEXTURE_2D, Some(&texture));
unsafe {
if PIXEL_DATA_UPDATED == true {
gl.tex_sub_image_2d_with_i32_and_i32_and_u32_and_type_and_opt_u8_array(
WebGlRenderingContext::TEXTURE_2D,
0,
0,
0,
WIDTH,
HEIGHT,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should update GPU memory OK");
PIXEL_DATA_UPDATED = false;
}
}
gl.clear_color(0.0, 0.0, 0.0, 1.0);
gl.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
gl.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
//update_texture_and_draw(gl, texture, texture_location);
request_animation_frame(f.borrow().as_ref().unwrap());
}) as Box<dyn FnMut()>));
}
request_animation_frame(g.borrow().as_ref().unwrap());
}
pub fn | (
context: &WebGlRenderingContext,
shader_type: u32,
source: &str,
) -> Result<WebGlShader, String> {
let shader = context
.create_shader(shader_type)
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.shader_source(&shader, source);
context.compile_shader(&shader);
if context
.get_shader_parameter(&shader, WebGlRenderingContext::COMPILE_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(shader)
} else {
Err(context
.get_shader_info_log(&shader)
.unwrap_or_else(|| String::from("Unknown error creating shader")))
}
}
pub fn link_program(
context: &WebGlRenderingContext,
vert_shader: &WebGlShader,
frag_shader: &WebGlShader,
) -> Result<WebGlProgram, String> {
let program = context
.create_program()
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.attach_shader(&program, vert_shader);
context.attach_shader(&program, frag_shader);
context.link_program(&program);
if context
.get_program_parameter(&program, WebGlRenderingContext::LINK_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(program)
} else {
Err(context
.get_program_info_log(&program)
.unwrap_or_else(|| String::from("Unknown error creating program object")))
}
}
#[wasm_bindgen]
pub fn copy(data: &ImageData) -> Result<(), JsValue> {
unsafe {
// TODO use mutex
if PIXEL_DATA_UPDATED == false && PIXEL_DATA_UPDATING == false {
PIXEL_DATA_UPDATING = true;
for i in 0..BUFFER_SIZE {
PIXEL_DATA[i] = data.data()[i];
}
PIXEL_DATA_UPDATING = false;
PIXEL_DATA_UPDATED = true;
}
}
Ok(())
}
| compile_shader | identifier_name |
lib.rs | mod utils;
use std::cell::RefCell;
use std::rc::Rc;
use wasm_bindgen::prelude::*;
use wasm_bindgen::JsCast;
use web_sys::{ImageData, WebGlProgram, WebGlRenderingContext, WebGlShader};
const WIDTH: i32 = 128;
const HEIGHT: i32 = 128;
const CHANNELS: i32 = 4;
const BUFFER_SIZE: usize = ((WIDTH * HEIGHT) * CHANNELS) as usize;
static mut PIXEL_DATA: [u8; BUFFER_SIZE] = [255; BUFFER_SIZE];
static mut PIXEL_DATA_UPDATING: bool = false;
static mut PIXEL_DATA_UPDATED: bool = false;
// static mut CLIENT_READY: bool = false;
const VERTICES: [f32; 18] = [
-1.0, -1.0, 0.0, // Bottom left
1.0, -1.0, 0.0, // Bottem right
1.0, 1.0, 0.0, // Top right
-1.0, -1.0, 0.0, // Bottom left
1.0, 1.0, 0.0, // Top right
-1.0, 1.0, 0.0, // Top left
];
fn window() -> web_sys::Window {
web_sys::window().expect("no global `window` exists")
}
fn request_animation_frame(f: &Closure<dyn FnMut()>) |
#[wasm_bindgen(start)]
pub fn start() {
utils::set_panic_hook();
log!("Hello there! Compositor canvas starting/loading");
}
#[wasm_bindgen]
pub fn initialise(element_id: String) -> Result<(), JsValue> {
log!(
"Compositor canvas (element_id: String = `{}`) initialisation",
&element_id
);
let document = web_sys::window().unwrap().document().unwrap();
let canvas = document.get_element_by_id(&element_id).unwrap();
let canvas: web_sys::HtmlCanvasElement = canvas.dyn_into::<web_sys::HtmlCanvasElement>()?;
let context = canvas
.get_context("webgl")?
.unwrap()
.dyn_into::<WebGlRenderingContext>()?;
let vert_shader = compile_shader(
&context,
WebGlRenderingContext::VERTEX_SHADER,
r#"
attribute vec4 position;
attribute vec2 textureCoord;
varying highp vec2 vTextureCoord;
void main(void) {
gl_Position = position;
vTextureCoord = textureCoord;
}
"#,
)?;
let frag_shader = compile_shader(
&context,
WebGlRenderingContext::FRAGMENT_SHADER,
r#"
varying highp vec2 vTextureCoord;
uniform sampler2D image;
void main(void) {
gl_FragColor = texture2D(image, vTextureCoord);
gl_FragColor = vec4(gl_FragColor.b, gl_FragColor.g, gl_FragColor.r, gl_FragColor.a);
}
"#,
)?;
let program = link_program(&context, &vert_shader, &frag_shader)?;
let position_location = context.get_attrib_location(&program, "position");
let texcoord_location = context.get_attrib_location(&program, "textureCoord");
let texture_location = context.get_uniform_location(&program, "image"); //.unwrap();
// Bind shader
context.use_program(Some(&program));
// Build model
let vertex_buffer = context
.create_buffer()
.ok_or("failed to create vertex buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&vertex_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let vert_array = js_sys::Float32Array::view(&VERTICES);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&vert_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
position_location as u32,
3,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(position_location as u32);
// Add uvs
let uvs: [f32; 12] = [
0.0, 1.0, // Bottom left
1.0, 1.0, // Bottem right
1.0, 0.0, // Top right
0.0, 1.0, // Bottom left
1.0, 0.0, // Top right
0.0, 0.0, // Top left
];
let uv_buffer = context
.create_buffer()
.ok_or("failed to create uv buffer")?;
context.bind_buffer(WebGlRenderingContext::ARRAY_BUFFER, Some(&uv_buffer));
// Note that `Float32Array::view` is somewhat dangerous (hence the
// `unsafe`!). This is creating a raw view into our module's
// `WebAssembly.Memory` buffer, but if we allocate more pages for ourself
// (aka do a memory allocation in Rust) it'll cause the buffer to change,
// causing the `Float32Array` to be invalid.
//
// As a result, after `Float32Array::view` we have to be very careful not to
// do any memory allocations before it's dropped.
unsafe {
let uv_array = js_sys::Float32Array::view(&uvs);
context.buffer_data_with_array_buffer_view(
WebGlRenderingContext::ARRAY_BUFFER,
&uv_array,
WebGlRenderingContext::STATIC_DRAW,
);
}
context.vertex_attrib_pointer_with_i32(
texcoord_location as u32,
2,
WebGlRenderingContext::FLOAT,
false,
0,
0,
);
context.enable_vertex_attrib_array(texcoord_location as u32);
// Create a texture
let texture = context.create_texture();
context.bind_texture(WebGlRenderingContext::TEXTURE_2D, texture.as_ref());
unsafe {
context
.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_u8_array(
//context.tex_image_2d_with_i32_and_i32_and_i32_and_format_and_type_and_opt_array_buffer_view(
WebGlRenderingContext::TEXTURE_2D,
0,
WebGlRenderingContext::RGBA as i32,
WIDTH,
HEIGHT,
0,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should create GPU memory OK");
}
context.generate_mipmap(WebGlRenderingContext::TEXTURE_2D);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_S,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_WRAP_T,
WebGlRenderingContext::CLAMP_TO_EDGE as i32,
);
context.tex_parameteri(
WebGlRenderingContext::TEXTURE_2D,
WebGlRenderingContext::TEXTURE_MAG_FILTER,
WebGlRenderingContext::LINEAR as i32,
);
context.uniform1i(Some(texture_location.unwrap().as_ref()), 0);
// draw()
context.clear_color(0.0, 0.0, 0.0, 1.0);
context.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
context.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
input_data_update_loop(context, texture.unwrap());
// Fin
Ok(())
}
pub fn input_data_update_loop(gl: WebGlRenderingContext, texture: web_sys::WebGlTexture) {
let f = Rc::new(RefCell::new(None));
let g = f.clone();
{
*g.borrow_mut() = Some(Closure::wrap(Box::new(move || {
gl.bind_texture(WebGlRenderingContext::TEXTURE_2D, Some(&texture));
unsafe {
if PIXEL_DATA_UPDATED == true {
gl.tex_sub_image_2d_with_i32_and_i32_and_u32_and_type_and_opt_u8_array(
WebGlRenderingContext::TEXTURE_2D,
0,
0,
0,
WIDTH,
HEIGHT,
WebGlRenderingContext::RGBA,
WebGlRenderingContext::UNSIGNED_BYTE,
Some(&PIXEL_DATA),
)
.expect("should update GPU memory OK");
PIXEL_DATA_UPDATED = false;
}
}
gl.clear_color(0.0, 0.0, 0.0, 1.0);
gl.clear(WebGlRenderingContext::COLOR_BUFFER_BIT);
gl.draw_arrays(
WebGlRenderingContext::TRIANGLES,
0,
(VERTICES.len() / 3) as i32,
);
//update_texture_and_draw(gl, texture, texture_location);
request_animation_frame(f.borrow().as_ref().unwrap());
}) as Box<dyn FnMut()>));
}
request_animation_frame(g.borrow().as_ref().unwrap());
}
pub fn compile_shader(
context: &WebGlRenderingContext,
shader_type: u32,
source: &str,
) -> Result<WebGlShader, String> {
let shader = context
.create_shader(shader_type)
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.shader_source(&shader, source);
context.compile_shader(&shader);
if context
.get_shader_parameter(&shader, WebGlRenderingContext::COMPILE_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(shader)
} else {
Err(context
.get_shader_info_log(&shader)
.unwrap_or_else(|| String::from("Unknown error creating shader")))
}
}
pub fn link_program(
context: &WebGlRenderingContext,
vert_shader: &WebGlShader,
frag_shader: &WebGlShader,
) -> Result<WebGlProgram, String> {
let program = context
.create_program()
.ok_or_else(|| String::from("Unable to create shader object"))?;
context.attach_shader(&program, vert_shader);
context.attach_shader(&program, frag_shader);
context.link_program(&program);
if context
.get_program_parameter(&program, WebGlRenderingContext::LINK_STATUS)
.as_bool()
.unwrap_or(false)
{
Ok(program)
} else {
Err(context
.get_program_info_log(&program)
.unwrap_or_else(|| String::from("Unknown error creating program object")))
}
}
#[wasm_bindgen]
pub fn copy(data: &ImageData) -> Result<(), JsValue> {
unsafe {
// TODO use mutex
if PIXEL_DATA_UPDATED == false && PIXEL_DATA_UPDATING == false {
PIXEL_DATA_UPDATING = true;
for i in 0..BUFFER_SIZE {
PIXEL_DATA[i] = data.data()[i];
}
PIXEL_DATA_UPDATING = false;
PIXEL_DATA_UPDATED = true;
}
}
Ok(())
}
| {
window()
.request_animation_frame(f.as_ref().unchecked_ref())
.expect("should register `requestAnimationFrame` OK");
} | identifier_body |
async_stream_cdc.rs | //
// Copyright (c) 2023 Nathan Fiedler
//
use super::*;
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::{
io::{AsyncRead, AsyncReadExt},
stream::Stream,
};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::Stream;
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio::io::{AsyncRead, AsyncReadExt};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use async_stream::try_stream;
///
/// An async-streamable version of the FastCDC chunker implementation from 2020
/// with streaming support.
///
/// Use `new` to construct an instance, and then `as_stream` to produce an async
/// [Stream] of the chunks.
///
/// Both `futures` and `tokio`-based [AsyncRead] inputs are supported via
/// feature flags. But, if necessary you can also use the
/// [`async_compat`](https://docs.rs/async-compat/latest/async_compat/) crate to
/// adapt your inputs as circumstances may require.
///
/// Note that this struct allocates a `Vec<u8>` of `max_size` bytes to act as a
/// buffer when reading from the source and finding chunk boundaries.
///
/// ```no_run
/// # use std::fs::File;
/// # use fastcdc::v2020::AsyncStreamCDC;
/// # #[cfg(all(feature = "futures", not(feature = "tokio")))]
/// # use futures::stream::StreamExt;
/// # #[cfg(all(feature = "tokio", not(feature = "futures")))]
/// # use tokio_stream::StreamExt;
///
/// async fn run() {
/// let source = std::fs::read("test/fixtures/SekienAkashita.jpg").unwrap();
/// let mut chunker = AsyncStreamCDC::new(source.as_ref(), 4096, 16384, 65535);
/// let stream = chunker.as_stream();
///
/// let chunks = stream.collect::<Vec<_>>().await;
///
/// for result in chunks {
/// let chunk = result.unwrap();
/// println!("offset={} length={}", chunk.offset, chunk.length);
/// }
/// }
/// ```
///
pub struct AsyncStreamCDC<R> {
/// Buffer of data from source for finding cut points.
buffer: Vec<u8>,
/// Maximum capacity of the buffer (always `max_size`).
capacity: usize,
/// Number of relevant bytes in the `buffer`.
length: usize,
/// Source from which data is read into `buffer`.
source: R,
/// Number of bytes read from the source so far.
processed: u64,
/// True when the source produces no more data.
eof: bool,
min_size: usize,
avg_size: usize,
max_size: usize,
mask_s: u64,
mask_l: u64,
mask_s_ls: u64,
mask_l_ls: u64,
}
impl<R: AsyncRead + Unpin> AsyncStreamCDC<R> {
///
/// Construct a `StreamCDC` that will process bytes from the given source.
///
/// Uses chunk size normalization level 1 by default.
///
pub fn new(source: R, min_size: u32, avg_size: u32, max_size: u32) -> Self {
Self::with_level(source, min_size, avg_size, max_size, Normalization::Level1)
}
///
/// Create a new `StreamCDC` with the given normalization level.
///
pub fn with_level(
source: R,
min_size: u32,
avg_size: u32,
max_size: u32,
level: Normalization,
) -> Self {
assert!(min_size >= MINIMUM_MIN);
assert!(min_size <= MINIMUM_MAX);
assert!(avg_size >= AVERAGE_MIN);
assert!(avg_size <= AVERAGE_MAX);
assert!(max_size >= MAXIMUM_MIN);
assert!(max_size <= MAXIMUM_MAX);
let bits = logarithm2(avg_size);
let normalization = level.bits();
let mask_s = MASKS[(bits + normalization) as usize];
let mask_l = MASKS[(bits - normalization) as usize];
Self {
buffer: vec![0_u8; max_size as usize],
capacity: max_size as usize,
length: 0,
source,
eof: false,
processed: 0,
min_size: min_size as usize,
avg_size: avg_size as usize,
max_size: max_size as usize,
mask_s,
mask_l,
mask_s_ls: mask_s << 1,
mask_l_ls: mask_l << 1,
}
}
/// Fill the buffer with data from the source, returning the number of bytes
/// read (zero if end of source has been reached).
async fn fill_buffer(&mut self) -> Result<usize, Error> {
// this code originally copied from asuran crate
if self.eof {
Ok(0)
} else {
let mut all_bytes_read = 0;
while !self.eof && self.length < self.capacity {
let bytes_read = self.source.read(&mut self.buffer[self.length..]).await?;
if bytes_read == 0 {
self.eof = true;
} else {
self.length += bytes_read;
all_bytes_read += bytes_read;
}
}
Ok(all_bytes_read)
}
}
/// Drains a specified number of bytes from the buffer, then resizes the
/// buffer back to `capacity` size in preparation for further reads.
fn drain_bytes(&mut self, count: usize) -> Result<Vec<u8>, Error> {
// this code originally copied from asuran crate
if count > self.length {
Err(Error::Other(format!(
"drain_bytes() called with count larger than length: {} > {}",
count, self.length
)))
} else {
let data = self.buffer.drain(..count).collect::<Vec<u8>>();
self.length -= count;
self.buffer.resize(self.capacity, 0_u8);
Ok(data)
}
}
/// Find the next chunk in the source. If the end of the source has been
/// reached, returns `Error::Empty` as the error.
async fn read_chunk(&mut self) -> Result<ChunkData, Error> {
self.fill_buffer().await?;
if self.length == 0 {
Err(Error::Empty)
} else {
let (hash, count) = cut(
&self.buffer[..self.length],
self.min_size,
self.avg_size,
self.max_size,
self.mask_s,
self.mask_l,
self.mask_s_ls,
self.mask_l_ls,
);
if count == 0 {
Err(Error::Empty)
} else {
let offset = self.processed;
self.processed += count as u64;
let data = self.drain_bytes(count)?;
Ok(ChunkData {
hash,
offset,
length: count,
data,
})
}
}
}
#[cfg(all(feature = "tokio", not(feature = "futures")))]
pub fn as_stream(&mut self) -> impl Stream<Item = Result<ChunkData, Error>> + '_ {
try_stream! {
loop {
match self.read_chunk().await {
Ok(chunk) => yield chunk,
Err(Error::Empty) => {
break;
}
error @ Err(_) => {
error?;
}
}
}
}
}
#[cfg(all(feature = "futures", not(feature = "tokio")))]
pub fn as_stream(&mut self) -> impl Stream<Item = Result<ChunkData, Error>> + '_ {
futures::stream::unfold(self, |this| async {
let chunk = this.read_chunk().await;
if let Err(Error::Empty) = chunk {
None
} else {
Some((chunk, this))
}
})
}
}
#[cfg(test)]
mod tests {
use crate::v2020::MASKS;
use super::AsyncStreamCDC;
#[test]
#[should_panic]
fn test_minimum_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 63, 256, 1024);
}
#[test]
#[should_panic]
fn test_minimum_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 67_108_867, 256, 1024);
}
#[test]
#[should_panic]
fn | () {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 255, 1024);
}
#[test]
#[should_panic]
fn test_average_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 268_435_457, 1024);
}
#[test]
#[should_panic]
fn test_maximum_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 256, 1023);
}
#[test]
#[should_panic]
fn test_maximum_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 256, 1_073_741_825);
}
#[test]
fn test_masks() {
let source = [0u8; 1024];
let chunker = AsyncStreamCDC::new(source.as_slice(), 64, 256, 1024);
assert_eq!(chunker.mask_l, MASKS[7]);
assert_eq!(chunker.mask_s, MASKS[9]);
let chunker = AsyncStreamCDC::new(source.as_slice(), 8192, 16384, 32768);
assert_eq!(chunker.mask_l, MASKS[13]);
assert_eq!(chunker.mask_s, MASKS[15]);
let chunker = AsyncStreamCDC::new(source.as_slice(), 1_048_576, 4_194_304, 16_777_216);
assert_eq!(chunker.mask_l, MASKS[21]);
assert_eq!(chunker.mask_s, MASKS[23]);
}
struct ExpectedChunk {
hash: u64,
offset: u64,
length: usize,
digest: String,
}
use md5::{Digest, Md5};
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::stream::StreamExt;
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::StreamExt;
#[cfg_attr(all(feature = "tokio", not(feature = "futures")), tokio::test)]
#[cfg_attr(all(feature = "futures", not(feature = "tokio")), futures_test::test)]
async fn test_iter_sekien_16k_chunks() {
let read_result = std::fs::read("test/fixtures/SekienAkashita.jpg");
assert!(read_result.is_ok());
let contents = read_result.unwrap();
// The digest values are not needed here, but they serve to validate
// that the streaming version tested below is returning the correct
// chunk data on each iteration.
let expected_chunks = vec![
ExpectedChunk {
hash: 17968276318003433923,
offset: 0,
length: 21325,
digest: "2bb52734718194617c957f5e07ee6054".into(),
},
ExpectedChunk {
hash: 8197189939299398838,
offset: 21325,
length: 17140,
digest: "badfb0757fe081c20336902e7131f768".into(),
},
ExpectedChunk {
hash: 13019990849178155730,
offset: 38465,
length: 28084,
digest: "18412d7414de6eb42f638351711f729d".into(),
},
ExpectedChunk {
hash: 4509236223063678303,
offset: 66549,
length: 18217,
digest: "04fe1405fc5f960363bfcd834c056407".into(),
},
ExpectedChunk {
hash: 2504464741100432583,
offset: 84766,
length: 24700,
digest: "1aa7ad95f274d6ba34a983946ebc5af3".into(),
},
];
let mut chunker = AsyncStreamCDC::new(contents.as_ref(), 4096, 16384, 65535);
let stream = chunker.as_stream();
let chunks = stream.collect::<Vec<_>>().await;
let mut index = 0;
for chunk in chunks {
let chunk = chunk.unwrap();
assert_eq!(chunk.hash, expected_chunks[index].hash);
assert_eq!(chunk.offset, expected_chunks[index].offset);
assert_eq!(chunk.length, expected_chunks[index].length);
let mut hasher = Md5::new();
hasher
.update(&contents[(chunk.offset as usize)..(chunk.offset as usize) + chunk.length]);
let table = hasher.finalize();
let digest = format!("{:x}", table);
assert_eq!(digest, expected_chunks[index].digest);
index += 1;
}
assert_eq!(index, 5);
}
}
| test_average_too_low | identifier_name |
async_stream_cdc.rs | //
// Copyright (c) 2023 Nathan Fiedler
//
use super::*;
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::{
io::{AsyncRead, AsyncReadExt},
stream::Stream,
};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::Stream;
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio::io::{AsyncRead, AsyncReadExt};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use async_stream::try_stream;
///
/// An async-streamable version of the FastCDC chunker implementation from 2020
/// with streaming support.
///
/// Use `new` to construct an instance, and then `as_stream` to produce an async
/// [Stream] of the chunks.
///
/// Both `futures` and `tokio`-based [AsyncRead] inputs are supported via
/// feature flags. But, if necessary you can also use the
/// [`async_compat`](https://docs.rs/async-compat/latest/async_compat/) crate to
/// adapt your inputs as circumstances may require.
///
/// Note that this struct allocates a `Vec<u8>` of `max_size` bytes to act as a
/// buffer when reading from the source and finding chunk boundaries.
///
/// ```no_run
/// # use std::fs::File;
/// # use fastcdc::v2020::AsyncStreamCDC;
/// # #[cfg(all(feature = "futures", not(feature = "tokio")))]
/// # use futures::stream::StreamExt;
/// # #[cfg(all(feature = "tokio", not(feature = "futures")))]
/// # use tokio_stream::StreamExt;
///
/// async fn run() {
/// let source = std::fs::read("test/fixtures/SekienAkashita.jpg").unwrap();
/// let mut chunker = AsyncStreamCDC::new(source.as_ref(), 4096, 16384, 65535);
/// let stream = chunker.as_stream();
///
/// let chunks = stream.collect::<Vec<_>>().await;
///
/// for result in chunks {
/// let chunk = result.unwrap();
/// println!("offset={} length={}", chunk.offset, chunk.length);
/// }
/// }
/// ```
///
pub struct AsyncStreamCDC<R> {
/// Buffer of data from source for finding cut points.
buffer: Vec<u8>,
/// Maximum capacity of the buffer (always `max_size`).
capacity: usize,
/// Number of relevant bytes in the `buffer`.
length: usize,
/// Source from which data is read into `buffer`.
source: R,
/// Number of bytes read from the source so far.
processed: u64,
/// True when the source produces no more data.
eof: bool,
min_size: usize,
avg_size: usize,
max_size: usize,
mask_s: u64,
mask_l: u64,
mask_s_ls: u64,
mask_l_ls: u64,
}
impl<R: AsyncRead + Unpin> AsyncStreamCDC<R> {
///
/// Construct a `StreamCDC` that will process bytes from the given source.
///
/// Uses chunk size normalization level 1 by default.
///
pub fn new(source: R, min_size: u32, avg_size: u32, max_size: u32) -> Self {
Self::with_level(source, min_size, avg_size, max_size, Normalization::Level1)
}
///
/// Create a new `StreamCDC` with the given normalization level.
///
pub fn with_level(
source: R,
min_size: u32,
avg_size: u32,
max_size: u32,
level: Normalization,
) -> Self {
assert!(min_size >= MINIMUM_MIN);
assert!(min_size <= MINIMUM_MAX);
assert!(avg_size >= AVERAGE_MIN);
assert!(avg_size <= AVERAGE_MAX);
assert!(max_size >= MAXIMUM_MIN);
assert!(max_size <= MAXIMUM_MAX);
let bits = logarithm2(avg_size);
let normalization = level.bits();
let mask_s = MASKS[(bits + normalization) as usize];
let mask_l = MASKS[(bits - normalization) as usize];
Self {
buffer: vec![0_u8; max_size as usize],
capacity: max_size as usize,
length: 0,
source,
eof: false,
processed: 0,
min_size: min_size as usize,
avg_size: avg_size as usize,
max_size: max_size as usize,
mask_s,
mask_l,
mask_s_ls: mask_s << 1,
mask_l_ls: mask_l << 1,
}
}
/// Fill the buffer with data from the source, returning the number of bytes
/// read (zero if end of source has been reached).
async fn fill_buffer(&mut self) -> Result<usize, Error> {
// this code originally copied from asuran crate
if self.eof {
Ok(0)
} else {
let mut all_bytes_read = 0;
while !self.eof && self.length < self.capacity {
let bytes_read = self.source.read(&mut self.buffer[self.length..]).await?;
if bytes_read == 0 {
self.eof = true;
} else |
}
Ok(all_bytes_read)
}
}
/// Drains a specified number of bytes from the buffer, then resizes the
/// buffer back to `capacity` size in preparation for further reads.
fn drain_bytes(&mut self, count: usize) -> Result<Vec<u8>, Error> {
// this code originally copied from asuran crate
if count > self.length {
Err(Error::Other(format!(
"drain_bytes() called with count larger than length: {} > {}",
count, self.length
)))
} else {
let data = self.buffer.drain(..count).collect::<Vec<u8>>();
self.length -= count;
self.buffer.resize(self.capacity, 0_u8);
Ok(data)
}
}
/// Find the next chunk in the source. If the end of the source has been
/// reached, returns `Error::Empty` as the error.
async fn read_chunk(&mut self) -> Result<ChunkData, Error> {
self.fill_buffer().await?;
if self.length == 0 {
Err(Error::Empty)
} else {
let (hash, count) = cut(
&self.buffer[..self.length],
self.min_size,
self.avg_size,
self.max_size,
self.mask_s,
self.mask_l,
self.mask_s_ls,
self.mask_l_ls,
);
if count == 0 {
Err(Error::Empty)
} else {
let offset = self.processed;
self.processed += count as u64;
let data = self.drain_bytes(count)?;
Ok(ChunkData {
hash,
offset,
length: count,
data,
})
}
}
}
#[cfg(all(feature = "tokio", not(feature = "futures")))]
pub fn as_stream(&mut self) -> impl Stream<Item = Result<ChunkData, Error>> + '_ {
try_stream! {
loop {
match self.read_chunk().await {
Ok(chunk) => yield chunk,
Err(Error::Empty) => {
break;
}
error @ Err(_) => {
error?;
}
}
}
}
}
#[cfg(all(feature = "futures", not(feature = "tokio")))]
pub fn as_stream(&mut self) -> impl Stream<Item = Result<ChunkData, Error>> + '_ {
futures::stream::unfold(self, |this| async {
let chunk = this.read_chunk().await;
if let Err(Error::Empty) = chunk {
None
} else {
Some((chunk, this))
}
})
}
}
#[cfg(test)]
mod tests {
use crate::v2020::MASKS;
use super::AsyncStreamCDC;
#[test]
#[should_panic]
fn test_minimum_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 63, 256, 1024);
}
#[test]
#[should_panic]
fn test_minimum_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 67_108_867, 256, 1024);
}
#[test]
#[should_panic]
fn test_average_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 255, 1024);
}
#[test]
#[should_panic]
fn test_average_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 268_435_457, 1024);
}
#[test]
#[should_panic]
fn test_maximum_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 256, 1023);
}
#[test]
#[should_panic]
fn test_maximum_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 256, 1_073_741_825);
}
#[test]
fn test_masks() {
let source = [0u8; 1024];
let chunker = AsyncStreamCDC::new(source.as_slice(), 64, 256, 1024);
assert_eq!(chunker.mask_l, MASKS[7]);
assert_eq!(chunker.mask_s, MASKS[9]);
let chunker = AsyncStreamCDC::new(source.as_slice(), 8192, 16384, 32768);
assert_eq!(chunker.mask_l, MASKS[13]);
assert_eq!(chunker.mask_s, MASKS[15]);
let chunker = AsyncStreamCDC::new(source.as_slice(), 1_048_576, 4_194_304, 16_777_216);
assert_eq!(chunker.mask_l, MASKS[21]);
assert_eq!(chunker.mask_s, MASKS[23]);
}
struct ExpectedChunk {
hash: u64,
offset: u64,
length: usize,
digest: String,
}
use md5::{Digest, Md5};
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::stream::StreamExt;
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::StreamExt;
#[cfg_attr(all(feature = "tokio", not(feature = "futures")), tokio::test)]
#[cfg_attr(all(feature = "futures", not(feature = "tokio")), futures_test::test)]
async fn test_iter_sekien_16k_chunks() {
let read_result = std::fs::read("test/fixtures/SekienAkashita.jpg");
assert!(read_result.is_ok());
let contents = read_result.unwrap();
// The digest values are not needed here, but they serve to validate
// that the streaming version tested below is returning the correct
// chunk data on each iteration.
let expected_chunks = vec![
ExpectedChunk {
hash: 17968276318003433923,
offset: 0,
length: 21325,
digest: "2bb52734718194617c957f5e07ee6054".into(),
},
ExpectedChunk {
hash: 8197189939299398838,
offset: 21325,
length: 17140,
digest: "badfb0757fe081c20336902e7131f768".into(),
},
ExpectedChunk {
hash: 13019990849178155730,
offset: 38465,
length: 28084,
digest: "18412d7414de6eb42f638351711f729d".into(),
},
ExpectedChunk {
hash: 4509236223063678303,
offset: 66549,
length: 18217,
digest: "04fe1405fc5f960363bfcd834c056407".into(),
},
ExpectedChunk {
hash: 2504464741100432583,
offset: 84766,
length: 24700,
digest: "1aa7ad95f274d6ba34a983946ebc5af3".into(),
},
];
let mut chunker = AsyncStreamCDC::new(contents.as_ref(), 4096, 16384, 65535);
let stream = chunker.as_stream();
let chunks = stream.collect::<Vec<_>>().await;
let mut index = 0;
for chunk in chunks {
let chunk = chunk.unwrap();
assert_eq!(chunk.hash, expected_chunks[index].hash);
assert_eq!(chunk.offset, expected_chunks[index].offset);
assert_eq!(chunk.length, expected_chunks[index].length);
let mut hasher = Md5::new();
hasher
.update(&contents[(chunk.offset as usize)..(chunk.offset as usize) + chunk.length]);
let table = hasher.finalize();
let digest = format!("{:x}", table);
assert_eq!(digest, expected_chunks[index].digest);
index += 1;
}
assert_eq!(index, 5);
}
}
| {
self.length += bytes_read;
all_bytes_read += bytes_read;
} | conditional_block |
async_stream_cdc.rs | //
// Copyright (c) 2023 Nathan Fiedler
//
use super::*;
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::{
io::{AsyncRead, AsyncReadExt},
stream::Stream,
};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::Stream;
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio::io::{AsyncRead, AsyncReadExt};
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use async_stream::try_stream;
///
/// An async-streamable version of the FastCDC chunker implementation from 2020
/// with streaming support.
///
/// Use `new` to construct an instance, and then `as_stream` to produce an async
/// [Stream] of the chunks.
///
/// Both `futures` and `tokio`-based [AsyncRead] inputs are supported via
/// feature flags. But, if necessary you can also use the
/// [`async_compat`](https://docs.rs/async-compat/latest/async_compat/) crate to
/// adapt your inputs as circumstances may require.
///
/// Note that this struct allocates a `Vec<u8>` of `max_size` bytes to act as a
/// buffer when reading from the source and finding chunk boundaries.
///
/// ```no_run
/// # use std::fs::File;
/// # use fastcdc::v2020::AsyncStreamCDC;
/// # #[cfg(all(feature = "futures", not(feature = "tokio")))]
/// # use futures::stream::StreamExt;
/// # #[cfg(all(feature = "tokio", not(feature = "futures")))]
/// # use tokio_stream::StreamExt;
///
/// async fn run() {
/// let source = std::fs::read("test/fixtures/SekienAkashita.jpg").unwrap();
/// let mut chunker = AsyncStreamCDC::new(source.as_ref(), 4096, 16384, 65535);
/// let stream = chunker.as_stream();
///
/// let chunks = stream.collect::<Vec<_>>().await;
///
/// for result in chunks {
/// let chunk = result.unwrap();
/// println!("offset={} length={}", chunk.offset, chunk.length);
/// }
/// }
/// ```
///
pub struct AsyncStreamCDC<R> {
/// Buffer of data from source for finding cut points.
buffer: Vec<u8>,
/// Maximum capacity of the buffer (always `max_size`).
capacity: usize,
/// Number of relevant bytes in the `buffer`.
length: usize,
/// Source from which data is read into `buffer`.
source: R,
/// Number of bytes read from the source so far.
processed: u64, | max_size: usize,
mask_s: u64,
mask_l: u64,
mask_s_ls: u64,
mask_l_ls: u64,
}
impl<R: AsyncRead + Unpin> AsyncStreamCDC<R> {
///
/// Construct a `StreamCDC` that will process bytes from the given source.
///
/// Uses chunk size normalization level 1 by default.
///
pub fn new(source: R, min_size: u32, avg_size: u32, max_size: u32) -> Self {
Self::with_level(source, min_size, avg_size, max_size, Normalization::Level1)
}
///
/// Create a new `StreamCDC` with the given normalization level.
///
pub fn with_level(
source: R,
min_size: u32,
avg_size: u32,
max_size: u32,
level: Normalization,
) -> Self {
assert!(min_size >= MINIMUM_MIN);
assert!(min_size <= MINIMUM_MAX);
assert!(avg_size >= AVERAGE_MIN);
assert!(avg_size <= AVERAGE_MAX);
assert!(max_size >= MAXIMUM_MIN);
assert!(max_size <= MAXIMUM_MAX);
let bits = logarithm2(avg_size);
let normalization = level.bits();
let mask_s = MASKS[(bits + normalization) as usize];
let mask_l = MASKS[(bits - normalization) as usize];
Self {
buffer: vec![0_u8; max_size as usize],
capacity: max_size as usize,
length: 0,
source,
eof: false,
processed: 0,
min_size: min_size as usize,
avg_size: avg_size as usize,
max_size: max_size as usize,
mask_s,
mask_l,
mask_s_ls: mask_s << 1,
mask_l_ls: mask_l << 1,
}
}
/// Fill the buffer with data from the source, returning the number of bytes
/// read (zero if end of source has been reached).
async fn fill_buffer(&mut self) -> Result<usize, Error> {
// this code originally copied from asuran crate
if self.eof {
Ok(0)
} else {
let mut all_bytes_read = 0;
while !self.eof && self.length < self.capacity {
let bytes_read = self.source.read(&mut self.buffer[self.length..]).await?;
if bytes_read == 0 {
self.eof = true;
} else {
self.length += bytes_read;
all_bytes_read += bytes_read;
}
}
Ok(all_bytes_read)
}
}
/// Drains a specified number of bytes from the buffer, then resizes the
/// buffer back to `capacity` size in preparation for further reads.
fn drain_bytes(&mut self, count: usize) -> Result<Vec<u8>, Error> {
// this code originally copied from asuran crate
if count > self.length {
Err(Error::Other(format!(
"drain_bytes() called with count larger than length: {} > {}",
count, self.length
)))
} else {
let data = self.buffer.drain(..count).collect::<Vec<u8>>();
self.length -= count;
self.buffer.resize(self.capacity, 0_u8);
Ok(data)
}
}
/// Find the next chunk in the source. If the end of the source has been
/// reached, returns `Error::Empty` as the error.
async fn read_chunk(&mut self) -> Result<ChunkData, Error> {
self.fill_buffer().await?;
if self.length == 0 {
Err(Error::Empty)
} else {
let (hash, count) = cut(
&self.buffer[..self.length],
self.min_size,
self.avg_size,
self.max_size,
self.mask_s,
self.mask_l,
self.mask_s_ls,
self.mask_l_ls,
);
if count == 0 {
Err(Error::Empty)
} else {
let offset = self.processed;
self.processed += count as u64;
let data = self.drain_bytes(count)?;
Ok(ChunkData {
hash,
offset,
length: count,
data,
})
}
}
}
#[cfg(all(feature = "tokio", not(feature = "futures")))]
pub fn as_stream(&mut self) -> impl Stream<Item = Result<ChunkData, Error>> + '_ {
try_stream! {
loop {
match self.read_chunk().await {
Ok(chunk) => yield chunk,
Err(Error::Empty) => {
break;
}
error @ Err(_) => {
error?;
}
}
}
}
}
#[cfg(all(feature = "futures", not(feature = "tokio")))]
pub fn as_stream(&mut self) -> impl Stream<Item = Result<ChunkData, Error>> + '_ {
futures::stream::unfold(self, |this| async {
let chunk = this.read_chunk().await;
if let Err(Error::Empty) = chunk {
None
} else {
Some((chunk, this))
}
})
}
}
#[cfg(test)]
mod tests {
use crate::v2020::MASKS;
use super::AsyncStreamCDC;
#[test]
#[should_panic]
fn test_minimum_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 63, 256, 1024);
}
#[test]
#[should_panic]
fn test_minimum_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 67_108_867, 256, 1024);
}
#[test]
#[should_panic]
fn test_average_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 255, 1024);
}
#[test]
#[should_panic]
fn test_average_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 268_435_457, 1024);
}
#[test]
#[should_panic]
fn test_maximum_too_low() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 256, 1023);
}
#[test]
#[should_panic]
fn test_maximum_too_high() {
let array = [0u8; 1024];
AsyncStreamCDC::new(array.as_slice(), 64, 256, 1_073_741_825);
}
#[test]
fn test_masks() {
let source = [0u8; 1024];
let chunker = AsyncStreamCDC::new(source.as_slice(), 64, 256, 1024);
assert_eq!(chunker.mask_l, MASKS[7]);
assert_eq!(chunker.mask_s, MASKS[9]);
let chunker = AsyncStreamCDC::new(source.as_slice(), 8192, 16384, 32768);
assert_eq!(chunker.mask_l, MASKS[13]);
assert_eq!(chunker.mask_s, MASKS[15]);
let chunker = AsyncStreamCDC::new(source.as_slice(), 1_048_576, 4_194_304, 16_777_216);
assert_eq!(chunker.mask_l, MASKS[21]);
assert_eq!(chunker.mask_s, MASKS[23]);
}
struct ExpectedChunk {
hash: u64,
offset: u64,
length: usize,
digest: String,
}
use md5::{Digest, Md5};
#[cfg(all(feature = "futures", not(feature = "tokio")))]
use futures::stream::StreamExt;
#[cfg(all(feature = "tokio", not(feature = "futures")))]
use tokio_stream::StreamExt;
#[cfg_attr(all(feature = "tokio", not(feature = "futures")), tokio::test)]
#[cfg_attr(all(feature = "futures", not(feature = "tokio")), futures_test::test)]
async fn test_iter_sekien_16k_chunks() {
let read_result = std::fs::read("test/fixtures/SekienAkashita.jpg");
assert!(read_result.is_ok());
let contents = read_result.unwrap();
// The digest values are not needed here, but they serve to validate
// that the streaming version tested below is returning the correct
// chunk data on each iteration.
let expected_chunks = vec![
ExpectedChunk {
hash: 17968276318003433923,
offset: 0,
length: 21325,
digest: "2bb52734718194617c957f5e07ee6054".into(),
},
ExpectedChunk {
hash: 8197189939299398838,
offset: 21325,
length: 17140,
digest: "badfb0757fe081c20336902e7131f768".into(),
},
ExpectedChunk {
hash: 13019990849178155730,
offset: 38465,
length: 28084,
digest: "18412d7414de6eb42f638351711f729d".into(),
},
ExpectedChunk {
hash: 4509236223063678303,
offset: 66549,
length: 18217,
digest: "04fe1405fc5f960363bfcd834c056407".into(),
},
ExpectedChunk {
hash: 2504464741100432583,
offset: 84766,
length: 24700,
digest: "1aa7ad95f274d6ba34a983946ebc5af3".into(),
},
];
let mut chunker = AsyncStreamCDC::new(contents.as_ref(), 4096, 16384, 65535);
let stream = chunker.as_stream();
let chunks = stream.collect::<Vec<_>>().await;
let mut index = 0;
for chunk in chunks {
let chunk = chunk.unwrap();
assert_eq!(chunk.hash, expected_chunks[index].hash);
assert_eq!(chunk.offset, expected_chunks[index].offset);
assert_eq!(chunk.length, expected_chunks[index].length);
let mut hasher = Md5::new();
hasher
.update(&contents[(chunk.offset as usize)..(chunk.offset as usize) + chunk.length]);
let table = hasher.finalize();
let digest = format!("{:x}", table);
assert_eq!(digest, expected_chunks[index].digest);
index += 1;
}
assert_eq!(index, 5);
}
} | /// True when the source produces no more data.
eof: bool,
min_size: usize,
avg_size: usize, | random_line_split |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers.trainer_utils import is_main_process
from mydatasets import BERTPretrainedPairWiseDataset, PairCollator
from mymodels import PairWiseBertForPreTraining
logger = logging.getLogger(__name__)
MODEL_CONFIG_CLASSES = list(MODEL_FOR_MASKED_LM_MAPPING.keys())
MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES)
@dataclass
class | :
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization."
"Don't set if you want to train a model from scratch."
},
)
model_type: Optional[str] = field(
default=None,
metadata={"help": "If training from scratch, pass a model type from the list: " + ", ".join(MODEL_TYPES)},
)
config_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
)
tokenizer_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"}
)
cache_dir: Optional[str] = field(
default=None,
metadata={"help": "Where do you want to store the pretrained models downloaded from huggingface.co"},
)
use_fast_tokenizer: bool = field(
default=True,
metadata={"help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not."},
)
model_revision: str = field(
default="main",
metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
)
use_auth_token: bool = field(
default=False,
metadata={
"help": "Will use the token generated when running `transformers-cli login` (necessary to use this script "
"with private models)."
},
)
@dataclass
class DataTrainingArguments:
"""
Arguments pertaining to what data we are going to input our model for training and eval.
"""
dataset_name: Optional[str] = field(
default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
)
dataset_config_name: Optional[str] = field(
default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
)
train_file: Optional[str] = field(default=None, metadata={"help": "The input training data file (a text file)."})
validation_file: Optional[str] = field(
default=None,
metadata={"help": "An optional input evaluation data file to evaluate the perplexity on (a text file)."},
)
overwrite_cache: bool = field(
default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
)
validation_split_percentage: Optional[int] = field(
default=5,
metadata={
"help": "The percentage of the train set used as validation set in case there's no validation split"
},
)
max_seq_length: Optional[int] = field(
default=None,
metadata={
"help": "The maximum total input sequence length after tokenization. Sequences longer "
"than this will be truncated."
},
)
preprocessing_num_workers: Optional[int] = field(
default=None,
metadata={"help": "The number of processes to use for the preprocessing."},
)
mlm_probability: float = field(
default=0.15, metadata={"help": "Ratio of tokens to mask for masked language modeling loss"}
)
line_by_line: bool = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
pad_to_max_length: bool = field(
default=False,
metadata={
"help": "Whether to pad all samples to `max_seq_length`. "
"If False, will pad the samples dynamically when batching to the maximum length in the batch."
},
)
dataset_cache_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
dataset_script_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
limit: Optional[int] = field(
default=50000000,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
def __post_init__(self):
print("no need assert")
def main():
parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments))
model_args, data_args, training_args = parser.parse_args_into_dataclasses()
if (
os.path.exists(training_args.output_dir)
and os.listdir(training_args.output_dir)
and training_args.do_train
and not training_args.overwrite_output_dir
):
raise ValueError(
f"Output directory ({training_args.output_dir}) already exists and is not empty."
"Use --overwrite_output_dir to overcome."
)
# Setup logging
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO if is_main_process(training_args.local_rank) else logging.WARN,
)
# Log on each process the small summary:
logger.warning(
f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
+ f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
)
# Set the verbosity to info of the Transformers logger (on main process only):
if is_main_process(training_args.local_rank):
transformers.utils.logging.set_verbosity_info()
transformers.utils.logging.enable_default_handler()
transformers.utils.logging.enable_explicit_format()
logger.info("Training/evaluation parameters %s", training_args)
# Set seed before initializing model.
set_seed(training_args.seed)
# data_files = {}
# if data_args.train_file is not None:
# data_files["train"] = data_args.train_file
# if data_args.validation_file is not None:
# data_files["validation"] = data_args.validation_file
config_kwargs = {
"cache_dir": model_args.cache_dir,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.config_name:
config = AutoConfig.from_pretrained(model_args.config_name, **config_kwargs)
elif model_args.model_name_or_path:
config = AutoConfig.from_pretrained(model_args.model_name_or_path, **config_kwargs)
else:
config = CONFIG_MAPPING[model_args.model_type]()
logger.warning("You are instantiating a new config instance from scratch.")
tokenizer_kwargs = {
"cache_dir": model_args.cache_dir,
"use_fast": model_args.use_fast_tokenizer,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.tokenizer_name:
tokenizer = AutoTokenizer.from_pretrained(model_args.tokenizer_name, **tokenizer_kwargs)
elif model_args.model_name_or_path:
tokenizer = AutoTokenizer.from_pretrained(model_args.model_name_or_path, **tokenizer_kwargs)
else:
raise ValueError(
"You are instantiating a new tokenizer from scratch. This is not supported by this script."
"You can do it from another script, save it, and load it from here, using --tokenizer_name."
)
if model_args.model_name_or_path:
model = PairWiseBertForPreTraining.from_pretrained(
model_args.model_name_or_path,
from_tf=bool(".ckpt" in model_args.model_name_or_path),
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
)
else:
logger.info("Training new model from scratch")
model = PairWiseBertForPreTraining.from_config(config)
model.resize_token_embeddings(len(tokenizer))
# Get datasets
print("start getting dataset....................")
if training_args.do_train:
print("start getting training dataset........")
train_dataset = BERTPretrainedPairWiseDataset(
data_args, tokenizer, data_args.dataset_cache_dir, data_args.dataset_script_dir
)
else:
train_dataset = None
print('getting dataset succcess................')
data_collator = PairCollator(tokenizer=tokenizer)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=train_dataset if training_args.do_train else None,
tokenizer=tokenizer,
data_collator=data_collator,
)
if training_args.do_train:
model_path = (
model_args.model_name_or_path
if (model_args.model_name_or_path is not None and os.path.isdir(model_args.model_name_or_path))
else None
)
train_result = trainer.train(model_path=model_path)
trainer.save_model() # Saves the tokenizer too for easy upload
output_train_file = os.path.join(training_args.output_dir, "train_results.txt")
if trainer.is_world_process_zero():
with open(output_train_file, "w") as writer:
logger.info("***** Train results *****")
for key, value in sorted(train_result.metrics.items()):
logger.info(f" {key} = {value}")
writer.write(f"{key} = {value}\n")
# Need to save the state, since Trainer.save_model saves only the tokenizer with the model
trainer.state.save_to_json(os.path.join(training_args.output_dir, "trainer_state.json"))
if __name__ == "__main__":
main()
| ModelArguments | identifier_name |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers.trainer_utils import is_main_process
from mydatasets import BERTPretrainedPairWiseDataset, PairCollator
from mymodels import PairWiseBertForPreTraining
logger = logging.getLogger(__name__)
MODEL_CONFIG_CLASSES = list(MODEL_FOR_MASKED_LM_MAPPING.keys())
MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES)
@dataclass
class ModelArguments:
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization."
"Don't set if you want to train a model from scratch."
},
)
model_type: Optional[str] = field(
default=None,
metadata={"help": "If training from scratch, pass a model type from the list: " + ", ".join(MODEL_TYPES)},
)
config_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
)
tokenizer_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"}
)
cache_dir: Optional[str] = field(
default=None,
metadata={"help": "Where do you want to store the pretrained models downloaded from huggingface.co"},
)
use_fast_tokenizer: bool = field(
default=True,
metadata={"help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not."},
)
model_revision: str = field(
default="main",
metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
)
use_auth_token: bool = field(
default=False,
metadata={
"help": "Will use the token generated when running `transformers-cli login` (necessary to use this script "
"with private models)."
},
)
@dataclass
class DataTrainingArguments:
"""
Arguments pertaining to what data we are going to input our model for training and eval.
"""
dataset_name: Optional[str] = field(
default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
)
dataset_config_name: Optional[str] = field(
default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
)
train_file: Optional[str] = field(default=None, metadata={"help": "The input training data file (a text file)."})
validation_file: Optional[str] = field(
default=None,
metadata={"help": "An optional input evaluation data file to evaluate the perplexity on (a text file)."},
)
overwrite_cache: bool = field(
default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
)
validation_split_percentage: Optional[int] = field(
default=5,
metadata={
"help": "The percentage of the train set used as validation set in case there's no validation split"
},
)
max_seq_length: Optional[int] = field(
default=None,
metadata={
"help": "The maximum total input sequence length after tokenization. Sequences longer "
"than this will be truncated."
},
)
preprocessing_num_workers: Optional[int] = field(
default=None,
metadata={"help": "The number of processes to use for the preprocessing."},
)
mlm_probability: float = field(
default=0.15, metadata={"help": "Ratio of tokens to mask for masked language modeling loss"}
)
line_by_line: bool = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
pad_to_max_length: bool = field(
default=False,
metadata={
"help": "Whether to pad all samples to `max_seq_length`. "
"If False, will pad the samples dynamically when batching to the maximum length in the batch."
},
)
dataset_cache_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
dataset_script_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
limit: Optional[int] = field(
default=50000000,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
def __post_init__(self):
print("no need assert")
def main():
parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments))
model_args, data_args, training_args = parser.parse_args_into_dataclasses()
if (
os.path.exists(training_args.output_dir)
and os.listdir(training_args.output_dir)
and training_args.do_train
and not training_args.overwrite_output_dir
):
raise ValueError(
f"Output directory ({training_args.output_dir}) already exists and is not empty."
"Use --overwrite_output_dir to overcome."
)
# Setup logging
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO if is_main_process(training_args.local_rank) else logging.WARN,
)
# Log on each process the small summary:
logger.warning(
f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
+ f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
)
# Set the verbosity to info of the Transformers logger (on main process only):
if is_main_process(training_args.local_rank):
transformers.utils.logging.set_verbosity_info()
transformers.utils.logging.enable_default_handler()
transformers.utils.logging.enable_explicit_format()
logger.info("Training/evaluation parameters %s", training_args)
# Set seed before initializing model.
set_seed(training_args.seed)
# data_files = {}
# if data_args.train_file is not None:
# data_files["train"] = data_args.train_file
# if data_args.validation_file is not None:
# data_files["validation"] = data_args.validation_file
config_kwargs = {
"cache_dir": model_args.cache_dir,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.config_name:
config = AutoConfig.from_pretrained(model_args.config_name, **config_kwargs)
elif model_args.model_name_or_path:
config = AutoConfig.from_pretrained(model_args.model_name_or_path, **config_kwargs)
else:
config = CONFIG_MAPPING[model_args.model_type]()
logger.warning("You are instantiating a new config instance from scratch.")
tokenizer_kwargs = {
"cache_dir": model_args.cache_dir,
"use_fast": model_args.use_fast_tokenizer,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.tokenizer_name:
tokenizer = AutoTokenizer.from_pretrained(model_args.tokenizer_name, **tokenizer_kwargs)
elif model_args.model_name_or_path:
tokenizer = AutoTokenizer.from_pretrained(model_args.model_name_or_path, **tokenizer_kwargs)
else:
raise ValueError(
"You are instantiating a new tokenizer from scratch. This is not supported by this script."
"You can do it from another script, save it, and load it from here, using --tokenizer_name."
)
if model_args.model_name_or_path:
model = PairWiseBertForPreTraining.from_pretrained( | revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
)
else:
logger.info("Training new model from scratch")
model = PairWiseBertForPreTraining.from_config(config)
model.resize_token_embeddings(len(tokenizer))
# Get datasets
print("start getting dataset....................")
if training_args.do_train:
print("start getting training dataset........")
train_dataset = BERTPretrainedPairWiseDataset(
data_args, tokenizer, data_args.dataset_cache_dir, data_args.dataset_script_dir
)
else:
train_dataset = None
print('getting dataset succcess................')
data_collator = PairCollator(tokenizer=tokenizer)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=train_dataset if training_args.do_train else None,
tokenizer=tokenizer,
data_collator=data_collator,
)
if training_args.do_train:
model_path = (
model_args.model_name_or_path
if (model_args.model_name_or_path is not None and os.path.isdir(model_args.model_name_or_path))
else None
)
train_result = trainer.train(model_path=model_path)
trainer.save_model() # Saves the tokenizer too for easy upload
output_train_file = os.path.join(training_args.output_dir, "train_results.txt")
if trainer.is_world_process_zero():
with open(output_train_file, "w") as writer:
logger.info("***** Train results *****")
for key, value in sorted(train_result.metrics.items()):
logger.info(f" {key} = {value}")
writer.write(f"{key} = {value}\n")
# Need to save the state, since Trainer.save_model saves only the tokenizer with the model
trainer.state.save_to_json(os.path.join(training_args.output_dir, "trainer_state.json"))
if __name__ == "__main__":
main() | model_args.model_name_or_path,
from_tf=bool(".ckpt" in model_args.model_name_or_path),
config=config,
cache_dir=model_args.cache_dir, | random_line_split |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers.trainer_utils import is_main_process
from mydatasets import BERTPretrainedPairWiseDataset, PairCollator
from mymodels import PairWiseBertForPreTraining
logger = logging.getLogger(__name__)
MODEL_CONFIG_CLASSES = list(MODEL_FOR_MASKED_LM_MAPPING.keys())
MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES)
@dataclass
class ModelArguments:
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization."
"Don't set if you want to train a model from scratch."
},
)
model_type: Optional[str] = field(
default=None,
metadata={"help": "If training from scratch, pass a model type from the list: " + ", ".join(MODEL_TYPES)},
)
config_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
)
tokenizer_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"}
)
cache_dir: Optional[str] = field(
default=None,
metadata={"help": "Where do you want to store the pretrained models downloaded from huggingface.co"},
)
use_fast_tokenizer: bool = field(
default=True,
metadata={"help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not."},
)
model_revision: str = field(
default="main",
metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
)
use_auth_token: bool = field(
default=False,
metadata={
"help": "Will use the token generated when running `transformers-cli login` (necessary to use this script "
"with private models)."
},
)
@dataclass
class DataTrainingArguments:
"""
Arguments pertaining to what data we are going to input our model for training and eval.
"""
dataset_name: Optional[str] = field(
default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
)
dataset_config_name: Optional[str] = field(
default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
)
train_file: Optional[str] = field(default=None, metadata={"help": "The input training data file (a text file)."})
validation_file: Optional[str] = field(
default=None,
metadata={"help": "An optional input evaluation data file to evaluate the perplexity on (a text file)."},
)
overwrite_cache: bool = field(
default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
)
validation_split_percentage: Optional[int] = field(
default=5,
metadata={
"help": "The percentage of the train set used as validation set in case there's no validation split"
},
)
max_seq_length: Optional[int] = field(
default=None,
metadata={
"help": "The maximum total input sequence length after tokenization. Sequences longer "
"than this will be truncated."
},
)
preprocessing_num_workers: Optional[int] = field(
default=None,
metadata={"help": "The number of processes to use for the preprocessing."},
)
mlm_probability: float = field(
default=0.15, metadata={"help": "Ratio of tokens to mask for masked language modeling loss"}
)
line_by_line: bool = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
pad_to_max_length: bool = field(
default=False,
metadata={
"help": "Whether to pad all samples to `max_seq_length`. "
"If False, will pad the samples dynamically when batching to the maximum length in the batch."
},
)
dataset_cache_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
dataset_script_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
limit: Optional[int] = field(
default=50000000,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
def __post_init__(self):
print("no need assert")
def main():
parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments))
model_args, data_args, training_args = parser.parse_args_into_dataclasses()
if (
os.path.exists(training_args.output_dir)
and os.listdir(training_args.output_dir)
and training_args.do_train
and not training_args.overwrite_output_dir
):
raise ValueError(
f"Output directory ({training_args.output_dir}) already exists and is not empty."
"Use --overwrite_output_dir to overcome."
)
# Setup logging
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO if is_main_process(training_args.local_rank) else logging.WARN,
)
# Log on each process the small summary:
logger.warning(
f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
+ f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
)
# Set the verbosity to info of the Transformers logger (on main process only):
if is_main_process(training_args.local_rank):
transformers.utils.logging.set_verbosity_info()
transformers.utils.logging.enable_default_handler()
transformers.utils.logging.enable_explicit_format()
logger.info("Training/evaluation parameters %s", training_args)
# Set seed before initializing model.
set_seed(training_args.seed)
# data_files = {}
# if data_args.train_file is not None:
# data_files["train"] = data_args.train_file
# if data_args.validation_file is not None:
# data_files["validation"] = data_args.validation_file
config_kwargs = {
"cache_dir": model_args.cache_dir,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.config_name:
config = AutoConfig.from_pretrained(model_args.config_name, **config_kwargs)
elif model_args.model_name_or_path:
config = AutoConfig.from_pretrained(model_args.model_name_or_path, **config_kwargs)
else:
config = CONFIG_MAPPING[model_args.model_type]()
logger.warning("You are instantiating a new config instance from scratch.")
tokenizer_kwargs = {
"cache_dir": model_args.cache_dir,
"use_fast": model_args.use_fast_tokenizer,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.tokenizer_name:
tokenizer = AutoTokenizer.from_pretrained(model_args.tokenizer_name, **tokenizer_kwargs)
elif model_args.model_name_or_path:
tokenizer = AutoTokenizer.from_pretrained(model_args.model_name_or_path, **tokenizer_kwargs)
else:
|
if model_args.model_name_or_path:
model = PairWiseBertForPreTraining.from_pretrained(
model_args.model_name_or_path,
from_tf=bool(".ckpt" in model_args.model_name_or_path),
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
)
else:
logger.info("Training new model from scratch")
model = PairWiseBertForPreTraining.from_config(config)
model.resize_token_embeddings(len(tokenizer))
# Get datasets
print("start getting dataset....................")
if training_args.do_train:
print("start getting training dataset........")
train_dataset = BERTPretrainedPairWiseDataset(
data_args, tokenizer, data_args.dataset_cache_dir, data_args.dataset_script_dir
)
else:
train_dataset = None
print('getting dataset succcess................')
data_collator = PairCollator(tokenizer=tokenizer)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=train_dataset if training_args.do_train else None,
tokenizer=tokenizer,
data_collator=data_collator,
)
if training_args.do_train:
model_path = (
model_args.model_name_or_path
if (model_args.model_name_or_path is not None and os.path.isdir(model_args.model_name_or_path))
else None
)
train_result = trainer.train(model_path=model_path)
trainer.save_model() # Saves the tokenizer too for easy upload
output_train_file = os.path.join(training_args.output_dir, "train_results.txt")
if trainer.is_world_process_zero():
with open(output_train_file, "w") as writer:
logger.info("***** Train results *****")
for key, value in sorted(train_result.metrics.items()):
logger.info(f" {key} = {value}")
writer.write(f"{key} = {value}\n")
# Need to save the state, since Trainer.save_model saves only the tokenizer with the model
trainer.state.save_to_json(os.path.join(training_args.output_dir, "trainer_state.json"))
if __name__ == "__main__":
main()
| raise ValueError(
"You are instantiating a new tokenizer from scratch. This is not supported by this script."
"You can do it from another script, save it, and load it from here, using --tokenizer_name."
) | conditional_block |
run_mlm_my.py | import logging
import os
from dataclasses import dataclass, field
from typing import Optional
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoTokenizer,
HfArgumentParser,
Trainer,
TrainingArguments,
set_seed,
)
from transformers.trainer_utils import is_main_process
from mydatasets import BERTPretrainedPairWiseDataset, PairCollator
from mymodels import PairWiseBertForPreTraining
logger = logging.getLogger(__name__)
MODEL_CONFIG_CLASSES = list(MODEL_FOR_MASKED_LM_MAPPING.keys())
MODEL_TYPES = tuple(conf.model_type for conf in MODEL_CONFIG_CLASSES)
@dataclass
class ModelArguments:
|
@dataclass
class DataTrainingArguments:
"""
Arguments pertaining to what data we are going to input our model for training and eval.
"""
dataset_name: Optional[str] = field(
default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
)
dataset_config_name: Optional[str] = field(
default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
)
train_file: Optional[str] = field(default=None, metadata={"help": "The input training data file (a text file)."})
validation_file: Optional[str] = field(
default=None,
metadata={"help": "An optional input evaluation data file to evaluate the perplexity on (a text file)."},
)
overwrite_cache: bool = field(
default=False, metadata={"help": "Overwrite the cached training and evaluation sets"}
)
validation_split_percentage: Optional[int] = field(
default=5,
metadata={
"help": "The percentage of the train set used as validation set in case there's no validation split"
},
)
max_seq_length: Optional[int] = field(
default=None,
metadata={
"help": "The maximum total input sequence length after tokenization. Sequences longer "
"than this will be truncated."
},
)
preprocessing_num_workers: Optional[int] = field(
default=None,
metadata={"help": "The number of processes to use for the preprocessing."},
)
mlm_probability: float = field(
default=0.15, metadata={"help": "Ratio of tokens to mask for masked language modeling loss"}
)
line_by_line: bool = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
pad_to_max_length: bool = field(
default=False,
metadata={
"help": "Whether to pad all samples to `max_seq_length`. "
"If False, will pad the samples dynamically when batching to the maximum length in the batch."
},
)
dataset_cache_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
dataset_script_dir: str = field(
default=False,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
limit: Optional[int] = field(
default=50000000,
metadata={"help": "Whether distinct lines of text in the dataset are to be handled as distinct sequences."},
)
def __post_init__(self):
print("no need assert")
def main():
parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments))
model_args, data_args, training_args = parser.parse_args_into_dataclasses()
if (
os.path.exists(training_args.output_dir)
and os.listdir(training_args.output_dir)
and training_args.do_train
and not training_args.overwrite_output_dir
):
raise ValueError(
f"Output directory ({training_args.output_dir}) already exists and is not empty."
"Use --overwrite_output_dir to overcome."
)
# Setup logging
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO if is_main_process(training_args.local_rank) else logging.WARN,
)
# Log on each process the small summary:
logger.warning(
f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
+ f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
)
# Set the verbosity to info of the Transformers logger (on main process only):
if is_main_process(training_args.local_rank):
transformers.utils.logging.set_verbosity_info()
transformers.utils.logging.enable_default_handler()
transformers.utils.logging.enable_explicit_format()
logger.info("Training/evaluation parameters %s", training_args)
# Set seed before initializing model.
set_seed(training_args.seed)
# data_files = {}
# if data_args.train_file is not None:
# data_files["train"] = data_args.train_file
# if data_args.validation_file is not None:
# data_files["validation"] = data_args.validation_file
config_kwargs = {
"cache_dir": model_args.cache_dir,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.config_name:
config = AutoConfig.from_pretrained(model_args.config_name, **config_kwargs)
elif model_args.model_name_or_path:
config = AutoConfig.from_pretrained(model_args.model_name_or_path, **config_kwargs)
else:
config = CONFIG_MAPPING[model_args.model_type]()
logger.warning("You are instantiating a new config instance from scratch.")
tokenizer_kwargs = {
"cache_dir": model_args.cache_dir,
"use_fast": model_args.use_fast_tokenizer,
"revision": model_args.model_revision,
"use_auth_token": True if model_args.use_auth_token else None,
}
if model_args.tokenizer_name:
tokenizer = AutoTokenizer.from_pretrained(model_args.tokenizer_name, **tokenizer_kwargs)
elif model_args.model_name_or_path:
tokenizer = AutoTokenizer.from_pretrained(model_args.model_name_or_path, **tokenizer_kwargs)
else:
raise ValueError(
"You are instantiating a new tokenizer from scratch. This is not supported by this script."
"You can do it from another script, save it, and load it from here, using --tokenizer_name."
)
if model_args.model_name_or_path:
model = PairWiseBertForPreTraining.from_pretrained(
model_args.model_name_or_path,
from_tf=bool(".ckpt" in model_args.model_name_or_path),
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
)
else:
logger.info("Training new model from scratch")
model = PairWiseBertForPreTraining.from_config(config)
model.resize_token_embeddings(len(tokenizer))
# Get datasets
print("start getting dataset....................")
if training_args.do_train:
print("start getting training dataset........")
train_dataset = BERTPretrainedPairWiseDataset(
data_args, tokenizer, data_args.dataset_cache_dir, data_args.dataset_script_dir
)
else:
train_dataset = None
print('getting dataset succcess................')
data_collator = PairCollator(tokenizer=tokenizer)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=train_dataset if training_args.do_train else None,
tokenizer=tokenizer,
data_collator=data_collator,
)
if training_args.do_train:
model_path = (
model_args.model_name_or_path
if (model_args.model_name_or_path is not None and os.path.isdir(model_args.model_name_or_path))
else None
)
train_result = trainer.train(model_path=model_path)
trainer.save_model() # Saves the tokenizer too for easy upload
output_train_file = os.path.join(training_args.output_dir, "train_results.txt")
if trainer.is_world_process_zero():
with open(output_train_file, "w") as writer:
logger.info("***** Train results *****")
for key, value in sorted(train_result.metrics.items()):
logger.info(f" {key} = {value}")
writer.write(f"{key} = {value}\n")
# Need to save the state, since Trainer.save_model saves only the tokenizer with the model
trainer.state.save_to_json(os.path.join(training_args.output_dir, "trainer_state.json"))
if __name__ == "__main__":
main()
| """
Arguments pertaining to which model/config/tokenizer we are going to fine-tune, or train from scratch.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={
"help": "The model checkpoint for weights initialization."
"Don't set if you want to train a model from scratch."
},
)
model_type: Optional[str] = field(
default=None,
metadata={"help": "If training from scratch, pass a model type from the list: " + ", ".join(MODEL_TYPES)},
)
config_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
)
tokenizer_name: Optional[str] = field(
default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"}
)
cache_dir: Optional[str] = field(
default=None,
metadata={"help": "Where do you want to store the pretrained models downloaded from huggingface.co"},
)
use_fast_tokenizer: bool = field(
default=True,
metadata={"help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not."},
)
model_revision: str = field(
default="main",
metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
)
use_auth_token: bool = field(
default=False,
metadata={
"help": "Will use the token generated when running `transformers-cli login` (necessary to use this script "
"with private models)."
},
) | identifier_body |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
stderr = sys.stderr
sys.stderr = open(os.devnull, 'w')
from keras.wrappers.scikit_learn import KerasClassifier
sys.stderr = stderr
from autoclf.classification import eval_utils as eu
from autoclf import auto_utils as au
from autoclf.classification import neuralnets as nn
from autoclf.classification import train_calibrate as tc
import autoclf.getargs as ga
from autoclf.classification.param_grids_distros import Keras_param_grid
from autoclf.classification.evaluate import create_keras_classifiers
from autoclf.classification.evaluate import create_best_keras_clf_architecture
from pkg_resources import resource_string
from io import StringIO
def select_cv_method():
is_valid = 0
choice = 0
while not is_valid:
try:
choice = int(input("Select cv method: [1] Classical CV, [2] Nested-CV?\n"))
if choice in (1, 2):
is_valid = 1
else:
print("Invalid number. Try again...")
except ValueError as e:
print("'%s' is not a valid integer." % e.args[0].split(": ")[1])
return choice
# starting program
if __name__ == '__main__':
print("### Probability Calibration Experiment -- CalibratedClassifierCV "
"with cv=cv (no prefit) ###")
print()
d_name = ga.get_name()
if d_name is None:
d_name = "titanic"
# fix random seed for reproducibility
seed = 7
np.random.seed(seed)
# load data
try:
df = read_csv(
'datasets\\titanic_train.csv', delimiter=",",
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
print("Found data in autoclf\\autoclf\\datasets")
except FileNotFoundError as fe:
titanic_bytes = resource_string(
"autoclf", os.path.join("datasets", 'titanic_train.csv'))
titanic_file = StringIO(str(titanic_bytes,'utf-8'))
names = ['PassengerId','Survived','Pclass','Name','Sex','Age','SibSp',
'Parch','Ticket','Fare','Cabin','Embarked']
df = read_csv(
titanic_file, delimiter=",",
# header=0, names=names,
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
except Exception as e:
raise e
# data exploration
print("shape: ", df.shape)
# statistical summary
description = df.describe()
print("description - no encoding:\n", description)
print()
plt.style.use('ggplot')
# input("Enter key to continue... \n")
# Feature-Feature Relationships
# scatter_matrix(df)
print()
# too many missing values in 'Cabin' columns: about 3/4
print("Dropping 'Cabin' column -- too many missing values")
# df.Cabin.replace(to_replace=np.nan, value='Unknown', inplace=True)
df.drop(['Cabin'], axis=1, inplace=True)
print()
print("Now, shape: ", df.shape)
print("df.head():\n", df.head())
print()
description = df.describe()
print("Once again, description - no encoding:\n", description)
print()
# input("Enter key to continue... \n")
target = 'Survived'
# feature preprocessing
sltt = eu.scoring_and_tt_split(df, target, 0.2, seed)
X_train, X_test, y_train, y_test = sltt['arrays']
scoring = sltt['scoring']
Y_type = sltt['target_type']
labels = sltt['labels']
print("scoring:", scoring)
print()
print("Classes:", labels)
print()
print("X_train shape: ", X_train.shape)
print("X_train -- first row:", X_train.values[0])
print("y_train shape: ", y_train.shape)
print()
print("X_test shape: ", X_test.shape)
print("X_test -- first row:", X_test.values[0])
print("y_test shape: ", y_test.shape)
print()
print("y_train:", y_train[:3])
# input("Enter key to continue... \n")
print()
auto_feat_eng_data = eu.auto_X_encoding(sltt, seed)
print()
encoding = auto_feat_eng_data['encoding']
scaler_tuple = auto_feat_eng_data['scaler']
featselector = auto_feat_eng_data['feat_selector']
steps = auto_feat_eng_data['steps']
X_train_transformed, y_train, X_test_transformed, y_test = auto_feat_eng_data['data_arrays']
X, y = auto_feat_eng_data['Xy']
train_index, test_index = auto_feat_eng_data['tt_index']
n_splits = au.select_nr_of_splits_for_kfold_cv()
# n_iter = au.select_nr_of_iterations()
print()
# This cross-validation object is a variation of KFold that returns stratified folds.
# The folds are made by preserving the percentage of samples for each class.
# uncomment to evaluate models != KerasClfs or GaussianNB w nested cv
# inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
outer_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
### reproducing the whole autoclf workflow
names = []
results = []
print("Metric:", scoring)
print("Calibration of untrained models -- CCCV 2nd")
print()
# Evaluation of best modelwith nested CV -- inner: RSCV
# dict of models and their associated parameters
# if it comes out that the best model is LogReg, no comparison is needed
# scoring == 'roc_auc' ==>
best_score = 0.5 # 0.0
best_score_dev = 0.1
best_cv_results = np.zeros(n_splits)
best_exec_time = 31536000 # one year in seconds
best_model = ('Random', None, None)
Dummy_scores = []
models_data = []
names = []
results = []
scores_of_best_model = (best_score, best_score_dev, best_cv_results,
best_exec_time, best_model)
# Start evaluation process
print()
print("=== [task] Evaluation of DummyClassifier")
print()
wtr = eu.calculate_sample_weight(y_train)
average_scores_and_best_scores = eu.single_classic_cv_evaluation(
X_train_transformed, y_train, 'DummyClf_2nd',
DummyClassifier(strategy='most_frequent'), wtr, scoring, outer_cv,
dict(), scores_of_best_model, results, names, seed)
scores_of_best_model = average_scores_and_best_scores[1]
Dummy_scores.append(scores_of_best_model[0]) # Dummy score -- ROC_AUC
Dummy_scores.append(scores_of_best_model[1]) # Dummy score std
Dummy_scores.append(scores_of_best_model[2]) # Dummy cv results
Dummy_scores.append(scores_of_best_model[3]) # Dummy execution time
# Dummy model's name and estimator
Dummy_scores.append(scores_of_best_model[4])
names = []
results = []
print()
complex_models_and_parameters = dict()
average_scores_across_outer_folds_complex = dict()
all_models_and_parameters = dict()
# Let's add some simple neural network
print("=== [task] Comparing DummyClassifier to best Keras Clf (NN)")
print()
# This is an experiment to check
# how different Keras architectures perform
# to avoid hard-coding NNs, you should determine at least
# nr of layers and nr of nodes by using Grid or Randomized Search CV
input_dim = int(X_train_transformed.shape[1])
output_dim = 1
nb_epoch = au.select_nr_of_iterations('nn')
# evaluate Keras clfs
cv_method = select_cv_method()
if cv_method == 1:
batch_size = 32
complex_models_and_parameters = create_keras_classifiers(
Y_type, input_dim, labels, nb_epoch, batch_size)
average_scores_and_best_scores = eu.classic_cv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters, scoring,
outer_cv, average_scores_across_outer_folds_complex,
scores_of_best_model, results, names, seed)
else:
inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
n_iter = au.select_nr_of_iterations()
keras_clf_name = "KerasClf_2nd"
keras_nn_model, keras_param_grid = create_best_keras_clf_architecture(
keras_clf_name, Y_type, labels, input_dim, nb_epoch, Keras_param_grid)
complex_models_and_parameters[keras_clf_name] = (
keras_nn_model, keras_param_grid)
average_scores_and_best_scores = eu.nested_rscv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters,
scoring, n_iter, inner_cv, outer_cv,
average_scores_across_outer_folds_complex, scores_of_best_model,
results, names, seed)
print()
au.box_plots_of_models_performance(results, names)
cv_method_name = "Classic" if cv_method == 1 else "Nested"
print()
print("=== After %s CV evaluation of Keras NNs..." % cv_method_name)
print()
scores_of_best_model = average_scores_and_best_scores[1]
best_model_name = scores_of_best_model[4][0]
best_model_estim = scores_of_best_model[4][1]
best_score = scores_of_best_model[0]
best_score_dev = scores_of_best_model[1]
best_cv_results = scores_of_best_model[2]
# best_brier_score = scores_of_best_model[2]
best_exec_time = scores_of_best_model[3]
Dummy_score = Dummy_scores[0]
Dummy_score_dev = Dummy_scores[1]
Dummy_cv_results = Dummy_scores[2]
# Dummy_brier_score = Dummy_scores[3]
Dummy_exec_time = Dummy_scores[3]
print()
print("Currently, best model is '%s' with score '%s': %1.3f (%1.3f)... :" %
(best_model_name, scoring.strip('neg_'), best_score, best_score_dev))
if best_model_name in (
'baseline_nn_default_Clf_2nd', 'baseline_nn_smaller_Clf_2nd',
'larger_nn_Clf_2nd', 'deep_nn_Clf_2nd', 'deeper_nn_Clf_2nd',
'KerasClf_2nd'):
best_nn_build_fn = scores_of_best_model[4][2]
print("Best build function:", best_nn_build_fn)
print("... execution time: %.2fs" % best_exec_time)
# print("and prediction confidence: %1.3f" % best_brier_score)
print()
if best_model_name != 'DummyClf_2nd':
# It's assumed best model's performance is
# satistically better than that of DummyClf on this dataset
print("DummyClassifier's scores -- '%s': %1.3f (%1.3f)" % (
scoring.strip('neg_'), Dummy_score, Dummy_score_dev))
print("'%s' does better than DummyClassifier." % best_model_name)
if best_exec_time < Dummy_exec_time:
|
print()
print()
input("Press key to continue...")
preprocessing = (encoding, scaler_tuple, featselector)
if labels is not None:
print("You have labels:", labels)
all_models_and_parameters['labels'] = labels
print("Defined dictionary with models, parameters and related data.")
print()
if cv_method == 1:
tc.calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, nb_epoch,
scoring, models_data, d_name, seed)
else:
tc.tune_calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, n_iter, nb_epoch,
scoring, models_data, d_name, seed)
else:
sys.exit("Your best classifier is not a good classifier.")
input("=== [End Of Program] Enter key to continue... \n") | print("'%s' is quicker than DummyClf." % best_model_name) | conditional_block |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
stderr = sys.stderr
sys.stderr = open(os.devnull, 'w')
from keras.wrappers.scikit_learn import KerasClassifier
sys.stderr = stderr
from autoclf.classification import eval_utils as eu
from autoclf import auto_utils as au
from autoclf.classification import neuralnets as nn
from autoclf.classification import train_calibrate as tc
import autoclf.getargs as ga
from autoclf.classification.param_grids_distros import Keras_param_grid
from autoclf.classification.evaluate import create_keras_classifiers
from autoclf.classification.evaluate import create_best_keras_clf_architecture
from pkg_resources import resource_string
from io import StringIO
def select_cv_method():
is_valid = 0
choice = 0
while not is_valid:
try:
choice = int(input("Select cv method: [1] Classical CV, [2] Nested-CV?\n"))
if choice in (1, 2):
is_valid = 1
else:
print("Invalid number. Try again...")
except ValueError as e:
print("'%s' is not a valid integer." % e.args[0].split(": ")[1])
return choice
# starting program
if __name__ == '__main__':
print("### Probability Calibration Experiment -- CalibratedClassifierCV "
"with cv=cv (no prefit) ###")
print()
d_name = ga.get_name()
if d_name is None:
d_name = "titanic"
# fix random seed for reproducibility
seed = 7
np.random.seed(seed)
# load data
try:
df = read_csv(
'datasets\\titanic_train.csv', delimiter=",",
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
print("Found data in autoclf\\autoclf\\datasets")
except FileNotFoundError as fe:
titanic_bytes = resource_string(
"autoclf", os.path.join("datasets", 'titanic_train.csv'))
titanic_file = StringIO(str(titanic_bytes,'utf-8'))
names = ['PassengerId','Survived','Pclass','Name','Sex','Age','SibSp',
'Parch','Ticket','Fare','Cabin','Embarked']
df = read_csv(
titanic_file, delimiter=",",
# header=0, names=names,
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
except Exception as e:
raise e
# data exploration
print("shape: ", df.shape)
# statistical summary
description = df.describe()
print("description - no encoding:\n", description)
print()
| # Feature-Feature Relationships
# scatter_matrix(df)
print()
# too many missing values in 'Cabin' columns: about 3/4
print("Dropping 'Cabin' column -- too many missing values")
# df.Cabin.replace(to_replace=np.nan, value='Unknown', inplace=True)
df.drop(['Cabin'], axis=1, inplace=True)
print()
print("Now, shape: ", df.shape)
print("df.head():\n", df.head())
print()
description = df.describe()
print("Once again, description - no encoding:\n", description)
print()
# input("Enter key to continue... \n")
target = 'Survived'
# feature preprocessing
sltt = eu.scoring_and_tt_split(df, target, 0.2, seed)
X_train, X_test, y_train, y_test = sltt['arrays']
scoring = sltt['scoring']
Y_type = sltt['target_type']
labels = sltt['labels']
print("scoring:", scoring)
print()
print("Classes:", labels)
print()
print("X_train shape: ", X_train.shape)
print("X_train -- first row:", X_train.values[0])
print("y_train shape: ", y_train.shape)
print()
print("X_test shape: ", X_test.shape)
print("X_test -- first row:", X_test.values[0])
print("y_test shape: ", y_test.shape)
print()
print("y_train:", y_train[:3])
# input("Enter key to continue... \n")
print()
auto_feat_eng_data = eu.auto_X_encoding(sltt, seed)
print()
encoding = auto_feat_eng_data['encoding']
scaler_tuple = auto_feat_eng_data['scaler']
featselector = auto_feat_eng_data['feat_selector']
steps = auto_feat_eng_data['steps']
X_train_transformed, y_train, X_test_transformed, y_test = auto_feat_eng_data['data_arrays']
X, y = auto_feat_eng_data['Xy']
train_index, test_index = auto_feat_eng_data['tt_index']
n_splits = au.select_nr_of_splits_for_kfold_cv()
# n_iter = au.select_nr_of_iterations()
print()
# This cross-validation object is a variation of KFold that returns stratified folds.
# The folds are made by preserving the percentage of samples for each class.
# uncomment to evaluate models != KerasClfs or GaussianNB w nested cv
# inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
outer_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
### reproducing the whole autoclf workflow
names = []
results = []
print("Metric:", scoring)
print("Calibration of untrained models -- CCCV 2nd")
print()
# Evaluation of best modelwith nested CV -- inner: RSCV
# dict of models and their associated parameters
# if it comes out that the best model is LogReg, no comparison is needed
# scoring == 'roc_auc' ==>
best_score = 0.5 # 0.0
best_score_dev = 0.1
best_cv_results = np.zeros(n_splits)
best_exec_time = 31536000 # one year in seconds
best_model = ('Random', None, None)
Dummy_scores = []
models_data = []
names = []
results = []
scores_of_best_model = (best_score, best_score_dev, best_cv_results,
best_exec_time, best_model)
# Start evaluation process
print()
print("=== [task] Evaluation of DummyClassifier")
print()
wtr = eu.calculate_sample_weight(y_train)
average_scores_and_best_scores = eu.single_classic_cv_evaluation(
X_train_transformed, y_train, 'DummyClf_2nd',
DummyClassifier(strategy='most_frequent'), wtr, scoring, outer_cv,
dict(), scores_of_best_model, results, names, seed)
scores_of_best_model = average_scores_and_best_scores[1]
Dummy_scores.append(scores_of_best_model[0]) # Dummy score -- ROC_AUC
Dummy_scores.append(scores_of_best_model[1]) # Dummy score std
Dummy_scores.append(scores_of_best_model[2]) # Dummy cv results
Dummy_scores.append(scores_of_best_model[3]) # Dummy execution time
# Dummy model's name and estimator
Dummy_scores.append(scores_of_best_model[4])
names = []
results = []
print()
complex_models_and_parameters = dict()
average_scores_across_outer_folds_complex = dict()
all_models_and_parameters = dict()
# Let's add some simple neural network
print("=== [task] Comparing DummyClassifier to best Keras Clf (NN)")
print()
# This is an experiment to check
# how different Keras architectures perform
# to avoid hard-coding NNs, you should determine at least
# nr of layers and nr of nodes by using Grid or Randomized Search CV
input_dim = int(X_train_transformed.shape[1])
output_dim = 1
nb_epoch = au.select_nr_of_iterations('nn')
# evaluate Keras clfs
cv_method = select_cv_method()
if cv_method == 1:
batch_size = 32
complex_models_and_parameters = create_keras_classifiers(
Y_type, input_dim, labels, nb_epoch, batch_size)
average_scores_and_best_scores = eu.classic_cv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters, scoring,
outer_cv, average_scores_across_outer_folds_complex,
scores_of_best_model, results, names, seed)
else:
inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
n_iter = au.select_nr_of_iterations()
keras_clf_name = "KerasClf_2nd"
keras_nn_model, keras_param_grid = create_best_keras_clf_architecture(
keras_clf_name, Y_type, labels, input_dim, nb_epoch, Keras_param_grid)
complex_models_and_parameters[keras_clf_name] = (
keras_nn_model, keras_param_grid)
average_scores_and_best_scores = eu.nested_rscv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters,
scoring, n_iter, inner_cv, outer_cv,
average_scores_across_outer_folds_complex, scores_of_best_model,
results, names, seed)
print()
au.box_plots_of_models_performance(results, names)
cv_method_name = "Classic" if cv_method == 1 else "Nested"
print()
print("=== After %s CV evaluation of Keras NNs..." % cv_method_name)
print()
scores_of_best_model = average_scores_and_best_scores[1]
best_model_name = scores_of_best_model[4][0]
best_model_estim = scores_of_best_model[4][1]
best_score = scores_of_best_model[0]
best_score_dev = scores_of_best_model[1]
best_cv_results = scores_of_best_model[2]
# best_brier_score = scores_of_best_model[2]
best_exec_time = scores_of_best_model[3]
Dummy_score = Dummy_scores[0]
Dummy_score_dev = Dummy_scores[1]
Dummy_cv_results = Dummy_scores[2]
# Dummy_brier_score = Dummy_scores[3]
Dummy_exec_time = Dummy_scores[3]
print()
print("Currently, best model is '%s' with score '%s': %1.3f (%1.3f)... :" %
(best_model_name, scoring.strip('neg_'), best_score, best_score_dev))
if best_model_name in (
'baseline_nn_default_Clf_2nd', 'baseline_nn_smaller_Clf_2nd',
'larger_nn_Clf_2nd', 'deep_nn_Clf_2nd', 'deeper_nn_Clf_2nd',
'KerasClf_2nd'):
best_nn_build_fn = scores_of_best_model[4][2]
print("Best build function:", best_nn_build_fn)
print("... execution time: %.2fs" % best_exec_time)
# print("and prediction confidence: %1.3f" % best_brier_score)
print()
if best_model_name != 'DummyClf_2nd':
# It's assumed best model's performance is
# satistically better than that of DummyClf on this dataset
print("DummyClassifier's scores -- '%s': %1.3f (%1.3f)" % (
scoring.strip('neg_'), Dummy_score, Dummy_score_dev))
print("'%s' does better than DummyClassifier." % best_model_name)
if best_exec_time < Dummy_exec_time:
print("'%s' is quicker than DummyClf." % best_model_name)
print()
print()
input("Press key to continue...")
preprocessing = (encoding, scaler_tuple, featselector)
if labels is not None:
print("You have labels:", labels)
all_models_and_parameters['labels'] = labels
print("Defined dictionary with models, parameters and related data.")
print()
if cv_method == 1:
tc.calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, nb_epoch,
scoring, models_data, d_name, seed)
else:
tc.tune_calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, n_iter, nb_epoch,
scoring, models_data, d_name, seed)
else:
sys.exit("Your best classifier is not a good classifier.")
input("=== [End Of Program] Enter key to continue... \n") | plt.style.use('ggplot')
# input("Enter key to continue... \n")
| random_line_split |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
stderr = sys.stderr
sys.stderr = open(os.devnull, 'w')
from keras.wrappers.scikit_learn import KerasClassifier
sys.stderr = stderr
from autoclf.classification import eval_utils as eu
from autoclf import auto_utils as au
from autoclf.classification import neuralnets as nn
from autoclf.classification import train_calibrate as tc
import autoclf.getargs as ga
from autoclf.classification.param_grids_distros import Keras_param_grid
from autoclf.classification.evaluate import create_keras_classifiers
from autoclf.classification.evaluate import create_best_keras_clf_architecture
from pkg_resources import resource_string
from io import StringIO
def | ():
is_valid = 0
choice = 0
while not is_valid:
try:
choice = int(input("Select cv method: [1] Classical CV, [2] Nested-CV?\n"))
if choice in (1, 2):
is_valid = 1
else:
print("Invalid number. Try again...")
except ValueError as e:
print("'%s' is not a valid integer." % e.args[0].split(": ")[1])
return choice
# starting program
if __name__ == '__main__':
print("### Probability Calibration Experiment -- CalibratedClassifierCV "
"with cv=cv (no prefit) ###")
print()
d_name = ga.get_name()
if d_name is None:
d_name = "titanic"
# fix random seed for reproducibility
seed = 7
np.random.seed(seed)
# load data
try:
df = read_csv(
'datasets\\titanic_train.csv', delimiter=",",
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
print("Found data in autoclf\\autoclf\\datasets")
except FileNotFoundError as fe:
titanic_bytes = resource_string(
"autoclf", os.path.join("datasets", 'titanic_train.csv'))
titanic_file = StringIO(str(titanic_bytes,'utf-8'))
names = ['PassengerId','Survived','Pclass','Name','Sex','Age','SibSp',
'Parch','Ticket','Fare','Cabin','Embarked']
df = read_csv(
titanic_file, delimiter=",",
# header=0, names=names,
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
except Exception as e:
raise e
# data exploration
print("shape: ", df.shape)
# statistical summary
description = df.describe()
print("description - no encoding:\n", description)
print()
plt.style.use('ggplot')
# input("Enter key to continue... \n")
# Feature-Feature Relationships
# scatter_matrix(df)
print()
# too many missing values in 'Cabin' columns: about 3/4
print("Dropping 'Cabin' column -- too many missing values")
# df.Cabin.replace(to_replace=np.nan, value='Unknown', inplace=True)
df.drop(['Cabin'], axis=1, inplace=True)
print()
print("Now, shape: ", df.shape)
print("df.head():\n", df.head())
print()
description = df.describe()
print("Once again, description - no encoding:\n", description)
print()
# input("Enter key to continue... \n")
target = 'Survived'
# feature preprocessing
sltt = eu.scoring_and_tt_split(df, target, 0.2, seed)
X_train, X_test, y_train, y_test = sltt['arrays']
scoring = sltt['scoring']
Y_type = sltt['target_type']
labels = sltt['labels']
print("scoring:", scoring)
print()
print("Classes:", labels)
print()
print("X_train shape: ", X_train.shape)
print("X_train -- first row:", X_train.values[0])
print("y_train shape: ", y_train.shape)
print()
print("X_test shape: ", X_test.shape)
print("X_test -- first row:", X_test.values[0])
print("y_test shape: ", y_test.shape)
print()
print("y_train:", y_train[:3])
# input("Enter key to continue... \n")
print()
auto_feat_eng_data = eu.auto_X_encoding(sltt, seed)
print()
encoding = auto_feat_eng_data['encoding']
scaler_tuple = auto_feat_eng_data['scaler']
featselector = auto_feat_eng_data['feat_selector']
steps = auto_feat_eng_data['steps']
X_train_transformed, y_train, X_test_transformed, y_test = auto_feat_eng_data['data_arrays']
X, y = auto_feat_eng_data['Xy']
train_index, test_index = auto_feat_eng_data['tt_index']
n_splits = au.select_nr_of_splits_for_kfold_cv()
# n_iter = au.select_nr_of_iterations()
print()
# This cross-validation object is a variation of KFold that returns stratified folds.
# The folds are made by preserving the percentage of samples for each class.
# uncomment to evaluate models != KerasClfs or GaussianNB w nested cv
# inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
outer_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
### reproducing the whole autoclf workflow
names = []
results = []
print("Metric:", scoring)
print("Calibration of untrained models -- CCCV 2nd")
print()
# Evaluation of best modelwith nested CV -- inner: RSCV
# dict of models and their associated parameters
# if it comes out that the best model is LogReg, no comparison is needed
# scoring == 'roc_auc' ==>
best_score = 0.5 # 0.0
best_score_dev = 0.1
best_cv_results = np.zeros(n_splits)
best_exec_time = 31536000 # one year in seconds
best_model = ('Random', None, None)
Dummy_scores = []
models_data = []
names = []
results = []
scores_of_best_model = (best_score, best_score_dev, best_cv_results,
best_exec_time, best_model)
# Start evaluation process
print()
print("=== [task] Evaluation of DummyClassifier")
print()
wtr = eu.calculate_sample_weight(y_train)
average_scores_and_best_scores = eu.single_classic_cv_evaluation(
X_train_transformed, y_train, 'DummyClf_2nd',
DummyClassifier(strategy='most_frequent'), wtr, scoring, outer_cv,
dict(), scores_of_best_model, results, names, seed)
scores_of_best_model = average_scores_and_best_scores[1]
Dummy_scores.append(scores_of_best_model[0]) # Dummy score -- ROC_AUC
Dummy_scores.append(scores_of_best_model[1]) # Dummy score std
Dummy_scores.append(scores_of_best_model[2]) # Dummy cv results
Dummy_scores.append(scores_of_best_model[3]) # Dummy execution time
# Dummy model's name and estimator
Dummy_scores.append(scores_of_best_model[4])
names = []
results = []
print()
complex_models_and_parameters = dict()
average_scores_across_outer_folds_complex = dict()
all_models_and_parameters = dict()
# Let's add some simple neural network
print("=== [task] Comparing DummyClassifier to best Keras Clf (NN)")
print()
# This is an experiment to check
# how different Keras architectures perform
# to avoid hard-coding NNs, you should determine at least
# nr of layers and nr of nodes by using Grid or Randomized Search CV
input_dim = int(X_train_transformed.shape[1])
output_dim = 1
nb_epoch = au.select_nr_of_iterations('nn')
# evaluate Keras clfs
cv_method = select_cv_method()
if cv_method == 1:
batch_size = 32
complex_models_and_parameters = create_keras_classifiers(
Y_type, input_dim, labels, nb_epoch, batch_size)
average_scores_and_best_scores = eu.classic_cv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters, scoring,
outer_cv, average_scores_across_outer_folds_complex,
scores_of_best_model, results, names, seed)
else:
inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
n_iter = au.select_nr_of_iterations()
keras_clf_name = "KerasClf_2nd"
keras_nn_model, keras_param_grid = create_best_keras_clf_architecture(
keras_clf_name, Y_type, labels, input_dim, nb_epoch, Keras_param_grid)
complex_models_and_parameters[keras_clf_name] = (
keras_nn_model, keras_param_grid)
average_scores_and_best_scores = eu.nested_rscv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters,
scoring, n_iter, inner_cv, outer_cv,
average_scores_across_outer_folds_complex, scores_of_best_model,
results, names, seed)
print()
au.box_plots_of_models_performance(results, names)
cv_method_name = "Classic" if cv_method == 1 else "Nested"
print()
print("=== After %s CV evaluation of Keras NNs..." % cv_method_name)
print()
scores_of_best_model = average_scores_and_best_scores[1]
best_model_name = scores_of_best_model[4][0]
best_model_estim = scores_of_best_model[4][1]
best_score = scores_of_best_model[0]
best_score_dev = scores_of_best_model[1]
best_cv_results = scores_of_best_model[2]
# best_brier_score = scores_of_best_model[2]
best_exec_time = scores_of_best_model[3]
Dummy_score = Dummy_scores[0]
Dummy_score_dev = Dummy_scores[1]
Dummy_cv_results = Dummy_scores[2]
# Dummy_brier_score = Dummy_scores[3]
Dummy_exec_time = Dummy_scores[3]
print()
print("Currently, best model is '%s' with score '%s': %1.3f (%1.3f)... :" %
(best_model_name, scoring.strip('neg_'), best_score, best_score_dev))
if best_model_name in (
'baseline_nn_default_Clf_2nd', 'baseline_nn_smaller_Clf_2nd',
'larger_nn_Clf_2nd', 'deep_nn_Clf_2nd', 'deeper_nn_Clf_2nd',
'KerasClf_2nd'):
best_nn_build_fn = scores_of_best_model[4][2]
print("Best build function:", best_nn_build_fn)
print("... execution time: %.2fs" % best_exec_time)
# print("and prediction confidence: %1.3f" % best_brier_score)
print()
if best_model_name != 'DummyClf_2nd':
# It's assumed best model's performance is
# satistically better than that of DummyClf on this dataset
print("DummyClassifier's scores -- '%s': %1.3f (%1.3f)" % (
scoring.strip('neg_'), Dummy_score, Dummy_score_dev))
print("'%s' does better than DummyClassifier." % best_model_name)
if best_exec_time < Dummy_exec_time:
print("'%s' is quicker than DummyClf." % best_model_name)
print()
print()
input("Press key to continue...")
preprocessing = (encoding, scaler_tuple, featselector)
if labels is not None:
print("You have labels:", labels)
all_models_and_parameters['labels'] = labels
print("Defined dictionary with models, parameters and related data.")
print()
if cv_method == 1:
tc.calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, nb_epoch,
scoring, models_data, d_name, seed)
else:
tc.tune_calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, n_iter, nb_epoch,
scoring, models_data, d_name, seed)
else:
sys.exit("Your best classifier is not a good classifier.")
input("=== [End Of Program] Enter key to continue... \n") | select_cv_method | identifier_name |
titanic_keras_exp.py | """Evaluate Keras Classifiers and learn from the Titanic data set."""
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyClassifier
from pandas import read_csv
# from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
stderr = sys.stderr
sys.stderr = open(os.devnull, 'w')
from keras.wrappers.scikit_learn import KerasClassifier
sys.stderr = stderr
from autoclf.classification import eval_utils as eu
from autoclf import auto_utils as au
from autoclf.classification import neuralnets as nn
from autoclf.classification import train_calibrate as tc
import autoclf.getargs as ga
from autoclf.classification.param_grids_distros import Keras_param_grid
from autoclf.classification.evaluate import create_keras_classifiers
from autoclf.classification.evaluate import create_best_keras_clf_architecture
from pkg_resources import resource_string
from io import StringIO
def select_cv_method():
|
# starting program
if __name__ == '__main__':
print("### Probability Calibration Experiment -- CalibratedClassifierCV "
"with cv=cv (no prefit) ###")
print()
d_name = ga.get_name()
if d_name is None:
d_name = "titanic"
# fix random seed for reproducibility
seed = 7
np.random.seed(seed)
# load data
try:
df = read_csv(
'datasets\\titanic_train.csv', delimiter=",",
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
print("Found data in autoclf\\autoclf\\datasets")
except FileNotFoundError as fe:
titanic_bytes = resource_string(
"autoclf", os.path.join("datasets", 'titanic_train.csv'))
titanic_file = StringIO(str(titanic_bytes,'utf-8'))
names = ['PassengerId','Survived','Pclass','Name','Sex','Age','SibSp',
'Parch','Ticket','Fare','Cabin','Embarked']
df = read_csv(
titanic_file, delimiter=",",
# header=0, names=names,
na_values={'Age': '', 'Cabin': '', 'Embarked': ''},
dtype={'Name': 'category', 'Sex': 'category',
'Ticket': 'category', 'Cabin': 'category',
'Embarked': 'category'})
except Exception as e:
raise e
# data exploration
print("shape: ", df.shape)
# statistical summary
description = df.describe()
print("description - no encoding:\n", description)
print()
plt.style.use('ggplot')
# input("Enter key to continue... \n")
# Feature-Feature Relationships
# scatter_matrix(df)
print()
# too many missing values in 'Cabin' columns: about 3/4
print("Dropping 'Cabin' column -- too many missing values")
# df.Cabin.replace(to_replace=np.nan, value='Unknown', inplace=True)
df.drop(['Cabin'], axis=1, inplace=True)
print()
print("Now, shape: ", df.shape)
print("df.head():\n", df.head())
print()
description = df.describe()
print("Once again, description - no encoding:\n", description)
print()
# input("Enter key to continue... \n")
target = 'Survived'
# feature preprocessing
sltt = eu.scoring_and_tt_split(df, target, 0.2, seed)
X_train, X_test, y_train, y_test = sltt['arrays']
scoring = sltt['scoring']
Y_type = sltt['target_type']
labels = sltt['labels']
print("scoring:", scoring)
print()
print("Classes:", labels)
print()
print("X_train shape: ", X_train.shape)
print("X_train -- first row:", X_train.values[0])
print("y_train shape: ", y_train.shape)
print()
print("X_test shape: ", X_test.shape)
print("X_test -- first row:", X_test.values[0])
print("y_test shape: ", y_test.shape)
print()
print("y_train:", y_train[:3])
# input("Enter key to continue... \n")
print()
auto_feat_eng_data = eu.auto_X_encoding(sltt, seed)
print()
encoding = auto_feat_eng_data['encoding']
scaler_tuple = auto_feat_eng_data['scaler']
featselector = auto_feat_eng_data['feat_selector']
steps = auto_feat_eng_data['steps']
X_train_transformed, y_train, X_test_transformed, y_test = auto_feat_eng_data['data_arrays']
X, y = auto_feat_eng_data['Xy']
train_index, test_index = auto_feat_eng_data['tt_index']
n_splits = au.select_nr_of_splits_for_kfold_cv()
# n_iter = au.select_nr_of_iterations()
print()
# This cross-validation object is a variation of KFold that returns stratified folds.
# The folds are made by preserving the percentage of samples for each class.
# uncomment to evaluate models != KerasClfs or GaussianNB w nested cv
# inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
outer_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
### reproducing the whole autoclf workflow
names = []
results = []
print("Metric:", scoring)
print("Calibration of untrained models -- CCCV 2nd")
print()
# Evaluation of best modelwith nested CV -- inner: RSCV
# dict of models and their associated parameters
# if it comes out that the best model is LogReg, no comparison is needed
# scoring == 'roc_auc' ==>
best_score = 0.5 # 0.0
best_score_dev = 0.1
best_cv_results = np.zeros(n_splits)
best_exec_time = 31536000 # one year in seconds
best_model = ('Random', None, None)
Dummy_scores = []
models_data = []
names = []
results = []
scores_of_best_model = (best_score, best_score_dev, best_cv_results,
best_exec_time, best_model)
# Start evaluation process
print()
print("=== [task] Evaluation of DummyClassifier")
print()
wtr = eu.calculate_sample_weight(y_train)
average_scores_and_best_scores = eu.single_classic_cv_evaluation(
X_train_transformed, y_train, 'DummyClf_2nd',
DummyClassifier(strategy='most_frequent'), wtr, scoring, outer_cv,
dict(), scores_of_best_model, results, names, seed)
scores_of_best_model = average_scores_and_best_scores[1]
Dummy_scores.append(scores_of_best_model[0]) # Dummy score -- ROC_AUC
Dummy_scores.append(scores_of_best_model[1]) # Dummy score std
Dummy_scores.append(scores_of_best_model[2]) # Dummy cv results
Dummy_scores.append(scores_of_best_model[3]) # Dummy execution time
# Dummy model's name and estimator
Dummy_scores.append(scores_of_best_model[4])
names = []
results = []
print()
complex_models_and_parameters = dict()
average_scores_across_outer_folds_complex = dict()
all_models_and_parameters = dict()
# Let's add some simple neural network
print("=== [task] Comparing DummyClassifier to best Keras Clf (NN)")
print()
# This is an experiment to check
# how different Keras architectures perform
# to avoid hard-coding NNs, you should determine at least
# nr of layers and nr of nodes by using Grid or Randomized Search CV
input_dim = int(X_train_transformed.shape[1])
output_dim = 1
nb_epoch = au.select_nr_of_iterations('nn')
# evaluate Keras clfs
cv_method = select_cv_method()
if cv_method == 1:
batch_size = 32
complex_models_and_parameters = create_keras_classifiers(
Y_type, input_dim, labels, nb_epoch, batch_size)
average_scores_and_best_scores = eu.classic_cv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters, scoring,
outer_cv, average_scores_across_outer_folds_complex,
scores_of_best_model, results, names, seed)
else:
inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=seed)
n_iter = au.select_nr_of_iterations()
keras_clf_name = "KerasClf_2nd"
keras_nn_model, keras_param_grid = create_best_keras_clf_architecture(
keras_clf_name, Y_type, labels, input_dim, nb_epoch, Keras_param_grid)
complex_models_and_parameters[keras_clf_name] = (
keras_nn_model, keras_param_grid)
average_scores_and_best_scores = eu.nested_rscv_model_evaluation(
X_train_transformed, y_train, complex_models_and_parameters,
scoring, n_iter, inner_cv, outer_cv,
average_scores_across_outer_folds_complex, scores_of_best_model,
results, names, seed)
print()
au.box_plots_of_models_performance(results, names)
cv_method_name = "Classic" if cv_method == 1 else "Nested"
print()
print("=== After %s CV evaluation of Keras NNs..." % cv_method_name)
print()
scores_of_best_model = average_scores_and_best_scores[1]
best_model_name = scores_of_best_model[4][0]
best_model_estim = scores_of_best_model[4][1]
best_score = scores_of_best_model[0]
best_score_dev = scores_of_best_model[1]
best_cv_results = scores_of_best_model[2]
# best_brier_score = scores_of_best_model[2]
best_exec_time = scores_of_best_model[3]
Dummy_score = Dummy_scores[0]
Dummy_score_dev = Dummy_scores[1]
Dummy_cv_results = Dummy_scores[2]
# Dummy_brier_score = Dummy_scores[3]
Dummy_exec_time = Dummy_scores[3]
print()
print("Currently, best model is '%s' with score '%s': %1.3f (%1.3f)... :" %
(best_model_name, scoring.strip('neg_'), best_score, best_score_dev))
if best_model_name in (
'baseline_nn_default_Clf_2nd', 'baseline_nn_smaller_Clf_2nd',
'larger_nn_Clf_2nd', 'deep_nn_Clf_2nd', 'deeper_nn_Clf_2nd',
'KerasClf_2nd'):
best_nn_build_fn = scores_of_best_model[4][2]
print("Best build function:", best_nn_build_fn)
print("... execution time: %.2fs" % best_exec_time)
# print("and prediction confidence: %1.3f" % best_brier_score)
print()
if best_model_name != 'DummyClf_2nd':
# It's assumed best model's performance is
# satistically better than that of DummyClf on this dataset
print("DummyClassifier's scores -- '%s': %1.3f (%1.3f)" % (
scoring.strip('neg_'), Dummy_score, Dummy_score_dev))
print("'%s' does better than DummyClassifier." % best_model_name)
if best_exec_time < Dummy_exec_time:
print("'%s' is quicker than DummyClf." % best_model_name)
print()
print()
input("Press key to continue...")
preprocessing = (encoding, scaler_tuple, featselector)
if labels is not None:
print("You have labels:", labels)
all_models_and_parameters['labels'] = labels
print("Defined dictionary with models, parameters and related data.")
print()
if cv_method == 1:
tc.calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, nb_epoch,
scoring, models_data, d_name, seed)
else:
tc.tune_calibrate_best_model(
X, y, X_train_transformed, X_test_transformed,
y_train, y_test, auto_feat_eng_data['tt_index'],
preprocessing, scores_of_best_model,
all_models_and_parameters, n_splits, n_iter, nb_epoch,
scoring, models_data, d_name, seed)
else:
sys.exit("Your best classifier is not a good classifier.")
input("=== [End Of Program] Enter key to continue... \n") | is_valid = 0
choice = 0
while not is_valid:
try:
choice = int(input("Select cv method: [1] Classical CV, [2] Nested-CV?\n"))
if choice in (1, 2):
is_valid = 1
else:
print("Invalid number. Try again...")
except ValueError as e:
print("'%s' is not a valid integer." % e.args[0].split(": ")[1])
return choice | identifier_body |
AUTO_ASSAM_PART3.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K','LEU':'L','MET':'M','ASN':'N','PRO':'P','GLN':'Q','ARG':'R','SER':'S','THR':'T','VAL':'V','TRP':'W','TYR':'Y','UNK':'X','MSE':'M'}
atom_list = {
"ALA":('N ','C ','O ','CA ','CB '), "CYS":('N ','C ','O ','CA ','CB ','SG '),"ASP":('N ','C ','O ','CA ','CB ','CG ','OD1','OD2'),"GLU":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','OE2'),"PHE":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ '),"GLY":('N ','C ','O ','CA '),"HIS":('N ','C ','O ','CA ','CB ','CG ','ND1','CD2','CE1','NE2'),
"ILE":('N ','C ','O ','CA ','CB ','CG1','CG2','CD1'),"LYS":('N ','C ','O ','CA ','CB ','CG ','CD ','CE ','NZ '),"LEU":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2'),"MET":('N ','C ','O ','CA ','CB ','CG ','SD ','CE '),"ASN":('N ','C ','O ','CA ','CB ','CG ','OD1','ND2'),"PRO":('N ','C ','O ','CA ','CB ','CG ','CD '),"GLN":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','NE2'),"ARG":('N ','C ','O ','CA ','CB ','CG ','CD ','NE ','CZ ','NH1','NH2'),
"SER":('N ','C ','O ','CA ','CB ','OG '),"THR":('N ','C ','O ','CA ','CB ','OG1','CG2'),"VAL":('N ','C ','O ','CA ','CB ','CG1','CG2'),"TRP":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','NE1','CE2','CE3','CZ2','CZ3','CH2'),"TYR":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ ','OH ')}
#=========PART 3a: SAVE INFORMATION===========
#save information of annotated drug binding sites for Drug ReposER application
#BINDING_INTERFACES_NEW, BINDING_INTERFACES_CLUSTERS, BINDING_INTERFACES_ASSAM, BINDING_INTERFACES_EXACT
def save_output_binding_interfaces():
csv_reader=csv.reader(open("pdbdescription.csv","r"),delimiter=",")
rows=[row for row in csv_reader][1:-2]
rows2=[row[:4]+[";".join(sorted(list(set([z+"("+y+")" for z,y in zip(list(set([n.split()[0] for n in row[4].split(", ")])),row[5].split(", "))])))) if row[4] != "" else "None"]+row[6:] for row in rows]
drugbank_mappings = [[i.replace("\n","").split("\t")[0]]+[i.replace("\n","").split("\t")[1]+"("+i.replace("\n","").split("\t")[2]+")"] for i in open("/Users/nursyatila/NSAG_PART2/db/pdb_drugbank.txt","r").readlines()]
#dictionary of drugbank annotation
dict_drugbank_mappings = collections.defaultdict(list)
#dictionary of drug indication
dict_indication_mappings = collections.defaultdict(list)
for d in drugbank_mappings:
dict_drugbank_mappings[d[0]].append(d[1]+"("+d[2]+")")
dict_indication_mappings[d[0]].append(d[3])
#dictionary of source organism
dict_source_mappings = collections.defaultdict(list)
for s in rows2: dict_source_mappings[s[0].lower()+s[1]].append(s[3])
#dictionary of pdb-macromolecule mappings
dict_macromolecule_mappings = collections.defaultdict(list)
for m in rows2: dict_macromolecule_mappings[m[0].lower()+m[1]].append(m[2])
#pfam annotation
pfam_annotation = collections.defaultdict(list)
for p in rows2: pfam_annotation[p[0].lower()+p[1]].append(p[4])
csv_writer = csv.writer(open("BINDING_INTERFACES.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
csv_writer2 = csv.writer(open("BINDING_INTERFACES_CLUSTERS.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES_CLUSTERS/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
def change_het_res(hetatm_residues):
if "from" in hetatm_residues:
if "site" not in hetatm_residues:
rr = hetatm_residues
het_resx = [" ".join([r.split(" from ")[1].replace("s","")[-9:]]+["("+r.split(" from ")[0].replace(" ","")+")" if "-" in r.split(" from ")[0] else "( "+r.split(" from ")[0].replace(" ","")+")" ]) if float(re.findall("[0-9]+[.][0-9]+",r.split(" from ")[0])[0])<5.0 else "None" for r in rr.split(";")]
if all(item == "None" for item in het_resx) == True: het_res = "None"
else: het_res = ";".join(het_resx)
else: het_res = "None"
else: het_res = "None"
return het_res
#BINDING_INTERFACES_ASSAM
def save_output_binding_interfaces_assam():
pdb_dict=collections.defaultdict(list)
pdb_new_dict=collections.defaultdict(list)
pdbs_all=[["_".join(i.split("/")[-1].split("_")[:3]).upper()]+[i.split("/")[-1].replace(".pdb","")] for i in glob.glob("renew_bs_finalized/*.pdb")]
for pdb in pdbs_all: pdb_dict[pdb[0]].append(pdb[1])
for k in pdb_dict.keys():
for index, pdb in enumerate(pdb_dict[k]):
pdb_new_dict[pdb].append(k+"_"+str(index))
csv_writer=csv.writer(open("BINDING_INTERFACES_ASSAM.csv","w"),delimiter=",")
all_cs=[cs for cs in glob.glob("/Users/nursyatila/NSAG_PART2/ASS_EXE/drreposer_output/*/*/*_sum_2.csv")] for cs in all_cs:
csv_readerx=[pdb_new_dict[row[0]]+row[1:] for row in csv.reader(open(cs,"r"),delimiter=",")]
#rowsx=[pdb_new_dict[row[0]]+row[1:6]+[";".join([change_het_res(hetatm_residues) for hetatm_residues in row[6].split(";")])]+row[7:] for row in csv_readerx]
for r in csv_readerx:
csv_writer.writerow(r)
#BINDING_INTERFACES_EXACT
def binding_interfaces_exact():
csv_readerx=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rowsx=[[row[0]]+[row[8]] for row in csv_readerx]
dreposer_id_dict=collections.defaultdict(list)
for r in rowsx: dreposer_id_dict[r[0]].append(len(r[1].split(";")))
csv_readerxx=csv.reader(open("BINDING_INTERFACES_ASSAM.csv","r"),delimiter=",")
rowsxx=[row for row in csv_readerxx if int(dreposer_id_dict[row[0]][0])==len(row[5].split(";"))]
csv_writerxx=csv.writer(open("BINDING_INTERFACES_ASSAM_EXACT.csv","w"),delimiter=",")
for r in rowsxx:
csv_writerxx.writerow([str(dreposer_id_dict[r[0]][0])]+r)
#=========PART 3b: SAVE PDB-FORMATTED AND GRAPH PATTERNS FOR SPRITE SEARCHES===========
#rename pdb file containing binding sites
def | ():
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
output = open("PDB_DBS/"+key+"_0"+str(ren)+".pdb","w")
pdb_lines = ["REMARK SOURCE "+key[:4]]+open(pdb,"r").readlines()
for li in pdb_lines: print>>output, li.replace("\n","")
print pdb, key+"_0"+str(ren)
#add information in pat files
def pik_for_sprite():
proc = subprocess.Popen('source dreposed_sprite_pat.sh',shell=True,stdin=subprocess.PIPE,stdout=subprocess.PIPE)
proc.communicate()
csv_reader=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rows=[row for row in csv_reader]
dictprotein=collections.defaultdict(list)
for m in rows: dictprotein[m[0]].append(m[6])
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
map_bsclus = pdb.split("/")[-1].replace(".pdb","")
pikfile = "PIK_DBS/"+key+"_0"+str(ren)+".pat"
to_add="COMPND source {} ".format(key[:4])+dictprotein[map_bsclus][0]+" ("+map_bsclus+")"
print pikfile, to_add
output = open(pikfile,"w")
pdb_lines = [to_add]+open(pikfile,"r").readlines()[1:]
for li in pdb_lines: print>>output, li.replace("\n","")
| rename_pdb_dbs | identifier_name |
AUTO_ASSAM_PART3.py | #A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K','LEU':'L','MET':'M','ASN':'N','PRO':'P','GLN':'Q','ARG':'R','SER':'S','THR':'T','VAL':'V','TRP':'W','TYR':'Y','UNK':'X','MSE':'M'}
atom_list = {
"ALA":('N ','C ','O ','CA ','CB '), "CYS":('N ','C ','O ','CA ','CB ','SG '),"ASP":('N ','C ','O ','CA ','CB ','CG ','OD1','OD2'),"GLU":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','OE2'),"PHE":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ '),"GLY":('N ','C ','O ','CA '),"HIS":('N ','C ','O ','CA ','CB ','CG ','ND1','CD2','CE1','NE2'),
"ILE":('N ','C ','O ','CA ','CB ','CG1','CG2','CD1'),"LYS":('N ','C ','O ','CA ','CB ','CG ','CD ','CE ','NZ '),"LEU":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2'),"MET":('N ','C ','O ','CA ','CB ','CG ','SD ','CE '),"ASN":('N ','C ','O ','CA ','CB ','CG ','OD1','ND2'),"PRO":('N ','C ','O ','CA ','CB ','CG ','CD '),"GLN":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','NE2'),"ARG":('N ','C ','O ','CA ','CB ','CG ','CD ','NE ','CZ ','NH1','NH2'),
"SER":('N ','C ','O ','CA ','CB ','OG '),"THR":('N ','C ','O ','CA ','CB ','OG1','CG2'),"VAL":('N ','C ','O ','CA ','CB ','CG1','CG2'),"TRP":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','NE1','CE2','CE3','CZ2','CZ3','CH2'),"TYR":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ ','OH ')}
#=========PART 3a: SAVE INFORMATION===========
#save information of annotated drug binding sites for Drug ReposER application
#BINDING_INTERFACES_NEW, BINDING_INTERFACES_CLUSTERS, BINDING_INTERFACES_ASSAM, BINDING_INTERFACES_EXACT
def save_output_binding_interfaces():
csv_reader=csv.reader(open("pdbdescription.csv","r"),delimiter=",")
rows=[row for row in csv_reader][1:-2]
rows2=[row[:4]+[";".join(sorted(list(set([z+"("+y+")" for z,y in zip(list(set([n.split()[0] for n in row[4].split(", ")])),row[5].split(", "))])))) if row[4] != "" else "None"]+row[6:] for row in rows]
drugbank_mappings = [[i.replace("\n","").split("\t")[0]]+[i.replace("\n","").split("\t")[1]+"("+i.replace("\n","").split("\t")[2]+")"] for i in open("/Users/nursyatila/NSAG_PART2/db/pdb_drugbank.txt","r").readlines()]
#dictionary of drugbank annotation
dict_drugbank_mappings = collections.defaultdict(list)
#dictionary of drug indication
dict_indication_mappings = collections.defaultdict(list)
for d in drugbank_mappings:
dict_drugbank_mappings[d[0]].append(d[1]+"("+d[2]+")")
dict_indication_mappings[d[0]].append(d[3])
#dictionary of source organism
dict_source_mappings = collections.defaultdict(list)
for s in rows2: dict_source_mappings[s[0].lower()+s[1]].append(s[3])
#dictionary of pdb-macromolecule mappings
dict_macromolecule_mappings = collections.defaultdict(list)
for m in rows2: dict_macromolecule_mappings[m[0].lower()+m[1]].append(m[2])
#pfam annotation
pfam_annotation = collections.defaultdict(list)
for p in rows2: pfam_annotation[p[0].lower()+p[1]].append(p[4])
csv_writer = csv.writer(open("BINDING_INTERFACES.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
csv_writer2 = csv.writer(open("BINDING_INTERFACES_CLUSTERS.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES_CLUSTERS/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
def change_het_res(hetatm_residues):
if "from" in hetatm_residues:
if "site" not in hetatm_residues:
rr = hetatm_residues
het_resx = [" ".join([r.split(" from ")[1].replace("s","")[-9:]]+["("+r.split(" from ")[0].replace(" ","")+")" if "-" in r.split(" from ")[0] else "( "+r.split(" from ")[0].replace(" ","")+")" ]) if float(re.findall("[0-9]+[.][0-9]+",r.split(" from ")[0])[0])<5.0 else "None" for r in rr.split(";")]
if all(item == "None" for item in het_resx) == True: het_res = "None"
else: het_res = ";".join(het_resx)
else: het_res = "None"
else: het_res = "None"
return het_res
#BINDING_INTERFACES_ASSAM
def save_output_binding_interfaces_assam():
pdb_dict=collections.defaultdict(list)
pdb_new_dict=collections.defaultdict(list)
pdbs_all=[["_".join(i.split("/")[-1].split("_")[:3]).upper()]+[i.split("/")[-1].replace(".pdb","")] for i in glob.glob("renew_bs_finalized/*.pdb")]
for pdb in pdbs_all: pdb_dict[pdb[0]].append(pdb[1])
for k in pdb_dict.keys():
for index, pdb in enumerate(pdb_dict[k]):
pdb_new_dict[pdb].append(k+"_"+str(index))
csv_writer=csv.writer(open("BINDING_INTERFACES_ASSAM.csv","w"),delimiter=",")
all_cs=[cs for cs in glob.glob("/Users/nursyatila/NSAG_PART2/ASS_EXE/drreposer_output/*/*/*_sum_2.csv")] for cs in all_cs:
csv_readerx=[pdb_new_dict[row[0]]+row[1:] for row in csv.reader(open(cs,"r"),delimiter=",")]
#rowsx=[pdb_new_dict[row[0]]+row[1:6]+[";".join([change_het_res(hetatm_residues) for hetatm_residues in row[6].split(";")])]+row[7:] for row in csv_readerx]
for r in csv_readerx:
csv_writer.writerow(r)
#BINDING_INTERFACES_EXACT
def binding_interfaces_exact():
csv_readerx=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rowsx=[[row[0]]+[row[8]] for row in csv_readerx]
dreposer_id_dict=collections.defaultdict(list)
for r in rowsx: dreposer_id_dict[r[0]].append(len(r[1].split(";")))
csv_readerxx=csv.reader(open("BINDING_INTERFACES_ASSAM.csv","r"),delimiter=",")
rowsxx=[row for row in csv_readerxx if int(dreposer_id_dict[row[0]][0])==len(row[5].split(";"))]
csv_writerxx=csv.writer(open("BINDING_INTERFACES_ASSAM_EXACT.csv","w"),delimiter=",")
for r in rowsxx:
csv_writerxx.writerow([str(dreposer_id_dict[r[0]][0])]+r)
#=========PART 3b: SAVE PDB-FORMATTED AND GRAPH PATTERNS FOR SPRITE SEARCHES===========
#rename pdb file containing binding sites
def rename_pdb_dbs():
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
output = open("PDB_DBS/"+key+"_0"+str(ren)+".pdb","w")
pdb_lines = ["REMARK SOURCE "+key[:4]]+open(pdb,"r").readlines()
for li in pdb_lines: print>>output, li.replace("\n","")
print pdb, key+"_0"+str(ren)
#add information in pat files
def pik_for_sprite():
proc = subprocess.Popen('source dreposed_sprite_pat.sh',shell=True,stdin=subprocess.PIPE,stdout=subprocess.PIPE)
proc.communicate()
csv_reader=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rows=[row for row in csv_reader]
dictprotein=collections.defaultdict(list)
for m in rows: dictprotein[m[0]].append(m[6])
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
map_bsclus = pdb.split("/")[-1].replace(".pdb","")
pikfile = "PIK_DBS/"+key+"_0"+str(ren)+".pat"
to_add="COMPND source {} ".format(key[:4])+dictprotein[map_bsclus][0]+" ("+map_bsclus+")"
print pikfile, to_add
output = open(pikfile,"w")
pdb_lines = [to_add]+open(pikfile,"r").readlines()[1:]
for li in pdb_lines: print>>output, li.replace("\n","") | #!/usr/bin/env python
# -*- coding: utf-8 -*- | random_line_split | |
AUTO_ASSAM_PART3.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K','LEU':'L','MET':'M','ASN':'N','PRO':'P','GLN':'Q','ARG':'R','SER':'S','THR':'T','VAL':'V','TRP':'W','TYR':'Y','UNK':'X','MSE':'M'}
atom_list = {
"ALA":('N ','C ','O ','CA ','CB '), "CYS":('N ','C ','O ','CA ','CB ','SG '),"ASP":('N ','C ','O ','CA ','CB ','CG ','OD1','OD2'),"GLU":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','OE2'),"PHE":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ '),"GLY":('N ','C ','O ','CA '),"HIS":('N ','C ','O ','CA ','CB ','CG ','ND1','CD2','CE1','NE2'),
"ILE":('N ','C ','O ','CA ','CB ','CG1','CG2','CD1'),"LYS":('N ','C ','O ','CA ','CB ','CG ','CD ','CE ','NZ '),"LEU":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2'),"MET":('N ','C ','O ','CA ','CB ','CG ','SD ','CE '),"ASN":('N ','C ','O ','CA ','CB ','CG ','OD1','ND2'),"PRO":('N ','C ','O ','CA ','CB ','CG ','CD '),"GLN":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','NE2'),"ARG":('N ','C ','O ','CA ','CB ','CG ','CD ','NE ','CZ ','NH1','NH2'),
"SER":('N ','C ','O ','CA ','CB ','OG '),"THR":('N ','C ','O ','CA ','CB ','OG1','CG2'),"VAL":('N ','C ','O ','CA ','CB ','CG1','CG2'),"TRP":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','NE1','CE2','CE3','CZ2','CZ3','CH2'),"TYR":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ ','OH ')}
#=========PART 3a: SAVE INFORMATION===========
#save information of annotated drug binding sites for Drug ReposER application
#BINDING_INTERFACES_NEW, BINDING_INTERFACES_CLUSTERS, BINDING_INTERFACES_ASSAM, BINDING_INTERFACES_EXACT
def save_output_binding_interfaces():
csv_reader=csv.reader(open("pdbdescription.csv","r"),delimiter=",")
rows=[row for row in csv_reader][1:-2]
rows2=[row[:4]+[";".join(sorted(list(set([z+"("+y+")" for z,y in zip(list(set([n.split()[0] for n in row[4].split(", ")])),row[5].split(", "))])))) if row[4] != "" else "None"]+row[6:] for row in rows]
drugbank_mappings = [[i.replace("\n","").split("\t")[0]]+[i.replace("\n","").split("\t")[1]+"("+i.replace("\n","").split("\t")[2]+")"] for i in open("/Users/nursyatila/NSAG_PART2/db/pdb_drugbank.txt","r").readlines()]
#dictionary of drugbank annotation
dict_drugbank_mappings = collections.defaultdict(list)
#dictionary of drug indication
dict_indication_mappings = collections.defaultdict(list)
for d in drugbank_mappings:
dict_drugbank_mappings[d[0]].append(d[1]+"("+d[2]+")")
dict_indication_mappings[d[0]].append(d[3])
#dictionary of source organism
dict_source_mappings = collections.defaultdict(list)
for s in rows2: dict_source_mappings[s[0].lower()+s[1]].append(s[3])
#dictionary of pdb-macromolecule mappings
dict_macromolecule_mappings = collections.defaultdict(list)
for m in rows2: dict_macromolecule_mappings[m[0].lower()+m[1]].append(m[2])
#pfam annotation
pfam_annotation = collections.defaultdict(list)
for p in rows2: pfam_annotation[p[0].lower()+p[1]].append(p[4])
csv_writer = csv.writer(open("BINDING_INTERFACES.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
csv_writer2 = csv.writer(open("BINDING_INTERFACES_CLUSTERS.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES_CLUSTERS/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
def change_het_res(hetatm_residues):
if "from" in hetatm_residues:
if "site" not in hetatm_residues:
rr = hetatm_residues
het_resx = [" ".join([r.split(" from ")[1].replace("s","")[-9:]]+["("+r.split(" from ")[0].replace(" ","")+")" if "-" in r.split(" from ")[0] else "( "+r.split(" from ")[0].replace(" ","")+")" ]) if float(re.findall("[0-9]+[.][0-9]+",r.split(" from ")[0])[0])<5.0 else "None" for r in rr.split(";")]
if all(item == "None" for item in het_resx) == True: |
else: het_res = ";".join(het_resx)
else: het_res = "None"
else: het_res = "None"
return het_res
#BINDING_INTERFACES_ASSAM
def save_output_binding_interfaces_assam():
pdb_dict=collections.defaultdict(list)
pdb_new_dict=collections.defaultdict(list)
pdbs_all=[["_".join(i.split("/")[-1].split("_")[:3]).upper()]+[i.split("/")[-1].replace(".pdb","")] for i in glob.glob("renew_bs_finalized/*.pdb")]
for pdb in pdbs_all: pdb_dict[pdb[0]].append(pdb[1])
for k in pdb_dict.keys():
for index, pdb in enumerate(pdb_dict[k]):
pdb_new_dict[pdb].append(k+"_"+str(index))
csv_writer=csv.writer(open("BINDING_INTERFACES_ASSAM.csv","w"),delimiter=",")
all_cs=[cs for cs in glob.glob("/Users/nursyatila/NSAG_PART2/ASS_EXE/drreposer_output/*/*/*_sum_2.csv")] for cs in all_cs:
csv_readerx=[pdb_new_dict[row[0]]+row[1:] for row in csv.reader(open(cs,"r"),delimiter=",")]
#rowsx=[pdb_new_dict[row[0]]+row[1:6]+[";".join([change_het_res(hetatm_residues) for hetatm_residues in row[6].split(";")])]+row[7:] for row in csv_readerx]
for r in csv_readerx:
csv_writer.writerow(r)
#BINDING_INTERFACES_EXACT
def binding_interfaces_exact():
csv_readerx=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rowsx=[[row[0]]+[row[8]] for row in csv_readerx]
dreposer_id_dict=collections.defaultdict(list)
for r in rowsx: dreposer_id_dict[r[0]].append(len(r[1].split(";")))
csv_readerxx=csv.reader(open("BINDING_INTERFACES_ASSAM.csv","r"),delimiter=",")
rowsxx=[row for row in csv_readerxx if int(dreposer_id_dict[row[0]][0])==len(row[5].split(";"))]
csv_writerxx=csv.writer(open("BINDING_INTERFACES_ASSAM_EXACT.csv","w"),delimiter=",")
for r in rowsxx:
csv_writerxx.writerow([str(dreposer_id_dict[r[0]][0])]+r)
#=========PART 3b: SAVE PDB-FORMATTED AND GRAPH PATTERNS FOR SPRITE SEARCHES===========
#rename pdb file containing binding sites
def rename_pdb_dbs():
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
output = open("PDB_DBS/"+key+"_0"+str(ren)+".pdb","w")
pdb_lines = ["REMARK SOURCE "+key[:4]]+open(pdb,"r").readlines()
for li in pdb_lines: print>>output, li.replace("\n","")
print pdb, key+"_0"+str(ren)
#add information in pat files
def pik_for_sprite():
proc = subprocess.Popen('source dreposed_sprite_pat.sh',shell=True,stdin=subprocess.PIPE,stdout=subprocess.PIPE)
proc.communicate()
csv_reader=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rows=[row for row in csv_reader]
dictprotein=collections.defaultdict(list)
for m in rows: dictprotein[m[0]].append(m[6])
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
map_bsclus = pdb.split("/")[-1].replace(".pdb","")
pikfile = "PIK_DBS/"+key+"_0"+str(ren)+".pat"
to_add="COMPND source {} ".format(key[:4])+dictprotein[map_bsclus][0]+" ("+map_bsclus+")"
print pikfile, to_add
output = open(pikfile,"w")
pdb_lines = [to_add]+open(pikfile,"r").readlines()[1:]
for li in pdb_lines: print>>output, li.replace("\n","")
| het_res = "None" | conditional_block |
AUTO_ASSAM_PART3.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#A program to parse user.LP
import itertools, sys, os, subprocess, shutil, glob, numpy as np, re, collections, operator, datetime, optparse, csv
#import Bio
trans = {'ALA':'A','CYS':'C','CYH':'C','CSS':'C','ASP':'D','GLU':'E','PHE':'F','GLY':'G','HIS':'H','ILE':'I','LYS':'K','LEU':'L','MET':'M','ASN':'N','PRO':'P','GLN':'Q','ARG':'R','SER':'S','THR':'T','VAL':'V','TRP':'W','TYR':'Y','UNK':'X','MSE':'M'}
atom_list = {
"ALA":('N ','C ','O ','CA ','CB '), "CYS":('N ','C ','O ','CA ','CB ','SG '),"ASP":('N ','C ','O ','CA ','CB ','CG ','OD1','OD2'),"GLU":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','OE2'),"PHE":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ '),"GLY":('N ','C ','O ','CA '),"HIS":('N ','C ','O ','CA ','CB ','CG ','ND1','CD2','CE1','NE2'),
"ILE":('N ','C ','O ','CA ','CB ','CG1','CG2','CD1'),"LYS":('N ','C ','O ','CA ','CB ','CG ','CD ','CE ','NZ '),"LEU":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2'),"MET":('N ','C ','O ','CA ','CB ','CG ','SD ','CE '),"ASN":('N ','C ','O ','CA ','CB ','CG ','OD1','ND2'),"PRO":('N ','C ','O ','CA ','CB ','CG ','CD '),"GLN":('N ','C ','O ','CA ','CB ','CG ','CD ','OE1','NE2'),"ARG":('N ','C ','O ','CA ','CB ','CG ','CD ','NE ','CZ ','NH1','NH2'),
"SER":('N ','C ','O ','CA ','CB ','OG '),"THR":('N ','C ','O ','CA ','CB ','OG1','CG2'),"VAL":('N ','C ','O ','CA ','CB ','CG1','CG2'),"TRP":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','NE1','CE2','CE3','CZ2','CZ3','CH2'),"TYR":('N ','C ','O ','CA ','CB ','CG ','CD1','CD2','CE1','CE2','CZ ','OH ')}
#=========PART 3a: SAVE INFORMATION===========
#save information of annotated drug binding sites for Drug ReposER application
#BINDING_INTERFACES_NEW, BINDING_INTERFACES_CLUSTERS, BINDING_INTERFACES_ASSAM, BINDING_INTERFACES_EXACT
def save_output_binding_interfaces():
csv_reader=csv.reader(open("pdbdescription.csv","r"),delimiter=",")
rows=[row for row in csv_reader][1:-2]
rows2=[row[:4]+[";".join(sorted(list(set([z+"("+y+")" for z,y in zip(list(set([n.split()[0] for n in row[4].split(", ")])),row[5].split(", "))])))) if row[4] != "" else "None"]+row[6:] for row in rows]
drugbank_mappings = [[i.replace("\n","").split("\t")[0]]+[i.replace("\n","").split("\t")[1]+"("+i.replace("\n","").split("\t")[2]+")"] for i in open("/Users/nursyatila/NSAG_PART2/db/pdb_drugbank.txt","r").readlines()]
#dictionary of drugbank annotation
dict_drugbank_mappings = collections.defaultdict(list)
#dictionary of drug indication
dict_indication_mappings = collections.defaultdict(list)
for d in drugbank_mappings:
dict_drugbank_mappings[d[0]].append(d[1]+"("+d[2]+")")
dict_indication_mappings[d[0]].append(d[3])
#dictionary of source organism
dict_source_mappings = collections.defaultdict(list)
for s in rows2: dict_source_mappings[s[0].lower()+s[1]].append(s[3])
#dictionary of pdb-macromolecule mappings
dict_macromolecule_mappings = collections.defaultdict(list)
for m in rows2: dict_macromolecule_mappings[m[0].lower()+m[1]].append(m[2])
#pfam annotation
pfam_annotation = collections.defaultdict(list)
for p in rows2: pfam_annotation[p[0].lower()+p[1]].append(p[4])
csv_writer = csv.writer(open("BINDING_INTERFACES.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
csv_writer2 = csv.writer(open("BINDING_INTERFACES_CLUSTERS.csv","w",),delimiter=",")
for test_file in glob.glob("BINDING_SITES_CLUSTERS/*.pdb"):
pdbs = test_file.split("/")[-1]
pdb = pdbs[:4].lower() #pdbid
dreposed_id = pdbs.replace(".pdb","").upper() #drreposed id
binding_residues = ";".join(sorted(list(set([line[17:26] for line in open(test_file,"r") if line[:4] == "ATOM"])),key=lambda x:int(x[5:]))) #binding residues in 'ATOM' record
hetatm_residues = list(set([line[17:26] for line in open(test_file,"r").readlines() if line[:6] == "HETATM"]))[0] #drug molecule in 'HETATM' record
pdb_ligand_id = hetatm_residues[:3].replace(" ","") #pdb ligand id
pdbchains0 = sorted(list(set([pdb+line[21:22] for line in open(test_file,"r").readlines()])))
drugbank_id = ";".join(sorted(list(set(dict_drugbank_mappings[pdb_ligand_id.replace(" ","")])))) #drugbank id
if drugbank_id == "": drugbank_id = "-"
indications = ";".join(sorted(list(set(dict_indication_mappings[pdb_ligand_id]))))
organism = ";".join(sorted(list(set([k for n in [dict_source_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).replace(",",";")
if organism == "": organism = "-"
macromolecule = ";".join(sorted(list(set([k for n in [dict_macromolecule_mappings[pdbchain] for pdbchain in pdbchains0] for k in n])))).upper()
if macromolecule == "": macromolecule = "-"
pfam_id = ";".join(sorted(list(set([k for n in [pfam_annotation[pdbchain] for pdbchain in pdbchains0] for k in n]))))
compiled_details = [dreposed_id]+[pdb]+[pdb_ligand_id]+[drugbank_id]+[indications]+[organism]+[macromolecule]+[pfam_id]+[binding_residues]+[hetatm_residues] #arrangement in csv file
#print compiled_details
csv_writer.writerow(compiled_details)
def change_het_res(hetatm_residues):
if "from" in hetatm_residues:
if "site" not in hetatm_residues:
rr = hetatm_residues
het_resx = [" ".join([r.split(" from ")[1].replace("s","")[-9:]]+["("+r.split(" from ")[0].replace(" ","")+")" if "-" in r.split(" from ")[0] else "( "+r.split(" from ")[0].replace(" ","")+")" ]) if float(re.findall("[0-9]+[.][0-9]+",r.split(" from ")[0])[0])<5.0 else "None" for r in rr.split(";")]
if all(item == "None" for item in het_resx) == True: het_res = "None"
else: het_res = ";".join(het_resx)
else: het_res = "None"
else: het_res = "None"
return het_res
#BINDING_INTERFACES_ASSAM
def save_output_binding_interfaces_assam():
|
#BINDING_INTERFACES_EXACT
def binding_interfaces_exact():
csv_readerx=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rowsx=[[row[0]]+[row[8]] for row in csv_readerx]
dreposer_id_dict=collections.defaultdict(list)
for r in rowsx: dreposer_id_dict[r[0]].append(len(r[1].split(";")))
csv_readerxx=csv.reader(open("BINDING_INTERFACES_ASSAM.csv","r"),delimiter=",")
rowsxx=[row for row in csv_readerxx if int(dreposer_id_dict[row[0]][0])==len(row[5].split(";"))]
csv_writerxx=csv.writer(open("BINDING_INTERFACES_ASSAM_EXACT.csv","w"),delimiter=",")
for r in rowsxx:
csv_writerxx.writerow([str(dreposer_id_dict[r[0]][0])]+r)
#=========PART 3b: SAVE PDB-FORMATTED AND GRAPH PATTERNS FOR SPRITE SEARCHES===========
#rename pdb file containing binding sites
def rename_pdb_dbs():
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
output = open("PDB_DBS/"+key+"_0"+str(ren)+".pdb","w")
pdb_lines = ["REMARK SOURCE "+key[:4]]+open(pdb,"r").readlines()
for li in pdb_lines: print>>output, li.replace("\n","")
print pdb, key+"_0"+str(ren)
#add information in pat files
def pik_for_sprite():
proc = subprocess.Popen('source dreposed_sprite_pat.sh',shell=True,stdin=subprocess.PIPE,stdout=subprocess.PIPE)
proc.communicate()
csv_reader=csv.reader(open("BINDING_INTERFACES_CLUSTERS.csv","r"),delimiter=",")
rows=[row for row in csv_reader]
dictprotein=collections.defaultdict(list)
for m in rows: dictprotein[m[0]].append(m[6])
pdbs_to_edit = [i for i in glob.glob("BINDING_SITES_CLUSTERS/*.pdb")]
pdbs_to_edit2 = [[i]+[i.split("/")[-1].split("_")[0].lower()] for i in pdbs_to_edit]
d_dct = collections.defaultdict(list)
for n in pdbs_to_edit2: d_dct[n[1]].append(n[0])
keys = sorted([key for key in d_dct.keys()])
for key in keys:
for ren, pdb in enumerate(d_dct[key]):
map_bsclus = pdb.split("/")[-1].replace(".pdb","")
pikfile = "PIK_DBS/"+key+"_0"+str(ren)+".pat"
to_add="COMPND source {} ".format(key[:4])+dictprotein[map_bsclus][0]+" ("+map_bsclus+")"
print pikfile, to_add
output = open(pikfile,"w")
pdb_lines = [to_add]+open(pikfile,"r").readlines()[1:]
for li in pdb_lines: print>>output, li.replace("\n","")
| pdb_dict=collections.defaultdict(list)
pdb_new_dict=collections.defaultdict(list)
pdbs_all=[["_".join(i.split("/")[-1].split("_")[:3]).upper()]+[i.split("/")[-1].replace(".pdb","")] for i in glob.glob("renew_bs_finalized/*.pdb")]
for pdb in pdbs_all: pdb_dict[pdb[0]].append(pdb[1])
for k in pdb_dict.keys():
for index, pdb in enumerate(pdb_dict[k]):
pdb_new_dict[pdb].append(k+"_"+str(index))
csv_writer=csv.writer(open("BINDING_INTERFACES_ASSAM.csv","w"),delimiter=",")
all_cs=[cs for cs in glob.glob("/Users/nursyatila/NSAG_PART2/ASS_EXE/drreposer_output/*/*/*_sum_2.csv")] for cs in all_cs:
csv_readerx=[pdb_new_dict[row[0]]+row[1:] for row in csv.reader(open(cs,"r"),delimiter=",")]
#rowsx=[pdb_new_dict[row[0]]+row[1:6]+[";".join([change_het_res(hetatm_residues) for hetatm_residues in row[6].split(";")])]+row[7:] for row in csv_readerx]
for r in csv_readerx:
csv_writer.writerow(r) | identifier_body |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t believe you have found it!\n",
"It has been a lifelong dream of mine to forge a weapon from the mythical metal.\n"
]
for text in texts:
storyline.slow_type(text)
time.sleep(0.5)
weapon_list = {'Dagger': items.Carnwennan,
'Sword': items.Excalibur,
'Mace': items.Mjolnir,
'Fist': items.GodsHand,
'Axe': items.Jarnbjorn,
'Polearm': items.Gungnir,
'Staff': [items.PrincessGuard, items.DragonStaff],
'Hammer': items.Skullcrusher,
'Ninja Blades': items.Ninjato}
make_list = []
i = 0
for typ, weapon in weapon_list.items():
if typ == 'Staff':
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
if classes.equip_check(weapon, 'Weapon', player.cls):
make_list.append((typ, i))
i += 1
make_list.append(('Not yet', i))
while True:
print('What type of weapon would you like me to make?')
weapon_ind = storyline.get_response(make_list)
break
if make_list[weapon_ind][0] == 'Not yet':
print("I am sorry to hear that...please come back if you change your mind.")
else:
weapon = weapon_list[make_list[weapon_ind][0]]
if type(weapon) == list:
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
print("Give me a moment and I will make you an ultimate weapon...")
time.sleep(5)
print("I present to you, {}, the mighty {}!".format(player.name, weapon().name))
player.modify_inventory(weapon, num=1)
del player.inventory['UNOBTAINIUM']
time.sleep(2)
def blacksmith(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Griswold's! What can I do you for?"
if 'UNOBTAINIUM' in list(player.inventory.keys()) and player.pro_level == 3:
ultimate(player)
buy_list = [('Weapon', 0), ('OffHand', 1)]
shop(player, buy_list, shop_text)
def armory(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "I have the finest armors for sale. Come in and look around."
buy_list = [('Armor', 0)]
shop(player, buy_list, shop_text)
def alchemist(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Ye Olde Item Shoppe."
buy_list = [('Potion', 0), ('Misc', 1)]
shop(player, buy_list, shop_text)
def jeweler(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Come glimpse the finest jewelry in the land."
buy_list = [('Accessory', 0)]
shop(player, buy_list, shop_text)
def tavern(player):
"""
Quests
"""
print("Sorry but we are closed for construction. Come back once we are open!")
time.sleep(1)
def church(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
while True:
print("Come in my child. You are always welcome in the arms of Elysia.")
print("How can we be of service?")
church_options = [('Promotion', 0), ('Save', 1), ('Quit', 2), ('Leave', 3)]
church_index = storyline.get_response(church_options)
if church_options[church_index][1] == 0:
if player.level // 20 > 0 and player.pro_level < 3:
print("You have qualified for a promotion. Which path would you like to follow?")
classes.promotion(player)
print("Let the light of Elysia guide you on your new path.")
elif player.pro_level == 3:
print("You are at max promotion level and can no longer be promoted.")
else:
print("You need to be at least level 20 before you can promote your character.")
time.sleep(1)
elif church_options[church_index][1] == 1:
player.save(wmap) # Can only save at church in town
elif church_options[church_index][1] == 2:
player.game_quit()
elif church_options[church_index][1] == 3:
print("Let the light of Elysia guide you.")
time.sleep(1)
break
os.system('cls' if os.name == 'nt' else 'clear')
def secret_shop(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "You have found me in this god forsaken place. Since you're here, you might as well buy some supplies."
buy_list = [('Weapon', 0), ('OffHand', 1), ('Armor', 2), ('Accessory', 3), ('Potion', 4)]
shop(player, buy_list, shop_text, in_town=False)
player.location_y += 1
def shop(player, buy_list, shop_text, in_town=True):
items_dict = items.items_dict
while True:
print(shop_text)
print("You have {} gold.".format(player.gold))
print("Did you want to buy or sell?")
option_list = [('Buy', 0), ('Sell', 1), ('Leave', 2)]
opt_index = storyline.get_response(option_list)
if option_list[opt_index][0] == 'Leave':
print("We're sorry to see you go. Come back anytime!")
time.sleep(1)
break
elif option_list[opt_index][0] == 'Buy':
print("Great! What would you like to buy?")
if len(buy_list) > 1:
buy_index = storyline.get_response(buy_list)
else:
buy_index = 0
cat_list = []
i = 0
for cat in items_dict[buy_list[buy_index][0]]:
cat_list.append((cat, i))
i += 1
cat_list.append(('Go back', i))
cat_index = storyline.get_response(cat_list)
if cat_list[cat_index][0] == 'Go back':
continue
item_list = []
item_options = []
i = 0
for item in items_dict[buy_list[buy_index][0]][cat_list[cat_index][0]]:
adj_cost = max(1, int(item().value - player.charisma * 2))
if in_town:
if item().rarity < 35:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
else:
if 35 <= item().rarity <= 40:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
item_options.append(('Go back', i))
item_index = storyline.get_response(item_options)
if item_options[item_index][0] == 'Go back':
continue
buy_item = item_list[item_index]
buy_price = max(1, int(buy_item().value - (player.charisma * 2)))
if player.gold < buy_price:
print("You do not have enough gold.")
time.sleep(0.25)
else:
print("You have {} gold coins.".format(player.gold))
while True:
try:
num = int(input("How many {}s would you like to buy? ".format(buy_item().name)))
if num * buy_price > player.gold:
print("You do not have enough money for that purchase.")
elif num == 0:
break
else:
buy_price *= num
print("That will cost {} gold coins.".format(buy_price))
confirm = input("Do you still want to buy {} {}s? ".format(num, buy_item().name)).lower()
if confirm == 'y':
player.gold -= buy_price
player.modify_inventory(buy_item, num=num, sell=False)
print("{} {} will be added to your inventory.".format(num, buy_item().name))
else:
print("Sorry to hear that. Come back when you have something you wish to buy.")
break
except ValueError:
print("Please enter a valid number.")
input()
elif option_list[opt_index][0] == 'Sell':
print("We could always use more product. What do you have to sell?")
sell_list = []
i = 0
for key in player.inventory.keys():
if player.inventory[key][0]().rarity < 99:
sell_list.append((key, i))
i += 1
if len(sell_list) == 0:
print("You don't have anything to sell.")
break
sell_list.append(('Exit', i))
typ_index = storyline.get_response(sell_list)
if sell_list[typ_index][0] == 'Exit':
break
else:
sell_item = player.inventory[sell_list[typ_index][0]][0]
sell_amt = player.inventory[sell_list[typ_index][0]][1]
if sell_item().rarity >= 50:
print("Wow, that's something you don't see everyday!")
print("You have {} {} to sell.".format(sell_amt, sell_item().name))
while True:
try:
num = int(input("How many would you like to sell? "))
if num <= sell_amt and num != 0:
sale_price = int(0.5 * num * sell_item().value + (player.charisma * 2))
print("I'll give you {} gold coins for that.".format(sale_price))
confirm = input("Do you still want to sell? ").lower()
if confirm == 'y':
player.modify_inventory(player.inventory[sell_list[typ_index][0]][0], num=num,
sell=True)
player.gold += sale_price
print("You sold {} {} for {} gold.".format(num, sell_item().name, sale_price))
else:
print("I am sorry to hear that. Come back when you have something you wish to sell.")
break
elif num == 0:
break
else:
print("You cannot sell more than you have.")
except ValueError:
print("Please enter a valid number.")
input()
else:
|
time.sleep(1)
os.system('cls' if os.name == 'nt' else 'clear')
def town(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
locations = [blacksmith, armory, alchemist, jeweler, church, tavern]
town_options = [('Blacksmith', 0), ('Armory', 1), ('Alchemist', 2), ('Jeweler', 3), ('Church', 4), ('Tavern', 5),
('Dungeon', 6), ('Status', 7)]
while True:
print("Welcome to the town of Silvana!")
print("Where would you like to go?")
town_index = storyline.get_response(town_options)
if town_options[town_index][0] == 'Dungeon':
print("You descend into the dungeon.")
time.sleep(1)
player.location_x, player.location_y, player.location_z = (5, 10, 1)
break
elif town_options[town_index][0] == 'Status':
player.status()
elif town_options[town_index][0] == 'Church':
locations[town_index](player, wmap)
else:
locations[town_index](player)
os.system('cls' if os.name == 'nt' else 'clear')
| print("Please enter a valid option.") | conditional_block |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t believe you have found it!\n",
"It has been a lifelong dream of mine to forge a weapon from the mythical metal.\n"
]
for text in texts:
storyline.slow_type(text)
time.sleep(0.5)
weapon_list = {'Dagger': items.Carnwennan,
'Sword': items.Excalibur,
'Mace': items.Mjolnir,
'Fist': items.GodsHand,
'Axe': items.Jarnbjorn,
'Polearm': items.Gungnir,
'Staff': [items.PrincessGuard, items.DragonStaff],
'Hammer': items.Skullcrusher,
'Ninja Blades': items.Ninjato}
make_list = []
i = 0
for typ, weapon in weapon_list.items():
if typ == 'Staff':
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
if classes.equip_check(weapon, 'Weapon', player.cls):
make_list.append((typ, i))
i += 1
make_list.append(('Not yet', i))
while True:
print('What type of weapon would you like me to make?')
weapon_ind = storyline.get_response(make_list)
break
if make_list[weapon_ind][0] == 'Not yet':
print("I am sorry to hear that...please come back if you change your mind.")
else:
weapon = weapon_list[make_list[weapon_ind][0]]
if type(weapon) == list:
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
print("Give me a moment and I will make you an ultimate weapon...")
time.sleep(5)
print("I present to you, {}, the mighty {}!".format(player.name, weapon().name))
player.modify_inventory(weapon, num=1)
del player.inventory['UNOBTAINIUM']
time.sleep(2)
def blacksmith(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Griswold's! What can I do you for?"
if 'UNOBTAINIUM' in list(player.inventory.keys()) and player.pro_level == 3:
ultimate(player)
buy_list = [('Weapon', 0), ('OffHand', 1)]
shop(player, buy_list, shop_text)
def armory(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "I have the finest armors for sale. Come in and look around."
buy_list = [('Armor', 0)]
shop(player, buy_list, shop_text)
def alchemist(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Ye Olde Item Shoppe."
buy_list = [('Potion', 0), ('Misc', 1)]
shop(player, buy_list, shop_text)
def jeweler(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Come glimpse the finest jewelry in the land."
buy_list = [('Accessory', 0)]
shop(player, buy_list, shop_text)
def tavern(player):
"""
Quests
"""
print("Sorry but we are closed for construction. Come back once we are open!")
time.sleep(1)
def church(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
while True:
print("Come in my child. You are always welcome in the arms of Elysia.")
print("How can we be of service?")
church_options = [('Promotion', 0), ('Save', 1), ('Quit', 2), ('Leave', 3)]
church_index = storyline.get_response(church_options)
if church_options[church_index][1] == 0:
if player.level // 20 > 0 and player.pro_level < 3:
print("You have qualified for a promotion. Which path would you like to follow?")
classes.promotion(player)
print("Let the light of Elysia guide you on your new path.")
elif player.pro_level == 3:
print("You are at max promotion level and can no longer be promoted.")
else:
print("You need to be at least level 20 before you can promote your character.")
time.sleep(1)
elif church_options[church_index][1] == 1:
player.save(wmap) # Can only save at church in town
elif church_options[church_index][1] == 2:
player.game_quit()
elif church_options[church_index][1] == 3:
print("Let the light of Elysia guide you.")
time.sleep(1)
break
os.system('cls' if os.name == 'nt' else 'clear')
def secret_shop(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "You have found me in this god forsaken place. Since you're here, you might as well buy some supplies."
buy_list = [('Weapon', 0), ('OffHand', 1), ('Armor', 2), ('Accessory', 3), ('Potion', 4)]
shop(player, buy_list, shop_text, in_town=False)
player.location_y += 1
def shop(player, buy_list, shop_text, in_town=True):
items_dict = items.items_dict
while True:
print(shop_text)
print("You have {} gold.".format(player.gold))
print("Did you want to buy or sell?")
option_list = [('Buy', 0), ('Sell', 1), ('Leave', 2)]
opt_index = storyline.get_response(option_list)
if option_list[opt_index][0] == 'Leave':
print("We're sorry to see you go. Come back anytime!")
time.sleep(1)
break
elif option_list[opt_index][0] == 'Buy':
print("Great! What would you like to buy?")
if len(buy_list) > 1:
buy_index = storyline.get_response(buy_list)
else:
buy_index = 0
cat_list = []
i = 0
for cat in items_dict[buy_list[buy_index][0]]:
cat_list.append((cat, i))
i += 1
cat_list.append(('Go back', i))
cat_index = storyline.get_response(cat_list)
if cat_list[cat_index][0] == 'Go back':
continue
item_list = []
item_options = []
i = 0
for item in items_dict[buy_list[buy_index][0]][cat_list[cat_index][0]]:
adj_cost = max(1, int(item().value - player.charisma * 2))
if in_town:
if item().rarity < 35:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
else:
if 35 <= item().rarity <= 40:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
item_options.append(('Go back', i))
item_index = storyline.get_response(item_options)
if item_options[item_index][0] == 'Go back':
continue
buy_item = item_list[item_index]
buy_price = max(1, int(buy_item().value - (player.charisma * 2)))
if player.gold < buy_price:
print("You do not have enough gold.")
time.sleep(0.25)
else:
print("You have {} gold coins.".format(player.gold))
while True:
try:
num = int(input("How many {}s would you like to buy? ".format(buy_item().name)))
if num * buy_price > player.gold:
print("You do not have enough money for that purchase.")
elif num == 0:
break
else:
buy_price *= num
print("That will cost {} gold coins.".format(buy_price))
confirm = input("Do you still want to buy {} {}s? ".format(num, buy_item().name)).lower()
if confirm == 'y':
player.gold -= buy_price
player.modify_inventory(buy_item, num=num, sell=False)
print("{} {} will be added to your inventory.".format(num, buy_item().name))
else:
print("Sorry to hear that. Come back when you have something you wish to buy.")
break
except ValueError:
print("Please enter a valid number.")
input()
elif option_list[opt_index][0] == 'Sell':
print("We could always use more product. What do you have to sell?")
sell_list = []
i = 0
for key in player.inventory.keys():
if player.inventory[key][0]().rarity < 99:
sell_list.append((key, i))
i += 1
if len(sell_list) == 0:
print("You don't have anything to sell.")
break
sell_list.append(('Exit', i))
typ_index = storyline.get_response(sell_list)
if sell_list[typ_index][0] == 'Exit':
break
else:
sell_item = player.inventory[sell_list[typ_index][0]][0]
sell_amt = player.inventory[sell_list[typ_index][0]][1]
if sell_item().rarity >= 50:
print("Wow, that's something you don't see everyday!")
print("You have {} {} to sell.".format(sell_amt, sell_item().name))
while True:
try:
num = int(input("How many would you like to sell? "))
if num <= sell_amt and num != 0:
sale_price = int(0.5 * num * sell_item().value + (player.charisma * 2))
print("I'll give you {} gold coins for that.".format(sale_price))
confirm = input("Do you still want to sell? ").lower()
if confirm == 'y':
player.modify_inventory(player.inventory[sell_list[typ_index][0]][0], num=num,
sell=True)
player.gold += sale_price
print("You sold {} {} for {} gold.".format(num, sell_item().name, sale_price))
else:
print("I am sorry to hear that. Come back when you have something you wish to sell.")
break
elif num == 0:
break
else:
print("You cannot sell more than you have.")
except ValueError:
print("Please enter a valid number.")
input()
else:
print("Please enter a valid option.")
time.sleep(1)
os.system('cls' if os.name == 'nt' else 'clear')
def town(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
locations = [blacksmith, armory, alchemist, jeweler, church, tavern]
town_options = [('Blacksmith', 0), ('Armory', 1), ('Alchemist', 2), ('Jeweler', 3), ('Church', 4), ('Tavern', 5),
('Dungeon', 6), ('Status', 7)]
while True:
print("Welcome to the town of Silvana!")
print("Where would you like to go?")
town_index = storyline.get_response(town_options)
if town_options[town_index][0] == 'Dungeon':
print("You descend into the dungeon.")
time.sleep(1)
player.location_x, player.location_y, player.location_z = (5, 10, 1)
break
elif town_options[town_index][0] == 'Status': | else:
locations[town_index](player)
os.system('cls' if os.name == 'nt' else 'clear') | player.status()
elif town_options[town_index][0] == 'Church':
locations[town_index](player, wmap) | random_line_split |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t believe you have found it!\n",
"It has been a lifelong dream of mine to forge a weapon from the mythical metal.\n"
]
for text in texts:
storyline.slow_type(text)
time.sleep(0.5)
weapon_list = {'Dagger': items.Carnwennan,
'Sword': items.Excalibur,
'Mace': items.Mjolnir,
'Fist': items.GodsHand,
'Axe': items.Jarnbjorn,
'Polearm': items.Gungnir,
'Staff': [items.PrincessGuard, items.DragonStaff],
'Hammer': items.Skullcrusher,
'Ninja Blades': items.Ninjato}
make_list = []
i = 0
for typ, weapon in weapon_list.items():
if typ == 'Staff':
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
if classes.equip_check(weapon, 'Weapon', player.cls):
make_list.append((typ, i))
i += 1
make_list.append(('Not yet', i))
while True:
print('What type of weapon would you like me to make?')
weapon_ind = storyline.get_response(make_list)
break
if make_list[weapon_ind][0] == 'Not yet':
print("I am sorry to hear that...please come back if you change your mind.")
else:
weapon = weapon_list[make_list[weapon_ind][0]]
if type(weapon) == list:
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
print("Give me a moment and I will make you an ultimate weapon...")
time.sleep(5)
print("I present to you, {}, the mighty {}!".format(player.name, weapon().name))
player.modify_inventory(weapon, num=1)
del player.inventory['UNOBTAINIUM']
time.sleep(2)
def blacksmith(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Griswold's! What can I do you for?"
if 'UNOBTAINIUM' in list(player.inventory.keys()) and player.pro_level == 3:
ultimate(player)
buy_list = [('Weapon', 0), ('OffHand', 1)]
shop(player, buy_list, shop_text)
def armory(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "I have the finest armors for sale. Come in and look around."
buy_list = [('Armor', 0)]
shop(player, buy_list, shop_text)
def alchemist(player):
|
def jeweler(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Come glimpse the finest jewelry in the land."
buy_list = [('Accessory', 0)]
shop(player, buy_list, shop_text)
def tavern(player):
"""
Quests
"""
print("Sorry but we are closed for construction. Come back once we are open!")
time.sleep(1)
def church(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
while True:
print("Come in my child. You are always welcome in the arms of Elysia.")
print("How can we be of service?")
church_options = [('Promotion', 0), ('Save', 1), ('Quit', 2), ('Leave', 3)]
church_index = storyline.get_response(church_options)
if church_options[church_index][1] == 0:
if player.level // 20 > 0 and player.pro_level < 3:
print("You have qualified for a promotion. Which path would you like to follow?")
classes.promotion(player)
print("Let the light of Elysia guide you on your new path.")
elif player.pro_level == 3:
print("You are at max promotion level and can no longer be promoted.")
else:
print("You need to be at least level 20 before you can promote your character.")
time.sleep(1)
elif church_options[church_index][1] == 1:
player.save(wmap) # Can only save at church in town
elif church_options[church_index][1] == 2:
player.game_quit()
elif church_options[church_index][1] == 3:
print("Let the light of Elysia guide you.")
time.sleep(1)
break
os.system('cls' if os.name == 'nt' else 'clear')
def secret_shop(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "You have found me in this god forsaken place. Since you're here, you might as well buy some supplies."
buy_list = [('Weapon', 0), ('OffHand', 1), ('Armor', 2), ('Accessory', 3), ('Potion', 4)]
shop(player, buy_list, shop_text, in_town=False)
player.location_y += 1
def shop(player, buy_list, shop_text, in_town=True):
items_dict = items.items_dict
while True:
print(shop_text)
print("You have {} gold.".format(player.gold))
print("Did you want to buy or sell?")
option_list = [('Buy', 0), ('Sell', 1), ('Leave', 2)]
opt_index = storyline.get_response(option_list)
if option_list[opt_index][0] == 'Leave':
print("We're sorry to see you go. Come back anytime!")
time.sleep(1)
break
elif option_list[opt_index][0] == 'Buy':
print("Great! What would you like to buy?")
if len(buy_list) > 1:
buy_index = storyline.get_response(buy_list)
else:
buy_index = 0
cat_list = []
i = 0
for cat in items_dict[buy_list[buy_index][0]]:
cat_list.append((cat, i))
i += 1
cat_list.append(('Go back', i))
cat_index = storyline.get_response(cat_list)
if cat_list[cat_index][0] == 'Go back':
continue
item_list = []
item_options = []
i = 0
for item in items_dict[buy_list[buy_index][0]][cat_list[cat_index][0]]:
adj_cost = max(1, int(item().value - player.charisma * 2))
if in_town:
if item().rarity < 35:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
else:
if 35 <= item().rarity <= 40:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
item_options.append(('Go back', i))
item_index = storyline.get_response(item_options)
if item_options[item_index][0] == 'Go back':
continue
buy_item = item_list[item_index]
buy_price = max(1, int(buy_item().value - (player.charisma * 2)))
if player.gold < buy_price:
print("You do not have enough gold.")
time.sleep(0.25)
else:
print("You have {} gold coins.".format(player.gold))
while True:
try:
num = int(input("How many {}s would you like to buy? ".format(buy_item().name)))
if num * buy_price > player.gold:
print("You do not have enough money for that purchase.")
elif num == 0:
break
else:
buy_price *= num
print("That will cost {} gold coins.".format(buy_price))
confirm = input("Do you still want to buy {} {}s? ".format(num, buy_item().name)).lower()
if confirm == 'y':
player.gold -= buy_price
player.modify_inventory(buy_item, num=num, sell=False)
print("{} {} will be added to your inventory.".format(num, buy_item().name))
else:
print("Sorry to hear that. Come back when you have something you wish to buy.")
break
except ValueError:
print("Please enter a valid number.")
input()
elif option_list[opt_index][0] == 'Sell':
print("We could always use more product. What do you have to sell?")
sell_list = []
i = 0
for key in player.inventory.keys():
if player.inventory[key][0]().rarity < 99:
sell_list.append((key, i))
i += 1
if len(sell_list) == 0:
print("You don't have anything to sell.")
break
sell_list.append(('Exit', i))
typ_index = storyline.get_response(sell_list)
if sell_list[typ_index][0] == 'Exit':
break
else:
sell_item = player.inventory[sell_list[typ_index][0]][0]
sell_amt = player.inventory[sell_list[typ_index][0]][1]
if sell_item().rarity >= 50:
print("Wow, that's something you don't see everyday!")
print("You have {} {} to sell.".format(sell_amt, sell_item().name))
while True:
try:
num = int(input("How many would you like to sell? "))
if num <= sell_amt and num != 0:
sale_price = int(0.5 * num * sell_item().value + (player.charisma * 2))
print("I'll give you {} gold coins for that.".format(sale_price))
confirm = input("Do you still want to sell? ").lower()
if confirm == 'y':
player.modify_inventory(player.inventory[sell_list[typ_index][0]][0], num=num,
sell=True)
player.gold += sale_price
print("You sold {} {} for {} gold.".format(num, sell_item().name, sale_price))
else:
print("I am sorry to hear that. Come back when you have something you wish to sell.")
break
elif num == 0:
break
else:
print("You cannot sell more than you have.")
except ValueError:
print("Please enter a valid number.")
input()
else:
print("Please enter a valid option.")
time.sleep(1)
os.system('cls' if os.name == 'nt' else 'clear')
def town(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
locations = [blacksmith, armory, alchemist, jeweler, church, tavern]
town_options = [('Blacksmith', 0), ('Armory', 1), ('Alchemist', 2), ('Jeweler', 3), ('Church', 4), ('Tavern', 5),
('Dungeon', 6), ('Status', 7)]
while True:
print("Welcome to the town of Silvana!")
print("Where would you like to go?")
town_index = storyline.get_response(town_options)
if town_options[town_index][0] == 'Dungeon':
print("You descend into the dungeon.")
time.sleep(1)
player.location_x, player.location_y, player.location_z = (5, 10, 1)
break
elif town_options[town_index][0] == 'Status':
player.status()
elif town_options[town_index][0] == 'Church':
locations[town_index](player, wmap)
else:
locations[town_index](player)
os.system('cls' if os.name == 'nt' else 'clear')
| os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Ye Olde Item Shoppe."
buy_list = [('Potion', 0), ('Misc', 1)]
shop(player, buy_list, shop_text) | identifier_body |
town.py | ###########################################
""" Town manager """
# Imports
import os
import time
import items
import storyline
import classes
# Functions
def shop_inventory():
pass
def ultimate(player):
texts = [
"Oh my...can it possibly be?...the legendary ore...Unobtainium?\n",
"I can\'t believe you have found it!\n",
"It has been a lifelong dream of mine to forge a weapon from the mythical metal.\n"
]
for text in texts:
storyline.slow_type(text)
time.sleep(0.5)
weapon_list = {'Dagger': items.Carnwennan,
'Sword': items.Excalibur,
'Mace': items.Mjolnir,
'Fist': items.GodsHand,
'Axe': items.Jarnbjorn,
'Polearm': items.Gungnir,
'Staff': [items.PrincessGuard, items.DragonStaff],
'Hammer': items.Skullcrusher,
'Ninja Blades': items.Ninjato}
make_list = []
i = 0
for typ, weapon in weapon_list.items():
if typ == 'Staff':
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
if classes.equip_check(weapon, 'Weapon', player.cls):
make_list.append((typ, i))
i += 1
make_list.append(('Not yet', i))
while True:
print('What type of weapon would you like me to make?')
weapon_ind = storyline.get_response(make_list)
break
if make_list[weapon_ind][0] == 'Not yet':
print("I am sorry to hear that...please come back if you change your mind.")
else:
weapon = weapon_list[make_list[weapon_ind][0]]
if type(weapon) == list:
if 'Archbishop' == player.cls:
weapon = weapon[0]
else:
weapon = weapon[1]
print("Give me a moment and I will make you an ultimate weapon...")
time.sleep(5)
print("I present to you, {}, the mighty {}!".format(player.name, weapon().name))
player.modify_inventory(weapon, num=1)
del player.inventory['UNOBTAINIUM']
time.sleep(2)
def blacksmith(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Griswold's! What can I do you for?"
if 'UNOBTAINIUM' in list(player.inventory.keys()) and player.pro_level == 3:
ultimate(player)
buy_list = [('Weapon', 0), ('OffHand', 1)]
shop(player, buy_list, shop_text)
def | (player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "I have the finest armors for sale. Come in and look around."
buy_list = [('Armor', 0)]
shop(player, buy_list, shop_text)
def alchemist(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Welcome to Ye Olde Item Shoppe."
buy_list = [('Potion', 0), ('Misc', 1)]
shop(player, buy_list, shop_text)
def jeweler(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "Come glimpse the finest jewelry in the land."
buy_list = [('Accessory', 0)]
shop(player, buy_list, shop_text)
def tavern(player):
"""
Quests
"""
print("Sorry but we are closed for construction. Come back once we are open!")
time.sleep(1)
def church(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
while True:
print("Come in my child. You are always welcome in the arms of Elysia.")
print("How can we be of service?")
church_options = [('Promotion', 0), ('Save', 1), ('Quit', 2), ('Leave', 3)]
church_index = storyline.get_response(church_options)
if church_options[church_index][1] == 0:
if player.level // 20 > 0 and player.pro_level < 3:
print("You have qualified for a promotion. Which path would you like to follow?")
classes.promotion(player)
print("Let the light of Elysia guide you on your new path.")
elif player.pro_level == 3:
print("You are at max promotion level and can no longer be promoted.")
else:
print("You need to be at least level 20 before you can promote your character.")
time.sleep(1)
elif church_options[church_index][1] == 1:
player.save(wmap) # Can only save at church in town
elif church_options[church_index][1] == 2:
player.game_quit()
elif church_options[church_index][1] == 3:
print("Let the light of Elysia guide you.")
time.sleep(1)
break
os.system('cls' if os.name == 'nt' else 'clear')
def secret_shop(player):
os.system('cls' if os.name == 'nt' else 'clear')
shop_text = "You have found me in this god forsaken place. Since you're here, you might as well buy some supplies."
buy_list = [('Weapon', 0), ('OffHand', 1), ('Armor', 2), ('Accessory', 3), ('Potion', 4)]
shop(player, buy_list, shop_text, in_town=False)
player.location_y += 1
def shop(player, buy_list, shop_text, in_town=True):
items_dict = items.items_dict
while True:
print(shop_text)
print("You have {} gold.".format(player.gold))
print("Did you want to buy or sell?")
option_list = [('Buy', 0), ('Sell', 1), ('Leave', 2)]
opt_index = storyline.get_response(option_list)
if option_list[opt_index][0] == 'Leave':
print("We're sorry to see you go. Come back anytime!")
time.sleep(1)
break
elif option_list[opt_index][0] == 'Buy':
print("Great! What would you like to buy?")
if len(buy_list) > 1:
buy_index = storyline.get_response(buy_list)
else:
buy_index = 0
cat_list = []
i = 0
for cat in items_dict[buy_list[buy_index][0]]:
cat_list.append((cat, i))
i += 1
cat_list.append(('Go back', i))
cat_index = storyline.get_response(cat_list)
if cat_list[cat_index][0] == 'Go back':
continue
item_list = []
item_options = []
i = 0
for item in items_dict[buy_list[buy_index][0]][cat_list[cat_index][0]]:
adj_cost = max(1, int(item().value - player.charisma * 2))
if in_town:
if item().rarity < 35:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
else:
if 35 <= item().rarity <= 40:
item_options.append((item().name + ' ' + str(adj_cost), i))
item_list.append(item)
i += 1
item_options.append(('Go back', i))
item_index = storyline.get_response(item_options)
if item_options[item_index][0] == 'Go back':
continue
buy_item = item_list[item_index]
buy_price = max(1, int(buy_item().value - (player.charisma * 2)))
if player.gold < buy_price:
print("You do not have enough gold.")
time.sleep(0.25)
else:
print("You have {} gold coins.".format(player.gold))
while True:
try:
num = int(input("How many {}s would you like to buy? ".format(buy_item().name)))
if num * buy_price > player.gold:
print("You do not have enough money for that purchase.")
elif num == 0:
break
else:
buy_price *= num
print("That will cost {} gold coins.".format(buy_price))
confirm = input("Do you still want to buy {} {}s? ".format(num, buy_item().name)).lower()
if confirm == 'y':
player.gold -= buy_price
player.modify_inventory(buy_item, num=num, sell=False)
print("{} {} will be added to your inventory.".format(num, buy_item().name))
else:
print("Sorry to hear that. Come back when you have something you wish to buy.")
break
except ValueError:
print("Please enter a valid number.")
input()
elif option_list[opt_index][0] == 'Sell':
print("We could always use more product. What do you have to sell?")
sell_list = []
i = 0
for key in player.inventory.keys():
if player.inventory[key][0]().rarity < 99:
sell_list.append((key, i))
i += 1
if len(sell_list) == 0:
print("You don't have anything to sell.")
break
sell_list.append(('Exit', i))
typ_index = storyline.get_response(sell_list)
if sell_list[typ_index][0] == 'Exit':
break
else:
sell_item = player.inventory[sell_list[typ_index][0]][0]
sell_amt = player.inventory[sell_list[typ_index][0]][1]
if sell_item().rarity >= 50:
print("Wow, that's something you don't see everyday!")
print("You have {} {} to sell.".format(sell_amt, sell_item().name))
while True:
try:
num = int(input("How many would you like to sell? "))
if num <= sell_amt and num != 0:
sale_price = int(0.5 * num * sell_item().value + (player.charisma * 2))
print("I'll give you {} gold coins for that.".format(sale_price))
confirm = input("Do you still want to sell? ").lower()
if confirm == 'y':
player.modify_inventory(player.inventory[sell_list[typ_index][0]][0], num=num,
sell=True)
player.gold += sale_price
print("You sold {} {} for {} gold.".format(num, sell_item().name, sale_price))
else:
print("I am sorry to hear that. Come back when you have something you wish to sell.")
break
elif num == 0:
break
else:
print("You cannot sell more than you have.")
except ValueError:
print("Please enter a valid number.")
input()
else:
print("Please enter a valid option.")
time.sleep(1)
os.system('cls' if os.name == 'nt' else 'clear')
def town(player, wmap):
os.system('cls' if os.name == 'nt' else 'clear')
locations = [blacksmith, armory, alchemist, jeweler, church, tavern]
town_options = [('Blacksmith', 0), ('Armory', 1), ('Alchemist', 2), ('Jeweler', 3), ('Church', 4), ('Tavern', 5),
('Dungeon', 6), ('Status', 7)]
while True:
print("Welcome to the town of Silvana!")
print("Where would you like to go?")
town_index = storyline.get_response(town_options)
if town_options[town_index][0] == 'Dungeon':
print("You descend into the dungeon.")
time.sleep(1)
player.location_x, player.location_y, player.location_z = (5, 10, 1)
break
elif town_options[town_index][0] == 'Status':
player.status()
elif town_options[town_index][0] == 'Church':
locations[town_index](player, wmap)
else:
locations[town_index](player)
os.system('cls' if os.name == 'nt' else 'clear')
| armory | identifier_name |
impl_encryption.rs | // Copyright 2019 TiKV Project Authors. Licensed under Apache-2.0.
use openssl::hash::{self, MessageDigest};
use tidb_query_codegen::rpn_fn;
use tidb_query_datatype::expr::{Error, EvalContext};
use tidb_query_common::Result;
use tidb_query_datatype::codec::data_type::*;
use tidb_query_shared_expr::rand::{gen_random_bytes, MAX_RAND_BYTES_LENGTH};
const SHA0: i64 = 0;
const SHA224: i64 = 224;
const SHA256: i64 = 256;
const SHA384: i64 = 384;
const SHA512: i64 = 512;
#[rpn_fn(nullable)]
#[inline]
pub fn md5(arg: Option<BytesRef>) -> Result<Option<Bytes>> {
match arg {
Some(arg) => hex_digest(MessageDigest::md5(), arg).map(Some),
None => Ok(None),
}
}
#[rpn_fn(nullable)]
#[inline]
pub fn sha1(arg: Option<BytesRef>) -> Result<Option<Bytes>> {
match arg {
Some(arg) => hex_digest(MessageDigest::sha1(), arg).map(Some),
None => Ok(None),
}
}
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn sha2(
ctx: &mut EvalContext,
input: Option<BytesRef>,
hash_length: Option<&Int>,
) -> Result<Option<Bytes>> {
match (input, hash_length) {
(Some(input), Some(hash_length)) => {
let sha2 = match *hash_length {
SHA0 | SHA256 => MessageDigest::sha256(),
SHA224 => MessageDigest::sha224(),
SHA384 => MessageDigest::sha384(),
SHA512 => MessageDigest::sha512(),
_ => {
ctx.warnings
.append_warning(Error::incorrect_parameters("sha2"));
return Ok(None);
}
};
hex_digest(sha2, input).map(Some)
}
_ => Ok(None),
}
}
// https://dev.mysql.com/doc/refman/5.7/en/password-hashing.html
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn password(ctx: &mut EvalContext, input: Option<BytesRef>) -> Result<Option<Bytes>> {
ctx.warnings.append_warning(Error::Other(box_err!(
"Warning: Deprecated syntax PASSWORD"
)));
match input {
Some(bytes) => {
if bytes.is_empty() {
Ok(Some(Vec::new()))
} else {
let hash1 = hex_digest(MessageDigest::sha1(), bytes)?;
let mut hash2 = hex_digest(MessageDigest::sha1(), hash1.as_slice())?;
hash2.insert(0, b'*');
Ok(Some(hash2))
}
}
None => Ok(None),
}
}
#[inline]
fn hex_digest(hashtype: MessageDigest, input: &[u8]) -> Result<Bytes> {
hash::hash(hashtype, input)
.map(|digest| hex::encode(digest).into_bytes())
.map_err(|e| box_err!("OpenSSL error: {:?}", e))
}
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn uncompressed_length(ctx: &mut EvalContext, arg: Option<BytesRef>) -> Result<Option<Int>> {
use byteorder::{ByteOrder, LittleEndian};
Ok(arg.as_ref().map(|s| {
if s.is_empty() {
0
} else if s.len() <= 4 {
ctx.warnings.append_warning(Error::zlib_data_corrupted());
0
} else {
Int::from(LittleEndian::read_u32(&s[0..4]))
}
}))
}
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn random_bytes(_ctx: &mut EvalContext, arg: Option<&Int>) -> Result<Option<Bytes>> {
match arg {
Some(arg) => {
if *arg < 1 || *arg > MAX_RAND_BYTES_LENGTH {
return Err(Error::overflow("length", "random_bytes").into());
}
Ok(Some(gen_random_bytes(*arg as usize)))
}
_ => Ok(None),
}
}
#[cfg(test)]
mod tests {
use tipb::ScalarFuncSig;
use super::*;
use crate::types::test_util::RpnFnScalarEvaluator;
fn test_unary_func_ok_none<'a, I: EvaluableRef<'a>, O: EvaluableRet>(sig: ScalarFuncSig)
where
O: PartialEq,
Option<I>: Into<ScalarValue>,
Option<O>: From<ScalarValue>,
{
assert_eq!(
None,
RpnFnScalarEvaluator::new()
.push_param(Option::<I>::None)
.evaluate::<O>(sig)
.unwrap()
);
}
#[test]
fn test_md5() {
let test_cases = vec![
(vec![], "d41d8cd98f00b204e9800998ecf8427e"),
(b"a".to_vec(), "0cc175b9c0f1b6a831c399e269772661"),
(b"ab".to_vec(), "187ef4436122d1cc2f40dc2b92f0eba0"),
(b"abc".to_vec(), "900150983cd24fb0d6963f7d28e17f72"),
(b"123".to_vec(), "202cb962ac59075b964b07152d234b70"),
(
"你好".as_bytes().to_vec(),
"7eca689f0d3389d9dea66ae112e5cfd7",
),
(
"分布式データベース".as_bytes().to_vec(),
"63c0354797bd261e2cbf8581147eeeda",
),
(vec![0xc0, 0x80], "b26555f33aedac7b2684438cc5d4d05e"),
(vec![0xED, 0xA0, 0x80], "546d3dc8de10fbf8b448f678a47901e4"),
];
for (arg, expect_output) in test_cases {
let expect_output = Some(Bytes::from(expect_output));
let output = RpnFnScalarEvaluator::new()
.push_param(arg)
.evaluate::<Bytes>(ScalarFuncSig::Md5)
.unwrap();
assert_eq!(output, expect_output);
}
test_unary_func_ok_none::<BytesRef, Bytes>(ScalarFuncSig::Md5);
}
#[test]
fn test_sha1() {
let test_cases = vec![
(vec![], "da39a3ee5e6b4b0d3255bfef95601890afd80709"),
(b"a".to_vec(), "86f7e437faa5a7fce15d1ddcb9eaeaea377667b8"),
(b"ab".to_vec(), "da23614e02469a0d7c7bd1bdab5c9c474b1904dc"),
(b"abc".to_vec(), "a9993e364706816aba3e25717850c26c9cd0d89d"),
(b"123".to_vec(), "40bd001563085fc35165329ea1ff5c5ecbdbbeef"),
(
"你好".as_bytes().to_vec(),
"440ee0853ad1e99f962b63e459ef992d7c211722",
),
(
"分布式データベース".as_bytes().to_vec(),
"82aa64080df2ca37550ddfc3419d75ac1df3e0d0",
),
(vec![0xc0, 0x80], "8bf4822782a21d7ac68ece130ac36987548003bd"),
(
vec![0xED, 0xA0, 0x80],
"10db70ec072d000c68dd95879f9b831e43a859fd",
),
];
for (arg, expect_output) in test_cases {
let expect_output = Some(Bytes::from(expect_output));
let output = RpnFnScalarEvaluator::new()
.push_param(arg)
.evaluate::<Bytes>(ScalarFuncSig::Sha1)
.unwrap();
assert_eq!(output, expect_output);
}
test_unary_func_ok_none::<BytesRef, Bytes>(ScalarFuncSig::Sha1);
}
#[test]
fn test_uncompressed_length() {
let cases = vec![
(Some(""), Some(0)),
(
Some("0B000000789CCB48CDC9C95728CF2FCA4901001A0B045D"),
Some(11),
),
(
Some("0C000000789CCB48CDC9C95728CF2F32303402001D8004202E"),
Some(12),
),
(Some("020000000000"), Some(2)),
(Some("0000000001"), Some(0)),
(
Some("02000000789CCB48CDC9C95728CF2FCA4901001A0B045D"),
Some(2),
),
(Some("010203"), Some(0)),
(Some("01020304"), Some(0)),
(None, None),
];
for (s, exp) in cases {
let s = s.map(|inner| hex::decode(inner.as_bytes().to_vec()).unwrap());
let output = RpnFnScalarEvaluator::new()
.push_param(s)
.evaluate(ScalarFuncSig::UncompressedLength)
.unwrap();
assert_eq!(output, exp);
}
}
#[test]
fn test_sha2() {
let cases = vec![
("pingcap", 0, "2871823be240f8ecd1d72f24c99eaa2e58af18b4b8ba99a4fc2823ba5c43930a"),
("pingcap", 224, "cd036dc9bec69e758401379c522454ea24a6327b48724b449b40c6b7"),
("pingcap", 256, "2871823be240f8ecd1d72f24c99eaa2e58af18b4b8ba99a4fc2823ba5c43930a"),
("pingcap", 384, "c50955b6b0c7b9919740d956849eedcb0f0f90bf8a34e8c1f4e071e3773f53bd6f8f16c04425ff728bed04de1b63db51"),
("pingcap", 512, "ea903c574370774c4844a83b7122105a106e04211673810e1baae7c2ae7aba2cf07465e02f6c413126111ef74a417232683ce7ba210052e63c15fc82204aad80"),
("13572468", 0, "1c91ab1c162fd0cae60a5bb9880f3e7d5a133a65b6057a644b26973d9c55dcfe"),
("13572468", 224, "8ad67735bbf49576219f364f4640d595357a440358d15bf6815a16e4"),
("13572468", 256, "1c91ab1c162fd0cae60a5bb9880f3e7d5a133a65b6057a644b26973d9c55dcfe"),
("13572468.123", 384, "3b4ee302435dc1e15251efd9f3982b1ca6fe4ac778d3260b7bbf3bea613849677eda830239420e448e4c6dc7c2649d89"),
("13572468.123", 512, "4820aa3f2760836557dc1f2d44a0ba7596333fdb60c8a1909481862f4ab0921c00abb23d57b7e67a970363cc3fcb78b25b6a0d45cdcac0e87aa0c96bc51f7f96"),
];
for (input_str, hash_length_i64, exp_str) in cases {
let exp = Some(Bytes::from(exp_str));
let got = RpnFnScalarEvaluator::new()
.push_param(Some(Bytes::from(input_str)))
.push_param(Some(Int::from(hash_length_i64)))
.evaluate::<Bytes>(ScalarFuncSig::Sha2)
.unwrap();
assert_eq!(got, exp, "sha2('{:?}', {:?})", input_str, hash_length_i64);
}
let null_cases = vec![
(ScalarValue::Bytes(None), ScalarValue::Int(Some(1))),
(
ScalarValue::Bytes(Some(b"13572468".to_vec())),
ScalarValue::Int(None),
),
(ScalarValue::Bytes(None), ScalarValue::Int(None)),
(
ScalarValue::Bytes(Some(b"pingcap".to_vec())),
ScalarValue::Int(Some(-1)),
),
(
ScalarValue::Bytes(Some(b"13572468".to_vec())),
ScalarValue::Int(Some(999)),
),
];
for (input_str, hash_length_i64) in null_cases {
assert!(RpnFnScalarEvaluator::new()
.push_param(input_str)
.push_param(hash_length_i64)
.evaluate::<Bytes>(ScalarFuncSig::Sha2)
.unwrap()
.is_none())
}
}
#[test]
fn test_random_bytes() {
let cases = vec![1, 32, 233, 1024];
for len in cases {
let got = RpnFnScalarEvaluator::new()
.push_param(Some(Int::from(len as i64)))
.evaluate::<Bytes>(ScalarFuncSig::RandomBytes)
.unwrap();
assert_eq!(got.unwrap().len(), len);
}
let overflow_tests = vec![
ScalarValue::Int(Some(-32)),
ScalarValue::Int(Some(1025)),
ScalarValue::Int(Some(0)),
];
for len in overflow_tests {
assert!(RpnFnScalarEvaluator::new()
.push_param(len)
.evaluate::<Bytes>(ScalarFuncSig::RandomBytes)
.is_err(),);
}
//test NULL case
assert!(RpnFnScalarEvaluator::new()
.push_param(ScalarValue::Int(None))
.evaluate::<Bytes>(ScalarFuncSig::RandomBytes)
.unwrap()
.is_none())
}
#[test]
fn test_password() {
let cases = vec![
("Ti | KV", "*cca644408381f962dba8dfb9889db1371ee74208"),
("Pingcap", "*f33bc75eac70ac317621fbbfa560d6251c43cf8a"),
("rust", "*090c2b08e0c1776910e777b917c2185be6554c2e"),
("database", "*02e86b4af5219d0ba6c974908aea62d42eb7da24"),
("raft", "*b23a77787ed44e62ef2570f03ce8982d119fb699"),
];
for (input, output) in cases {
let res = RpnFnScalarEvaluator::new()
.push_param(Some(Bytes::from(input)))
.evaluate::<Bytes>(ScalarFuncSig::Password)
.unwrap();
assert_eq!(res, Some(Bytes::from(output)))
}
// test for null
let res = RpnFnScalarEvaluator::new()
.push_param(ScalarValue::Bytes(None))
.evaluate::<Bytes>(ScalarFuncSig::Password)
.unwrap();
assert_eq!(None, res)
}
}
| identifier_body | |
impl_encryption.rs | // Copyright 2019 TiKV Project Authors. Licensed under Apache-2.0.
use openssl::hash::{self, MessageDigest};
use tidb_query_codegen::rpn_fn;
use tidb_query_datatype::expr::{Error, EvalContext};
use tidb_query_common::Result;
use tidb_query_datatype::codec::data_type::*;
use tidb_query_shared_expr::rand::{gen_random_bytes, MAX_RAND_BYTES_LENGTH};
const SHA0: i64 = 0;
const SHA224: i64 = 224;
const SHA256: i64 = 256;
const SHA384: i64 = 384;
const SHA512: i64 = 512;
#[rpn_fn(nullable)]
#[inline]
pub fn md5(arg: Option<BytesRef>) -> Result<Option<Bytes>> {
match arg {
Some(arg) => hex_digest(MessageDigest::md5(), arg).map(Some),
None => Ok(None),
}
}
#[rpn_fn(nullable)]
#[inline]
pub fn sha1(arg: Option<BytesRef>) -> Result<Option<Bytes>> {
match arg {
Some(arg) => hex_digest(MessageDigest::sha1(), arg).map(Some),
None => Ok(None),
}
}
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn sha2(
ctx: &mut EvalContext,
input: Option<BytesRef>,
hash_length: Option<&Int>,
) -> Result<Option<Bytes>> {
match (input, hash_length) {
(Some(input), Some(hash_length)) => {
let sha2 = match *hash_length {
SHA0 | SHA256 => MessageDigest::sha256(),
SHA224 => MessageDigest::sha224(),
SHA384 => MessageDigest::sha384(),
SHA512 => MessageDigest::sha512(),
_ => {
ctx.warnings
.append_warning(Error::incorrect_parameters("sha2"));
return Ok(None);
}
};
hex_digest(sha2, input).map(Some)
}
_ => Ok(None),
}
}
// https://dev.mysql.com/doc/refman/5.7/en/password-hashing.html
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn password(ctx: &mut EvalContext, input: Option<BytesRef>) -> Result<Option<Bytes>> {
ctx.warnings.append_warning(Error::Other(box_err!(
"Warning: Deprecated syntax PASSWORD"
)));
match input {
Some(bytes) => {
if bytes.is_empty() {
Ok(Some(Vec::new()))
} else {
let hash1 = hex_digest(MessageDigest::sha1(), bytes)?;
let mut hash2 = hex_digest(MessageDigest::sha1(), hash1.as_slice())?;
hash2.insert(0, b'*');
Ok(Some(hash2))
}
}
None => Ok(None),
}
}
#[inline]
fn hex_digest(hashtype: MessageDigest, input: &[u8]) -> Result<Bytes> {
hash::hash(hashtype, input)
.map(|digest| hex::encode(digest).into_bytes())
.map_err(|e| box_err!("OpenSSL error: {:?}", e))
}
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn uncompressed_length(ctx: &mut EvalContext, arg: Option<BytesRef>) -> Result<Option<Int>> {
use byteorder::{ByteOrder, LittleEndian};
Ok(arg.as_ref().map(|s| {
if s.is_empty() {
0
} else if s.len() <= 4 {
ctx.warnings.append_warning(Error::zlib_data_corrupted());
0
} else {
Int::from(LittleEndian::read_u32(&s[0..4]))
}
}))
}
#[rpn_fn(nullable, capture = [ctx])]
#[inline]
pub fn random_bytes(_ctx: &mut EvalContext, arg: Option<&Int>) -> Result<Option<Bytes>> {
match arg {
Some(arg) => {
if *arg < 1 || *arg > MAX_RAND_BYTES_LENGTH {
return Err(Error::overflow("length", "random_bytes").into());
}
Ok(Some(gen_random_bytes(*arg as usize)))
}
_ => Ok(None),
}
}
#[cfg(test)]
mod tests {
use tipb::ScalarFuncSig;
use super::*;
use crate::types::test_util::RpnFnScalarEvaluator;
fn test_unary_func_ok_none<'a, I: EvaluableRef<'a>, O: EvaluableRet>(sig: ScalarFuncSig)
where
O: PartialEq,
Option<I>: Into<ScalarValue>,
Option<O>: From<ScalarValue>,
{
assert_eq!(
None,
RpnFnScalarEvaluator::new()
.push_param(Option::<I>::None)
.evaluate::<O>(sig)
.unwrap()
);
}
#[test]
fn test_md5() {
let test_cases = vec![ | (b"abc".to_vec(), "900150983cd24fb0d6963f7d28e17f72"),
(b"123".to_vec(), "202cb962ac59075b964b07152d234b70"),
(
"你好".as_bytes().to_vec(),
"7eca689f0d3389d9dea66ae112e5cfd7",
),
(
"分布式データベース".as_bytes().to_vec(),
"63c0354797bd261e2cbf8581147eeeda",
),
(vec![0xc0, 0x80], "b26555f33aedac7b2684438cc5d4d05e"),
(vec![0xED, 0xA0, 0x80], "546d3dc8de10fbf8b448f678a47901e4"),
];
for (arg, expect_output) in test_cases {
let expect_output = Some(Bytes::from(expect_output));
let output = RpnFnScalarEvaluator::new()
.push_param(arg)
.evaluate::<Bytes>(ScalarFuncSig::Md5)
.unwrap();
assert_eq!(output, expect_output);
}
test_unary_func_ok_none::<BytesRef, Bytes>(ScalarFuncSig::Md5);
}
#[test]
fn test_sha1() {
let test_cases = vec![
(vec![], "da39a3ee5e6b4b0d3255bfef95601890afd80709"),
(b"a".to_vec(), "86f7e437faa5a7fce15d1ddcb9eaeaea377667b8"),
(b"ab".to_vec(), "da23614e02469a0d7c7bd1bdab5c9c474b1904dc"),
(b"abc".to_vec(), "a9993e364706816aba3e25717850c26c9cd0d89d"),
(b"123".to_vec(), "40bd001563085fc35165329ea1ff5c5ecbdbbeef"),
(
"你好".as_bytes().to_vec(),
"440ee0853ad1e99f962b63e459ef992d7c211722",
),
(
"分布式データベース".as_bytes().to_vec(),
"82aa64080df2ca37550ddfc3419d75ac1df3e0d0",
),
(vec![0xc0, 0x80], "8bf4822782a21d7ac68ece130ac36987548003bd"),
(
vec![0xED, 0xA0, 0x80],
"10db70ec072d000c68dd95879f9b831e43a859fd",
),
];
for (arg, expect_output) in test_cases {
let expect_output = Some(Bytes::from(expect_output));
let output = RpnFnScalarEvaluator::new()
.push_param(arg)
.evaluate::<Bytes>(ScalarFuncSig::Sha1)
.unwrap();
assert_eq!(output, expect_output);
}
test_unary_func_ok_none::<BytesRef, Bytes>(ScalarFuncSig::Sha1);
}
#[test]
fn test_uncompressed_length() {
let cases = vec![
(Some(""), Some(0)),
(
Some("0B000000789CCB48CDC9C95728CF2FCA4901001A0B045D"),
Some(11),
),
(
Some("0C000000789CCB48CDC9C95728CF2F32303402001D8004202E"),
Some(12),
),
(Some("020000000000"), Some(2)),
(Some("0000000001"), Some(0)),
(
Some("02000000789CCB48CDC9C95728CF2FCA4901001A0B045D"),
Some(2),
),
(Some("010203"), Some(0)),
(Some("01020304"), Some(0)),
(None, None),
];
for (s, exp) in cases {
let s = s.map(|inner| hex::decode(inner.as_bytes().to_vec()).unwrap());
let output = RpnFnScalarEvaluator::new()
.push_param(s)
.evaluate(ScalarFuncSig::UncompressedLength)
.unwrap();
assert_eq!(output, exp);
}
}
#[test]
fn test_sha2() {
let cases = vec![
("pingcap", 0, "2871823be240f8ecd1d72f24c99eaa2e58af18b4b8ba99a4fc2823ba5c43930a"),
("pingcap", 224, "cd036dc9bec69e758401379c522454ea24a6327b48724b449b40c6b7"),
("pingcap", 256, "2871823be240f8ecd1d72f24c99eaa2e58af18b4b8ba99a4fc2823ba5c43930a"),
("pingcap", 384, "c50955b6b0c7b9919740d956849eedcb0f0f90bf8a34e8c1f4e071e3773f53bd6f8f16c04425ff728bed04de1b63db51"),
("pingcap", 512, "ea903c574370774c4844a83b7122105a106e04211673810e1baae7c2ae7aba2cf07465e02f6c413126111ef74a417232683ce7ba210052e63c15fc82204aad80"),
("13572468", 0, "1c91ab1c162fd0cae60a5bb9880f3e7d5a133a65b6057a644b26973d9c55dcfe"),
("13572468", 224, "8ad67735bbf49576219f364f4640d595357a440358d15bf6815a16e4"),
("13572468", 256, "1c91ab1c162fd0cae60a5bb9880f3e7d5a133a65b6057a644b26973d9c55dcfe"),
("13572468.123", 384, "3b4ee302435dc1e15251efd9f3982b1ca6fe4ac778d3260b7bbf3bea613849677eda830239420e448e4c6dc7c2649d89"),
("13572468.123", 512, "4820aa3f2760836557dc1f2d44a0ba7596333fdb60c8a1909481862f4ab0921c00abb23d57b7e67a970363cc3fcb78b25b6a0d45cdcac0e87aa0c96bc51f7f96"),
];
for (input_str, hash_length_i64, exp_str) in cases {
let exp = Some(Bytes::from(exp_str));
let got = RpnFnScalarEvaluator::new()
.push_param(Some(Bytes::from(input_str)))
.push_param(Some(Int::from(hash_length_i64)))
.evaluate::<Bytes>(ScalarFuncSig::Sha2)
.unwrap();
assert_eq!(got, exp, "sha2('{:?}', {:?})", input_str, hash_length_i64);
}
let null_cases = vec![
(ScalarValue::Bytes(None), ScalarValue::Int(Some(1))),
(
ScalarValue::Bytes(Some(b"13572468".to_vec())),
ScalarValue::Int(None),
),
(ScalarValue::Bytes(None), ScalarValue::Int(None)),
(
ScalarValue::Bytes(Some(b"pingcap".to_vec())),
ScalarValue::Int(Some(-1)),
),
(
ScalarValue::Bytes(Some(b"13572468".to_vec())),
ScalarValue::Int(Some(999)),
),
];
for (input_str, hash_length_i64) in null_cases {
assert!(RpnFnScalarEvaluator::new()
.push_param(input_str)
.push_param(hash_length_i64)
.evaluate::<Bytes>(ScalarFuncSig::Sha2)
.unwrap()
.is_none())
}
}
#[test]
fn test_random_bytes() {
let cases = vec![1, 32, 233, 1024];
for len in cases {
let got = RpnFnScalarEvaluator::new()
.push_param(Some(Int::from(len as i64)))
.evaluate::<Bytes>(ScalarFuncSig::RandomBytes)
.unwrap();
assert_eq!(got.unwrap().len(), len);
}
let overflow_tests = vec![
ScalarValue::Int(Some(-32)),
ScalarValue::Int(Some(1025)),
ScalarValue::Int(Some(0)),
];
for len in overflow_tests {
assert!(RpnFnScalarEvaluator::new()
.push_param(len)
.evaluate::<Bytes>(ScalarFuncSig::RandomBytes)
.is_err(),);
}
//test NULL case
assert!(RpnFnScalarEvaluator::new()
.push_param(ScalarValue::Int(None))
.evaluate::<Bytes>(ScalarFuncSig::RandomBytes)
.unwrap()
.is_none())
}
#[test]
fn test_password() {
let cases = vec![
("TiKV", "*cca644408381f962dba8dfb9889db1371ee74208"),
("Pingcap", "*f33bc75eac70ac317621fbbfa560d6251c43cf8a"),
("rust", "*090c2b08e0c1776910e777b917c2185be6554c2e"),
("database", "*02e86b4af5219d0ba6c974908aea62d42eb7da24"),
("raft", "*b23a77787ed44e62ef2570f03ce8982d119fb699"),
];
for (input, output) in cases {
let res = RpnFnScalarEvaluator::new()
.push_param(Some(Bytes::from(input)))
.evaluate::<Bytes>(ScalarFuncSig::Password)
.unwrap();
assert_eq!(res, Some(Bytes::from(output)))
}
// test for null
let res = RpnFnScalarEvaluator::new()
.push_param(ScalarValue::Bytes(None))
.evaluate::<Bytes>(ScalarFuncSig::Password)
.unwrap();
assert_eq!(None, res)
}
} | (vec![], "d41d8cd98f00b204e9800998ecf8427e"),
(b"a".to_vec(), "0cc175b9c0f1b6a831c399e269772661"),
(b"ab".to_vec(), "187ef4436122d1cc2f40dc2b92f0eba0"), | random_line_split |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.