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#!/usr/bin/env python3
#
# Copyright 2015-2016 Carnegie Mellon University
#
# 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.
import argparse
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
plt.style.use('bmh')
import pandas as pd
import os
import sys
scriptDir = os.path.dirname(os.path.realpath(__file__))
plotDir = os.path.join(scriptDir, 'plots')
# workDir = os.path.join(scriptDir, 'work')
def plot(workDirs):
trainDfs = []
testDfs = []
for d in workDirs:
trainF = os.path.join(d, 'train.log')
testF = os.path.join(d, 'test.log')
trainDfs.append(pd.read_csv(trainF, sep='\t'))
testDfs.append(pd.read_csv(testF, sep='\t'))
if len(trainDfs[-1]) != len(testDfs[-1]):
print("Error: Train/test dataframe shapes "
"for '{}' don't match: {}, {}".format(
d, trainDfs[-1].shape, testDfs[-1].shape))
sys.exit(-1)
trainDf = pd.concat(trainDfs, ignore_index=True)
testDf = pd.concat(testDfs, ignore_index=True)
# print("train, test:")
# print("\n".join(["{:0.2e}, {:0.2e}".format(x, y) for (x, y) in
# zip(trainDf['avg triplet loss (train set)'].values[-5:],
# testDf['avg triplet loss (test set)'].values[-5:])]))
fig, ax = plt.subplots(1, 1)
trainDf.index += 1
trainDf['avg triplet loss (train set)'].plot(ax=ax)
plt.xlabel("Epoch")
plt.ylabel("Average Triplet Loss, Training")
plt.ylim(ymin=0)
# plt.xlim(xmin=1)
plt.grid(b=True, which='major', color='k', linestyle='-')
plt.grid(b=True, which='minor', color='k', linestyle='-', alpha=0.2)
plt.minorticks_on()
# ax.set_yscale('log')
d = os.path.join(plotDir, "train-loss.pdf")
fig.savefig(d)
print("Created {}".format(d))
fig, ax = plt.subplots(1, 1)
testDf.index += 1
testDf['lfwAcc'].plot(ax=ax)
plt.xlabel("Epoch")
plt.ylabel("LFW Accuracy")
plt.ylim(ymin=0, ymax=1)
plt.grid(b=True, which='major', color='k', linestyle='-')
plt.grid(b=True, which='minor', color='k', linestyle='-', alpha=0.2)
plt.minorticks_on()
# plt.xlim(xmin=1)
# ax.set_yscale('log')
d = os.path.join(plotDir, "lfw-accuracy.pdf")
fig.savefig(d)
print("Created {}".format(d))
if __name__ == '__main__':
os.makedirs(plotDir, exist_ok=True)
parser = argparse.ArgumentParser()
parser.add_argument('workDirs', type=str, nargs='+')
args = parser.parse_args()
plot(args.workDirs)
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