def __init__(self):
self.val = Validator()
self.db = DatabaseMaker()
self.reader = FileReader()
self.py = PyGal()
self.converted_file = None
self.file_count = 1
def scenario_A(file_in):
print("Input file: {}".format(file_in))
global DEBUG
reader = FileReader(file_in)
problem = reader.read()
solver = Solver(problem)
print("Description:")
print(solver.description())
solution = solver.initial_solution()
# print(solver.initial_solution().print_free())
# print("-------")
# print(solver.initial_solution().print_solution())
# print("here")
# print("\n".join(str(i) for i in solver.initial_solution().slices))
# print("here2")
print("Initial solution score: {}".format(solution.score()))
if DEBUG:
solution.print_solution()
optimized_solution = solver.search(solution, time_limit=60)
print("Optimized solution score: {}".format(optimized_solution.score()))
# print("\n".join(str(i) for i in optimized_solution.slices))
if DEBUG:
optimized_solution.print_solution()
trace = solver.get_search_trace()
if trace is not None:
print("Trace:")
print("\n".join([str(x) for x in trace]))
def scenario_A(file_in, file_out=None):
print("Input file: {}".format(file_in))
reader = FileReader(file_in)
problem = reader.read()
solver = Pizza(problem)
print("Description:")
print(solver.description())
slices = solver.solve()
is_valid, result = problem.validate_solution(slices)
if is_valid:
print("Solution for problem {} is correct. Score is {}".format(
file_in, result))
solution = Solution(problem)
solution.load_slices(slices)
if DEBUG:
solution.print_solution()
if file_out:
writer = FileWriter(file_in + ".out")
writer.write(solution)
else:
print("Incorrect solution. Please check the error messages below")
for msg in result:
print(msg)
def main():
"""Main function for commandline call
"""
# end user version for user_input
# args = user_input(sys.argv[1:])
# add your own args = user_input() for testing and debugging so that you
# don't have to call the script with full command line input
args = user_input(['Input/Task1/', '-o', 'Output/Task2/'])
# read files
reader = FileReader(args.path)
input_df = reader.read()
# perform statistical analysis
stat_ana = analysis.Statistical_Analysis(args.output)
stat_ana.correlation(input_df['npop.t'])
stat_ana.eucl_distance(input_df['table.dat'])
# perfomr numerical analysis
num_ana = analysis.Numerical_Analysis(args.output)
# return new df with the desired columns
df_efield_relevant = num_ana.remove_low_variance(input_df['efield.t'])
# fft with freq of the df
df_efield_fft = num_ana.fft_with_freq_analysis(df_efield_relevant, "y")
# disabled plot to not have it get on my nerves
num_ana.plot_and_save(df_efield_fft,
"freq",
"intensitys",
"efield_fft_analysis",
xlabel="Freq",
show_graph=False)
df_autocorr = num_ana.autocorrelation(input_df["nstate_i.t"], "time")
num_ana.plot_and_save(df_autocorr,
"time",
["autocorr_abs", "autocorr_real", "autocorr_imag"],
"nstate_autocorr_analysis",
xlabel="time",
show_graph=False)
df_autocorr_fft = num_ana.fft_with_freq_analysis(df_autocorr,
"autocorr",
type="complex")
# adding abs**2 to the dataframe
df_autocorr_fft["intensitys_squared"] = np.abs(
df_autocorr_fft["intensitys"].values)**2
num_ana.plot_and_save(df_autocorr_fft,
"freq", ["intensitys", "intensitys_squared"],
"nstate_autocorr_fft_analysis",
xlabel="Freq",
show_graph=True,
crop_edge=3)
def scenario_A(file_in, file_out):
global DEBUG
reader = FileReader(file_in)
problem = reader.read()
init_solver = InitSolverSilly()
solution = init_solver.run(problem)
print("Initial solution score: {}".format(solution.score()))
if DEBUG:
solution.print_solution()
writer = FileWriter(file_out)
writer.write(solution)
def scenario_C(file_in, file_out, file_par=None):
global DEBUG
reader = FileReader(file_in)
problem = reader.read()
init_solver = ParallelInitSolver(InitSolverSillyParameterized,
file_output=file_out)
solution = init_solver.run(problem, file_par)
print("Initial solution score: {}".format(solution.score()))
if DEBUG:
solution.print_solution()
writer = FileWriter(file_out)
writer.write(solution)
def scenario_A(file_in):
print("Input file: {}".format(file_in))
global DEBUG
reader = FileReader(file_in)
problem = reader.read()
solver = Solver(problem)
print("Description:")
print(solver.description())
solution = solver.initial_solution()
print("Initial solution score: {}".format(solution.score()))
if DEBUG:
solution.print_solution()
optimized_solution = solver.search(solution, time_limit=60)
print("Optimized solution score: {}".format(optimized_solution.score()))
if DEBUG:
optimized_solution.print_solution()
trace = solver.get_search_trace()
def scenario_B(file_in, file_out):
global DEBUG
reader = FileReader(file_in)
problem = reader.read()
init_solver = InitSolverSilly()
solution = init_solver.run(problem)
print("Initial solution score: {}".format(solution.score()))
if DEBUG:
solution.print_solution()
optimizer = Tabu(problem,
solution,
Neighbourhood_ChangeFormats,
debug=True)
optimized_solution = optimizer.run(time_limit=100)
print("optimized solution score: {}".format(optimized_solution.score()))
if DEBUG:
optimized_solution.print_solution()
writer = FileWriter(file_out)
writer.write(optimized_solution)
def plot_specific_heat_ratio_isobaric(filename, plot_cp=True):
data = FileReader(filename)
# Plot 1
fig, ax1 = plt.subplots()
if plot_cp:
color = 'b'
else:
color = 'k'
ax1.plot(data.temperature, data.gamma, color, label='Specific Heat Ratio')
ax1.set_xlabel(data.titles.temperature)
ax1.set_ylabel(data.titles.gamma)
if plot_cp:
# Plot 2
ax2 = ax1.twinx()
ax2.plot(data.temperature, data.cp, 'r', label='Cp')
ax2.set_ylabel(data.titles.cp)
fig.legend(loc="upper center", bbox_to_anchor=(0.5, 0.9))
plt.title('Specific heat ratio of water (g) at 6 bar')
fig.tight_layout()
plt.show()
def scenario_D(file_in, file_out, file_par=None):
global DEBUG
reader = FileReader(file_in)
problem = reader.read()
init_solver = ParallelInitSolver(InitSolverSillyParameterized,
file_output=file_out)
solution = init_solver.run(problem, file_par)
print("Initial solution score: {}".format(solution.score()))
if DEBUG:
solution.print_solution()
optimizer = ParallelTabu(problem,
solution,
Neighbourhood_ChangeFormats,
debug=True)
optimized_solution = optimizer.run(time_limit=1000)
print("optimized solution score: {}".format(optimized_solution.score()))
if DEBUG:
optimized_solution.print_solution()
writer = FileWriter(file_out)
writer.write(solution)
def __init__(self, filename):
self.filename = FileReader(filename)
def __init__(self):
self.data = FileReader().readFile("district.csv")
def __init__(self):
self.data = FileReader().readFile("trans.csv")
def __init__(self):
self.data = FileReader().readFile("client.csv")
def __init__(self):
self.data = FileReader().readFile("loan.csv")
import math
import time
from flask import Flask, request, jsonify
from flask_cors import CORS
from reader import FileReader, Bolder
app = Flask(__name__)
CORS(app)
start_reading = time.time()
reader = FileReader('./data/IR-F19-Project01-Input.xlsx', True,
'./matches.json', './exceptions.txt')
# reader = FileReader('./data/IR-F19-Project01-Input-2k.xlsx', True, './matches.json', './exceptions.txt')
# reader = FileReader('./data/IR-F19-Project02-14k.csv', False, './matches.json', './exceptions.txt')
end_reading = time.time()
print("Reading Files:", end_reading - start_reading, "secs")
bolder = Bolder()
@app.route('/')
def query():
q = request.args.get('q')
start_searching = time.time()
print("Query:", q)
docs, query_tokens = reader.search(q, 50)
docs, query_tokens = list(docs), list(query_tokens)
print("Results:", len(docs))
items = int(request.args.get('items', 10))
print("Items:", items)
pages = math.ceil(len(docs) / items)
print("Pages:", pages)
page = int(request.args.get('page', 0))
from reader import FileReader, UrlReader
from sma import SMA, SMAPlt
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Лабораторная №4')
parser.add_argument('--paths=',
help='Список адресов через запятую',
required=True,
dest="paths")
parser.add_argument('--frame=',
help='Размер окна',
required=True,
dest="frame")
args = parser.parse_args()
paths = [item for item in args.paths.split(',')]
if len(paths) < 25:
print('Кол-во данных меньше 25')
exit()
sma = SMA()
print('Загрузка данных...')
for path in paths:
reader = FileReader() if FileReader.path_is_file(path) else UrlReader()
sma.read_data(reader, path)
sma.frame = args.frame
SMAPlt.draw(*sma.calculate_sma())
def __init__(self):
self.data = FileReader().readFile("account.csv")
