Save and load results as HDF5 files¶

[1]:

import pypesto
import numpy as np
import scipy as sp
import pypesto.optimize as optimize
import matplotlib.pyplot as plt
import pypesto.store as store
import tempfile

%matplotlib inline

This notebook we will demonstrate, how to save and (re-)load optimization results and traces to a .hdf5 file. The use case of this notebook is to generate visulaizations from reloaded optimization results and traces.

Define the objective and problem¶

[2]:

objective = pypesto.Objective(fun=sp.optimize.rosen,
                              grad=sp.optimize.rosen_der,
                              hess=sp.optimize.rosen_hess)

dim_full = 20
lb = -5 * np.ones((dim_full, 1))
ub = 5 * np.ones((dim_full, 1))

problem = pypesto.Problem(objective=objective, lb=lb, ub=ub)

Define history options and run optimization¶

[21]:

# create optimizers
optimizer = optimize.ScipyOptimizer()

# set number of starts
n_starts = 10

# save optimizer trace (to temporary file fn)
fn = tempfile.mktemp(".hdf5")
history_options = pypesto.HistoryOptions(trace_record=True, storage_file=fn)

# Run optimizaitons
result = optimize.minimize(
    problem=problem, optimizer=optimizer,
    n_starts=n_starts, history_options=history_options)

Plot result¶

We now want to plot the results (before saving).

[22]:

import pypesto.visualize

# plot waterfalls
pypesto.visualize.waterfall(result, size=(15,6))

[22]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fa5266cf880>

Plot trace¶

[23]:

pypesto.visualize.optimizer_history(result,
                                    legends=['L-BFGS-B'])

[23]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fa5263af430>

../_images/example_hdf5_storage_10_1.png

Save optimization result as HDF5 file¶

[24]:

# name of the (in this case temporary) file
# fn = tempfile.mktemp(".hdf5")

# Write result
hdf5_writer = store.OptimizationResultHDF5Writer(fn)
hdf5_writer.write(result, overwrite=True)

# Write problem
hdf5_writer = store.ProblemHDF5Writer(fn)
hdf5_writer.write(problem)

Reload results¶

[25]:

# Read result and problem
hdf5_reader = store.OptimizationResultHDF5Reader(fn)
result2 = hdf5_reader.read()

Plot (reloaded) results¶

[26]:

# plot waterfalls
pypesto.visualize.waterfall(result2, size=(15,6))

[26]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fa5262e9ca0>

../_images/example_hdf5_storage_16_1.png

[27]:

pypesto.visualize.parameters(result2,
                            balance_alpha=False)

[27]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fa5262a1280>

../_images/example_hdf5_storage_17_1.png

Plot (reloaded) traces¶

[30]:

pypesto.visualize.optimizer_history(result2,
                                    legends=['L-BFGS-B'])

[30]:

<matplotlib.axes._subplots.AxesSubplot at 0x7fa5260d1a00>

../_images/example_hdf5_storage_19_1.png

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