def test_load_save_fitresult(self, tmp_path):
#todo missing read batch result test
fpath = Path(tmp_path) / 'fit_result_single.csv'
self.fit_result.to_file(fpath)
df = csv_to_dataframe(fpath)
assert df.attrs['metadata'] == self.fit_result.metadata
fit_result_dir = Path(tmp_path) / 'fit_result'
save_fitresult(fit_result_dir, self.fit_result, log_lines=['test123'])
log_lines = Path(fit_result_dir / 'log.txt').read_text().split('\n')
assert log_lines[-1] == 'test123'
fit_result_loaded = load_fitresult(fit_result_dir)
assert isinstance(fit_result_loaded.losses, pd.DataFrame)
assert isinstance(fit_result_loaded.hdxm_set, HDXMeasurementSet)
timepoints = np.linspace(0, 30*60, num=100)
d_calc = fit_result_loaded(timepoints)
assert d_calc.shape == (1, self.hdxm.Np, len(timepoints))
losses = csv_to_dataframe(fit_result_dir / 'losses.csv')
fr_load_with_hdxm_and_losses = load_fitresult(fit_result_dir)
assert len(fr_load_with_hdxm_and_losses.losses) == 100
assert fr_load_with_hdxm_and_losses.metadata['total_loss'] == losses.iloc[-1].sum()
"""Generate a pdf output with all peptide fits. Requires pdflatex"""
from pyhdx.output import FitReport
from pyhdx.fileIO import load_fitresult
from pathlib import Path
from concurrent import futures
import proplot as pplt
current_dir = Path().cwd()
fit_result = load_fitresult(current_dir / 'output' /
'SecB_tetramer_dimer_batch')
tmp_dir = Path(__file__).parent / 'temp'
tmp_dir.mkdir(exist_ok=True)
if __name__ == '__main__':
report = FitReport(fit_result, temp_dir=tmp_dir)
report.add_standard_figure('peptide_coverage_figure')
report.add_standard_figure('residue_time_scatter_figure')
report.add_standard_figure('residue_scatter_figure')
report.add_standard_figure('dG_scatter_figure', ncols=1, aspect=3)
report.add_standard_figure('ddG_scatter_figure', ncols=1, reference=0)
report.add_standard_figure('linear_bars',
cmap='viridis',
norm=pplt.Norm('linear', 15e3,
35e3)) #todo name from kwargs
report.add_standard_figure('rainbowclouds')
report.add_peptide_uptake_curves()
executor = futures.ProcessPoolExecutor(max_workers=10)
"""Load a fit result from a a directory directly ino the web interface"""
from pyhdx.fileIO import load_fitresult
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
from pyhdx.web.apps import main_app
from pyhdx.web.base import STATIC_DIR
import sys
import panel as pn
current_dir = Path(__file__).parent
fit_result = load_fitresult(current_dir.parent / 'tests' / 'test_data' /
'output' / 'ecsecb_tetramer_dimer')
ctrl, tmpl = main_app()
src = ctrl.sources['main']
for hdxm in fit_result.hdxm_set:
src.add(hdxm, hdxm.name)
src.add(fit_result, 'fitresult_1')
pn.serve(tmpl, show=True, static_dirs={'pyhdx': STATIC_DIR})
"""
Automagically plot all available figures from a fit result
"""
from pyhdx.fileIO import load_fitresult
from pyhdx.plot import FitResultPlot
from pathlib import Path
#%%
# __file__ = Path().cwd() / 'templates'/ 'script.py' # Uncomment for PyCharm scientific mode
cwd = Path(__file__).parent
output_dir = cwd / 'output' / 'figures'
output_dir.mkdir(exist_ok=True)
fit_result = load_fitresult(cwd / 'output' / 'SecB_tetramer_dimer_batch')
fr_plot = FitResultPlot(fit_result, output_path=output_dir)
kwargs = {
'residue_scatter': {
'cmap': 'BuGn'
}, # change default colormap
'ddG_scatter': {
'reference': 1
} # Set reference for ΔΔG to the second (index 1 state) (+ APO state (tetramer))
}
fr_plot.plot_all(**kwargs)