From 80ef2d0dc2438b83365437c610b7958e556d442f Mon Sep 17 00:00:00 2001
From: Danilo Ferreira de Lima <danilo.enoque.ferreira.de.lima@xfel.de>
Date: Fri, 12 May 2023 16:10:09 +0200
Subject: [PATCH] Save plots as CSV for later replotting.
---
pes_to_spec/test/offline_analysis.py | 20 +++++++++++++++++---
1 file changed, 17 insertions(+), 3 deletions(-)
diff --git a/pes_to_spec/test/offline_analysis.py b/pes_to_spec/test/offline_analysis.py
index 7ea0441..a9ba794 100755
--- a/pes_to_spec/test/offline_analysis.py
+++ b/pes_to_spec/test/offline_analysis.py
@@ -16,6 +16,8 @@ from itertools import product
import matplotlib
matplotlib.use('Agg')
+import pandas as pd
+from copy import deepcopy
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from mpl_toolkits.axes_grid1.inset_locator import InsetPosition
@@ -102,12 +104,24 @@ def plot_result(filename: str,
intensity: The XGM intensity in uJ.
"""
- fig = plt.figure(figsize=(12, 8))
- gs = GridSpec(1, 1)
- ax = fig.add_subplot(gs[0, 0])
unc_stat = spec_pred["unc"]
unc_pca = spec_pred["pca"]
unc = np.sqrt(unc_stat**2 + unc_pca**2)
+ df = pd.DataFrame(dict(energy=spec_raw_pe,
+ spec=spec_smooth,
+ prediction=spec_pred["expected"],
+ unc=unc,
+ beam_intensity=intensity*1e-3*np.ones_like(spec_raw_pe)
+ ))
+ df.to_csv(filename.replace('.png', '.csv'))
+ pes_data = deepcopy(pes)
+ pes_data['bin'] = np.arange(len(pes['channel_1_D']))
+ df = pd.DataFrame(pes_data)
+ df.to_csv(filename.replace('.png', '_pes.csv'))
+
+ fig = plt.figure(figsize=(12, 8))
+ gs = GridSpec(1, 1)
+ ax = fig.add_subplot(gs[0, 0])
ax.plot(spec_raw_pe, spec_smooth, c='b', lw=3, label="High-res. measurement (smoothened)")
ax.plot(spec_raw_pe, spec_pred["expected"], c='r', ls='--', lw=3, label="High-res. prediction")
#ax.fill_between(spec_raw_pe, spec_pred["expected"] - unc, spec_pred["expected"] + unc, facecolor='green', alpha=0.6, label="68% unc.")
--
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