From 853636f4677b9cc56657117d195844c832f4af3a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lo=C3=AFc=20Le=20Guyader?= <loic.le.guyader@xfel.eu>
Date: Tue, 15 Feb 2022 17:17:50 +0100
Subject: [PATCH] Adds spot center calculation
---
doc/source/Interactive TZPG calculator.ipynb | 5600 +++++++++++++++++-
src/TZPGcalc/TZPGcalc.py | 32 +-
2 files changed, 5626 insertions(+), 6 deletions(-)
diff --git a/doc/source/Interactive TZPG calculator.ipynb b/doc/source/Interactive TZPG calculator.ipynb
index 5a166b4..7a6e8c8 100644
--- a/doc/source/Interactive TZPG calculator.ipynb
+++ b/doc/source/Interactive TZPG calculator.ipynb
@@ -53,9 +53,9 @@
"\n",
"The detector can be placed at various distance from the nominal interaction point and displaced laterally.\n",
"\n",
- "## Spot size\n",
+ "## Spot sizes and spot centers\n",
"\n",
- "Two table give the spot size at the sample position for the low and high energy bound of the calculation, for zone plate zero order **F0** which is unfocused by the zone plate but still focused by the KBS and the zone plate first order **F1**. In each case, the positive first **G1**, zero **G0** and negative first **G-1** grating order are also given."
+ "Two table give the spot size at the sample position for the low and high energy bound of the calculation, for zone plate zero order **F0** which is unfocused by the zone plate but still focused by the KBS and the zone plate first order **F1**. In each case, the positive first **G1**, zero **G0** and negative first **G-1** grating order are also given. In addition, two additional tables provides the beam centers such that the distances between beam can be quickly calculated."
]
},
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@@ -50716,6 +56095,19 @@
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@@ -50901,6 +56315,12 @@
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@@ -50922,6 +56342,16 @@
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}
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+ "style": "IPY_MODEL_e11e7bd2829d435085a1c89f0eebc967",
+ "value": "Low energy"
+ }
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@@ -51034,6 +56464,20 @@
"model_name": "LayoutModel",
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+ "f7a036d48ab841bebc59420f254ede8b": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "AccordionModel",
+ "state": {
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+ "0": "Spot sizes and centers"
+ },
+ "children": [
+ "IPY_MODEL_991dfeccc90f41678819d30659ed0f60"
+ ],
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@@ -51268,6 +56712,12 @@
"model_name": "LayoutModel",
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"f8eb35e8995a44069ccf1ac5516965f6": {
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"model_module_version": "1.5.0",
@@ -51455,6 +56905,16 @@
"model_name": "LayoutModel",
"state": {}
},
+ "f98fd0c409f14aff858f241ce0ce9ea6": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "ButtonModel",
+ "state": {
+ "description": "Update",
+ "layout": "IPY_MODEL_8a537d4dbd7c494ebab2214df2599c66",
+ "style": "IPY_MODEL_73533f79c774463d86178b8505f27198"
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"f99a4e28327d459698f5b3178865a17b": {
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"model_module_version": "1.2.0",
@@ -51481,6 +56941,12 @@
"model_name": "LayoutModel",
"state": {}
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+ "model_module": "@jupyter-widgets/base",
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+ "model_name": "LayoutModel",
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"f9c79e0b4c27466498abd941f9289bde": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
@@ -51541,6 +57007,12 @@
"layout": "IPY_MODEL_1642786509284923a561d8a7370bd41e"
}
},
+ "fa03024c71ca46b9b7f6f7a4bb7e7554": {
+ "model_module": "@jupyter-widgets/base",
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"fa138215173b4521b5351478382700b4": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
@@ -51706,6 +57178,12 @@
"model_name": "LayoutModel",
"state": {}
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+ "fab7bff050a1409a87a8d28ce0ad684e": {
+ "model_module": "@jupyter-widgets/base",
+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
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"fac94f8e6b734f0bb8e447d19a9c198d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
@@ -51786,6 +57264,20 @@
"value": "Sample Offset (mm), "
}
},
+ "fb50b22d60654949a06964ddc924d26b": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "AccordionModel",
+ "state": {
+ "_titles": {
+ "0": "Sample"
+ },
+ "children": [
+ "IPY_MODEL_6b777009915f4f97b25baad78d15bec3"
+ ],
+ "layout": "IPY_MODEL_0628f064308943cd9bebf492664051c9"
+ }
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"fb5521a8d977436dbf0e1b5332c1f8bf": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -51863,6 +57355,12 @@
"layout": "IPY_MODEL_d10140f801634658bec84de787485a43"
}
},
+ "fb81b8016b6f4e62acd9652d0e2790dd": {
+ "model_module": "@jupyter-widgets/base",
+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
+ "state": {}
+ },
"fb8f9b2cb89d4452b9ff58bef715f2e3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -51909,6 +57407,20 @@
"description_width": "initial"
}
},
+ "fbba4b92131e4e3081126258f0c201f3": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "BoundedFloatTextModel",
+ "state": {
+ "description": "Y:",
+ "layout": "IPY_MODEL_e8dc0688190043b7befb3908e4f6881f",
+ "max": 50,
+ "min": -50,
+ "step": 0.5,
+ "style": "IPY_MODEL_10afd305a155430f9e36c8e030db259a",
+ "value": -2
+ }
+ },
"fbbb036dc1944c2e9684617d704be335": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52064,6 +57576,12 @@
"model_name": "LayoutModel",
"state": {}
},
+ "fcb6c1b40c1b48659be69ac6f2b64cb2": {
+ "model_module": "@jupyter-widgets/base",
+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
+ "state": {}
+ },
"fcbf7c2e8a794e0da0e5921708297f9f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52092,6 +57610,12 @@
"model_name": "LayoutModel",
"state": {}
},
+ "fce8d030813c4da3ad5ad73dfab8e683": {
+ "model_module": "@jupyter-widgets/base",
+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
+ "state": {}
+ },
"fcf95f63046b43559aa22979352c5360": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52226,6 +57750,14 @@
"model_name": "LayoutModel",
"state": {}
},
+ "fd9c1bd58b384bdeb3a87af278c3f653": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "DescriptionStyleModel",
+ "state": {
+ "description_width": ""
+ }
+ },
"fd9dc13d7ce74a13b5817d1d0ae82eef": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
@@ -52291,6 +57823,14 @@
"model_name": "LayoutModel",
"state": {}
},
+ "fe0337e1454640df8308be4427cb934d": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "DescriptionStyleModel",
+ "state": {
+ "description_width": ""
+ }
+ },
"fe29da589ba040df97e805143e410098": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52303,6 +57843,16 @@
"value": 4.6
}
},
+ "fe2cd8076b0a4abd9079e39fc9f64045": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "LabelModel",
+ "state": {
+ "layout": "IPY_MODEL_56ec24e77e8148eeb159d1e3c27429c7",
+ "style": "IPY_MODEL_fe0337e1454640df8308be4427cb934d",
+ "value": "Grating Pitch:379 nm"
+ }
+ },
"fe37ef878dc34dbda374ed50b58976ca": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52366,6 +57916,20 @@
"model_name": "LayoutModel",
"state": {}
},
+ "fe8a27bb0e4042cfbcc66e4e6111f978": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "BoundedFloatTextModel",
+ "state": {
+ "description": "Z:",
+ "layout": "IPY_MODEL_f0db49e62d5d46c8b8cca89827c1d74d",
+ "max": 5800,
+ "min": 1000,
+ "step": 1,
+ "style": "IPY_MODEL_78b873227a644689959b6bbdb24b4486",
+ "value": 2000
+ }
+ },
"fe9b30da901a4bb2b6aeea7c278070ff": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
@@ -52495,6 +58059,14 @@
"layout": "IPY_MODEL_709b51df5ea34a629b82af6f76799400"
}
},
+ "ff2ef4d3f18f4a91932c880cec749373": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "DescriptionStyleModel",
+ "state": {
+ "description_width": ""
+ }
+ },
"ff3dcdac3a884084b957cfc92f200413": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52503,6 +58075,20 @@
"description_width": ""
}
},
+ "ff4253add546479eb2de8effe5879e34": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "DescriptionStyleModel",
+ "state": {
+ "description_width": "initial"
+ }
+ },
+ "ff4c5ffe73d846679acf881e58835c8d": {
+ "model_module": "@jupyter-widgets/base",
+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
+ "state": {}
+ },
"ff4c6090397e4711844908bcc1240fac": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
@@ -52718,6 +58304,12 @@
"layout": "IPY_MODEL_b2c6250059694c1dbe592cb914396593"
}
},
+ "ffefe4efa7fb4e0fa77fe6d8c0b9db07": {
+ "model_module": "@jupyter-widgets/base",
+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
+ "state": {}
+ },
"fff53d924f7148d59b7ef89124008453": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
diff --git a/src/TZPGcalc/TZPGcalc.py b/src/TZPGcalc/TZPGcalc.py
index 4a21c16..59b2978 100644
--- a/src/TZPGcalc/TZPGcalc.py
+++ b/src/TZPGcalc/TZPGcalc.py
@@ -113,6 +113,13 @@ class TZPGcalc():
for k in ['L', 'H']:
self.SpotSizes[d][k] = np.zeros((6, 2))
+ # spot center of all beams
+ self.SpotCenters = {}
+ for d in ['det', 'sam']:
+ self.SpotCenters[d] = {}
+ for k in ['L', 'H']:
+ self.SpotCenters[d][k] = np.zeros((6, 2))
+
self.UpdateFig()
display(self.control)
@@ -367,6 +374,8 @@ class TZPGcalc():
vs = corners[:, k]
self.SpotSizes[img['type']][conf['Energy']][z, k] = (
1e3*(np.max(vs) - np.min(vs)))
+ self.SpotCenters[img['type']][conf['Energy']][z, k] = (
+ 1e3*0.5*(np.max(vs) + np.min(vs)))
# 3 beams configuration
b = self.widgets['3beams'].value
@@ -554,6 +563,12 @@ class TZPGcalc():
columns=['H (um)', 'V (um)'])
self.widgets[f'SpotSize{v}'].value = df.to_html(
float_format='{:.2f}'.format)
+ df = pd.DataFrame(self.SpotCenters['sam'][v],
+ index=['F0G-1', 'F0G0', 'F0G1',
+ 'F1G-1', 'F1G0', 'F1G1'],
+ columns=['H (um)', 'V (um)'])
+ self.widgets[f'SpotCenter{v}'].value = df.to_html(
+ float_format='{:.2f}'.format)
# update the detector
detXoff = self.widgets['detX'].value*1e-3 # [m]
@@ -589,6 +604,19 @@ class TZPGcalc():
widgets.Label(value='High energy'),
self.widgets['SpotSizeH']])
])
+ # Spot centers
+ self.widgets['SpotCenterL'] = widgets.HTML()
+ self.widgets['SpotCenterH'] = widgets.HTML()
+ SpotCenter = HBox([VBox([widgets.Label(value='Low energy'),
+ self.widgets['SpotCenterL']]),
+ VBox([
+ widgets.Label(value='High energy'),
+ self.widgets['SpotCenterH']])
+ ])
+ SpotSizeAndCenter = HBox([
+ VBox([widgets.Label(value='Spot Size'), SpotSize]),
+ VBox([widgets.Label(value='Spot center'), SpotCenter])
+ ])
# Source
self.Reset = widgets.Button(
@@ -959,8 +987,8 @@ class TZPGcalc():
tab3.set_title(0, 'Detector')
tab3.selected_index = 0
- tab4 = widgets.Accordion([SpotSize])
- tab4.set_title(0, 'Spot sizes')
+ tab4 = widgets.Accordion([SpotSizeAndCenter])
+ tab4.set_title(0, 'Spot sizes and centers')
tab4.selected_index = 0
self.control = VBox([self.Update, tab0, tab1, tab2, tab3, tab4])
--
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