added some draft plots
This commit is contained in:
@@ -1,5 +1,5 @@
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{
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"Number_of_cycles": 5,
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"Number_of_cycles": 2,
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"Amplitude_mm": 10,
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"Time_in_beam_s": 5,
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"Time_out_of_beam_s": 10
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@@ -1,4 +1,4 @@
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{"std_test_mov": [10, -10],
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"std_test_wait": [1],
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{"std_test_mov": [1, -1],
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"std_test_wait": [1, 2],
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"backlsh_meas_mov": [10, -10, -10, 10],
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"backlash_meas_wait": [1]}
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@@ -31,7 +31,7 @@ import ad
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import myutility as myu
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workdir = \
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os.path.expanduser(rf'C:\Users\berti_r\Python_Projects\StagePerformaceDocu\data{get_datestr()}_alignment_tests')
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os.path.expanduser(rf'C:\Users\berti_r\Python_Projects\StagePerformaceDocu\data\data{get_datestr()}_alignment_tests')
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if not os.path.exists(workdir):
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os.makedirs(workdir)
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@@ -74,15 +74,17 @@ def run_repeatability_series(
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#--------------------------------------load coordinates from file-----------------------
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x_coordinates_json = myu.load_object(measurement_mov_path)
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x_coordinates = x_coordinates_json.get('std_test_mov')
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wait_x_json = myu.load_object(measurement_mov_path)
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wait_x = wait_x_json.get('std_test_wait')
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print(wait_x)
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for i in range(ntries):
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#---------------------------------------------move------------------------------------------
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#add multithreading for simultanious movement of y and x axis
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for mov in x_coordinates:
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for mov,wait in x_coordinates,wait_x:
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axis1.moveRelativeAndWait(mov)
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sleep(0.1)
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sleep(1)
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sleep(wait)
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start_pos_rbv = 4 #????
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meas_pos_rbv = 5 #????
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#---------------------------------------------capture------------------------------------------
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@@ -188,10 +190,11 @@ def analyze_repeatability(input_file, pixel_size, units='um'):
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'Y-neg', p2v_y_neg, rms_y_neg, sigma_y_neg, 3*sigma_y_neg))
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print(result_str)
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"""
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result_file = os.path.splitext(input_file)[0] + "_results.dat"
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with open(result_file, 'w') as fh:
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fh.write(result_str)
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print(f"Results saved in: {result_file:s}")
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print(f"Results saved in: {result_file:s}")"""
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def plot_repeatability(
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ax, index, com, mean, p2v, rms, pos_mask, neg_mask):
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@@ -1,4 +1,8 @@
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import json
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import glob
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from datetime import datetime
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import os
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import numpy as np
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# Load config from JSON file
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def load_object(path):
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with open(path, 'r') as f:
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@@ -7,4 +11,30 @@ def load_object(path):
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# Save updated config to JSON file
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def save_config(path, updated_config):
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with open(path, 'w') as f:
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json.dump(updated_config, f, indent=4)
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json.dump(updated_config, f, indent=4)
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def find_newest_dat_file(folder):
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dat_files = glob.glob(os.path.join(folder, '*.dat'))
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if not dat_files:
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raise FileNotFoundError("No .dat files found in the specified directory.")
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return max(dat_files, key=os.path.getmtime)
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def load_data(filepath):
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times = []
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temps = [[] for _ in range(5)]
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with open(filepath, 'r') as file:
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for line in file:
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parts = line.strip().split()
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if len(parts) == 6:
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try:
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*temp_values, timestamp = map(float, parts)
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dt = datetime.fromtimestamp(timestamp)
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times.append(dt)
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for i in range(5):
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temps[i].append(temp_values[i])
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except ValueError:
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continue # skip lines with invalid data
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return np.array(times), [np.array(t) for t in temps]
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@@ -0,0 +1,2 @@
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0 4.000000 5.000000 37.588 32.706 1752579103.475
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1 4.000000 5.000000 26.667 34.583 1752579113.614
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@@ -0,0 +1,5 @@
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3 4.000000 5.000000 26.045 8.455 1752579197.156
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4 4.000000 5.000000 39.571 21.000 1752579207.221
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99
data/Temp/20250715_154024.dat
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data/Temp/20250715_154024.dat
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@@ -0,0 +1,99 @@
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BIN
data/Temp/20250715_154024.pdf
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data/Temp/20250715_154024.pdf
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@@ -0,0 +1,2 @@
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0 4.000000 5.000000 24.706 23.529 1752579920.330
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1 4.000000 5.000000 22.412 31.176 1752579924.312
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@@ -38,6 +38,11 @@
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"- Motor properties\n",
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"- Humidity\n",
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"- enc resolution\n",
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"## Measurement tests\n",
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"### unidirectional repetabillity\n",
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"### bidirectional repetability\n",
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"### thermal expansion\n",
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"### relative distance accuracy\n",
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"\n"
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],
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"id": "ac98fcd46a8e41f9",
|
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@@ -53,8 +58,8 @@
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{
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-07-15T07:13:05.822677Z",
|
||||
"start_time": "2025-07-15T07:13:05.801198Z"
|
||||
"end_time": "2025-07-15T15:21:34.553058Z",
|
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"start_time": "2025-07-15T15:21:34.403724Z"
|
||||
}
|
||||
},
|
||||
"cell_type": "code",
|
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@@ -178,18 +183,27 @@
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Scripts\n",
|
||||
"Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\config.json\n"
|
||||
"Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\config.json\n",
|
||||
"Path exists: C:\\Users\\berti_r\\Python_Projects\\templates\\motion_libs\n",
|
||||
"Path exists: C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\measurement.json\n",
|
||||
"Constructor for PLC\n",
|
||||
"Connect to PLC\n",
|
||||
"is_open()=True\n",
|
||||
"get_local_address()=None\n",
|
||||
"read_device_info()=('Plc30 App', <pyads.structs.AdsVersion object at 0x0000023C8668CC20>)\n",
|
||||
"GVL_APP.nAXIS_NUM=3\n",
|
||||
"Constructor for axis\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"BoundedIntText(value=5, description='Nr of cycles:', max=1000, min=1)"
|
||||
"BoundedIntText(value=2, description='Nr of cycles:', max=1000, min=1)"
|
||||
],
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"version_major": 2,
|
||||
"version_minor": 0,
|
||||
"model_id": "931ffe1c6a4c4fe1af39442aafcd5a6d"
|
||||
"model_id": "3b0d5b4ffb8e49818c298b9f4aa88c9a"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -203,7 +217,7 @@
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"version_major": 2,
|
||||
"version_minor": 0,
|
||||
"model_id": "49d711d81ca94028bd6c60a4ab0d22fa"
|
||||
"model_id": "e6a7e81d76c54669996f666432736c9a"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -217,7 +231,7 @@
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"version_major": 2,
|
||||
"version_minor": 0,
|
||||
"model_id": "39198dfeeaa243cba9d410027dffe994"
|
||||
"model_id": "e984d8a357044a279564d1bf46272beb"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -231,14 +245,21 @@
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"version_major": 2,
|
||||
"version_minor": 0,
|
||||
"model_id": "24e25cd7cc814f898ca4503bca9184f1"
|
||||
"model_id": "841448ed4ad34367b522a923213d4d23"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"BIG TODO: ADD dropdown menue for choosing which test to run\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"execution_count": 5
|
||||
"execution_count": 1
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
@@ -249,16 +270,100 @@
|
||||
{
|
||||
"metadata": {},
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"axis_path = r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\data20250715_alignment_tests\\20250715_170343_repeatibility_0\"\n",
|
||||
"axis_data_file_path = myu.find_newest_dat_file(axis_path)\n",
|
||||
"print(axis_data_file_path)\n",
|
||||
"mf.analyze_repeatability(axis_data_file_path,1.1)\n"
|
||||
],
|
||||
"id": "35424a827215f084",
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"source": "",
|
||||
"id": "35424a827215f084"
|
||||
"execution_count": null
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
"cell_type": "markdown",
|
||||
"source": "## Temperature time plot\n",
|
||||
"id": "ffd60bd1525f3b15"
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# Live update function\n",
|
||||
"data_folder = r'C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\data\\Temp'\n",
|
||||
"%matplotlib widget\n",
|
||||
"from matplotlib.widgets import Cursor\n",
|
||||
"import matplotlib.dates as mdates\n",
|
||||
"# Load the newest file\n",
|
||||
"\n",
|
||||
"# Load file\n",
|
||||
"file_path = myu.find_newest_dat_file(data_folder)\n",
|
||||
"times, temps = myu.load_data(file_path)\n",
|
||||
"\n",
|
||||
"# Initial plot range setup\n",
|
||||
"initial_xlim = (mdates.date2num(times[0]), mdates.date2num(times[-1]))\n",
|
||||
"colors = ['red', 'green', 'blue', 'orange', 'purple']\n",
|
||||
"labels = [f\"Temp {i+1}\" for i in range(5)]\n",
|
||||
"\n",
|
||||
"# Setup plot\n",
|
||||
"fig, ax = plt.subplots(figsize=(10, 5))\n",
|
||||
"lines = []\n",
|
||||
"\n",
|
||||
"# Plot initial downsampled data\n",
|
||||
"def plot_initial():\n",
|
||||
" ind_min, ind_max = 0, len(times)\n",
|
||||
" step = max((ind_max - ind_min) // 1000, 1)\n",
|
||||
"\n",
|
||||
" for i in range(5):\n",
|
||||
" line, = ax.plot(times[ind_min:ind_max:step],\n",
|
||||
" temps[i][ind_min:ind_max:step],\n",
|
||||
" label=labels[i], color=colors[i])\n",
|
||||
" lines.append(line)\n",
|
||||
"\n",
|
||||
" ax.set_title(\"Temperature Over Time\")\n",
|
||||
" ax.set_xlabel(\"Time\")\n",
|
||||
" ax.set_ylabel(\"Temperature (°C)\")\n",
|
||||
" ax.legend()\n",
|
||||
" ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M:%S'))\n",
|
||||
" ax.set_xlim(initial_xlim)\n",
|
||||
" ax.relim()\n",
|
||||
" ax.autoscale_view()\n",
|
||||
"\n",
|
||||
"# Update on zoom/pan\n",
|
||||
"def update_plot(event=None):\n",
|
||||
" xlim = ax.get_xlim()\n",
|
||||
" t_nums = mdates.date2num(times)\n",
|
||||
" ind_min, ind_max = np.searchsorted(t_nums, xlim)\n",
|
||||
" ind_max = min(len(times), ind_max)\n",
|
||||
" step = max((ind_max - ind_min) // 1000, 1)\n",
|
||||
"\n",
|
||||
" for line, temp_data in zip(lines, temps):\n",
|
||||
" line.set_data(times[ind_min:ind_max:step], temp_data[ind_min:ind_max:step])\n",
|
||||
"\n",
|
||||
" ax.relim()\n",
|
||||
" ax.autoscale_view()\n",
|
||||
" fig.canvas.draw_idle()\n",
|
||||
"\n",
|
||||
"# Hook zoom & pan events\n",
|
||||
"fig.canvas.mpl_connect('button_release_event', update_plot)\n",
|
||||
"fig.canvas.mpl_connect('scroll_event', update_plot)\n",
|
||||
"fig.canvas.mpl_connect('motion_notify_event', update_plot)\n",
|
||||
"\n",
|
||||
"# Run\n",
|
||||
"plot_initial()\n",
|
||||
"update_plot()\n",
|
||||
"plt.tight_layout()\n",
|
||||
"fig.canvas.draw_idle()"
|
||||
],
|
||||
"id": "6b1735e5aee89bc6",
|
||||
"outputs": [],
|
||||
"execution_count": null
|
||||
},
|
||||
{
|
||||
"metadata": {},
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"~~~~# Live update function\n",
|
||||
"def load_recent_data():\n",
|
||||
"\n",
|
||||
" return 0\n",
|
||||
@@ -337,35 +442,22 @@
|
||||
"execution_count": null
|
||||
},
|
||||
{
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-07-15T07:22:40.123332Z",
|
||||
"start_time": "2025-07-15T07:22:40.118923Z"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"x_coordinates_json = myu.load_object(r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\measurement.json\")\n",
|
||||
"x_coordinates = x_coordinates_json.get('backlsh_meas_mov')\n",
|
||||
"x_coordinates = x_coordinates_json.get('std_test_mov')\n",
|
||||
"wait_x_json = myu.load_object(r\"C:\\Users\\berti_r\\Python_Projects\\StagePerformaceDocu\\Config\\measurement.json\")\n",
|
||||
"wait_x = wait_x_json.get('std_test_wait')\n",
|
||||
"print(x_coordinates)\n",
|
||||
"for mov in x_coordinates:\n",
|
||||
" print(mov)"
|
||||
"print(wait_x)\n",
|
||||
"for mov,wait in x_coordinates, wait_x:\n",
|
||||
" print(mov)\n",
|
||||
" print(wait)"
|
||||
],
|
||||
"id": "9813d493bd439789",
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"[10, -10, -10, 10]\n",
|
||||
"10\n",
|
||||
"-10\n",
|
||||
"-10\n",
|
||||
"10\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"execution_count": 9
|
||||
"outputs": [],
|
||||
"execution_count": null
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Reference in New Issue
Block a user