Switch to tauri

.gitignore

@@ -1,13 +1,21 @@
 /*
 /*/
 !/.gitignore
+!/.gitignore.tauri
 
 !/Cargo.lock
 !/Cargo.toml
 !/config.toml
 !/index.html
+!/package.json
+!/README.md
 !/rust-toolchain.toml
+!/svelte.config.js
+!/tsconfig.json
+!/tsconfig.node.json
+!/vite.config.ts
 
 !/beanconqueror/
-!/shots/
+!/public/
 !/src/
+!/src-tauri/

.gitignore.tauri

@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

README.md

@@ -0,0 +1,7 @@
+# Tauri + Svelte + Typescript
+
+This template should help get you started developing with Tauri, Svelte and TypeScript in Vite.
+
+## Recommended IDE Setup
+
+[VS Code](https://code.visualstudio.com/) + [Svelte](https://marketplace.visualstudio.com/items?itemName=svelte.svelte-vscode) + [Tauri](https://marketplace.visualstudio.com/items?itemName=tauri-apps.tauri-vscode) + [rust-analyzer](https://marketplace.visualstudio.com/items?itemName=rust-lang.rust-analyzer).

Shots/Shots.py

@@ -1,161 +0,0 @@
-import pandas as pd
-
-from datetime import datetime
-
-import numpy as np
-from numpy import diff
-
-from scipy.interpolate import make_interp_spline
-from scipy.signal import savgol_filter
-
-import matplotlib.pyplot as plt
-
-timestamp_start = None
-
-def unix_to_datetime(unix_string):
-    return datetime.strptime(unix_string, "%H:%M:%S.%f")
-
-def deltatime(time):
-    global timestamp_start
-    return (time - timestamp_start).total_seconds()
-
-def timestamp_converter(timestamp):
-    time = unix_to_datetime(timestamp)
-
-    global timestamp_start
-    if timestamp_start == None:
-        timestamp_start = time
-
-    delta = deltatime(time)
-    return delta
-
-shots = [
-        {
-            'filename': 'Elisabeth/16_06_2022_1.xlsx',
-            'title': 'Elisabeth 16.06.2022 #1',
-            'cutoff': 38,
-        }, # [0]
-        {
-            'filename': 'Elisabeth/19_06_2022_1.xlsx',
-            'title': 'Elisabeth 19.06.2022 #1',
-        }, # [1]
-        {
-            'filename': 'Laura/20_06_2022_1.xlsx',
-            'title': 'Laura 20.06.2022 #1',
-            'cutoff': 38.7,
-        }, # [2]
-        {
-            'filename': 'Laura/20_06_2022_2.xlsx',
-            'title': 'Laura 20.06.2022 #2',
-            'cutoff': 32.6,
-        }, # [3]
-        ]
-
-comparison = {
-        'Elisabeth 19.06.22 Shot #1 vs. #2': (0, 1), #[0]
-        'Laura 20.06.22 Shot #1 vs #2': (2, 3), #[1]
-        #'comparison': {
-        #    'Elisabeth Shots 06/13/22 - 06/10/22': (1, 2), #[0]
-        #    'Elisabeth Shots 06/15/22 - 06/10/22': (1, 3), #[1]
-        #    'Elisabeth Shots 06/15/22 - 06/13/22': (2, 3), #[2]
-        #    }
-        }
-
-
-curr_figure = 0
-
-fig1 = plt.figure(curr_figure)
-ax1 = plt.subplot(2, 2, 1)
-# ax1.minorticks_on()
-# plt.title('Shotweight over time')
-plt.ylabel('Weight (g)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-ax2 = plt.subplot(2, 2, 3, sharex=ax1)
-# plt.title('Flow-rate over time')
-plt.ylabel('Flow-rate (g/s)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-ax3 = plt.subplot(2, 2, 2, sharex=ax1, sharey=ax1)
-# plt.title('Shotweight over time')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-ax4 = plt.subplot(2, 2, 4, sharex=ax2, sharey=ax2)
-# plt.title('Flow-rate over time')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-fig1.supxlabel('Time (s)')
-plt.tight_layout()
-
-plt.subplot(2, 2, 1)
-
-for shot in shots:
-    timestamp_start = None
-
-    df_raw = pd.read_excel(shot['filename'], converters={
-        0: lambda x: timestamp_converter(x)
-        }, sheet_name=0)
-    df_calc = pd.read_excel(shot['filename'], converters={
-        0: lambda x: timestamp_converter(x)
-        }, sheet_name=1)
-
-    time_col_raw = df_raw.keys()[0]
-    profile_col_raw = df_raw.keys()[5]
-
-    time_col_calc = df_calc.keys()[0]
-    profile_col_calc = df_calc.keys()[2]
-
-    if 'cutoff' in shot:
-        if shot['cutoff'] != -1:
-            df_raw = df_raw.loc[df_raw[time_col_raw] < shot['cutoff']]
-            df_calc = df_calc.loc[df_calc[time_col_calc] < shot['cutoff']]
-
-    shot['data'] = {}
-
-    shot['data']['profile'] = df_raw
-    shot['data']['flowrate'] = df_calc
-
-    time = df_raw[time_col_raw].tolist()
-    weight = df_raw[profile_col_raw].tolist()
-    # print("time: ", time)
-    # print("weight: ", time)
-    plt.plot(time, weight, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 2, 3)
-
-    flow_time = df_calc[time_col_calc].tolist()
-    flowrate = df_calc[profile_col_calc].tolist()
-    # print("flow_time: ", flow_time)
-    # print("flowrate: ", flowrate)
-    plt.plot(flow_time, flowrate, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 2, 1)
-
-plt.subplot(2, 2, 4)
-
-for key in comparison:
-    calc1 = shots[comparison[key][0]]['data']['flowrate']
-    calc2 = shots[comparison[key][1]]['data']['flowrate']
-
-    t1 = np.array(calc1[calc1.keys()[0]].tolist())
-    r1 = np.array(calc1[calc1.keys()[2]].tolist())
-
-    t2 = np.array(calc2[calc2.keys()[0]].tolist())
-    r2 = np.array(calc2[calc2.keys()[2]].tolist())
-
-    dt = None
-    size_diff = t2.size - t1.size
-    if size_diff > 0:
-        dt = t2
-        r1 = np.pad(r1, (0, size_diff), 'constant')
-    elif size_diff < 0:
-        dt = t1
-        r2 = np.pad(r2, (0, -size_diff), 'constant')
-
-    dr = r2 - r1
-
-    plt.plot(dt, dr, label = key, linewidth=1)
-
-plt.legend(loc='best')
-
-plt.show()

Shots/Shots_brew_time.py

@@ -1,75 +0,0 @@
-import pandas as pd
-
-import numpy as np
-from numpy import diff
-
-from scipy.interpolate import make_interp_spline
-from scipy.signal import savgol_filter
-
-import matplotlib.pyplot as plt
-
-shots = [
-        {
-            'filename': 'Elisabeth/16_06_2022_1.xlsx',
-            'title': 'Elisabeth 16.06.2022 #1',
-            'cutoff': 38,
-            'data': {}
-        }, # [0]
-        ]
-
-curr_figure = 0
-
-plt.figure(curr_figure)
-plt.subplot(2, 1, 1)
-# plt.title('Shotweight over time')
-# plt.xlabel('Time (s)')
-plt.ylabel('Weight (g)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 2)
-# plt.title('Flow-rate over time')
-plt.xlabel('Time (s)')
-plt.ylabel('Flow-rate (g/s)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 1)
-
-for shot in shots:
-    df_raw = pd.read_excel(shot['filename'], converters={
-        1: lambda x: float(x) if not str(x).endswith('.10') else float(x) + 0.85
-        }, sheet_name=0)
-    df_calc = pd.read_excel(shot['filename'], converters={
-        1: lambda x: float(x) if not str(x).endswith('.10') else float(x) + 0.85
-        }, sheet_name=1)
-
-    time_col_raw = df_raw.keys()[1]
-    profile_col_raw = df_raw.keys()[5]
-
-    time_col_calc = df_calc.keys()[1]
-    profile_col_calc = df_calc.keys()[2]
-
-    df_raw_co = df_raw.loc[df_raw[time_col_raw] < shot['cutoff']]
-    df_calc_co = df_calc.loc[df_calc[time_col_calc] < shot['cutoff']]
-
-    shot['data']['profile'] = df_raw_co
-    shot['data']['flowrate'] = df_calc_co
-
-    time = df_raw_co[time_col_raw].tolist()
-    weight = df_raw_co[profile_col_raw].tolist()
-    print("time: ", time)
-    print("weight: ", time)
-    plt.plot(time, weight, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 1, 2)
-
-    flow_time = df_calc_co[time_col_calc].tolist()
-    flowrate = df_calc_co[profile_col_calc].tolist()
-    print("flow_time: ", flow_time)
-    print("flowrate: ", flowrate)
-    plt.plot(flow_time, flowrate, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 1, 1)
-
-plt.legend(loc='best')
-
-plt.show()

Shots/Shots_csv.py

@@ -1,160 +0,0 @@
-import csv
-
-import numpy as np
-from numpy import diff
-
-from scipy.interpolate import make_interp_spline
-from scipy.signal import savgol_filter
-
-import matplotlib.pyplot as plt
-
-filenames = [
-        'Laura/06_09-1.csv', # [0]
-        'Laura/06_09-2.csv', # [1]
-        'Elisabeth/06_10-1.csv', #[2]
-        'Elisabeth/06_10-2.csv', #[3]
-        # 'Elisabeth/06_12-1.csv',
-        'Elisabeth/06_13-1.csv', #[4]
-        'Elisabeth/06_13-2.csv', #[5]
-        'Elisabeth/06_15-1.csv', #[6]
-        'Elisabeth/06_15-2.csv', #[7]
-        ]
-
-comparison = {
-        'Laura Shot #1 vs #2': (0, 1), #[0]
-        'Elisabeth 06/10/22 Shot #2 - #1': (2, 3), #[1]
-        'Elisabeth 06/13/22 Shot #2 - #1': (4, 5), #[2]
-        'Elisabeth 06/15/22 Shot #2 - #1': (6, 7), #[3]
-        'comparison': {
-            'Elisabeth Shots 06/13/22 - 06/10/22': (1, 2), #[0]
-            'Elisabeth Shots 06/15/22 - 06/10/22': (1, 3), #[1]
-            'Elisabeth Shots 06/15/22 - 06/13/22': (2, 3), #[2]
-            }
-        }
-
-
-data = {}
-
-curr_figure = 0
-
-plt.figure(curr_figure)
-plt.subplot(2, 1, 1)
-# plt.title('Shotweight over time')
-# plt.xlabel('Time (s)')
-plt.ylabel('Weight (g)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 2)
-# plt.title('Flow-rate over time')
-plt.xlabel('Time (s)')
-plt.ylabel('Flow-rate (g/s)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 1)
-
-for filename in filenames:
-    data[filename] = {
-            'shot_name': '',
-            'rows': [],
-            'time': [],
-            'weight': []
-            }
-
-    with open(filename, newline='') as file:
-        reader = csv.DictReader(file, delimiter=',')
-
-        for row in reader:
-            data[filename]['rows'].append(row)
-
-            if row['information_type'] == 'meta':
-                if row['metatype'] == 'Name':
-                    data[filename]['shot_name'] = row['metadata']
-            elif row['information_type'] == 'moment':
-                try:
-                    elapsed = float(row['elapsed'])
-                    weight = float(row['current_total_shot_weight'])
-
-                    data[filename]['time'].append(elapsed)
-                    data[filename]['weight'].append(weight)
-                except ValueError:
-                    continue
-                    #print("Not a float!")
-
-    time = data[filename]['time']
-    weight = data[filename]['weight']
-
-    first_zero = list(x > 0 for x in weight).index(True) - 1
-    zero_time = time[first_zero]
-
-    weight = weight[first_zero:]
-    time = time[first_zero:]
-    time = list(map(lambda t: t - zero_time, time))
-
-    data[filename]['time'] = time
-    data[filename]['weight'] = weight
-
-    weight_savgol = savgol_filter(weight, 30, 3)
-
-    plt.plot(time, weight_savgol, label = data[filename]['shot_name'], linewidth=1)
-    plt.scatter(time, weight, label = '', s=0.25)
-
-    plt.subplot(2, 1, 2)
-
-    dweight_dt = diff(weight)/diff(time)
-    dweight_dt_savgol = savgol_filter(dweight_dt, 60, 3)
-
-    plt.plot(time[:-1], dweight_dt_savgol, label = data[filename]['shot_name'], linewidth=1)
-    plt.scatter(time[1:-1], dweight_dt[1:], label = '', s=0.25)
-
-    plt.subplot(2, 1, 1)
-
-    #print(filename, "\n", time, "\n", weight)
-
-plt.legend(loc='best')
-
-def comparison_plot(curr_figure, comparison_dict):
-    curr_figure += 1
-    plt.figure(curr_figure)
-
-    for key in comparison_dict:
-        if key != 'comparison':
-            item = comparison_dict[key]
-            i0 = item[0]
-            i1 = item[1]
-
-            fn0 = filenames[i0]
-            fn1 = filenames[i1]
-
-            plt.xlabel('Time (s)')
-            plt.ylabel('Weight difference (g)')
-            plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-            t0 = np.array(data[fn0]['time'])
-            w0 = np.array(data[fn0]['weight'])
-
-            t1 = np.array(data[fn1]['time'])
-            w1 = np.array(data[fn1]['weight'])
-
-            time_linspace = np.linspace(max(np.array(t0).min(), np.array(t1).min()), min(np.array(t0).max(), np.array(t1).max()), max(len(t0), len(t1)))
-
-            i0 = make_interp_spline(t0, w0, k=3)
-            wi0 = i0(time_linspace)
-            i1 = make_interp_spline(t1, w1, k=3)
-            wi1 = i1(time_linspace)
-
-            dw = wi1 - wi0
-
-            dw_savgol = savgol_filter(dw, 30, 3)
-
-            plt.plot(time_linspace, dw_savgol, label = key, linewidth=1)
-            plt.scatter(time_linspace, dw, label = '', s=0.25)
-
-            plt.legend(loc='best')
-        else:
-            curr_figure = comparison_plot(curr_figure, comparison_dict['comparison'])
-    return curr_figure
-
-curr_figure = comparison_plot(curr_figure, comparison)
-
-
-plt.show()

index.html

@@ -1,16 +1,14 @@
 <!doctype html>
 <html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <link rel="icon" type="image/svg+xml" href="/vite.svg" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Tauri + Svelte + TS</title>
+  </head>
 
-<head>
-    <meta charset="utf-8" />
-    <title>RustyBeans</title>
-    <meta name="viewport">
-    <link data-trunk rel="copy-file" href="/config.toml">
-    <link data-trunk rel="copy-dir" href="/Shots">
-</head>
-
-<body>
-    <div id="main"></div>
-</body>
-
+  <body>
+    <div id="app"></div>
+    <script type="module" src="/src/main.ts"></script>
+  </body>
 </html>

package.json

@@ -0,0 +1,27 @@
+{
+  "name": "rustybeans-sveltekit",
+  "private": true,
+  "version": "0.0.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview",
+    "check": "svelte-check --tsconfig ./tsconfig.json",
+    "tauri": "tauri"
+  },
+  "dependencies": {
+    "@tauri-apps/api": "^1.4.0"
+  },
+  "devDependencies": {
+    "@sveltejs/vite-plugin-svelte": "^2.4.2",
+    "@tsconfig/svelte": "^5.0.0",
+    "svelte": "^4.0.5",
+    "svelte-check": "^3.4.6",
+    "svelte-preprocess": "^5.0.0",
+    "tslib": "^2.6.0",
+    "typescript": "^5.0.2",
+    "vite": "^4.4.4",
+    "@tauri-apps/cli": "^1.4.0"
+  }
+}

public/svelte.svg

@@ -0,0 +1 @@
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public/tauri.svg

@@ -0,0 +1,6 @@
+<svg width="206" height="231" viewBox="0 0 206 231" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M143.143 84C143.143 96.1503 133.293 106 121.143 106C108.992 106 99.1426 96.1503 99.1426 84C99.1426 71.8497 108.992 62 121.143 62C133.293 62 143.143 71.8497 143.143 84Z" fill="#FFC131"/>
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public/vite.svg

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shots/Shots.py

@@ -1,161 +0,0 @@
-import pandas as pd
-
-from datetime import datetime
-
-import numpy as np
-from numpy import diff
-
-from scipy.interpolate import make_interp_spline
-from scipy.signal import savgol_filter
-
-import matplotlib.pyplot as plt
-
-timestamp_start = None
-
-def unix_to_datetime(unix_string):
-    return datetime.strptime(unix_string, "%H:%M:%S.%f")
-
-def deltatime(time):
-    global timestamp_start
-    return (time - timestamp_start).total_seconds()
-
-def timestamp_converter(timestamp):
-    time = unix_to_datetime(timestamp)
-
-    global timestamp_start
-    if timestamp_start == None:
-        timestamp_start = time
-
-    delta = deltatime(time)
-    return delta
-
-shots = [
-        {
-            'filename': 'Elisabeth/16_06_2022_1.xlsx',
-            'title': 'Elisabeth 16.06.2022 #1',
-            'cutoff': 38,
-        }, # [0]
-        {
-            'filename': 'Elisabeth/19_06_2022_1.xlsx',
-            'title': 'Elisabeth 19.06.2022 #1',
-        }, # [1]
-        {
-            'filename': 'Laura/20_06_2022_1.xlsx',
-            'title': 'Laura 20.06.2022 #1',
-            'cutoff': 38.7,
-        }, # [2]
-        {
-            'filename': 'Laura/20_06_2022_2.xlsx',
-            'title': 'Laura 20.06.2022 #2',
-            'cutoff': 32.6,
-        }, # [3]
-        ]
-
-comparison = {
-        'Elisabeth 19.06.22 Shot #1 vs. #2': (0, 1), #[0]
-        'Laura 20.06.22 Shot #1 vs #2': (2, 3), #[1]
-        #'comparison': {
-        #    'Elisabeth Shots 06/13/22 - 06/10/22': (1, 2), #[0]
-        #    'Elisabeth Shots 06/15/22 - 06/10/22': (1, 3), #[1]
-        #    'Elisabeth Shots 06/15/22 - 06/13/22': (2, 3), #[2]
-        #    }
-        }
-
-
-curr_figure = 0
-
-fig1 = plt.figure(curr_figure)
-ax1 = plt.subplot(2, 2, 1)
-# ax1.minorticks_on()
-# plt.title('Shotweight over time')
-plt.ylabel('Weight (g)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-ax2 = plt.subplot(2, 2, 3, sharex=ax1)
-# plt.title('Flow-rate over time')
-plt.ylabel('Flow-rate (g/s)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-ax3 = plt.subplot(2, 2, 2, sharex=ax1, sharey=ax1)
-# plt.title('Shotweight over time')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-ax4 = plt.subplot(2, 2, 4, sharex=ax2, sharey=ax2)
-# plt.title('Flow-rate over time')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-fig1.supxlabel('Time (s)')
-plt.tight_layout()
-
-plt.subplot(2, 2, 1)
-
-for shot in shots:
-    timestamp_start = None
-
-    df_raw = pd.read_excel(shot['filename'], converters={
-        0: lambda x: timestamp_converter(x)
-        }, sheet_name=0)
-    df_calc = pd.read_excel(shot['filename'], converters={
-        0: lambda x: timestamp_converter(x)
-        }, sheet_name=1)
-
-    time_col_raw = df_raw.keys()[0]
-    profile_col_raw = df_raw.keys()[5]
-
-    time_col_calc = df_calc.keys()[0]
-    profile_col_calc = df_calc.keys()[2]
-
-    if 'cutoff' in shot:
-        if shot['cutoff'] != -1:
-            df_raw = df_raw.loc[df_raw[time_col_raw] < shot['cutoff']]
-            df_calc = df_calc.loc[df_calc[time_col_calc] < shot['cutoff']]
-
-    shot['data'] = {}
-
-    shot['data']['profile'] = df_raw
-    shot['data']['flowrate'] = df_calc
-
-    time = df_raw[time_col_raw].tolist()
-    weight = df_raw[profile_col_raw].tolist()
-    # print("time: ", time)
-    # print("weight: ", time)
-    plt.plot(time, weight, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 2, 3)
-
-    flow_time = df_calc[time_col_calc].tolist()
-    flowrate = df_calc[profile_col_calc].tolist()
-    # print("flow_time: ", flow_time)
-    # print("flowrate: ", flowrate)
-    plt.plot(flow_time, flowrate, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 2, 1)
-
-plt.subplot(2, 2, 4)
-
-for key in comparison:
-    calc1 = shots[comparison[key][0]]['data']['flowrate']
-    calc2 = shots[comparison[key][1]]['data']['flowrate']
-
-    t1 = np.array(calc1[calc1.keys()[0]].tolist())
-    r1 = np.array(calc1[calc1.keys()[2]].tolist())
-
-    t2 = np.array(calc2[calc2.keys()[0]].tolist())
-    r2 = np.array(calc2[calc2.keys()[2]].tolist())
-
-    dt = None
-    size_diff = t2.size - t1.size
-    if size_diff > 0:
-        dt = t2
-        r1 = np.pad(r1, (0, size_diff), 'constant')
-    elif size_diff < 0:
-        dt = t1
-        r2 = np.pad(r2, (0, -size_diff), 'constant')
-
-    dr = r2 - r1
-
-    plt.plot(dt, dr, label = key, linewidth=1)
-
-plt.legend(loc='best')
-
-plt.show()

shots/Shots_brew_time.py

@@ -1,75 +0,0 @@
-import pandas as pd
-
-import numpy as np
-from numpy import diff
-
-from scipy.interpolate import make_interp_spline
-from scipy.signal import savgol_filter
-
-import matplotlib.pyplot as plt
-
-shots = [
-        {
-            'filename': 'Elisabeth/16_06_2022_1.xlsx',
-            'title': 'Elisabeth 16.06.2022 #1',
-            'cutoff': 38,
-            'data': {}
-        }, # [0]
-        ]
-
-curr_figure = 0
-
-plt.figure(curr_figure)
-plt.subplot(2, 1, 1)
-# plt.title('Shotweight over time')
-# plt.xlabel('Time (s)')
-plt.ylabel('Weight (g)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 2)
-# plt.title('Flow-rate over time')
-plt.xlabel('Time (s)')
-plt.ylabel('Flow-rate (g/s)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 1)
-
-for shot in shots:
-    df_raw = pd.read_excel(shot['filename'], converters={
-        1: lambda x: float(x) if not str(x).endswith('.10') else float(x) + 0.85
-        }, sheet_name=0)
-    df_calc = pd.read_excel(shot['filename'], converters={
-        1: lambda x: float(x) if not str(x).endswith('.10') else float(x) + 0.85
-        }, sheet_name=1)
-
-    time_col_raw = df_raw.keys()[1]
-    profile_col_raw = df_raw.keys()[5]
-
-    time_col_calc = df_calc.keys()[1]
-    profile_col_calc = df_calc.keys()[2]
-
-    df_raw_co = df_raw.loc[df_raw[time_col_raw] < shot['cutoff']]
-    df_calc_co = df_calc.loc[df_calc[time_col_calc] < shot['cutoff']]
-
-    shot['data']['profile'] = df_raw_co
-    shot['data']['flowrate'] = df_calc_co
-
-    time = df_raw_co[time_col_raw].tolist()
-    weight = df_raw_co[profile_col_raw].tolist()
-    print("time: ", time)
-    print("weight: ", time)
-    plt.plot(time, weight, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 1, 2)
-
-    flow_time = df_calc_co[time_col_calc].tolist()
-    flowrate = df_calc_co[profile_col_calc].tolist()
-    print("flow_time: ", flow_time)
-    print("flowrate: ", flowrate)
-    plt.plot(flow_time, flowrate, label = shot['title'], linewidth=1)
-
-    plt.subplot(2, 1, 1)
-
-plt.legend(loc='best')
-
-plt.show()

shots/Shots_csv.py

@@ -1,160 +0,0 @@
-import csv
-
-import numpy as np
-from numpy import diff
-
-from scipy.interpolate import make_interp_spline
-from scipy.signal import savgol_filter
-
-import matplotlib.pyplot as plt
-
-filenames = [
-        'Laura/06_09-1.csv', # [0]
-        'Laura/06_09-2.csv', # [1]
-        'Elisabeth/06_10-1.csv', #[2]
-        'Elisabeth/06_10-2.csv', #[3]
-        # 'Elisabeth/06_12-1.csv',
-        'Elisabeth/06_13-1.csv', #[4]
-        'Elisabeth/06_13-2.csv', #[5]
-        'Elisabeth/06_15-1.csv', #[6]
-        'Elisabeth/06_15-2.csv', #[7]
-        ]
-
-comparison = {
-        'Laura Shot #1 vs #2': (0, 1), #[0]
-        'Elisabeth 06/10/22 Shot #2 - #1': (2, 3), #[1]
-        'Elisabeth 06/13/22 Shot #2 - #1': (4, 5), #[2]
-        'Elisabeth 06/15/22 Shot #2 - #1': (6, 7), #[3]
-        'comparison': {
-            'Elisabeth Shots 06/13/22 - 06/10/22': (1, 2), #[0]
-            'Elisabeth Shots 06/15/22 - 06/10/22': (1, 3), #[1]
-            'Elisabeth Shots 06/15/22 - 06/13/22': (2, 3), #[2]
-            }
-        }
-
-
-data = {}
-
-curr_figure = 0
-
-plt.figure(curr_figure)
-plt.subplot(2, 1, 1)
-# plt.title('Shotweight over time')
-# plt.xlabel('Time (s)')
-plt.ylabel('Weight (g)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 2)
-# plt.title('Flow-rate over time')
-plt.xlabel('Time (s)')
-plt.ylabel('Flow-rate (g/s)')
-plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-plt.subplot(2, 1, 1)
-
-for filename in filenames:
-    data[filename] = {
-            'shot_name': '',
-            'rows': [],
-            'time': [],
-            'weight': []
-            }
-
-    with open(filename, newline='') as file:
-        reader = csv.DictReader(file, delimiter=',')
-
-        for row in reader:
-            data[filename]['rows'].append(row)
-
-            if row['information_type'] == 'meta':
-                if row['metatype'] == 'Name':
-                    data[filename]['shot_name'] = row['metadata']
-            elif row['information_type'] == 'moment':
-                try:
-                    elapsed = float(row['elapsed'])
-                    weight = float(row['current_total_shot_weight'])
-
-                    data[filename]['time'].append(elapsed)
-                    data[filename]['weight'].append(weight)
-                except ValueError:
-                    continue
-                    #print("Not a float!")
-
-    time = data[filename]['time']
-    weight = data[filename]['weight']
-
-    first_zero = list(x > 0 for x in weight).index(True) - 1
-    zero_time = time[first_zero]
-
-    weight = weight[first_zero:]
-    time = time[first_zero:]
-    time = list(map(lambda t: t - zero_time, time))
-
-    data[filename]['time'] = time
-    data[filename]['weight'] = weight
-
-    weight_savgol = savgol_filter(weight, 30, 3)
-
-    plt.plot(time, weight_savgol, label = data[filename]['shot_name'], linewidth=1)
-    plt.scatter(time, weight, label = '', s=0.25)
-
-    plt.subplot(2, 1, 2)
-
-    dweight_dt = diff(weight)/diff(time)
-    dweight_dt_savgol = savgol_filter(dweight_dt, 60, 3)
-
-    plt.plot(time[:-1], dweight_dt_savgol, label = data[filename]['shot_name'], linewidth=1)
-    plt.scatter(time[1:-1], dweight_dt[1:], label = '', s=0.25)
-
-    plt.subplot(2, 1, 1)
-
-    #print(filename, "\n", time, "\n", weight)
-
-plt.legend(loc='best')
-
-def comparison_plot(curr_figure, comparison_dict):
-    curr_figure += 1
-    plt.figure(curr_figure)
-
-    for key in comparison_dict:
-        if key != 'comparison':
-            item = comparison_dict[key]
-            i0 = item[0]
-            i1 = item[1]
-
-            fn0 = filenames[i0]
-            fn1 = filenames[i1]
-
-            plt.xlabel('Time (s)')
-            plt.ylabel('Weight difference (g)')
-            plt.grid(visible=True, which='both', axis='both', linewidth=0.5)
-
-            t0 = np.array(data[fn0]['time'])
-            w0 = np.array(data[fn0]['weight'])
-
-            t1 = np.array(data[fn1]['time'])
-            w1 = np.array(data[fn1]['weight'])
-
-            time_linspace = np.linspace(max(np.array(t0).min(), np.array(t1).min()), min(np.array(t0).max(), np.array(t1).max()), max(len(t0), len(t1)))
-
-            i0 = make_interp_spline(t0, w0, k=3)
-            wi0 = i0(time_linspace)
-            i1 = make_interp_spline(t1, w1, k=3)
-            wi1 = i1(time_linspace)
-
-            dw = wi1 - wi0
-
-            dw_savgol = savgol_filter(dw, 30, 3)
-
-            plt.plot(time_linspace, dw_savgol, label = key, linewidth=1)
-            plt.scatter(time_linspace, dw, label = '', s=0.25)
-
-            plt.legend(loc='best')
-        else:
-            curr_figure = comparison_plot(curr_figure, comparison_dict['comparison'])
-    return curr_figure
-
-curr_figure = comparison_plot(curr_figure, comparison)
-
-
-plt.show()

src-tauri/.gitignore

@@ -0,0 +1,4 @@
+# Generated by Cargo
+# will have compiled files and executables
+/target/
+

src-tauri/Cargo.toml

@@ -0,0 +1,23 @@
+[package]
+name = "rustybeans-sveltekit"
+version = "0.0.0"
+description = "A Tauri App"
+authors = ["you"]
+license = ""
+repository = ""
+edition = "2021"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[build-dependencies]
+tauri-build = { version = "1.4", features = [] }
+
+[dependencies]
+tauri = { version = "1.4", features = ["shell-open"] }
+serde = { version = "1.0", features = ["derive"] }
+serde_json = "1.0"
+
+[features]
+# this feature is used for production builds or when `devPath` points to the filesystem
+# DO NOT REMOVE!!
+custom-protocol = ["tauri/custom-protocol"]

src-tauri/build.rs

@@ -0,0 +1,3 @@
+fn main() {
+  tauri_build::build()
+}

src-tauri/src/main.rs

@@ -0,0 +1,15 @@
+// Prevents additional console window on Windows in release, DO NOT REMOVE!!
+#![cfg_attr(not(debug_assertions), windows_subsystem = "windows")]
+
+// Learn more about Tauri commands at https://tauri.app/v1/guides/features/command
+#[tauri::command]
+fn greet(name: &str) -> String {
+    format!("Hello, {}! You've been greeted from Rust!", name)
+}
+
+fn main() {
+    tauri::Builder::default()
+        .invoke_handler(tauri::generate_handler![greet])
+        .run(tauri::generate_context!())
+        .expect("error while running tauri application");
+}

src-tauri/tauri.conf.json

@@ -0,0 +1,46 @@
+{
+  "build": {
+    "beforeDevCommand": "pnpm dev",
+    "beforeBuildCommand": "pnpm build",
+    "devPath": "http://localhost:1420",
+    "distDir": "../dist",
+    "withGlobalTauri": false
+  },
+  "package": {
+    "productName": "rustybeans-sveltekit",
+    "version": "0.0.0"
+  },
+  "tauri": {
+    "allowlist": {
+      "all": false,
+      "shell": {
+        "all": false,
+        "open": true
+      }
+    },
+    "bundle": {
+      "active": true,
+      "targets": "all",
+      "identifier": "com.tauri.dev",
+      "icon": [
+        "icons/32x32.png",
+        "icons/128x128.png",
+        "icons/128x128@2x.png",
+        "icons/icon.icns",
+        "icons/icon.ico"
+      ]
+    },
+    "security": {
+      "csp": null
+    },
+    "windows": [
+      {
+        "fullscreen": false,
+        "resizable": true,
+        "title": "rustybeans-sveltekit",
+        "width": 800,
+        "height": 600
+      }
+    ]
+  }
+}

src/src/App.svelte

@@ -0,0 +1,39 @@
+<script lang="ts">
+  import Greet from './lib/Greet.svelte'
+</script>
+
+<main class="container">
+  <h1>Welcome to Tauri!</h1>
+
+  <div class="row">
+    <a href="https://vitejs.dev" target="_blank">
+      <img src="/vite.svg" class="logo vite" alt="Vite Logo" />
+    </a>
+    <a href="https://tauri.app" target="_blank">
+      <img src="/tauri.svg" class="logo tauri" alt="Tauri Logo" />
+    </a>
+    <a href="https://svelte.dev" target="_blank">
+      <img src="/svelte.svg" class="logo svelte" alt="Svelte Logo" />
+    </a>
+  </div>
+
+  <p>
+    Click on the Tauri, Vite, and Svelte logos to learn more.
+  </p>
+
+  <div class="row">
+    <Greet />
+  </div>
+
+
+</main>
+
+<style>
+  .logo.vite:hover {
+    filter: drop-shadow(0 0 2em #747bff);
+  }
+
+  .logo.svelte:hover {
+    filter: drop-shadow(0 0 2em #ff3e00);
+  }
+</style>

src/src/lib/Greet.svelte

@@ -0,0 +1,19 @@
+<script lang="ts">
+  import { invoke } from "@tauri-apps/api/tauri"
+
+  let name = "";
+  let greetMsg = ""
+
+  async function greet(){
+    // Learn more about Tauri commands at https://tauri.app/v1/guides/features/command
+    greetMsg = await invoke("greet", { name })
+  }
+</script>
+
+<div>
+  <form class="row" on:submit|preventDefault={greet}>
+    <input id="greet-input" placeholder="Enter a name..." bind:value={name} />
+    <button type="submit">Greet</button>
+  </form>
+  <p>{greetMsg}</p>
+</div>

src/src/main.ts

@@ -0,0 +1,8 @@
+import "./styles.css";
+import App from "./App.svelte";
+
+const app = new App({
+  target: document.getElementById("app"),
+});
+
+export default app;

src/src/styles.css

@@ -0,0 +1,109 @@
+:root {
+  font-family: Inter, Avenir, Helvetica, Arial, sans-serif;
+  font-size: 16px;
+  line-height: 24px;
+  font-weight: 400;
+
+  color: #0f0f0f;
+  background-color: #f6f6f6;
+
+  font-synthesis: none;
+  text-rendering: optimizeLegibility;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  -webkit-text-size-adjust: 100%;
+}
+
+.container {
+  margin: 0;
+  padding-top: 10vh;
+  display: flex;
+  flex-direction: column;
+  justify-content: center;
+  text-align: center;
+}
+
+.logo {
+  height: 6em;
+  padding: 1.5em;
+  will-change: filter;
+  transition: 0.75s;
+}
+
+.logo.tauri:hover {
+  filter: drop-shadow(0 0 2em #24c8db);
+}
+
+.row {
+  display: flex;
+  justify-content: center;
+}
+
+a {
+  font-weight: 500;
+  color: #646cff;
+  text-decoration: inherit;
+}
+
+a:hover {
+  color: #535bf2;
+}
+
+h1 {
+  text-align: center;
+}
+
+input,
+button {
+  border-radius: 8px;
+  border: 1px solid transparent;
+  padding: 0.6em 1.2em;
+  font-size: 1em;
+  font-weight: 500;
+  font-family: inherit;
+  color: #0f0f0f;
+  background-color: #ffffff;
+  transition: border-color 0.25s;
+  box-shadow: 0 2px 2px rgba(0, 0, 0, 0.2);
+}
+
+button {
+  cursor: pointer;
+}
+
+button:hover {
+  border-color: #396cd8;
+}
+button:active {
+  border-color: #396cd8;
+  background-color: #e8e8e8;
+}
+
+input,
+button {
+  outline: none;
+}
+
+#greet-input {
+  margin-right: 5px;
+}
+
+@media (prefers-color-scheme: dark) {
+  :root {
+    color: #f6f6f6;
+    background-color: #2f2f2f;
+  }
+
+  a:hover {
+    color: #24c8db;
+  }
+
+  input,
+  button {
+    color: #ffffff;
+    background-color: #0f0f0f98;
+  }
+  button:active {
+    background-color: #0f0f0f69;
+  }
+}