trohith89 commited on
Commit
2685224
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verified Β·
1 Parent(s): 5828081

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +156 -14
app.py CHANGED
@@ -2,16 +2,9 @@ import streamlit as st
2
  import numpy as np
3
  import plotly.graph_objects as go
4
 
5
- # Check page parameters for navigation
6
- params = st.query_params
7
- if "page" not in params or params["page"] != ["tool"]:
8
- st.warning("⚠️ Please navigate through the Home page!")
9
- if st.button("🏠 Go to Home"):
10
- st.query_params.update({"page": "home"})
11
- st.stop()
12
-
13
  # Safe function evaluation
14
  def safe_eval(func_str, x_val):
 
15
  allowed_names = {"x": x_val, "np": np}
16
  try:
17
  return eval(func_str, {"__builtins__": None}, allowed_names)
@@ -20,10 +13,12 @@ def safe_eval(func_str, x_val):
20
 
21
  # Function derivative using finite difference method
22
  def derivative(func_str, x_val, h=1e-5):
 
23
  return (safe_eval(func_str, x_val + h) - safe_eval(func_str, x_val - h)) / (2 * h)
24
 
25
  # Tangent line equation
26
  def tangent_line(func_str, x_val, x_range):
 
27
  y_val = safe_eval(func_str, x_val)
28
  slope = derivative(func_str, x_val)
29
  return slope * (x_range - x_val) + y_val
@@ -47,6 +42,82 @@ if "x" not in st.session_state:
47
  # Full-width layout
48
  st.set_page_config(layout="wide")
49
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
50
  st.title("🌟 Gradient Descent Interactive Tool 🌟")
51
 
52
  col1, col2 = st.columns([1, 2])
@@ -54,16 +125,38 @@ col1, col2 = st.columns([1, 2])
54
  # Left Section: User Input
55
  with col1:
56
  st.subheader("πŸ”§ Define Your Function")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
57
  func_input = st.text_input(
58
- "Enter a function of 'x':",
59
  key="func_input",
60
  on_change=reset_state
61
  )
 
62
  st.subheader("βš™οΈ Gradient Descent Parameters")
63
  starting_point = st.number_input(
64
  "Starting Point (Xβ‚€)",
65
  value=4.0,
66
  step=0.1,
 
67
  key="starting_point",
68
  on_change=reset_state
69
  )
@@ -71,6 +164,7 @@ with col1:
71
  "Learning Rate (Ε‹)",
72
  value=0.25,
73
  step=0.01,
 
74
  key="learning_rate",
75
  on_change=reset_state
76
  )
@@ -94,19 +188,23 @@ with col1:
94
  with col2:
95
  st.subheader("πŸ“Š Gradient Descent Visualization")
96
  try:
 
97
  x_plot = np.linspace(-10, 10, 400)
98
  y_plot = [safe_eval(st.session_state.func_input, x) for x in x_plot]
99
 
100
  fig = go.Figure()
101
 
 
102
  fig.add_trace(go.Scatter(
103
  x=x_plot,
104
  y=y_plot,
105
- mode="lines",
106
  line=dict(color="blue", width=2),
 
107
  name="Function"
108
  ))
109
 
 
110
  fig.add_trace(go.Scatter(
111
  x=st.session_state.x_vals,
112
  y=st.session_state.y_vals,
@@ -115,8 +213,9 @@ with col2:
115
  name="Gradient Descent Points"
116
  ))
117
 
 
118
  current_x = st.session_state.x
119
- tangent_x = np.linspace(-10, 10, 200)
120
  tangent_y = tangent_line(st.session_state.func_input, current_x, tangent_x)
121
  fig.add_trace(go.Scatter(
122
  x=tangent_x,
@@ -126,13 +225,56 @@ with col2:
126
  name="Tangent Line"
127
  ))
128
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
129
  st.plotly_chart(fig, use_container_width=True)
 
130
  except Exception as e:
131
  st.error(f"⚠️ Error in visualization: {str(e)}")
132
 
 
133
  col5, col6 = st.columns(2)
134
  col5.info(f"πŸ§‘β€πŸ’» Iteration: {st.session_state.iteration}")
135
  col6.success(f"βœ… Current x: {st.session_state.x:.4f}, Current f(x): {st.session_state.y_vals[-1]:.4f}")
136
-
137
- if st.button("🏠 Return to Home"):
138
- st.query_params.update({"page": "home"})
 
2
  import numpy as np
3
  import plotly.graph_objects as go
4
 
 
 
 
 
 
 
 
 
5
  # Safe function evaluation
6
  def safe_eval(func_str, x_val):
7
+ """ Safely evaluates the function at a given x value. """
8
  allowed_names = {"x": x_val, "np": np}
9
  try:
10
  return eval(func_str, {"__builtins__": None}, allowed_names)
 
13
 
14
  # Function derivative using finite difference method
15
  def derivative(func_str, x_val, h=1e-5):
16
+ """ Numerically compute the derivative of the function at x using finite differences. """
17
  return (safe_eval(func_str, x_val + h) - safe_eval(func_str, x_val - h)) / (2 * h)
18
 
19
  # Tangent line equation
20
  def tangent_line(func_str, x_val, x_range):
21
+ """ Compute the tangent line at a given x value. """
22
  y_val = safe_eval(func_str, x_val)
23
  slope = derivative(func_str, x_val)
24
  return slope * (x_range - x_val) + y_val
 
42
  # Full-width layout
43
  st.set_page_config(layout="wide")
44
 
45
+ # CSS Styles for Borders, Font, Reduced Padding, and Custom Border Color
46
+ st.markdown(
47
+ """
48
+ <style>
49
+ * {
50
+ font-family: Cambria, Arial, sans-serif !important;
51
+ }
52
+ h1, h2, h3, h4, h5 {
53
+ text-align: center;
54
+ margin-top: 0;
55
+ }
56
+ input, .stButton button, .stDownloadButton button {
57
+ border: 2px solid #ea445a;
58
+ border-radius: 5px;
59
+ padding: 10px;
60
+ }
61
+ .stInfo, .stSuccess {
62
+ border: 2px solid #ea445a;
63
+ border-radius: 5px;
64
+ padding: 10px;
65
+ }
66
+ .stButton {
67
+ margin-top: 10px;
68
+ }
69
+ /* Reduced Padding at the top */
70
+ .css-1d391kg {
71
+ padding-top: 0.5rem;
72
+ }
73
+ /* Centering the legend in the plot */
74
+ .stPlotlyChart {
75
+ display: block;
76
+ margin: 0 auto;
77
+ }
78
+ /* Adjusting for full width without scrolling */
79
+ .css-1lcbvhc {
80
+ padding-left: 0;
81
+ padding-right: 0;
82
+ }
83
+ /* Custom borders for input fields */
84
+ .stTextInput input, .stNumberInput input {
85
+ border: 2px solid #001A6E;
86
+ border-radius: 5px;
87
+ padding: 10px;
88
+ }
89
+ /* Tooltip styling */
90
+ .tooltip {
91
+ position: relative;
92
+ display: inline-block;
93
+ cursor: pointer;
94
+ }
95
+ .tooltip .tooltiptext {
96
+ visibility: hidden;
97
+ opacity: 0;
98
+ width: 300px;
99
+ background-color: #001A6E;
100
+ color: #fff;
101
+ text-align: center;
102
+ border-radius: 5px;
103
+ padding: 5px;
104
+ position: absolute;
105
+ z-index: 1;
106
+ bottom: 125%; /* Position the tooltip above */
107
+ left: 50%;
108
+ margin-left: -150px;
109
+ transition: opacity 0.3s;
110
+ }
111
+ .tooltip:hover .tooltiptext {
112
+ visibility: visible;
113
+ opacity: 1;
114
+ }
115
+ </style>
116
+ """,
117
+ unsafe_allow_html=True,
118
+ )
119
+
120
+ # Page Layout
121
  st.title("🌟 Gradient Descent Interactive Tool 🌟")
122
 
123
  col1, col2 = st.columns([1, 2])
 
125
  # Left Section: User Input
126
  with col1:
127
  st.subheader("πŸ”§ Define Your Function")
128
+
129
+ # Tooltip with instructions when hovering over the function input label
130
+ st.markdown(
131
+ """
132
+ <div class="tooltip">
133
+ <label for="func_input">Enter a function of 'x':</label>
134
+ <span class="tooltiptext">
135
+ **How to input your function:**
136
+ - Please give the inputs as mentioned below
137
+ - x^n as x**n,
138
+ - sin(x) as np.sin(x)
139
+ - log(x) as np.log(x),
140
+ - e^x or exp(x) as np.exp(x).
141
+ </span>
142
+ </div>
143
+ """,
144
+ unsafe_allow_html=True
145
+ )
146
+
147
+ # Use text input for the user to define a function, but no `value` argument
148
  func_input = st.text_input(
149
+ "πŸ‘‡",
150
  key="func_input",
151
  on_change=reset_state
152
  )
153
+
154
  st.subheader("βš™οΈ Gradient Descent Parameters")
155
  starting_point = st.number_input(
156
  "Starting Point (Xβ‚€)",
157
  value=4.0,
158
  step=0.1,
159
+ format="%.2f",
160
  key="starting_point",
161
  on_change=reset_state
162
  )
 
164
  "Learning Rate (Ε‹)",
165
  value=0.25,
166
  step=0.01,
167
+ format="%.2f",
168
  key="learning_rate",
169
  on_change=reset_state
170
  )
 
188
  with col2:
189
  st.subheader("πŸ“Š Gradient Descent Visualization")
190
  try:
191
+ # Plot the function and all current and previous gradient descent points
192
  x_plot = np.linspace(-10, 10, 400)
193
  y_plot = [safe_eval(st.session_state.func_input, x) for x in x_plot]
194
 
195
  fig = go.Figure()
196
 
197
+ # Function curve
198
  fig.add_trace(go.Scatter(
199
  x=x_plot,
200
  y=y_plot,
201
+ mode="lines+markers",
202
  line=dict(color="blue", width=2),
203
+ marker=dict(size=4, color="blue", symbol="circle"),
204
  name="Function"
205
  ))
206
 
207
+ # All gradient descent points (red points without coordinates)
208
  fig.add_trace(go.Scatter(
209
  x=st.session_state.x_vals,
210
  y=st.session_state.y_vals,
 
213
  name="Gradient Descent Points"
214
  ))
215
 
216
+ # Tangent line at the current gradient descent point
217
  current_x = st.session_state.x
218
+ tangent_x = np.linspace(-10, 10, 200) # Adjusting range to cover entire plot
219
  tangent_y = tangent_line(st.session_state.func_input, current_x, tangent_x)
220
  fig.add_trace(go.Scatter(
221
  x=tangent_x,
 
225
  name="Tangent Line"
226
  ))
227
 
228
+ # Dynamic zoom for better visibility
229
+ fig.update_layout(
230
+ xaxis=dict(
231
+ title="x-axis",
232
+ range=[-10, 10],
233
+ showline=True,
234
+ linecolor="white",
235
+ tickcolor="white",
236
+ tickfont=dict(color="white"),
237
+ ticks="outside",
238
+ ),
239
+ yaxis=dict(
240
+ title="y-axis",
241
+ range=[min(y_plot) - 5, min(max(y_plot) + 5, 1000)], # Limiting the max y to 1000
242
+ showline=True,
243
+ linecolor="white",
244
+ tickcolor="white",
245
+ tickfont=dict(color="white"),
246
+ ticks="outside",
247
+ ),
248
+ plot_bgcolor="black",
249
+ paper_bgcolor="black",
250
+ title="",
251
+ margin=dict(l=10, r=10, t=10, b=10),
252
+ width=800,
253
+ height=400,
254
+ showlegend=True,
255
+ legend=dict(
256
+ x=1.1,
257
+ y=0.5,
258
+ xanchor="left",
259
+ yanchor="middle",
260
+ orientation="v",
261
+ font=dict(size=12, color="white"),
262
+ bgcolor="black",
263
+ bordercolor="white",
264
+ borderwidth=2,
265
+ )
266
+ )
267
+
268
+ # Axis lines for quadrants
269
+ fig.add_shape(type="line", x0=-10, x1=10, y0=0, y1=0, line=dict(color="white", width=2)) # x-axis
270
+ fig.add_shape(type="line", x0=0, x1=0, y0=-100, y1=100, line=dict(color="white", width=2)) # y-axis
271
+
272
  st.plotly_chart(fig, use_container_width=True)
273
+
274
  except Exception as e:
275
  st.error(f"⚠️ Error in visualization: {str(e)}")
276
 
277
+ # Iteration stats and download
278
  col5, col6 = st.columns(2)
279
  col5.info(f"πŸ§‘β€πŸ’» Iteration: {st.session_state.iteration}")
280
  col6.success(f"βœ… Current x: {st.session_state.x:.4f}, Current f(x): {st.session_state.y_vals[-1]:.4f}")