Spaces:
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Sleeping
Lennard Schober
commited on
Commit
·
e1d92e1
1
Parent(s):
8226920
Store .npz files in current dir
Browse files
app.py
CHANGED
@@ -6,24 +6,23 @@ import numpy as np
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import gradio as gr
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import plotly.graph_objs as go
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# Path to the npz folder
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npz_folder = "npz"
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glob_a = -2
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glob_b = -2
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glob_c = -4
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glob_d = 7
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def
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def complex_heat_eq_solution(x, t, a=glob_a, b=glob_b, c=glob_c, d=glob_d, k=0.5):
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@@ -41,7 +40,7 @@ def plot_heat_equation(m, approx_type):
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n_t = 50
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try:
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loaded_values = np.load(f"
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except:
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raise gr.Error(f"First train the coefficients for {approx_type} and m = {m}")
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alpha = loaded_values["alpha"]
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@@ -138,7 +137,7 @@ def plot_errors(m, approx_type):
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n_t = 50
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try:
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loaded_values = np.load(f"
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except:
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raise gr.Error(f"First train the coefficients for {approx_type} and m = {m}")
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alpha = loaded_values["alpha"]
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@@ -216,14 +215,6 @@ def plot_errors(m, approx_type):
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fig.show(config=config)
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# Function to get the available .npz files in the npz folder
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def get_available_approx_files():
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files = os.listdir(npz_folder)
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npz_files = [f for f in files if f.endswith(".npz")]
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return npz_files
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def generate_data(n_x=32, n_t=50):
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"""Generate training data."""
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x = np.linspace(0, 1, n_x) # spatial points
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@@ -310,7 +301,7 @@ def train_coefficients(m, kernel):
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# Save values to the npz folder
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np.savez(
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f"{
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alpha=alpha,
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kernel=kernel,
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Phi=Phi,
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@@ -465,7 +456,7 @@ def create_gradio_ui():
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error_button.click(
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fn=plot_errors, inputs=[m_slider, kernel_dropdown], outputs=None
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)
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demo.load(fn=
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demo.load(fn=plot_function, inputs=[a_slider, b_slider, c_slider, d_slider], outputs=[plot_output])
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return demo
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import gradio as gr
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import plotly.graph_objs as go
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glob_a = -2
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glob_b = -2
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glob_c = -4
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glob_d = 7
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def clear_npz():
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current_directory = os.getcwd() # Get the current working directory
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for filename in os.listdir(current_directory):
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if filename.endswith(".npz"): # Check if the file ends with .npz
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file_path = os.path.join(current_directory, filename)
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try:
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if os.path.isfile(file_path) or os.path.islink(file_path):
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os.unlink(file_path) # Remove the file or symbolic link
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else:
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print(f"Skipping {file_path}, not a file or symbolic link.")
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except Exception as e:
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print(f"Failed to delete {file_path}. Reason: {e}")
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def complex_heat_eq_solution(x, t, a=glob_a, b=glob_b, c=glob_c, d=glob_d, k=0.5):
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n_t = 50
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try:
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loaded_values = np.load(f"{approx_type}_m{m}.npz")
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except:
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raise gr.Error(f"First train the coefficients for {approx_type} and m = {m}")
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alpha = loaded_values["alpha"]
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n_t = 50
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try:
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loaded_values = np.load(f"{approx_type}_m{m}.npz")
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except:
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raise gr.Error(f"First train the coefficients for {approx_type} and m = {m}")
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alpha = loaded_values["alpha"]
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fig.show(config=config)
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def generate_data(n_x=32, n_t=50):
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"""Generate training data."""
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x = np.linspace(0, 1, n_x) # spatial points
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# Save values to the npz folder
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np.savez(
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f"{kernel}_m{m}.npz",
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alpha=alpha,
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kernel=kernel,
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Phi=Phi,
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error_button.click(
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fn=plot_errors, inputs=[m_slider, kernel_dropdown], outputs=None
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)
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demo.load(fn=clear_npz, inputs=None, outputs=None)
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demo.load(fn=plot_function, inputs=[a_slider, b_slider, c_slider, d_slider], outputs=[plot_output])
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return demo
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