Create app.py

app.py

@@ -0,0 +1,83 @@
+import streamlit as st
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+def main():
+    st.set_page_config(layout="wide")
+    st.title(
+        "Procesamiento Digital de Señales - UNTREF \n ## Spectral Leakage en la DFT"
+    )
+    st.divider()
+    signal_expression, signal_settings = st.columns(2)
+
+    with signal_settings:
+        st.markdown("### Parámetros de la señal")
+        num_samples = st.slider(
+            "Cantidad de Muestras", min_value=4, max_value=64, value=8, step=1
+        )
+
+        freq = st.slider(
+            r"$\omega_0$",
+            min_value=-np.pi,
+            max_value=np.pi,
+            value=0.0,
+            step=np.pi / 64,
+        )
+    with signal_expression:
+        freq_samples = int(np.round(64 * freq / np.pi))
+        st.markdown("### Señal analizada:")
+        with st.columns(3)[1]:
+            st.markdown(f"# $$e^{{j\\frac{{{freq_samples}}}{{64}}\pi}}$$")
+
+    samples = np.arange(num_samples)
+    signal = np.exp(1j * (freq) * samples)
+
+    dft_result = np.fft.fftshift(np.fft.fft(signal))
+    dft_result = dft_result / np.max(np.abs(dft_result))
+    dft_freqs = np.fft.fftshift(np.fft.fftfreq(len(signal)))
+
+    dtft_samples = 2048
+    dtft_result = np.fft.fftshift(np.fft.fft(signal, dtft_samples))
+    dtft_result = dtft_result / np.max(np.abs(dtft_result))
+    dtft_freqs = np.fft.fftshift(np.fft.fftfreq(dtft_samples))
+
+    dft_freqs_rad = 2 * np.pi * dft_freqs
+    dtft_freqs_rad = 2 * np.pi * dtft_freqs
+
+    # Plot the signals
+    fig = plt.figure(figsize=(10, 4))
+    plt.axvline(freq, color="black", alpha=0.5, linestyle=":", label=r"$\omega_0$")
+    plt.plot(dtft_freqs_rad, np.abs(dtft_result), color="red", label="DTFT")
+    plt.stem(dft_freqs_rad, np.abs(dft_result), markerfmt="C0o", label="DFT")
+    plt.axvline(np.pi, color="black", linestyle="--")
+    plt.axvline(-np.pi, color="black", linestyle="--")
+
+    plt.xlabel("Frecuencia angular [rad]")
+    plt.ylabel("Magnitud de la transformada normalizada")
+    plt.ylim(0, 1.1)
+    plt.xlim(-np.pi - 0.1, np.pi + 0.1)
+    plt.xticks(
+        np.linspace(-np.pi, np.pi, 9),
+        [
+            r"$-\pi$",
+            r"$-\frac{3}{4}\pi$",
+            r"$-\frac{\pi}{2}$",
+            r"$-\frac{\pi}{4}$",
+            r"0",
+            r"$\frac{\pi}{4}$",
+            r"$\frac{\pi}{2}$",
+            r"$\frac{3}{4}\pi$",
+            r"$\pi$",
+        ],
+    )
+    plt.grid()
+    plt.legend(loc="upper right", framealpha=1, ncol=3, bbox_to_anchor=(0.65, 1.06))
+
+    plt.tight_layout()
+
+    st.pyplot(fig, use_container_width=True)
+
+
+if __name__ == "__main__":
+    main()