Merge pull request #1299 from anarkiwi/wfsplit

Move arg processing and waterfall drawing to own modules.

gamutrfwaterfall/gamutrfwaterfall/argparser.py

@@ -0,0 +1,111 @@
+import argparse
+
+
+def argument_parser():
+    parser = argparse.ArgumentParser(description="waterfall plotter from scan data")
+    parser.add_argument(
+        "--min_freq",
+        default=0,
+        type=float,
+        help="Minimum frequency for plot (or 0 for automatic).",
+    )
+    parser.add_argument(
+        "--max_freq",
+        default=0,
+        type=float,
+        help="Maximum frequency for plot (or 0 for automatic).",
+    )
+    parser.add_argument(
+        "--n_detect", default=0, type=int, help="Number of detected signals to plot."
+    )
+    parser.add_argument(
+        "--plot_snr", action="store_true", help="Plot SNR rather than power."
+    )
+    parser.add_argument(
+        "--detection_type",
+        default="",
+        type=str,
+        help="Detection type to plot (wideband, narrowband).",
+    )
+    parser.add_argument(
+        "--save_path", default="", type=str, help="Path to save screenshots."
+    )
+    parser.add_argument(
+        "--save_time",
+        default=1,
+        type=int,
+        help="Save screenshot every save_time minutes. Only used if save_path also defined.",
+    )
+    parser.add_argument(
+        "--scanners",
+        default="127.0.0.1:8001",
+        type=str,
+        help="Scanner FFT endpoints to use.",
+    )
+    parser.add_argument(
+        "--port",
+        default=0,
+        type=int,
+        help="If set, serve waterfall on this port.",
+    )
+    parser.add_argument(
+        "--rotate_secs",
+        default=900,
+        type=int,
+        help="If > 0, rotate save directories every N seconds",
+    )
+    parser.add_argument(
+        "--width",
+        default=28,
+        type=float,
+        help="Waterfall image width",
+    )
+    parser.add_argument(
+        "--height",
+        default=10,
+        type=float,
+        help="Waterfall image height",
+    )
+    parser.add_argument(
+        "--waterfall_height",
+        default=100,
+        type=int,
+        help="Waterfall height",
+    )
+    parser.add_argument(
+        "--waterfall_width",
+        default=5000,
+        type=int,
+        help="Waterfall width (maximum)",
+    )
+    parser.add_argument(
+        "--refresh",
+        default=5,
+        type=int,
+        help="Waterfall refresh time",
+    )
+    parser.add_argument(
+        "--predictions",
+        default=3,
+        type=int,
+        help="If set, render N recent predictions",
+    )
+    parser.add_argument(
+        "--inference_server",
+        default="",
+        type=str,
+        help="Address of scanner for inference feed",
+    )
+    parser.add_argument(
+        "--inference_port",
+        default=10002,
+        type=int,
+        help="Port on scanner to connect to inference feed",
+    )
+    parser.add_argument(
+        "--api_endpoint",
+        default="127.0.0.1:9001",
+        type=str,
+        help="Scanner API endpoints to use.",
+    )
+    return parser

gamutrfwaterfall/gamutrfwaterfall/flask_handler.py

@@ -0,0 +1,224 @@
+import datetime
+import json
+import logging
+import multiprocessing
+import os
+import time
+import requests
+import zmq
+from flask import (
+    Flask,
+    send_file,
+    render_template,
+    send_from_directory,
+    request,
+    redirect,
+)
+
+
+def get_scanner_args(api_endpoint, config_vars):
+    try:
+        response = requests.get(f"http://{api_endpoint}/getconf", timeout=30)
+        response.raise_for_status()
+
+        for name, val in json.loads(response.text).items():
+            config_vars[name] = val
+
+    except (
+        requests.exceptions.ConnectionError,
+        requests.exceptions.HTTPError,
+        requests.exceptions.ConnectTimeout,
+    ) as err:
+        logging.error(err)
+
+
+def write_scanner_args(config_vars_path, config_vars):
+    tmpfile = os.path.join(
+        os.path.dirname(config_vars_path),
+        "." + os.path.basename(config_vars_path),
+    )
+    with open(tmpfile, "w", encoding="utf8") as f:
+        json.dump(config_vars, f)
+    os.rename(tmpfile, config_vars_path)
+
+
+class FlaskHandler:
+    def __init__(
+        self,
+        savefig_path,
+        tempdir,
+        predictions,
+        port,
+        refresh,
+        inference_server,
+        inference_port,
+        api_endpoint,
+        config_vars,
+        config_vars_path,
+    ):
+        self.inference_addr = f"tcp://{inference_server}:{inference_port}"
+        self.savefig_path = savefig_path
+        self.config_vars = config_vars
+        self.config_vars_path = config_vars_path
+        self.tempdir = tempdir
+        self.predictions_file = "predictions.html"
+        self.refresh = refresh
+        self.predictions = predictions
+        self.api_endpoint = api_endpoint
+        self.app = Flask(__name__, template_folder="templates", static_folder="static")
+        self.savefig_file = os.path.basename(self.savefig_path)
+        self.app.add_url_rule("/", "index", self.serve_waterfall_page)
+        self.app.add_url_rule(
+            "/waterfall", "serve_waterfall_page", self.serve_waterfall_page
+        )
+        self.app.add_url_rule(
+            "/waterfall_img", "serve_waterfall_img", self.serve_waterfall_img
+        )
+        self.app.add_url_rule(
+            "/config_form", "config_form", self.config_form, methods=["POST", "GET"]
+        )
+        self.app.add_url_rule(
+            "/predictions", "serve_predictions_page", self.serve_predictions_page
+        )
+        self.app.add_url_rule(
+            "/predictions_content",
+            "serve_predictions_content",
+            self.serve_predictions_content,
+        )
+        self.app.add_url_rule("/<path:path>", "", self.serve)
+        self.process = multiprocessing.Process(
+            target=self.app.run,
+            kwargs={"host": "0.0.0.0", "port": port},  # nosec
+        )
+        self.zmq_process = multiprocessing.Process(target=self.poll_zmq)
+        self.write_predictions_content("no predictions yet")
+        self.read_config_vars()
+
+    def start(self):
+        self.process.start()
+        self.zmq_process.start()
+
+    def write_predictions_content(self, content):
+        tmpfile = os.path.join(self.tempdir, "." + self.predictions_file)
+        with open(tmpfile, "w", encoding="utf8") as f:
+            f.write(f"{content}")
+        os.rename(tmpfile, os.path.join(self.tempdir, self.predictions_file))
+
+    def poll_zmq(self):
+        zmq_context = zmq.Context()
+        socket = zmq_context.socket(zmq.SUB)
+        socket.connect(self.inference_addr)
+        socket.setsockopt_string(zmq.SUBSCRIBE, "")
+        DELIM = "\n\n"
+        json_buffer = ""
+        item_buffer = []
+
+        while True:
+            try:
+                while True:
+                    sock_txt = socket.recv(flags=zmq.NOBLOCK).decode("utf8")
+                    json_buffer += sock_txt
+            except zmq.error.Again:
+                pass
+            while True:
+                delim_pos = json_buffer.find(DELIM)
+                if delim_pos == -1:
+                    break
+                raw_item = json_buffer[:delim_pos]
+                json_buffer = json_buffer[delim_pos + len(DELIM) :]
+                try:
+                    item = json.loads(raw_item)
+                except json.decoder.JSONDecodeError:
+                    continue
+                ts = float(item["metadata"]["ts"])
+                if "predictions_image_path" not in item["metadata"]:
+                    continue
+                ts = float(item["metadata"]["ts"])
+                item_buffer.append((ts, item))
+            item_buffer = item_buffer[-self.predictions :]
+            predictions = sorted(item_buffer, key=lambda x: x[0], reverse=True)
+            images = []
+            now = time.time()
+            for ts, item in predictions:
+                image = item["metadata"]["predictions_image_path"]
+                age = now - ts
+                style = ""
+                if age > 3 * self.refresh:
+                    style = 'style="color:red;"'
+                images.append(
+                    "<p %s>%s (age %.1fs)</p><p %s><img src=%s></img></p>"
+                    % (style, image, age, style, image)
+                )
+            if images:
+                self.write_predictions_content(
+                    f"<p>{datetime.datetime.now().isoformat()}</p>" + "".join(images)
+                )
+            time.sleep(0.1)
+
+    def serve(self, path):
+        if path:
+            full_path = os.path.realpath(os.path.join("/", path))
+            if os.path.exists(full_path):
+                return send_file(full_path, mimetype="image/png")
+            return "%s: not found" % full_path, 404
+        if os.path.exists(self.savefig_path):
+            return (
+                '<html><head><meta http-equiv="refresh" content="%u"></head><body><img src="%s"></img></body></html>'
+                % (self.refresh, self.savefig_file),
+                200,
+            )
+        return (
+            '<html><head><meta http-equiv="refresh" content="%u"></head><body>waterfall initializing, please wait or reload...</body></html>'
+            % self.refresh,
+            200,
+        )
+
+    def serve_predictions_content(self):
+        return send_from_directory(self.tempdir, self.predictions_file)
+
+    def serve_predictions_page(self):
+        # return send_from_directory(self.tempdir, self.predictions_file)
+        return render_template("predictions.html")
+
+    def read_config_vars(self):
+        try:
+            with open(self.config_vars_path, encoding="utf8") as f:
+                self.config_vars = json.load(f)
+        except FileNotFoundError:
+            pass
+
+    def serve_waterfall_page(self):
+        self.read_config_vars()
+        return render_template("waterfall.html", config_vars=self.config_vars)
+
+    # @app.route("/file/<path:filename>")
+    # def serve_file(self, filename):
+    #     return send_from_directory(self.tempdir, filename)
+
+    def serve_waterfall_img(self):
+        return send_from_directory(self.tempdir, self.savefig_file)
+
+    def config_form(self):
+        for var in self.config_vars:
+            self.config_vars[var] = request.form.get(var, self.config_vars[var])
+        write_scanner_args(self.config_vars_path, self.config_vars)
+        reset = request.form.get("reset", None)
+        if reset == "reset":
+            reconf_query_str = "&".join(
+                [f"{k}={v}" for k, v in self.config_vars.items()]
+            )
+            logging.info(f"\n\n{reconf_query_str=}\n\n")
+            try:
+                response = requests.get(
+                    f"http://{self.api_endpoint}/reconf?{reconf_query_str}",
+                    timeout=30,
+                )
+                logging.info(f"\n\n{response=}\n\n")
+                logging.info(f"\n\n{response.text=}\n\n")
+            except (
+                requests.exceptions.ConnectionError,
+                requests.exceptions.HTTPError,
+                requests.exceptions.ConnectTimeout,
+            ) as err:
+                logging.error(str(err))
+        return redirect("/", code=302)