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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,150 @@ | ||
| import pandas as pd | ||
| import numpy as np | ||
| import os | ||
| import sys | ||
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| class createCSVfile: | ||
| def __init__(self, analysisResults, output_dir, column_delimiter=';'): | ||
| self.analysisResults = analysisResults | ||
| self.output_dir = output_dir | ||
| self.column_delimiter = column_delimiter | ||
| self.results_dict = {} | ||
| self.format_rules = { | ||
| "Azimuth": "{:.2f}", | ||
| "Elevation": "{:.2f}", | ||
| "MP_": "{:.4f}", | ||
| "SNR_": "{:.1f}" | ||
| } | ||
| self.time_stamps = self.analysisResults["ExtraOutputInfo"]["time_epochs_utc_time"] | ||
| self.mp_data_lst = ["PRN; Time_UTC; Elevation; Azimuth"] | ||
| self.GNSSsystemCode2Fullname = {'G': 'GPS', 'R': 'GLONASS', 'E': 'Galileo', 'C': 'BeiDou'} | ||
| self.GNSS_Name2Code = {v: k for k, v in self.GNSSsystemCode2Fullname.items()} | ||
| self.results_dict = self.build_results_dict() | ||
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| def flatten_result_array(self, arr): | ||
| """ | ||
| Flatten a numpy array to 1D | ||
| """ | ||
| flatten_array = arr[:, 1:].T.ravel().tolist() | ||
| return flatten_array | ||
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| def set_float_fmt_dataframe(self, df): | ||
| for column in df.columns: | ||
| for prefix, fmt in self.format_rules.items(): | ||
| if column.startswith(prefix): | ||
| df[column] = df[column].map(lambda x: fmt.format(x)) | ||
| break | ||
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| def extract_multipath_and_put_in_result_dict(self, sys_name): | ||
| """ | ||
| Extract the multipath values from "analysisResults" dictionary | ||
| and gather them in the results_dict. | ||
| """ | ||
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| for band in self.analysisResults[sys_name]["Bands"]: | ||
| for code in self.analysisResults[sys_name][band]["Codes"]: | ||
| curr_code_data = self.analysisResults[sys_name][band].get(code, None) if not isinstance(code, list) else None | ||
| if curr_code_data is not None: | ||
| rms_multipath_avg = np.round(curr_code_data["multipath_range1"], 4) | ||
| else: | ||
| continue | ||
| mp_header = f"MP_{code}" | ||
| self.mp_data_lst.append(mp_header) | ||
| self.results_dict[sys_name][mp_header] = rms_multipath_avg | ||
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| def extract_SNR_and_put_in_result_dict(self, sys_name): | ||
| """ | ||
| Extract the SNR values from "analysisResults" dictionary | ||
| and gather them in the results_dict. | ||
| """ | ||
| SNR_dict = self.analysisResults[sys_name].get("SNR", None) | ||
| if SNR_dict is not None: | ||
| for signal_code, snr_array in SNR_dict.items(): | ||
| snr_array[snr_array == 0] = np.nan # convert null to np.nan | ||
| if not np.all(np.isnan(snr_array)): | ||
| signal_header = f"SNR_{signal_code}" | ||
| self.mp_data_lst.append(signal_header) | ||
| # Append SNR data to results_dict if not all elements are np.nan | ||
| self.results_dict[sys_name][signal_header] = snr_array | ||
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| def build_results_dict(self): | ||
| # results_dict = {} | ||
| GNSS_systems = list(self.analysisResults["Sat_position"].keys()) | ||
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| for gnss_sys in GNSS_systems: | ||
| sys_name = self.GNSSsystemCode2Fullname[gnss_sys] | ||
| self.results_dict[sys_name] = {"Elevation": [], "Azimuth": []} | ||
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| # Build up result dict | ||
| for gnss_sys in GNSS_systems: | ||
| curr_sys = self.analysisResults["Sat_position"][gnss_sys] | ||
| sys_name = self.GNSSsystemCode2Fullname[gnss_sys] | ||
| self.results_dict[sys_name]["Azimuth"] = curr_sys["azimuth"] | ||
| self.results_dict[sys_name]["Elevation"] = curr_sys["elevation"] | ||
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| # Extract multipath and SNR values and store in results_dict | ||
| self.extract_multipath_and_put_in_result_dict(sys_name) | ||
| self.extract_SNR_and_put_in_result_dict(sys_name) | ||
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| return self.results_dict | ||
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| def write_results_to_csv(self): | ||
| for sys_name, sys_data in self.results_dict.items(): | ||
| # Extract data into arrays | ||
| sys_code = self.GNSS_Name2Code[sys_name] | ||
| timestamps = self.time_stamps * sys_data["Elevation"][:, 1:].shape[1] | ||
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| prns = list(range(1, sys_data["Azimuth"].shape[1])) | ||
| prns = [f"{sys_code}{prn:02d}" for prn in prns] | ||
| prn_repeated = list(np.repeat(prns, sys_data["Azimuth"].shape[0])) | ||
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| # Flatten numpy array to 1D | ||
| az = self.flatten_result_array(np.round(sys_data["Azimuth"], 2)) | ||
| el = self.flatten_result_array(np.round(sys_data["Elevation"], 2)) | ||
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| # Create a DataFrame for the current system | ||
| df = pd.DataFrame({ | ||
| "PRN": prn_repeated, | ||
| "Time_UTC": timestamps, | ||
| "Azimuth": az, | ||
| "Elevation": el | ||
| }, dtype=object) | ||
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| # Add SNR columns to the DataFrame | ||
| if any(key.startswith("MP") for key in sys_data.keys()): | ||
| mp_headers = [header for header in sys_data.keys() if header.startswith("MP_")] | ||
| for i, header in enumerate(mp_headers): | ||
| df[header] = self.flatten_result_array(sys_data[header]) | ||
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| # Add SNR columns to the DataFrame | ||
| if any(key.startswith("SNR") for key in sys_data.keys()): | ||
| snr_headers = [header for header in sys_data.keys() if header.startswith("SNR_")] | ||
| for i, header in enumerate(snr_headers): | ||
| df[header] = self.flatten_result_array(sys_data[header]) | ||
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| # Set specified float formatting on the columns | ||
| self.set_float_fmt_dataframe(df) | ||
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| # Remove rows where all values except PRN and time are np.nan | ||
| df[df.columns[2:]] = df[df.columns[2:]].apply(pd.to_numeric, errors='coerce') # Convert selected columns to numeric | ||
| df.dropna(subset=['Elevation'], inplace=True) # drop rows where the satellite is below the horizon | ||
| output_file = os.path.join(self.output_dir, f"{sys_name}_results.csv") | ||
| print(f'INFO: The result CSV file {output_file} has been written') | ||
| df.to_csv(output_file, index=False, sep=self.column_delimiter) | ||
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| if __name__ =="__main__": | ||
| sys.path.append(r"C:\Users\perhe\OneDrive\Documents\Python_skript\GNSS_repo\src") | ||
| from gnssmultipath import PickleHandler | ||
| analysisResults = PickleHandler.read_zstd_pickle(r"C:\Users\perhe\Desktop\CSV_export\analysisResults.pkl") | ||
| outputDir = r"C:\Users\perhe\Desktop\CSV_export\TEST" | ||
| createCSV = createCSVfile(analysisResults, outputDir) | ||
| createCSV.write_results_to_csv() |
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