diff --git a/PSPoperations/__init__.py b/PSPoperations/__init__.py
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diff --git a/PSPoperations/__pycache__/plot_settings.cpython-38.pyc b/PSPoperations/__pycache__/plot_settings.cpython-38.pyc
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diff --git a/PSPoperations/data_handling.py b/PSPoperations/data_handling.py
deleted file mode 100644
index 3772ca29c3fe956936c625488ba57f8e30934eb7..0000000000000000000000000000000000000000
--- a/PSPoperations/data_handling.py
+++ /dev/null
@@ -1,73 +0,0 @@
-import os
-import typing as tp
-import numpy as np
-
-# CDF library (is needed to interface with the measurement data files)
-# see https://cdf.gsfc.nasa.gov/
-os.environ["CDF_LIB"] = "/usr/local/cdf/lib"
-
-
-def cdf_slice(cdf_file, key: str):
- """
- DOC
-
- :param cdf_file:
- :param key:
- :return:
- """
- return cdf_file[key][...]
-
-
-def data_generation(cdf_file) -> tp.Dict:
- """
- DOC
-
- :param cdf_file:
- :return:
- """
- data = {
- "dqf": cdf_slice(cdf_file, key="general_flag"),
- "epoch": cdf_slice(cdf_file, key="Epoch"),
- "pos": cdf_slice(cdf_file, key="sc_pos_HCI"),
- "vr": cdf_slice(cdf_file, key="vp_moment_RTN")[:, 0],
- "dvrhi": cdf_slice(cdf_file, key="vp_moment_RTN_deltahigh")[:, 0],
- "dvrlo": cdf_slice(cdf_file, key="vp_moment_RTN_deltalow")[:, 0],
- "wp": cdf_slice(cdf_file, key="wp_moment"),
- "dwphi": cdf_slice(cdf_file, key="wp_moment_deltahigh"),
- "dwplo": cdf_slice(cdf_file, key="wp_moment_deltalow")
- }
-
- return data
-
-
-def array_reduction(data_array: np.ndarray,
- index_list: np.ndarray) -> np.ndarray:
- """
- Reduction of an array by a list of indices.
-
- :param data_array: NDARRAY,
- Array that is to be reduced
- :param index_list: NDARRAY,
- List of indices that should be deleted
- :return: NDARRAY,
- The reduced array
- """
- # Choose axis=0 to delete rows and not flatten the array
- reduced_array = np.delete(data_array, index_list, axis=0)
-
- return reduced_array
-
-
-def full_reduction(data_dict: tp.Dict,
- bad_indices: np.array) -> tp.Dict:
- """
- DOC
-
- :param data_dict:
- :param bad_indices:
- :return:
- """
- for key in data_dict.keys():
- data_dict[key] = array_reduction(data_dict[key], bad_indices)
-
- return data_dict
diff --git a/PSPoperations/data_quality.py b/PSPoperations/data_quality.py
deleted file mode 100644
index bdb6be47e210f365487e76aa9a3f6cf1522d5806..0000000000000000000000000000000000000000
--- a/PSPoperations/data_quality.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import numpy as np
-import typing as tp
-
-
-def general_flag(general_flag_array: np.ndarray) -> np.ndarray:
- """
- This function reads out index locations where data general flag is
- set to 0 (see documentation for PSP data). This requires correct
- handling of CDF array keys
-
- :param general_flag_array: NDARRAY,
- cdf_data["general_flag"][...] - Only good when set to 0. The
- input here must specifically be this array!
- :return: NDARRAY,
- An array of the "faulty" indices. These indices correspond to
- the index m in the m x n GENERAL CDF array, not a measurement
- subarray!
- """
- # Notable indices are where values are set to non-zero
- # From the data user guide: 0 means no condition present
- index_list = np.where(general_flag_array != 0)[0]
-
- return index_list
-
-
-def meas_failed(meas_array: np.ndarray) -> np.ndarray:
- """
- Takes a 1D array and returns indices of failed measurements (as
- indicated by a value of -1e30, SWEAP documentation)
-
- :param meas_array: NDARRAY,
- Measurement array
- :return: NDARRAY,
- Index array
- """
- index_array = np.where(meas_array <= -0.5e30)[0]
-
- return index_array
-
-
-def full_meas_eval(data_dict: tp.Dict):
- """DOC"""
- col_ind = []
-
- for key in data_dict.keys():
-
- # Skip unnecessary keys (maybe make this more dynamic?)
- if key in ["pos", "dqf", "epoch"]:
- continue
-
- col_ind.append(meas_failed(data_dict[key]))
-
- # Make an array of unique indices
- col_ind = np.unique(np.concatenate(col_ind))
-
- return col_ind
diff --git a/PSPoperations/data_transformation.py b/PSPoperations/data_transformation.py
deleted file mode 100644
index a3df0292cb5f080f0d595844cfdfd2644c382d08..0000000000000000000000000000000000000000
--- a/PSPoperations/data_transformation.py
+++ /dev/null
@@ -1,44 +0,0 @@
-import numpy as np
-import typing as tp
-# The warnings (for me) here don't seem to matter
-from astropy.constants import k_B, m_p
-
-
-def pos_cart_to_sph(position_matrix: np.ndarray) -> tp.Tuple:
- """
- Transforms cartesian coordinates to spherical coordinates.
-
- :param position_matrix: NDARRAY,
- (n x 3) matrix of (x, y, z) coordinates
- :return: TUPLE,
- r = heliocentric distance in KM
- theta = inclination in RADIANS
- phi = azimuth in RADIANS
- """
- # Sanity check: pos_mat MUST BE an (n x 3) matrix
- assert position_matrix.shape[1] == 3, \
- "PLEASE CHECK POSITION MATRIX FOR COORDINATE CONVERSION!"
-
- x = position_matrix[:, 0]
- y = position_matrix[:, 1]
- z = position_matrix[:, 2]
-
- r = np.sqrt(x * x + y * y + z * z)
- theta = np.arccos(z / r)
- phi = np.arctan2(y, x)
-
- return r, theta, phi
-
-
-def wp_to_temp(thermal_speed: np.ndarray) -> np.ndarray:
- """
- Calculate temperature from thermal speed of protons.
-
- :param thermal_speed: NDARRAY,
- Thermal speed (wp) of protons
- :return: NDARRAY,
- Temperature from wp = sqrt(2k_BT / m)
- """
- wp_si = thermal_speed * 1e3
-
- return wp_si ** 2 * m_p.value / (2 * k_B.value)
diff --git a/PSPoperations/plot_settings.py b/PSPoperations/plot_settings.py
deleted file mode 100644
index 8a50ac8149629e0f3a58cfc0687d1861b336adf9..0000000000000000000000000000000000000000
--- a/PSPoperations/plot_settings.py
+++ /dev/null
@@ -1,63 +0,0 @@
-import matplotlib as mpl
-import matplotlib.pyplot as plt
-
-
-def rc_setup():
- """Generalized plot attributes"""
- mpl.rcParams["xtick.direction"] = "in"
- mpl.rcParams["ytick.direction"] = "in"
- mpl.rcParams["xtick.minor.visible"] = "True"
- mpl.rcParams["ytick.minor.visible"] = "True"
-
-
-def plot_r_vr(r, vr, v_ulim, v_lolim, save_ind: str = "no"):
- """
- Plots radial velocity wrt heliocentric distance
-
- :param r: NDARRAY,
- Distance (must be in km)
- :param vr: NDARRAY,
- Radial velocity (must be in km/s)
- :param v_ulim, v_lolim: NDARRAY,
- Upper (lower) uncertainty of vr
- :param save_ind: STR,
- "yes" if plot should be saved (default: no)
- """
- fig, ax = plt.subplots(figsize=(10, 6))
- plt.plot(r / 6.957e5, vr)
- plt.fill_between(r / 6.957e5, vr + v_ulim, vr - v_lolim, color="grey",
- alpha=0.25)
- ax.set(
- xlabel="r [R$_\\odot$]", ylabel="v$_r$ [km s$^{-1}$]",
- ylim=(0, 800)
- )
- ax.grid(True, alpha=0.5)
-
- if save_ind.lower() == "yes":
- plt.savefig("plot_vr.png")
-
-
-def plot_r_temp(r, T, T_ulim, T_lolim, save_ind: str = "no"):
- """
- Plots logarithmic temperature wrt heliocentric distance
-
- :param r: NDARRAY,
- Heliocentric distance (mst be in km)
- :param T: NDARRAY,
- logarithmic Temperature (Kelvin)
- :param T_ulim, T_lolim: NDARRAY,
- Upper (lower) uncertainty of logT
- :param save_ind: STR,
- "yes" if plot should be saved (default: no)
- """
- fig, ax = plt.subplots(figsize=(10, 6))
- plt.plot(r / 6.957e5, T)
- plt.fill_between(r / 6.957e5, T_ulim, T - T_lolim,
- color="grey", alpha=0.25)
- ax.set(
- xlabel="r [R$_\\odot$]", ylabel="T [K]", yscale="log"
- )
- ax.grid(True, alpha=0.5)
-
- if save_ind.lower() == "yes":
- plt.savefig("plot_logT.png")
diff --git a/psp_swp_spc_l3i_20211117_v02.cdf b/psp_swp_spc_l3i_20211117_v02.cdf
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diff --git a/psp_swp_spc_l3i_20211121_v02.cdf b/psp_swp_spc_l3i_20211121_v02.cdf
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diff --git a/testing.py b/testing.py
deleted file mode 100644
index 307a7500cdd935fd6cbb7344912dce20b49ce3af..0000000000000000000000000000000000000000
--- a/testing.py
+++ /dev/null
@@ -1,40 +0,0 @@
-import os
-import numpy as np
-import matplotlib.pyplot as plt
-from spacepy import pycdf
-from PSPoperations import data_quality as dq
-from PSPoperations import data_transformation as dt
-
-# CDF library (is needed to interface with the measurement data files)
-# see https://cdf.gsfc.nasa.gov/
-os.environ["CDF_LIB"] = "/usr/local/cdf/lib"
-
-# open CDF file and generate faulty index array
-cdf_data = pycdf.CDF("psp_swp_spc_l3i_20211117_v02.cdf")
-dqf = cdf_data["general_flag"][...]
-bad_ind = dq.general_flag(dqf)
-
-# generate reduced epoch array
-time = dq.array_reduction(cdf_data["Epoch"][...], bad_ind)
-
-# generate reduced position array and spherical coordinates
-pos = dq.array_reduction(cdf_data["sc_pos_HCI"][...], bad_ind)
-r, theta, phi = dt.pos_cart_to_sph(pos)
-
-# generate (prelim.) velocity array (is [0] in RTN right?)
-vr = dq.array_reduction(cdf_data["vp_moment_RTN"][...][:, 0], bad_ind)
-del_vr_lo = dq.array_reduction(cdf_data["vp_moment_RTN_deltalow"][...][:, 0],
- bad_ind)
-del_vr_hi = dq.array_reduction(cdf_data["vp_moment_RTN_deltahigh"][...][:, 0],
- bad_ind)
-
-plt.figure()
-plt.plot(r / 1.49e8, vr)
-plt.fill_between(r / 1.49e8, vr + del_vr_hi, vr - del_vr_lo, color="grey",
- alpha=0.15)
-plt.ylim(0, 1000)
-
-plt.figure()
-plt.scatter(time, r / 1.49e8)
-
-plt.show()