hot bug fixes

.gitignore

@@ -149,6 +149,6 @@ poetry.lock
 tech_tests.ipynb
 /examples/random_test.ipynb
 /home_tests
-/pyquac/ddd.csv
+/pyquac/good_case.csv
 /pyquac/jyp_app.ipynb
 .vscode

examples/random_example.py

@@ -7,37 +7,61 @@
 # family class
 from pyquac.datatools import Spectroscopy, timer
 
+
 class Random_spectroscopy(Spectroscopy):
     """
     Two Tone Spectroscopy for 1 qubit measurements
     """
 
-    def __init__(self,
-                 *,
-                 x_min=None, x_max=None, y_min=None, y_max=None,
-                 nx_points=None, x_step=None,
-                 y_step=None, ny_points=None,
-                 x_arr=None, y_arr=None,
-                 ):
+    def __init__(
+        self,
+        *,
+        x_min=None,
+        x_max=None,
+        y_min=None,
+        y_max=None,
+        nx_points=None,
+        x_step=None,
+        y_step=None,
+        ny_points=None,
+        x_arr=None,
+        y_arr=None,
+    ):
 
-        super().__init__(x_min=x_min, x_max=x_max, nx_points=nx_points, y_min=y_min, y_max=y_max, ny_points=ny_points,
-                         x_step=x_step, y_step=y_step, x_arr=x_arr, y_arr=y_arr)
+        super().__init__(
+            x_min=x_min,
+            x_max=x_max,
+            nx_points=nx_points,
+            y_min=y_min,
+            y_max=y_max,
+            ny_points=ny_points,
+            x_step=x_step,
+            y_step=y_step,
+            x_arr=x_arr,
+            y_arr=y_arr,
+        )
         pass
 
-    def run_measurements(self, *, x_key: Union[float, int, Iterable] = None, y_key: Union[float, int, Iterable] = None,
-                         x_min=None, x_max=None, y_min=None, y_max=None,
-                         sleep=0.007):
-
-        self.iter_setup(x_key=x_key, y_key=y_key,
-                        x_min=x_min, x_max=x_max, y_min=y_min, y_max=y_max)
+    def run_measurements(
+        self,
+        *,
+        x_key: Union[float, int, Iterable] = None,
+        y_key: Union[float, int, Iterable] = None,
+        x_min=None,
+        x_max=None,
+        y_min=None,
+        y_max=None,
+        sleep=0.007,
+    ):
 
+        self.iter_setup(
+            x_key=x_key, y_key=y_key, x_min=x_min, x_max=x_max, y_min=y_min, y_max=y_max
+        )
+        iterations = len(self.load)
         try:
-            for i in range(len(self.load)):
+            for i in range(iterations):
 
-                self.write(x=self.load[i],
-                           y=self.frequency[i],
-                           z=np.random.random()
-                           )
+                self.write(x=self.load[i], y=self.frequency[i], z=np.random.random())
                 timer.sleep(sleep)
 
         except KeyboardInterrupt:

pyquac/datatools.py

@@ -63,7 +63,6 @@ def cust_range(cls, *args, rtol=1e-05, atol=1e-08, include=(True, False)):
         Avoids also floating point rounding errors as with
         numpy.arange(1, 1.3, 0.1)
         array([1. , 1.1, 1.2, 1.3])
-
         args: [start, ]stop, [step, ]
             as in numpy.arange
         rtol, atol: floats
@@ -113,7 +112,6 @@ class timer:
     """
     timer class provides accurate variation of time.sleep() method. Example:
     timer.sleep(1) #  sleeps for 1. second
-
     Why to use this? If you use time.sleep() for 1 iteration, it wouldn't bring you problem, but if your script
     requires a loop with time.sleep() inside, Windows OS will ruin your script execution. To explain why this
     happened, Windows OS has its default timer resolution set to 15.625 ms or 64 Hz, which is decently enough for
@@ -130,10 +128,8 @@ def sleep(sec: float):
 
 class Spectroscopy:
     """Data class for manipulating live-data for heatmap graph
-
     Raises:
         AttributeError: _description_
-
     Returns:
         _type_: _description_
     """
@@ -166,6 +162,7 @@ class Spectroscopy:
         "__len_y",
         "__x_for_approximate_idxs",
         "__approximation_y_keys",
+        "__z_container_numba"
     ]
 
     def __init__(
@@ -284,6 +281,9 @@ def __init__(
         self.__x_container = np.zeros(len(self.x_list) * len(self.y_list))
         self.__y_container = np.zeros(len(self.x_list) * len(self.y_list))
 
+        self.__z_container_numba = np.zeros(len(self.x_list) * len(self.y_list))
+        self.__z_container_numba[:] = np.nan
+
         self.x_1d = np.repeat(self.x_list, len(self.y_list))
         self.y_1d = np.tile(self.y_list, len(self.x_list))
         self.__n_steps = int(0.04 * len(self.y_list))
@@ -620,7 +620,7 @@ def njit_result(self):
             x_val, y_val, self.x_min, self.x_step, self.y_min, self.y_step, self.__len_y
         )
         if len(self.x_raw) >= 2:
-            array_to_process = np.copy(self.__z_container)
+            array_to_process = np.copy(self.__z_container_numba)
             array_to_process[ind_array.astype(int)] = z_val
 
             return array_to_process
@@ -952,17 +952,17 @@ def drop(
             self.__drop_the_cols(x, y)
             pass
 
-    def load_data(self, raw_file: str):
+    def load_data(self, raw_file: str, x_col_name:str = 'x_value', y_col_name:str = 'y_value', z_col_name:str = 'z_value'):
         """
         loads csv file to Spectroscopy class data structure. CSV file must contain three columns ['x_value', 'y_value', 'z_value']. Dtype of each value - Float | int
         :param raw_file: x value(s)
         :type raw_file: str
         """
         raw_csv = pd.read_csv(raw_file)
 
-        self.x_raw = list(raw_csv.x_value.values)
-        self.y_raw = list(raw_csv.y_value.values)
-        self.z_raw = list(raw_csv.z_value.values)
+        self.x_raw = list(raw_csv[x_col_name].values)
+        self.y_raw = list(raw_csv[y_col_name].values)
+        self.z_raw = list(raw_csv[z_col_name].values)
 
     def __drop_the(self, column: str, value_s: Union[float, int, Iterable]):
 
@@ -1150,4 +1150,4 @@ def __find_nearest_universal(self, arr, value):
     def __find_nearest(self, value):
         array = np.asarray(self.y_list)
         idx = (np.abs(array - value)).argmin()
-        return array[idx]
+        return array[idx]